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infectious disease

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Viral disease researchers Hilary Koprowski and Herald R. Cox

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infectious disease , in medicine , a process caused by an agent, often a type of microorganism , that impairs a person’s health . In many cases, infectious disease can be spread from person to person, either directly (e.g., via skin contact) or indirectly (e.g., via contaminated food or water).

An infectious disease can differ from simple infection , which is the invasion of and replication in the body by any of various agents—including bacteria , viruses , fungi , protozoans , and worms —as well as the reaction of tissues to their presence or to the toxins that they produce. When health is not altered, the process is called a subclinical infection. Thus, a person may be infected but not have an infectious disease. This principle is illustrated by the use of vaccines for the prevention of infectious diseases. For example, a virus such as that which causes measles may be attenuated (weakened) and used as an immunizing agent. The immunization is designed to produce a measles infection in the recipient but generally causes no discernible alteration in the state of health. It produces immunity to measles without producing a clinical illness (an infectious disease).

The difference between bacteria and viruses

The most important barriers to invasion of the human host by infectious agents are the skin and mucous membranes (the tissues that line the nose, mouth, and upper respiratory tract). When these tissues have been broken or affected by earlier disease, invasion by infectious agents may occur. These infectious agents may produce a local infectious disease, such as boils , or may invade the bloodstream and be carried throughout the body, producing generalized bloodstream infection ( septicemia ) or localized infection at a distant site, such as meningitis (an infection of the coverings of the brain and spinal cord). Infectious agents swallowed in food and drink can attack the wall of the intestinal tract and cause local or general disease. The conjunctiva , which covers the front of the eye, may be penetrated by viruses that cause a local inflammation of the eye or that pass into the bloodstream and cause a severe general disease, such as smallpox . Infectious agents can enter the body through the genital tract, causing the acute inflammatory reaction of gonorrhea in the genital and pelvic organs or spreading out to attack almost any organ of the body with the more chronic and destructive lesions of syphilis . Even before birth , viruses and other infectious agents can pass through the placenta and attack developing cells, so that an infant may be diseased or deformed at birth.

From conception to death, humans are targets for attack by multitudes of other living organisms, all of them competing for a place in the common environment . The air people breathe, the soil they walk on, the waters and vegetation around them, the buildings they inhabit and work in, all can be populated with forms of life that are potentially dangerous. Domestic animals may harbor organisms that are a threat, and wildlife teems with agents of infection that can afflict humans with serious disease. However, the human body is not without defenses against these threats, for it is equipped with a comprehensive immune system that reacts quickly and specifically against disease organisms when they attack. Survival throughout the ages has depended largely on these reactions, which today are supplemented and strengthened through the use of medical drugs .

Infectious agents

Categories of organisms.

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The agents of infection can be divided into different groups on the basis of their size, biochemical characteristics, or manner in which they interact with the human host. The groups of organisms that cause infectious diseases are categorized as bacteria, viruses, fungi, and parasites.

Bacteria can survive within the body but outside individual cells. Some bacteria, classified as aerobes , require oxygen for growth, while others, such as those normally found in the small intestine of healthy persons, grow only in the absence of oxygen and, therefore, are called anaerobes . Most bacteria are surrounded by a capsule that appears to play an important role in their ability to produce disease. Also, a number of bacterial species give off toxins that in turn may damage tissues. Bacteria are generally large enough to be seen under a light microscope . Streptococci, the bacteria that cause scarlet fever , are about 0.75 micrometer (0.00003 inch) in diameter . The spirochetes , which cause syphilis , leptospirosis , and rat-bite fever , are 5 to 15 micrometers long. Bacterial infections can be treated with antibiotics .

Bacterial infections are commonly caused by pneumococci , staphylococci , and streptococci , all of which are often commensals (that is, organisms living harmlessly on their hosts) in the upper respiratory tract but that can become virulent and cause serious conditions, such as pneumonia, septicemia (blood poisoning), and meningitis. The pneumococcus is the most common cause of lobar pneumonia , the disease in which one or more lobes, or segments, of the lung become solid and airless as a result of inflammation. Staphylococci affect the lungs either in the course of staphylococcal septicemia—when bacteria in the circulating blood cause scattered abscesses in the lungs—or as a complication of a viral infection, commonly influenza —when these organisms invade the damaged lung cells and cause a life-threatening form of pneumonia. Streptococcal pneumonia is the least common of the three and occurs usually as a complication of influenza or other lung disease.

Pneumococci often enter the bloodstream from inflamed lungs and cause septicemia, with continued fever but no other special symptoms . Staphylococci produce a type of septicemia with high spiking fever; the bacteria can reach almost any organ of the body—including the brain, the bones, and especially the lungs—and destructive abscesses form in the infected areas. Streptococci also cause septicemia with fever, but the organisms tend to cause inflammation of surface lining cells rather than abscesses—for example, pleurisy (inflammation of the chest lining) rather than lung abscess , and peritonitis (inflammation of the membrane lining the abdomen) rather than liver abscess. In the course of either of the last two forms of septicemia, organisms may enter the nervous system and cause streptococcal or staphylococcal meningitis , but these are rare conditions. Pneumococci, on the other hand, often spread directly into the central nervous system , causing one of the common forms of meningitis.

Staphylococci and streptococci are common causes of skin diseases. Boils and impetigo (in which the skin is covered with blisters, pustules, and yellow crusts) may be caused by either. Staphylococci also can cause a severe skin infection that strips the outer skin layers off the body and leaves the underlayers exposed, as in severe burns, a condition known as toxic epidermal necrolysis. Streptococcal organisms can cause a severe condition known as necrotizing fasciitis , commonly referred to as flesh-eating disease, which has a fatality rate between 25 and 75 percent. Streptococci can be the cause of the red cellulitis of the skin known as erysipelas .

Some staphylococci produce an intestinal toxin and cause food poisoning . Certain streptococci settling in the throat produce a reddening toxin that speeds through the bloodstream and produces the symptoms of scarlet fever . Streptococci and staphylococci also can cause toxic shock syndrome , a potentially fatal disease. Streptococcal toxic shock syndrome (STSS) is fatal in some 35 percent of cases.

Meningococci are fairly common inhabitants of the throat, in most cases causing no illness at all. As the number of healthy carriers increases in any population, however, there is a tendency for the meningococcus to become more invasive. When an opportunity is presented, it can gain access to the bloodstream, invade the central nervous system, and cause meningococcal meningitis (formerly called cerebrospinal meningitis or spotted fever). Meningococcal meningitis, at one time a dreaded and still a very serious disease, usually responds to treatment with penicillin if diagnosed early enough. When meningococci invade the bloodstream, some gain access to the skin and cause bloodstained spots, or purpura . If the condition is diagnosed early enough, antibiotics can clear the bloodstream of the bacterium and prevent any from getting far enough to cause meningitis. Sometimes the septicemia takes a mild, chronic, relapsing form with no tendency toward meningitis; this is curable once it is diagnosed. The meningococcus also can cause one of the most fulminating of all forms of septicemia, meningococcemia, in which the body is rapidly covered with a purple rash, purpura fulminans; in this form the blood pressure becomes dangerously low, the heart and blood vessels are affected by shock , and the infected person dies within a matter of hours. Few are saved, despite treatment with appropriate drugs.

Haemophilus influenzae is a microorganism named for its occurrence in the sputum of patients with influenza —an occurrence so common that it was at one time thought to be the cause of the disease. It is now known to be a common inhabitant of the nose and throat that may invade the bloodstream, producing meningitis, pneumonia, and various other diseases. In children it is the most common cause of acute epiglottitis , an infection in which tissue at the back of the tongue becomes rapidly swollen and obstructs the airway, creating a potentially fatal condition. H. influenzae also is the most common cause of meningitis and pneumonia in children under five years of age, and it is known to cause bronchitis in adults. The diagnosis is established by cultures of blood, cerebrospinal fluid , or other tissue from sites of infection. Antibiotic therapy is generally effective, although death from sepsis or meningitis is still common. In developed countries where H. influenza vaccine is used, there has been a great decrease in serious infections and deaths.

Chlamydia are intracellular organisms found in many vertebrates, including birds and humans and other mammals. Clinical illnesses are caused by the species C. trachomatis , which is a frequent cause of genital infections in women. If an infant passes through an infected birth canal, it can produce disease of the eye ( conjunctivitis ) and pneumonia in the newborn. Young children sometimes develop ear infections, laryngitis , and upper respiratory tract disease from Chlamydia . Such infections can be treated with erythromycin .

Another chlamydial organism, Chlamydophila psittaci , produces psittacosis , a disease that results from exposure to the discharges of infected birds. The illness is characterized by high fever with chills, a slow heart rate , pneumonia, headache , weakness, fatigue , muscle pains, anorexia , nausea, and vomiting. The diagnosis is usually suspected if the patient has a history of exposure to birds. It is confirmed by blood tests. Mortality is rare, and specific antibiotic treatment is available.

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  • Review Article
  • Published: 13 October 2021

Infectious disease in an era of global change

  • Rachel E. Baker   ORCID: orcid.org/0000-0002-2661-8103 1 , 2 ,
  • Ayesha S. Mahmud 3 ,
  • Ian F. Miller   ORCID: orcid.org/0000-0002-2673-9618 1 , 4 ,
  • Malavika Rajeev 1 ,
  • Fidisoa Rasambainarivo 1 , 2 , 5 ,
  • Benjamin L. Rice 1 , 6 ,
  • Saki Takahashi 7 ,
  • Andrew J. Tatem 8 ,
  • Caroline E. Wagner 9 ,
  • Lin-Fa Wang   ORCID: orcid.org/0000-0003-2752-0535 10 , 11 ,
  • Amy Wesolowski 12 &
  • C. Jessica E. Metcalf 1 , 13  

Nature Reviews Microbiology volume  20 ,  pages 193–205 ( 2022 ) Cite this article

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  • Infectious diseases
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The twenty-first century has witnessed a wave of severe infectious disease outbreaks, not least the COVID-19 pandemic, which has had a devastating impact on lives and livelihoods around the globe. The 2003 severe acute respiratory syndrome coronavirus outbreak, the 2009 swine flu pandemic, the 2012 Middle East respiratory syndrome coronavirus outbreak, the 2013–2016 Ebola virus disease epidemic in West Africa and the 2015 Zika virus disease epidemic all resulted in substantial morbidity and mortality while spreading across borders to infect people in multiple countries. At the same time, the past few decades have ushered in an unprecedented era of technological, demographic and climatic change: airline flights have doubled since 2000, since 2007 more people live in urban areas than rural areas, population numbers continue to climb and climate change presents an escalating threat to society. In this Review, we consider the extent to which these recent global changes have increased the risk of infectious disease outbreaks, even as improved sanitation and access to health care have resulted in considerable progress worldwide.

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Introduction.

In premodern times, colonization, slavery and war led to the global spread of infectious diseases, with devastating consequences (Fig.  1a ). Human diseases such as tuberculosis, polio, smallpox and diphtheria circulated widely, and before the advent of vaccines, these diseases caused substantial morbidity and mortality. At the same time, animal diseases such as rinderpest spread along trade routes and with travelling armies, with devastating impacts on livestock and dependent human populations 1 . However, in the past two decades, medical advances, access to health care and improved sanitation have reduced the overall mortality and morbidity linked to infectious diseases, particularly for lower respiratory tract infections and diarrhoeal disease (Fig.  1d ). The swift development of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine speaks to the efficacy of modern science in rapidly countering threats from emerging pathogens. Nevertheless, infectious disease burden remains substantial in countries with low and lower-middle incomes, while mortality and morbidity associated with neglected tropical diseases, HIV infection, tuberculosis and malaria remain high. Moreover, deaths from emerging and re-emerging infections, in comparison with seasonal and endemic infections, have persisted throughout the twenty-first century (Fig.  1c ). This points to a possible new era of infectious disease, defined by outbreaks of emerging, re-emerging and endemic pathogens that spread quickly, aided by global connectivity and shifted ranges owing to climate change (Fig.  1d ).

figure 1

a | Examples of epidemic periods associated with different eras of human transportation (land, maritime and air travel) are shown. Overland trade networks and war campaigns are thought to have contributed to multiple epidemics in the Mediterranean in late classical antiquity (green), beginning with the Antonine plague, which reportedly claimed the life of the Roman emperor Lucius Verus 125 , 126 , 127 , 128 . Maritime transportation (red and grey) leading to European contact with the Americas and the subsequent Atlantic slave trade resulted in the importation of Plasmodium falciparum malaria and novel viral pathogens 129 . In modern times, air travel (purple) resulted in the importation of severe acute respiratory syndrome (SARS) coronavirus to 27 countries before transmission was halted 130 . b | In recent years, increases in air travel, trade and urbanization at global (left) and regional (right) scales have accelerated, indicating ever more frequent transport of people and goods between growing urban areas (source World Bank ). c | Log deaths from major epidemics in the twenty-first century (source World Health Organization ). d | Disability-adjusted life years lost from infectious diseases (source Our World in Data ). MERS, Middle East respiratory syndrome; NTD, neglected tropical disease.

Here, we review how recent anthropogenic climatic, demographic and technological changes have altered the landscape of infectious disease risk in the past two decades. In terms of climate change, we consider both the influence of recent warming and projected future changes. For demographic change, we include trends such as urbanization (Fig.  1b ), population growth, land-use change, migration, ageing and changing birth rates. For technological changes, we primarily consider advances that enable cheaper, faster global travel and trade (Fig.  1b ), as well as improved health care. We do not explicitly address economic change; however, economic changes, including economic development, are crucial drivers of these three factors: climate, demography and technology. We also do not explicitly discuss natural drivers of pathogen evolution or biological processes unless they interact with human-driven global change.

New infections chart a pathway beginning with emergence, followed by local-scale transmission, movement beyond borders and possible global-scale spread. Global changes may differentially affect the risk of emergence, the dynamics of disease within a local population and the global spread of diseases between populations. We provide an overview of each step, first considering features of recent global change that have altered the risks of spillover of viral, fungal, bacterial and apicomplexan (malaria) infections into human populations, then detailing how spread within human populations, driven by the seasonal dynamics of transmission, may be impacted by global change, of relevance to both emergent and established pathogens. Finally, we consider changes to the drivers of global spread, focusing in particular on travel, migration and animal and plant trade.

Pathogen emergence into human populations

Recent decades have seen repeated pathogen emergence from wild or domestic animal reservoirs into human populations, from HIV-1 and HIV-2, to the 1918 influenza virus, to Middle East respiratory syndrome coronavirus, to SARS-CoV-2 (refs 2 , 3 , 4 ). For a novel pathogen to become a threat to human populations, first, contact between humans and the animal reservoir must occur; the pathogen must either have or evolve (Box  1 ) the capacity for human-to-human transmission 5 ; and finally, this human-to-human transmission must enable expansion of the pathogen’s geographical range beyond the zone of spillover. Recent global changes have affected each of these steps.

Patterns of contact between human and wildlife reservoirs have increased as human populations move into previously unoccupied regions. Population growth and agricultural expansion, coupled with increasing wealth and larger property sizes, are driving factors for these interactions and the resulting habitat destruction. This may occur alongside behaviours that increase the potential for spillover, such as consumption of wild meat 6 , or intensifying contact between wild and domestic animal hosts. For example, Nipah virus has been identified in several bat populations, particularly flying foxes, but in 1999 caused a severe disease outbreak in Malaysia, primarily among pig farmers 7 . It is hypothesized that the spillover of Nipah virus from bats to pigs was driven by three factors related to global change: pig farms expanding into the bat habitat; intensification of pig farming, leading to a high density of hosts; and international trade, leading to the spread of the infection among other pig populations in Malaysia and Singapore 8 . Expanding agriculture and its intensification may create conditions that favour pathogen circulation within domestic animal (or plant) reservoirs via high-density farming practices 9 . Beyond creating opportunities for emergence of problematic livestock pathogens, this could also increase opportunities for evolution of novel variants of risk to humans in domestic animal reservoirs. This may occur alongside increasing risk to workers interacting with animal populations 10 as a result of work practices. Global increase in the demand for and resulting intensification of meat production will importantly drive these processes, and associated use of antibiotics in domestic animals has the potential to select for resistant strains of bacteria with potential to affect human health 11 .

The nature of human populations that are exposed to potential spillover is also changing. For example, the elimination of smallpox led to the cessation of smallpox vaccination, which may have enabled the expansion of monkeypox 12 . More generally, globally ageing populations may provide an immune landscape that is more at risk of spillover, as ageing immune landscapes are less capable of containing infectious agents 13 . The intersection between declining function of immunity at later ages 14 and globally ageing populations may increase the probability of pathogen emergence, but this remains conjectural and an important area for research. The changing global context may allow existing human pathogens to both evolve novel characteristics and expand in scope. Selection for drug resistance now occurs worldwide, and antibiotic resistance has and will evolve repeatedly 15 . As with antibiotic resistance, rapid global spread is commonplace for antimalarial resistance following evolution 16 .

Climate change may play a role in the risk from pathogen spillover. Changing environmental conditions can alter species range and density, leading to novel interactions between species, and increase the risk of zoonotic emergence 17 . A series of compounded environmental factors, including a long period of drought followed by extreme precipitation, is hypothesized to have driven an upsurge in rodent populations causing the emergence of pulmonary hantavirus in 1993 (ref. 18 ). Similarly, evidence suggests that populations of the black flying fox in Australia, a key reservoir of Hendra virus, have moved 100 km southward in the past 100 years owing to climatic changes. This shifting range likely caused Hendra virus to spill over into southern horse populations, and these horses subsequently infected humans 19 , 20 . Patterns of change are likely occurring in other bat populations globally but remain understudied — a clear cause for concern given the crucial role bat populations play as a reservoir host for several high-fatality pathogens 21 .

Rapid rates of urbanization in low-income and middle-income countries, and the increase in populations residing in crowded, low-quality dwellings, have created new opportunities for the emergence of infectious diseases (Fig.  2 ). Urbanization has promoted the emergence and spread of arboviral diseases such as dengue, Zika virus disease and chikungunya, which are transmitted by Aedes aegypti and Aedes albopictus mosquitoes that are well adapted to urban areas 22 , 23 , 24 . Population density appears correlated with the preference of Ae. aegypti for human odour, and hence the evolution of human-biting — the transmission pathway for arboviral disease 24 . However the role of urbanization in vector-borne disease spread is complex: the preference of the Anopheles spp. vector for rural environments may have led to a decline in the prevalence of malaria in urbanizing regions 25 . Nevertheless, dense and highly connected urban areas are potential hot spots for the rapid spread of diseases such as COVID-19 and SARS, and cities can serve as a catalyst for rapid local and global transmission.

figure 2

Interactions between urbanization and infectious disease are complex, with increased urbanization driving both positive and negative changes to global disease burden.

Box 1 Global change and evolution of hosts and pathogens

Mutations constantly arise in the genomes of all species, from viruses to elephants. Some genetic changes may have no observable effects on fitness (and thus will be selectively neutral), but can be used to track pathogen spread; for example, to trace the impacts of global connectivity on an outbreak 70 . Some genetic changes will affect disease phenotypes, potentially increasing the transmissibility, virulence or immune escape of a pathogen lineage 133 . The degree to which such mutations increase in frequency or spread geographically will depend on the degree to which they increase fitness, as well as pathogen population dynamics, which may be modulated by the global change context. Increases in the density and geographical distribution of susceptible hosts (whether they be people, crops or livestock) may provide greater opportunity for novel variants to emerge 9 simply by amplifying pathogen populations and thus circulating mutations. While understanding the nuance of cross-scale selection (that is, how the selective context of the individual host translates into the selective context at the scale of populations) remains a challenging frontier 134 , it is likely that ageing populations or the presence of immunosuppressive pathogens might further modulate selection pressures. Indeed, it has been suggested that the emergence of more transmissible or less immune-vulnerable variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was enabled in part by selection processes occurring during chronic infections in immunosuppressed individuals 135 . Greater global connectivity leads to more frequent exchange of this genetic material between populations of the same or different species, potentially leading to the erosion of evolved or engineered host resistance and increased rates of pathogen evolution 136 . Associated spillover followed by spillback can create scenarios that facilitate amplification and potentially selection of problematic pathogen variants 137 , an issue highlighted by recent documentation of human to mink to human transmission of SARS-CoV-2 (ref. 138 ). Likewise, increased rates of pathogen importation provide increased opportunities for pathogen populations to evolve the ability to utilize novel vectors (as has been observed in the Americas for malaria 129 ). Increased population connectivity can also enable pathogens and their vectors to shift to novel host species, from infected mosquitoes travelling on boats or in planes to agricultural pathogens being inadvertently relocated. Hosts that have not previously been exposed to such pathogens, and thus have no co-evolved defences, yet are phylogenetically and/or genetically similar to the original host are often most at risk 139 , 140 , a fact that makes homogenization of crops 141 or livestock a concern. Novel pathogen introductions can have large-scale population and ecosystem impacts, of which one famous example is the extirpation of the American chestnut tree by chestnut blight 142 . Changes in selection pressure resulting from changes in health-care strategies (for example, introduction of vaccination) may have the potential to select for different pathogen characteristics, and could potentially drive the evolution of virulence in pathogens 143 , 144 .

Local-scale disease dynamics

Emerging, re-emerging and endemic pathogens in human populations may exhibit distinct dynamic patterns of spread at the local scale. These patterns will be governed by demographic factors, including the effects of human behaviour on transmission (for example, school terms drive transmission of many childhood infections 26 and sex-specific travel patterns may result in higher burdens of chikungunya in women in Bangladesh 27 ) and immunity (which, for immunizing infections such as measles and rotavirus infection, is, in turn, shaped by replenishment of susceptible individuals via births 28 , 29 and depletion by vaccination where vaccines are available 30 ). Transmission may also be affected by climatic variables acting spatially or over the course of the year in line with seasonal fluctuations 31 , 32 . Recent global changes have affected each of these drivers of local-scale dynamics (Fig.  3 ).

figure 3

The table summarizes select recent global changes (rows) and their impacts on disease emergence, local-scale dynamics and global spread (columns). An example susceptible ( S ), infected ( I ), recovered ( R ) model is shown, where β represents the transmission rate and γ is the recovery rate.

As school attendance not only modulates transmission of childhood infections 26 but also shapes human mobility 33 , dramatic increases in rates of school attendance globally thus have the potential to substantially alter the dynamics of many infections. That this has yet to be documented is perhaps in part because this change has happened alongside expansion of access to vaccines that protect children against many of the relevant infections, as well as global declines in birth rates, which also facilitate control efforts by diminishing the size of the susceptible pool 34 . If the burden of disease is age specific, the intersection between immunity and shifting demography may be particularly marked: declining birth rates translate into a smaller pool of susceptible individuals and thus infected individuals, reducing the overall rate at which susceptible individuals become infected, and thus increasing the average age of infection or disease, as reported for dengue in Thailand 35 and rubella in Costa Rica 36 as these countries went through the demographic transition. Conversely, ageing populations may increase transmission; for example, longer shedding has been suggested with increasing age for SARS-CoV-2 (ref. 37 ).

Demographic changes to population size and density via urbanization may also affect dynamics. Influenza, for example, tends to exhibit more persistent outbreaks in more populous, denser urban regions 38 (Fig.  2 ). A similar pattern was reported in the early COVID-19 pandemic 39 . If demographic change has importantly altered the context of infectious diseases in recent years, arguably an even larger effect is caused by changes in the occurrence of immunomodulatory infections, which, in turn, may affect other infections. For example, the emergence of HIV has amplified the burden of tuberculosis 40 . Mass drug administration efforts have reduced helminth prevalence, which will have knock-on effects on the burden of other infections, such as malaria, which may be increased in individuals experiencing a heavy worm burden 41 ; both will also intersect with the efficacy of vaccination programmes 42 .

The climate plays a key role in driving the local-scale seasonal dynamics of many infectious diseases, which may thus be altered by global change in climatic conditions 43 , 44 . Considering these impacts requires recognizing that interactions with climate differ by pathogen type. For directly transmitted infections, the role of climate is revealed by marked latitudinal gradients in epidemic timing 32 , 45 . Several respiratory pathogens, including influenza virus, are more highly seasonal in temperate climates and exhibit greater year-round persistence in tropical locations 32 , 46 . Climate change is expected to lead to an expansion of these tropical patterns, with possible implications for pathogen evolution 43 , 47 . At the individual level, susceptibility to respiratory viral infections may be impacted by exposure to local air pollution, which is a concern for rapidly urbanizing locations, where urban air pollution may disproportionately affect low-income communities and communities of colour 48 , 49 . For example, non-Hispanic Black and Hispanic populations in the USA were found to have higher exposure to certain PM 2.5 components than non-Hispanic white populations 49 . At the same time, globally, a move to an urban location may bring benefits in terms of increased access to health care (Fig.  2 ).

For some bacterial and fungal diseases, climatic changes may affect the pathogen’s environmental reservoir. Incidence of coccidioidomycosis (valley fever), caused by inhalation of fungal spores of Coccidioides spp., is expected to increase with climate change as the region with optimal conditions for fungal spore production expands 50 . Climate change may also have played a role in the emergence of the drug-resistant fungal pathogen Candida auris . C. auris emerged in several continents at the same time and has been shown to have increased thermotolerance compared with other closely related fungal species, which perhaps evolved in response to global warming 51 , 52 . This increased thermotolerance may have enabled the pathogen to jump from its environmental habitat into an intermediary avian host, given the higher body temperatures of avian fauna, before infecting humans 52 .

Demographic change and technological changes may alter a host’s interaction with the environmental reservoir. Cholera, caused by the bacterial pathogen Vibrio cholerae , persists in the environment, particularly in aquatic settings. Changes to environmental conditions, including elevated sea temperatures, lead to increased reproduction of the pathogen and local epidemics 53 , with clear links to longer-term climate phenomena such as El Niño 54 . However, improved sanitation lowers the risk of exposure to V. cholerae and has led to a decline of the disease in many locations 53 .

For vector-transmitted diseases, biological traits of both the vector and the pathogen may be sensitive to climate. Many transmission-related life cycle traits of the mosquito (biting rate, adult lifespan, population size and distribution) and the pathogen (extrinsic incubation rate) are temperature sensitive, and oviposition patterns depend on water availability 55 . Consequently, the geographical range for dengue, malaria and other vector-borne diseases 56 , 57 , 58 is affected by the local climate, and there is substantial effort to understand how these ranges may change with climate change 59 , 60 , 61 . For certain vector-borne diseases such as Zika virus disease, climate change may lead to an expanded range 62 . However, for other diseases, such as malaria, climate change may shift the spatial range of the infection to higher latitudes 63 . As ever, the footprint of human interventions may loom larger than these changes in local conditions 25 .

At the local scale, one of the strongest footprints detectable on the dynamics of many endemic infections in recent years is declines in incidence associated with access to vaccinations 64 . However, the introduction of a vaccine does not imply immediate elimination. As vaccination coverage increases, measles outbreaks, for instance, follow a pathway towards elimination defined by declines in mean incidence but high variability in outbreak size 34 . Imperfect vaccine coverage may allow population susceptibility to increase such that substantial outbreaks can occur if the disease is reintroduced; for example, the 2018 measles outbreak in Madagascar, which led to more than 100,000 cases 65 . Improved surveillance of the landscape of population immunity, via serological surveys, could help determine gaps in vaccination coverage 66 .

Global spread

As local conditions alter demographically, or as a result of climate change potentially expanding the range of locations suitable to a particular pathogen or vector, increased global connectivity will enable pathogens to reach these new environments more rapidly (Figs  3 , 4 ). Here, we review the impact of global change on three forms of global connectivity — international travel, human migration and local-scale mobility, and the international trade of animals, animal products and plants — while considering the impact on infectious disease risk. Technological change over the past two decades has dramatically lowered the cost of international travel, while demographic change has led to heightened demand for inexpensive flights (Fig.  1b ). Demographic and climatic drivers have altered patterns of local mobility and regional migration, while rising demand and technological change have increased the trade of plants and animals. At the same time, an increasingly urban population is better connected than ever before to global travel networks (Fig.  4 ). These changes to global connectivity will present unique risk factors for infectious disease spread, enabling pathogens to travel further and faster than ever before.

figure 4

a | The global international air travel network expanded substantially from 1933 to 2020 (data from WorldPop and ref. 131 ). b | Average monthly maximum temperature in 1970–2000) and difference between 2070–2100 and 1970–2000 averages (data from WorldClim , Shared Socioeconomic Pathway 3 (SSP3)). c | Population projections under SSP3 in 2010 and relative population change projected until 2100 (source NASA Socioeconomic Data and Applications Center (ref. 132 )). Part a adapted with permission from ref. 131 , OUP.

International travel

The late twentieth century and the early twenty-first century have been marked by technological developments enabling ever swifter movement of people and pathogens over large distances — from trains to planes, and an expanding international airline network (Fig.  4 ). The total number of airline passengers doubled from just below two billion in 2000 to more than four billion in 2019 (Fig.  1b ). This rampant increase in global connectivity brings with it new risks from emerging pathogens (Box  2 ). However, many endemic pathogens also circulate via transit routes: seasonal influenza circulation in the USA can be predicted by flight patterns 67 , 68 , with evidence that flight bans following the events of 9/11 caused a delayed outbreak, and a prolonged influenza season within the USA as measured by a 60% increase in the time to transnational spread 68 . Similarly, rapid global air travel is expected to have played a key role in the global spread of SARS-CoV-2. Genetic analyses demonstrate multiple introductions of SARS-CoV-2, driven by air travel, in the Middle East 69 , northern California 70 and Brazil 71 .

International travel can lead to the global spread of vector-borne diseases via the introduction of new vectors into regions with suitable environmental conditions or the introduction of new pathogens into native and invasive vector populations. Historically, vectors have been introduced via trade routes: ships are thought to have been key to the global dispersal of Ae. aegypti and Ae. albopictus , which then became established in locations with appropriate environmental conditions 72 , 73 . Anopheles gambiae , the primary vector of malaria in Africa, was introduced into Brazil in the 1930s and became established in a region with a climate similar to that of its native Kenya 74 . Although malaria was already endemic in Brazil at the time, An. gambiae proved a much more effective vector, leading to a severe outbreak and a costly (but successful) eradication campaign 73 . There has been relatively little documented evidence of the introduction of new vectors via air travel. This is likely due to the low probability of vectors surviving the flight, and disembarking in a suitable region, in sufficient numbers to establish and drive an epidemic 75 . However, cases of ‘airport malaria’, that is, malaria transmitted within international airports, even outside endemic regions, are rare but becoming more common 76 .

A more feasible scenario is that air travel can bring an infected human host into contact with a native or invasive vector population that then establishes local transmission. Climate change has driven a shift in the range of several key vectors, which may make this introduction more likely. The range of the biting midge Culicoides imicola , a vector of bluetongue virus, which causes disease in ruminants, has expanded over the past few decades from sub-Saharan Africa and the Middle East into Europe, bringing a wave of bluetongue epidemics 77 . Following this expansion, bluetongue virus then spread outside the range of C. imicola into native populations of Culicoides spp. in more northerly regions of Europe. In terms of air travel, the 2015 Zika virus disease epidemic in the Americas may provide a recent example of a pathogen spreading into a susceptible vector population, likely facilitated by high connectivity 78 . Zika virus is thought to have been introduced to Brazil from French Polynesia and vectored by Aedes spp., although the volume of air travel during this period makes it almost impossible to conclusively determine the origin 78 . Similarly, it is hard to pinpoint the pathway via which West Nile virus was introduced into the USA in the 1990s; however, transport by either shipping (transporting vectors) or aircraft (transporting a human host) is likely 79 . After introduction, West Nile virus spread in the native Culex spp. mosquito population. More broadly, climate change complicates the picture in terms of possible future introductions. As the range of locations with environmental suitability for certain vector species changes, successful introductions of pathogens into these vector populations may become more likely 80 . At the same time, changes to population structure (for example, via urbanization) may alter the suitability of an environment for vector reproduction (Fig.  2 ).

Box 2 Will there be another pandemic like COVID-19?

COVID-19 has had an unprecedented impact on both human lives and our society, and we will likely be dealing with the consequences for decades to come. As we reckon with these consequences, one concern is that a suite of global changes has increased the risk from emerging pathogens, such that pandemics similar to COVID-19 could be a more frequent occurrence. However, there are biological features of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that have made the pathogen distinctly difficult to control, primarily the virus’s ability to spread asymptomatically and presymptomatically. Many pathogens do not exhibit these features, which may be a cause for cautious optimism going forward.

The expansion of regional and global air travel, along with the increasing development of high-speed railway networks, has resulted in a substantial degree of connectivity between human populations 73 . At the same time, land-use change and climate change may have increased the risk of pathogen emergence. In combination, these drivers imply an era where pathogens are more likely to emerge, and more likely to spread globally on emergence. However, while the last century bore witness to several pandemics (Fig.  1 ), SARS-CoV-2 is unrivalled in its rapid, global reach. A key question is why SARS-CoV-2 was so successful at spreading globally and whether this was due to recent increases in global connectivity as opposed to epidemiological and biological characteristics of the virus itself 145 .

A clear distinction between SARS-CoV-2 and other recently emerged pathogens (for example, SARS-CoV and Ebola virus) is that an individual infected with SARS-CoV-2 may become infectious before developing symptoms 146 . This presents a unique challenge from a disease control perspective. A standard approach for limiting the onward spread of a new outbreak is to isolate infected individuals when they show symptoms. Case isolation proved successful in mitigating earlier SARS 147 and Ebola virus disease 148 outbreaks. However, symptoms for SARS-CoV-2 infection likely occur after an individual is already infectious 146 . This possible presymptomatic spread limits the efficacy of case isolation interventions as by the time the infected individual is isolated, the person may have already spread the pathogen to others 149 . In the figure, we plot the time to infectiousness (latent period) against the time to symptom onset (incubation period) for four pathogens that have caused severe outbreaks in recent decades. When the latent period equals the incubation period (dashed line in the figure), symptoms occur at a similar time to infectiousness (for example, influenza). The shaded region to the right of this line in the figure indicates possible presymptomatic spread, which may be uniquely difficult to control.

The 2–3-day delay between infectiousness and symptom onset provides ample time for long-distance spread of the disease, given current transport networks (see the figure). Control policies, such as testing before travel, provide a more effective option in this context, yet developing and distributing a test takes time, during which time the disease may spread rapidly. The good news is that this presymptomatic spread appears somewhat unique to SARS-CoV-2, at least compared with other acute infections such as influenza, SARS and Ebola virus disease (Fig.  4 ). In comparison, asymptomatic spread explains some of the difficulty in controlling acquired immunodeficiency syndrome before antiretroviral measures were available.

different types of infectious diseases essay

Migration and local mobility

Human migration is an intrinsic component of population dynamics driven by socio-economic, political and environmental factors, and one that has undergone considerable upheaval in the modern era. It is estimated that globally the number of international migrants, those who intentionally relocate to a country other than their birth country, is almost 272 million, representing 3.5% of the world’s population. By contrast, temporary migration, often considered ‘seasonal migration’, is driven largely by economic patterns, including agricultural seasons that require short periods of intense labour. The rate of migration continues to increase owing to both social, economic, political and environmental drivers in origin countries and economic opportunities, physical safety and security in destination countries. Projections for migration are unclear, with the UN projecting stable rates after 2050 (ref. 81 ). However, climate change will likely provide an escalating push factor, with sea level rise and extreme weather events leading to forced migration from exposed regions 82 .

Given the movement of people between countries, there remain risks of introduction of infectious diseases, including those common and uncommon in the country of migration 83 . It is possible for a infectious disease common in the source country, such as latent tuberculosis, malaria, viral hepatitis and infection with intestinal parasites, to be imported via this mechanism 84 , 85 , 86 . For example, in many destination countries, a large proportion of cases of tuberculosis are observed in the foreign-born population. However, the ultimate impact of these introduction events will depend largely on the population-level susceptibility and environmental suitability for sustained transmission in the destination country. More importantly, migrant groups often have more limited access to health care, treatment and resources, particularly those displaced, who are often provided with limited options to safely seek care and treatment 87 . Minimizing the impact of these possible disease threats depends on providing appropriate health care to these high-risk groups that takes into account the multifaceted social, political and economic components 88 .

Within-country population mobility can also play a key role in disease spread; however, it is typically difficult to track these movements. Aggregated mobile phone data are a valuable tool for tracing patterns of local mobility and predicting future outbreaks 89 . In recent work, mobility data have been shown to be predictive of inequities in COVID-19 burden in the USA 90 . Similarly, population mobility was found to predict the spread of the 2011 dengue epidemic in Pakistan 91 , while local travel following the Eid holidays was found to predict the spread of the chikungunya outbreak in 2017 in Bangladesh 92 . As the trend of urbanization continues, mobility to and from dense urban centres (that is, megacities) will likely play a future role in local spread of infections 92 . Better tracking of within-country population mobility, using novel data streams, may present an opportunity for forecasting future outbreaks 93 .

Intensification of animal and plant trade

International trade has expanded rapidly in the modern era and has been matched by a global proliferation of infectious diseases affecting not only humans but also animals and plants 94 , 95 . Trade drives this pattern by facilitating the translocation of hosts and pathogens across the geographical and ecological boundaries that constrain their spread. The economic and environmental threats posed by trade-driven infectious diseases of plants and animals are increasingly being recognized, and calls for more stringent containment measures have intensified in recent years 96 , 97 .

Plant trade

Deliberate transport of plant products has existed since the emergence of trade. Increases in the speed of transport during modern times have allowed more live plant tissue, and as a result more viable pathogen propagules , to be transported over long distances. Combined with the intensification of trade at the global scale, this pattern has driven a rise in long-distance transmission and disease emergence 98 , 99 . Trade drives the emergence of novel plant diseases by creating novel interactions between hosts and pathogens 100 . One pathway through which this can occur is the introduction of novel pathogens to native plants. For example, Xylella fastidiosa , a generalist bacterium vectored by xylem-feeding insects, was introduced into Europe in 2013 from the USA, likely as a result of trade. In Italy, X. fastidiosa is causing an ongoing epidemic of ‘olive quick decline syndrome’, resulting in severe losses of an economically and culturally important crop 101 , 102 . Trade can also drive the emergence of plant disease by introducing novel hosts to native pathogens. Eucalyptus rust, a disease caused by the fungal pathogen Austropuccinia psidii , emerged when the pathogen transferred from its native South American hosts in the myrtle family (Myrtaceae) to non-native Eucalyptus trees (which also belong to the myrtle family) being grown on plantations 103 . The disease now threatens to ‘spill back’ into naive endemic Eucalyptus populations in Australia.

Animal and animal-product trade

Animal trade has contributed to multiple outbreaks and emergence events globally, which have had major consequences for the agricultural sector as a whole and pose substantial risk for animal and public health. Large numbers of livestock are traded annually between countries and may facilitate the spread of pathogens. Rift Valley fever, for example, is a zoonotic vector-borne viral disease causing abortion and high neonatal mortality in domestic ruminants. The disease is widespread on the African continent and has recently been detected in Saudi Arabia and Yemen. Live cattle movement between East Africa and the Arabian peninsula or from the Union of Comoros to Madagascar is thought to have contributed to the introduction of Rift Valley fever virus and caused outbreaks in these locations in 2000 (Arabian Peninsula) and 2008 (Madagascar) 104 , 105 .

Additionally, the trade of animal-derived products such as meat may enable the movement of pathogens over large distances and between continents. For instance, African swine fever is a highly contagious viral disease affecting several members of the family Suidae, including domestic pigs and wild boars. Infection by African swine fever virus may result in up to 100% morbidity and mortality in affected pig herds and substantial economic losses for producers. In 2007, the accidental introduction of African swine fever virus to Georgia led to the first outbreak of African swine fever in Europe since the early 1990s 106 . The virus, which used to occur primarily in sub-Saharan Africa, was allegedly introduced to the Caucasian peninsula through meat products contaminated with viruses closely related to the ones found in Madagascar, Mozambique or Zambia 107 . Despite efforts to contain the virus, the disease has spread to more than 20 countries in Europe and Asia 108 , 109 .

Similarly, in recent decades there has been an expansion in infections of Vibrio parahaemolyticus — a bacterial pathogen found in shellfish and the leading cause of seafood-related illness globally. The pathogen is endemic to regions of the US Pacific Northwest but has recently spread to other parts of the USA, Europe and South America 110 , 111 . The concerning increase in V. parahaemolyticus infection is expected to have several drivers connected to global change. Declines in sea ice have increased ship traffic through the Bering Strait, with cargo ships possibly transporting V. parahaemolyticus in ballast water. At the same time, increasing sea temperatures may have increased the global environmental suitability for V. parahaemolyticus in the marine environment 110 . Finally, dispersal of the pathogen may have occurred via increasing global trade in shellfish, with evidence suggesting possible dispersal via Manila clams introduced into Spain from Canada 111 . This combination of possible drivers speaks to the complexity of understanding infectious disease risk in an era of global change, and the necessity of exploring concurrent changes.

Transboundary spread of diseases through legal and illegal trade of live animals may also have important consequences for biodiversity on a global scale. For example, the amphibian trade contributed to the expansion of novel strains of the fungal pathogen genus Batrachochytrium into naive hosts, devastating wild amphibian populations globally 112 . Conversely, infectious diseases also hamper trade, resulting in indirect economic losses in affected populations. Foot and mouth disease virus is a major reason for trade restrictions on livestock. While endemic in certain countries in Asia and Africa, foot and mouth disease virus causes outbreaks in naive populations, resulting in large economic losses 113 . While trade is a major driver of pathogen spread, food animal production has transformed in recent history into large-scale intensified systems with high-density, genetically homogenous populations, ideal for pathogen emergence and maintenance 114 . Critically, animal production systems often serve as the interface between wild and human populations, and multiple viral spillover events have occurred at this nexus. Nipah virus spilled over from fruit bats to the domestic pig population multiple times before subsequently infecting humans 115 . Pandemic variants of human influenza A virus are often the result of reassortment between human and avian viruses, with both domestic poultry and wild birds posited to play a role 116 , 117 , 118 . A non-viral example is the spillover of antimicrobial-resistant pathogens from livestock into humans: intensive antibiotic use in industrialized and smallholder livestock production systems to promote growth and prevent infections has been linked to the emergence of antibiotic resistance in humans 119 . Tackling emergence and disease spread in animal systems will require rethinking both food animal production and global trade of animals.

A new era of infectious disease

In recent decades, declines in mortality and morbidity, particularly childhood mortality, have been one of the great triumphs of public health. Greater access to care, such as therapeutics (including antibiotics), improved sanitation and the development of vaccines 120 have been core drivers of this progress. Even as medical advances in the twenty-first century have spurred advances in population health, inequalities in access to these advances remain widespread between and within countries 121 . Reducing inequities in access to health care and improving surveillance and monitoring for infectious diseases in low-income and middle-income countries, and in underserved populations within countries, should be a priority in tackling pathogen emergence and spread.

While life expectancy continues to increase, and life years lost to infectious diseases decline, the new threat of infectious disease will likely come from emerging and re-emerging infections. Climate change, rapid urbanization and changing land-use patterns will increase the risk of disease emergence in the coming decades. Climate change, in particular, may alter the range of global pathogens, allowing infections, particularly vector-borne infections, to expand into new locations. A continued uptick in global travel, trade and mobility will transport pathogens rapidly, following emergence. However, there are counterpoints to this trend: the rapid growth of connectivity observed in the early twenty-first century may stabilize, and structural changes wrought during the COVID-19 pandemic may persist 122 . Increased investment in outbreak response, such as the recent formation of the WHO Hub for Pandemic and Epidemic Intelligence, could help mitigate the threat from future emerging infections. In addition, efforts to develop universal vaccines (that is, vaccines that engender immunity against all strains of influenza viruses or coronaviruses, for example) could provide a monumental leap forward in tackling present and future infections 123 .

A changing world requires changing science to evaluate future risks from infectious disease. Future work needs to explicitly address concurrent changes: how shifting patterns of demographic, climatic and technological factors may collectively affect the risk of pathogen emergence, alterations to dynamics and global spread. More forward-looking research, to contend with possible future outcomes, is required in addition to the retroactive analyses that typically dominate the literature. Increasing attention needs to be paid to pathogens currently circulating in both wild and domestic animal populations, especially in cases where agriculture is expanding into native species’ habitats and, conversely, invasive species are moving into populous regions due to climate change. As the battle against certain long-term endemic infections is won, institutional structures built to address these old enemies can be co-opted and adapted for emerging threats. At the same time, new technologies, including advances in data collection and surveillance, need to be harnessed (Box  3 ). There is much recent innovation around surveillance, from reinterpreting information available from classic tools such as PCR 124 to leveraging multiplex serology approaches to identify anomalies that might suggest pathogen emergence, and there is increasing interest in integrating multiple surveillance platforms (from genomic to case data) to better understand pathogen spread. Finally, future research needs to align with a global view of disease risk. In an increasingly connected world, the risk from infectious disease is globally shared. The COVID-19 pandemic, including the rapid global circulation of evolved strains, highlights the need for a collaborative, worldwide framework for infectious disease research and control.

Box 3 Big data for disease

Recent technological advances in collecting, sharing and processing large datasets, from satellite images to genomes, represent a new opportunity to answer critical questions in global health. However, challenges remain, including the uneven geographical distribution of available data as well as biases in representative sampling. We highlight three areas of future growth.

Serological surveys

Serological surveys detect the presence of antibodies in blood — recent advances in testing now enable the detection of exposure to multiple pathogens with use of a small sample of blood 150 . Serological surveys have attracted attention during the COVID-19 pandemic as a means to track population exposure given under-reporting, although test performance characteristics differ widely between epidemiological contexts as well as the choice of assay used 151 . Historically, serological surveys have been financially and logistically expensive to run, but declining costs are leading to increased availability of serological data.

Genomic surveillance systems

Genomic surveillance systems are able to characterize and track the emergence of novel variants (for example, during the COVID-19 pandemic). Undoubtedly these data have enabled the rapid development of diagnostics and vaccines and, when combined with epidemiological information, are able to provide a more detailed picture of ongoing transmission dynamics. Efforts to develop national and international genomic surveillance networks are varied but with clear success stories 152 , 153 even in low-resources settings 154 . However, resource limitations, including sequencing platforms, bioinformatic pipelines and the regular collection of samples for processing, continue to limit the global expansion of sequencing.

Artificial intelligence and machine learning

These techniques are frequently proposed as tools for answering key public health questions, yet specific use cases remain elusive 155 . Using these tools to predict viral emergence, for example, may prove difficult due to microbiological complexities and the cost of data collection 156 , yet could prove valuable for targeting sampling efforts 157 . In terms of uncovering population-level drivers of disease transmission, statistical approaches, including machine learning, can be used to leverage novel, and high-volume, data streams. However, more classical, mechanistic models may provide a more robust framework for projecting future outcomes for the disease system under demographic, technological and climatic change. Future work should aim to improve the integration of machine learning approaches within the traditional mechanistic modelling frameworks to rapidly and accurately assess prospective challenges.

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Acknowledgements

R.E.B. is supported by the Cooperative Institute for Modelling Earth Systems. R.E.B., C.J.E.M. and F.R. are supported by the High Meadows Environmental Institute at Princeton University. A.W. is supported by the US National Institutes of Health through the National Library of Medicine (DP2LM013102) and the National Institute of Allergy and Infectious Diseases (1R01A1160780-01) and a Career Award at the Scientific Interface from the Burroughs Wellcome Fund. Research in the L.-F.W. group is supported by grants from the Singapore National Research Foundation (NRF2012NRF-CRP001-056 and NRF2016NRF-NSFC002-013), the National Medical Research Council of Singapore (MOH-OFIRG19MAY-0011, COVID19RF-003 and NMRC/BNIG/2040/2015) and the Ministry of Education, Singapore (MOE2019-T2-2-130). A.J.T. is supported by the Bill & Melinda Gates Foundation (INV-024911). S.T. is supported by the Schmidt Science Fellows programme, in partnership with the Rhodes Trust.

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A correlated series of climate events associated with the warm phase of the El Niño Southern Oscillation cycle.

Pathogen units responsible for infection, such as a fungal spore or viral particle.

The mixing of genetic material of different pathogens within an infected cell.

The measurement of antibody responses to multiple pathogens simultaneously.

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Baker, R.E., Mahmud, A.S., Miller, I.F. et al. Infectious disease in an era of global change. Nat Rev Microbiol 20 , 193–205 (2022). https://doi.org/10.1038/s41579-021-00639-z

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Introduction to Infectious Diseases

credit-expose

Infectious diseases are disorders that are caused by organisms, usually microscopic in size, such as bacteria, viruses, fungi, or parasites that are passed, directly or indirectly, from one person to another. Humans can also become infected following exposure to an infected animal that harbors a pathogenic organism that is capable of infecting humans.

Infectious diseases are a leading cause of death worldwide, particularly in low-income countries, especially in young children.

In 2019, two infectious diseases - lower respiratory infections and diarrheal diseases - were ranked in the top ten causes of death worldwide by the World Health Organization (WHO). Both of these diseases can be caused by a variety of infectious agents.

Deaths from the infectious diseases  HIV/AIDS  and  tuberculosis  have fallen significantly in recent years, and they no longer appear on the list of top ten causes of death globally. However, these diseases are still a leading cause of death in low-income countries. Malaria is another infectious disease that is a top cause of death in low-income countries. These three diseases are due to single infectious agents. 

A newly emerged infectious disease, COVID-19 , caused by the virus SARS-CoV-2, became a top cause of death in 2020. According to data analyzed by the Centers for Disease Control and Prevention (CDC), COVID-19 was listed as the third leading cause of death during 2020 in the United States, behind heart disease and cancer.

1

Heart disease

Neonatal conditions

Heart disease

2

Stroke

Alzheimer's disease

3

Chronic obstructive pulmonary disease

Heart disease

Stroke

4

Stroke

Lung cancers

5

Neonatal conditions

Chronic obstructive pulmonary disease

6

Lung cancers

7

Alzheimer's disease

Road injury

Colon cancers

8

Kidney diseases

9

Diabetes

Hypertensive heart disease

10

Kidney diseases

Cirrhosis of the liver

Diabetes

Source; WHO

Agents that Cause Infectious Diseases

Scanning electron micrograph image depicting numerous clumps of methicillin-resistant Staphylococcus aureus bacteria; Magnified 9560x.

Infectious diseases can be caused by several different classes of pathogenic organisms (commonly called germs). These are viruses , bacteria , protozoa, and fungi. Almost all of these organisms are microscopic in size and are often referred to as microbes or microorganisms .

Although microbes can be agents of infection, most microbes do not cause disease in humans. In fact, humans are inhabited by a collection of microbes, known as the microbiome , that plays important and beneficial roles in our bodies.

The majority of agents that cause disease in humans are viruses or bacteria, although the parasite that causes malaria is a notable example of a protozoan.

Examples of diseases caused by viruses are COVID-19 ,  influenza , HIV/AIDS , Ebola ,  diarrheal diseases , hepatitis, and West Nile. Diseases caused by bacteria include anthrax , tuberculosis , salmonella, and respiratory and diarrheal diseases.

Transmission of Infectious Diseases

There are a number of different routes by which a person can become infected with an infectious agent. For some agents, humans must come in direct contact with a source of infection, such as contaminated food, water, fecal material, body fluids or animal products. With other agents, infection can be transmitted through the air.

The route of transmission of infectious agents is clearly an important factor in how quickly an infectious agent can spread through a population. An agent that can spread through the air has greater potential for infecting a larger number of individuals than an agent that is spread through direct contact.

Another important factor in transmission is the survival time of the infectious agent in the environment. An agent that survives only a few seconds between hosts will not be able to infect as many people as an agent that can survive in the environment for hours, days, or even longer. These factors are important considerations when evaluating the risks of potential bioterrorism agents.

Impact of Infectious Diseases on Society

Transmission electron micrograph of Middle East Respiratory Syndrome Coronavirus particles, colorized in yellow.

Infectious diseases have plagued humans throughout history, and in fact have even shaped history on some occasions. The plagues of biblical times, the Black Death of the Middle Ages, and the “Spanish flu” pandemic of 1918 are but a few examples. The 1918 flu pandemic killed more than a half million people in the United States and up to 50 million people worldwide and is thought to have played a contributing role in ending World War I. 

Epidemics and pandemics have always had major social and economic impacts on affected populations, but in our current interconnected world, the impacts are truly global. This has been clearly demonstrated by the COVID-19 pandemic that began in 2020. Infections in one region can easily spread to another. Until the virus can be contained globally, a surge in cases in one area can cause a resurgence of cases in other areas around the world. 

Coronaviruses

Consider the SARS outbreak of early 2003. This epidemic demonstrated that new infectious diseases are just a plane trip away. The virus, SARS-CoV, which caused a severe, and sometimes fatal, respiratory illness emerged in China. Air travelers rapidly spread the disease to Canada, the United States, and Europe. Even though the SARS outbreak was relatively short-lived and geographically contained, the economic loss to Asian countries was estimated at $18 billion as fear inspired by the epidemic led to travel restrictions and the closing of schools, stores, factories, and airports. 

About a decade later, a new SARS-like virus emerged in Saudi Arabia. Named MERS-CoV, the virus causes Middle East respiratory syndrome, or MERS , a severe and often fatal respiratory disease. Infection occurs through direct contact with an infected animal (camel) or person. Even though MERS did not spread easily from person to person, the virus spread to 27 countries in the Middle East, Europe, Asia, and North America, including the United States.

The most recent coronavirus to emerge is named SARS-CoV-2. It causes the disease known as COVID-19 . The effects of COVID-19 pandemic have been felt around the worldwide, with schools and businesses closing, travel restricted, and in some cases even limitations on people leaving their homes. The pandemic has caused major economic hardships, stressed healthcare systems, and impacted mental health. Disagreements within and between countries have arisen in how to respond to the crisis and how to allocate scarce supplies of drugs and vaccines. 

The HIV/AIDS epidemic, particularly in sub-Saharan Africa, illustrates the economic and social impacts of a prolonged and widespread infection. The disproportionate loss of the most economically-productive individuals has reduced workforces and economic growth rates of affected countries, especially those with high infection rates. This impacts the health care, education, and political stability of these nations.

In southern Africa where the infection rate is highest, life expectancy plummeted in a mere decade from 62 years in 1990 -1995 to 48 years in 2000 – 2005. The existence of approximately 18 million children worldwide under that age of 18 that have been orphaned by HIV/AIDS highlights the impact of infectious diseases on families and societies.

Historically, there have been about three to four influenza pandemics each century. The  influenza virus is notable for its ability to change its genetic information. When a new version of the influenza virus arises that has either never circulated in the human population or has not circulated for a very long time (so that most people do not have immunity against the virus), a pandemic can occur. 

There were three influenza pandemics in the 20th century – the “Spanish” flu of 1918-19, the “Asian” flu of 1957-58, and the “Hong Kong” flu of 1968-69 – and one in the 21th century, so far – the 2009 H1N1 “swine flu” pandemic. 

Other influenza variants have emerged in recent decades including the avian H5N1 influenza (or “bird flu”) in 2005 and the H7N9 virus in 2013. The H5N1 virus caused concern because it was so deadly (more than half of the cases were fatal), but it did not spread easily from person to person. Additional novel versions will continue to emerge. The greatest danger would come from a version of the flu virus that is very deadly but is also transmitted readily from one individual to another.

Challenges in Infectious Disease Research

Despite significant advances in infectious disease research and treatment, the control and eradication of these diseases faces major challenges.

A WHO report released in 2007 warns that infectious diseases are spreading more rapidly than ever before and that new infectious diseases are being discovered at a higher rate than at any time in history. In just the past five years, the WHO has identified over 1000 epidemics of infectious diseases including avian flu, swine flu, polio, and cholera.

With greatly increased human mobility, infectious diseases have the potential to swiftly become global epidemics and pandemics.

Some of the reasons for the difficulty in combating infectious diseases are:

  • New infectious diseases continue to emerge
  • Old infectious diseases increase in incidence or geographical distribution
  • Old infectious diseases previously under control begin to re-emerge
  • Potential for intentional introduction of infectious agents by bioterrorists
  • Increasing resistance of pathogens to current antimicrobial drugs
  • Breakdowns in public health systems and communication between nations

The sections on Emerging Infectious Diseases and Bioterrorism Agents further explore these challenges.

For More Information

  • Information about infectious diseases from the National Institutes of Health (NIH)
  • Information about infectious diseases, from the Centers for Disease Control and Prevention (CDC)
  • Information about infectious diseases from the World Health Organization (WHO)
  • Listing of the top ten causes of death compiled by the WHO

Learn more about some of the technical terms found on this page by visiting our glossary of terms.

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Infectious diseases

On this page, when to see a doctor, risk factors, complications, infectious diseases care at mayo clinic.

Our caring teams of professionals offer expert care to people with infectious diseases, injuries and illnesses.

Infectious diseases are disorders caused by organisms — such as bacteria, viruses, fungi or parasites. Many organisms live in and on our bodies. They're normally harmless or even helpful. But under certain conditions, some organisms may cause disease.

Some infectious diseases can be passed from person to person. Some are transmitted by insects or other animals. And you may get others by consuming contaminated food or water or being exposed to organisms in the environment.

Signs and symptoms vary depending on the organism causing the infection, but often include fever and fatigue. Mild infections may respond to rest and home remedies, while some life-threatening infections may need hospitalization.

Many infectious diseases, such as measles and chickenpox, can be prevented by vaccines. Frequent and thorough hand-washing also helps protect you from most infectious diseases.

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Each infectious disease has its own specific signs and symptoms. General signs and symptoms common to a number of infectious diseases include:

  • Muscle aches

Seek medical attention if you:

  • Have been bitten by an animal
  • Are having trouble breathing
  • Have been coughing for more than a week
  • Have severe headache with fever
  • Experience a rash or swelling
  • Have unexplained or prolonged fever
  • Have sudden vision problems

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Infectious diseases can be caused by:

  • Bacteria. These one-cell organisms are responsible for illnesses such as strep throat, urinary tract infections and tuberculosis.
  • Viruses. Even smaller than bacteria, viruses cause a multitude of diseases ranging from the common cold to AIDS.
  • Fungi. Many skin diseases, such as ringworm and athlete's foot, are caused by fungi. Other types of fungi can infect your lungs or nervous system.
  • Parasites. Malaria is caused by a tiny parasite that is transmitted by a mosquito bite. Other parasites may be transmitted to humans from animal feces.

Direct contact

An easy way to catch most infectious diseases is by coming in contact with a person or an animal with the infection. Infectious diseases can be spread through direct contact such as:

Person to person. Infectious diseases commonly spread through the direct transfer of bacteria, viruses or other germs from one person to another. This can happen when an individual with the bacterium or virus touches, kisses, or coughs or sneezes on someone who isn't infected.

These germs can also spread through the exchange of body fluids from sexual contact. The person who passes the germ may have no symptoms of the disease, but may simply be a carrier.

  • Animal to person. Being bitten or scratched by an infected animal — even a pet — can make you sick and, in extreme circumstances, can be fatal. Handling animal waste can be hazardous, too. For example, you can get a toxoplasmosis infection by scooping your cat's litter box.
  • Mother to unborn child. A pregnant woman may pass germs that cause infectious diseases to her unborn baby. Some germs can pass through the placenta or through breast milk. Germs in the vagina can also be transmitted to the baby during birth.

Indirect contact

Disease-causing organisms also can be passed by indirect contact. Many germs can linger on an inanimate object, such as a tabletop, doorknob or faucet handle.

When you touch a doorknob handled by someone ill with the flu or a cold, for example, you can pick up the germs he or she left behind. If you then touch your eyes, mouth or nose before washing your hands, you may become infected.

Insect bites

Some germs rely on insect carriers — such as mosquitoes, fleas, lice or ticks — to move from host to host. These carriers are known as vectors. Mosquitoes can carry the malaria parasite or West Nile virus. Deer ticks may carry the bacterium that causes Lyme disease.

Food contamination

Disease-causing germs can also infect you through contaminated food and water. This mechanism of transmission allows germs to be spread to many people through a single source. Escherichia coli (E. coli), for example, is a bacterium present in or on certain foods — such as undercooked hamburger or unpasteurized fruit juice.

More Information

  • Ebola transmission: Can Ebola spread through the air?
  • Mayo Clinic Minute: What is the Asian longhorned tick?

While anyone can catch infectious diseases, you may be more likely to get sick if your immune system isn't working properly. This may occur if:

  • You're taking steroids or other medications that suppress your immune system, such as anti-rejection drugs for a transplanted organ
  • You have HIV or AIDS
  • You have certain types of cancer or other disorders that affect your immune system

In addition, certain other medical conditions may predispose you to infection, including implanted medical devices, malnutrition and extremes of age, among others.

Most infectious diseases have only minor complications. But some infections — such as pneumonia, AIDS and meningitis — can become life-threatening. A few types of infections have been linked to a long-term increased risk of cancer:

  • Human papillomavirus is linked to cervical cancer
  • Helicobacter pylori is linked to stomach cancer and peptic ulcers
  • Hepatitis B and C have been linked to liver cancer

In addition, some infectious diseases may become silent, only to appear again in the future — sometimes even decades later. For example, someone who's had chickenpox may develop shingles much later in life.

Follow these tips to decrease the risk of infection:

  • Wash your hands. This is especially important before and after preparing food, before eating, and after using the toilet. And try not to touch your eyes, nose or mouth with your hands, as that's a common way germs enter the body.
  • Get vaccinated. Vaccination can drastically reduce your chances of contracting many diseases. Make sure to keep up to date on your recommended vaccinations, as well as your children's.
  • Stay home when ill. Don't go to work if you are vomiting, have diarrhea or have a fever. Don't send your child to school if he or she has these signs, either.

Prepare food safely. Keep counters and other kitchen surfaces clean when preparing meals. Cook foods to the proper temperature, using a food thermometer to check for doneness. For ground meats, that means at least 160 F (71 C); for poultry, 165 F (74 C); and for most other meats, at least 145 F (63 C).

Also promptly refrigerate leftovers — don't let cooked foods remain at room temperature for long periods of time.

  • Practice safe sex. Always use condoms if you or your partner has a history of sexually transmitted infections or high-risk behavior.
  • Don't share personal items. Use your own toothbrush, comb and razor. Avoid sharing drinking glasses or dining utensils.
  • Travel wisely. If you're traveling out of the country, talk to your doctor about any special vaccinations — such as yellow fever, cholera, hepatitis A or B, or typhoid fever — you may need.
  • Vaccine guidance from Mayo Clinic
  • Enterovirus D68 and parechovirus: How can I protect my child?
  • What are superbugs and how can I protect myself from infection?

Feb 18, 2022

  • Facts about infectious disease. Infectious Disease Society of America. https://www.idsociety.org/public-health/facts-about-id/. Accessed May 29, 2019.
  • Jameson JL, et al., eds. Approach to the patient with an infectious disease. In: Harrison's Principles of Internal Medicine. 20th ed. New York, N.Y.: The McGraw-Hill Companies; 2018. https://accessmedicine.mhmedical.com. Accessed May 29, 2019.
  • Clean hands count for safe health care. Centers for Disease Control and Prevention. https://www.cdc.gov/features/handhygiene/index.html. Accessed May 29, 2019.
  • Kumar P, et al., eds. Infectious diseases and tropical medicine. In: Kumar and Clark's Clinical Medicine. 11th ed. Philadelphia, Pa.: Elsevier; 2017. https://www.clinicalkey.com. Accessed May 29, 2019.
  • LaRocque R, et al. Causes of infectious diarrhea and other foodborne illnesses in resource-rich settings. https://www.uptodate.com/contents/search. Accessed May 29, 2019.
  • Ryan KJ, ed. Infectious diseases: Syndromes and etiologies. In: Sherris Medical Microbiology. 7th ed. New York, N.Y.: McGraw-Hill Education; 2018. https://accessmedicine.mhmedical.com. Accessed May 29, 2019.
  • File TM, et al. Epidemiology, pathogenesis, and microbiology of community-acquired pneumonia in adults. https://www.uptodate.com/contents/search. Accessed May 29. 2019.
  • DeClerq E, et al. Approved antiviral drugs over the past 50 years. Clinical Microbiology Reviews. 2016;29:695.
  • Mousa HAL. Prevention and treatment of influenza, influenza-like illness and common cold by herbal, complementary, and natural therapies. Journal of Evidence-Based Complementary & Alternative Medicine. 2017;22:166.
  • Caring for someone sick. Centers for Disease Control and Prevention. https://www.cdc.gov/flu/treatment/caring-for-someone.htm. Accessed May 29, 2019.
  • Diseases & Conditions
  • Infectious diseases symptoms & causes

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Infectious Diseases

Infectious diseases have a wide variety of causes, and NIAID supports research to control and prevent diseases caused by virtually all human infectious agents. NIAID provides funding opportunities and a comprehensive set of resources for researchers that support basic research, pre-clinical development, and clinical evaluation.

Why Is the Study of Infectious Diseases a Priority for NIAID?

Infectious diseases continue to pose a significant threat to human health, with many types of infections having far-reaching, global consequences. NIAID recognizes the need to transform the way we prevent, control, and treat infectious diseases with the intent of reducing negative global impact.

How Is NIAID Addressing This Critical Topic?

NIAID conducts and supports research on infectious diseases, both through external collaboration with outside researchers, and at its own specialized research laboratories.

The Division of Microbiology and Infectious Diseases  supports research and provides resources for all stages of research and product development, partnering with public and private institutions to make advances in the efforts to control infectious agents.

The NIAID  Division of Intramural Research  conducts basic and clinical research through multiple labs in a wide range of disciplines related to infectious diseases, while the Vaccine Research Center  conducts research that facilitates the development of new vaccines, therapeutics, and diagnostics to address these diseases.

The results are research discoveries that are transforming the prevention, diagnosis, and treatment of infectious disease.

Types of Infectious Diseases

Viral diseases .

NIAID is conducting and supporting research to find new and improved ways to diagnose, treat, and prevent viral infections like influenza. Biomedical research supported by NIAID provides the tools necessary to develop diagnostic tests, new and improved treatments, vaccines, and other means to combat these threats. This includes working toward a universal flu vaccine that could provide long-lasting protection against multiple strains of influenza, including those that cause seasonal flu as well as emerging forms capable of causing a global pandemic.

Bacterial Diseases

Bacterial diseases continue to present a major threat to human health. Tuberculosis, for instance, still ranks among the world's leading causes of death. Streptococcus (Group B Streptococcus), another bacterium, continues to be a frequent cause of life-threatening infection during the first two months of life.

Research in basic bacteriology includes investigating molecular structure and function, genomics, biochemical composition, and physiologic and biochemical processes. Studies on these bacterial pathogens extend basic insights to identify vaccine candidate antigens and drug targets and to examine mechanisms of infection, pathogenicity, and virulence.

Areas of particular interest include streptococci, pneumonia, nosocomial (hospital-associated) infections, antibiotic resistance, bacterial sexually transmitted diseases, and bacterial diarrhea.

Fungal Diseases

Fungal diseases can be caused by a wide variety of microscopic fungi that are commonly found in the environment. While invasive fungal infections are rare in healthy people, they can still be deadly in isolated cases.

In addition, some fungal pathogens (such as  Candida auris ) are evolving resistance to standard antifungal treatments. This drug resistance poses a significant challenge to healthcare providers and researchers around the world.

NIAID is conducting and supporting basic research to understand how fungal pathogens cause disease and how the immune system responds to infection. NIAID is also supporting the development of new diagnostic tests, drugs, and preventative measures which could stop fungal infections.

Parasitic Diseases 

Diseases caused by protozoan (type of microbe) and helminth (type of worm) parasites are among the leading causes of death and disease in tropical and subtropical regions of the world. Efforts to control the vector (carrier) of these diseases are often difficult due to pesticide resistance, concerns regarding damage to the environment, and lack of adequate support to apply existing vector control methods.

NIAID research on parasitic infections is targeted at developing a better understanding of the pathogenesis of infections and developing more effective prevention approaches, diagnostics, and treatments for them.

16.3 Modes of Disease Transmission

Learning objectives.

By the end of this section, you will be able to:

  • Describe the different types of disease reservoirs
  • Compare contact, vector, and vehicle modes of transmission
  • Identify important disease vectors
  • Explain the prevalence of nosocomial infections

Understanding how infectious pathogens spread is critical to preventing infectious disease. Many pathogens require a living host to survive, while others may be able to persist in a dormant state outside of a living host. But having infected one host, all pathogens must also have a mechanism of transfer from one host to another or they will die when their host dies. Pathogens often have elaborate adaptations to exploit host biology, behavior, and ecology to live in and move between hosts. Hosts have evolved defenses against pathogens, but because their rates of evolution are typically slower than their pathogens (because their generation times are longer), hosts are usually at an evolutionary disadvantage. This section will explore where pathogens survive—both inside and outside hosts—and some of the many ways they move from one host to another.

Reservoirs and Carriers

For pathogens to persist over long periods of time they require reservoir s where they normally reside. Reservoirs can be living organisms or nonliving sites. Nonliving reservoirs can include soil and water in the environment. These may naturally harbor the organism because it may grow in that environment. These environments may also become contaminated with pathogens in human feces, pathogens shed by intermediate hosts, or pathogens contained in the remains of intermediate hosts.

Pathogens may have mechanisms of dormancy or resilience that allow them to survive (but typically not to reproduce) for varying periods of time in nonliving environments. For example, Clostridium tetani survives in the soil and in the presence of oxygen as a resistant endospore. Although many viruses are soon destroyed once in contact with air, water, or other non-physiological conditions, certain types are capable of persisting outside of a living cell for varying amounts of time. For example, a study that looked at the ability of influenza viruses to infect a cell culture after varying amounts of time on a banknote showed survival times from 48 hours to 17 days, depending on how they were deposited on the banknote. 8 On the other hand, cold-causing rhinoviruses are somewhat fragile, typically surviving less than a day outside of physiological fluids.

A human acting as a reservoir of a pathogen may or may not be capable of transmitting the pathogen, depending on the stage of infection and the pathogen. To help prevent the spread of disease among school children, the CDC has developed guidelines based on the risk of transmission during the course of the disease. For example, children with chickenpox are considered contagious for five days from the start of the rash, whereas children with most gastrointestinal illnesses should be kept home for 24 hours after the symptoms disappear.

An individual capable of transmitting a pathogen without displaying symptoms is referred to as a carrier. A passive carrier is contaminated with the pathogen and can mechanically transmit it to another host; however, a passive carrier is not infected. For example, a health-care professional who fails to wash his hands after seeing a patient harboring an infectious agent could become a passive carrier, transmitting the pathogen to another patient who becomes infected.

By contrast, an active carrier is an infected individual who can transmit the disease to others. An active carrier may or may not exhibit signs or symptoms of infection. For example, active carriers may transmit the disease during the incubation period (before they show signs and symptoms) or the period of convalescence (after symptoms have subsided). Active carriers who do not present signs or symptoms of disease despite infection are called asymptomatic carrier s . Pathogens such as hepatitis B virus , herpes simplex virus , and HIV are frequently transmitted by asymptomatic carriers. Mary Mallon , better known as Typhoid Mary , is a famous historical example of an asymptomatic carrier. An Irish immigrant, Mallon worked as a cook for households in and around New York City between 1900 and 1915. In each household, the residents developed typhoid fever (caused by Salmonella typhi ) a few weeks after Mallon started working. Later investigations determined that Mallon was responsible for at least 122 cases of typhoid fever, five of which were fatal. 9 See Eye on Ethics: Typhoid Mary for more about the Mallon case.

A pathogen may have more than one living reservoir. In zoonotic diseases, animals act as reservoirs of human disease and transmit the infectious agent to humans through direct or indirect contact. In some cases, the disease also affects the animal, but in other cases the animal is asymptomatic.

In parasitic infections, the parasite’s preferred host is called the definitive host . In parasites with complex life cycles, the definitive host is the host in which the parasite reaches sexual maturity. Some parasites may also infect one or more intermediate host s in which the parasite goes through several immature life cycle stages or reproduces asexually.

Link to Learning

George Soper, the sanitary engineer who traced the typhoid outbreak to Mary Mallon, gives an account of his investigation, an example of descriptive epidemiology, in “The Curious Career of Typhoid Mary.”

Check Your Understanding

  • List some nonliving reservoirs for pathogens.
  • Explain the difference between a passive carrier and an active carrier.

Transmission

Regardless of the reservoir, transmission must occur for an infection to spread. First, transmission from the reservoir to the individual must occur. Then, the individual must transmit the infectious agent to other susceptible individuals, either directly or indirectly. Pathogenic microorganisms employ diverse transmission mechanisms.

Contact Transmission

Contact transmission includes direct contact or indirect contact. Person-to-person transmission is a form of direct contact transmission . Here the agent is transmitted by physical contact between two individuals ( Figure 16.9 ) through actions such as touching, kissing, sexual intercourse, or droplet sprays . Direct contact can be categorized as vertical, horizontal, or droplet transmission. Vertical direct contact transmission occurs when pathogens are transmitted to a fetus or infant during pregnancy, birth, or breastfeeding. Other kinds of direct contact transmission are called horizontal direct contact transmission . Often, contact between mucous membranes is required for entry of the pathogen into the new host, although skin-to-skin contact can lead to mucous membrane contact if the new host subsequently touches a mucous membrane. Contact transmission may also be site-specific; for example, some diseases can be transmitted by sexual contact but not by other forms of contact.

When an individual coughs or sneezes, small droplets of mucus that may contain pathogens are ejected. This leads to direct droplet transmission , which refers to droplet transmission of a pathogen to a new host over distances of one meter or less. A wide variety of diseases are transmitted by droplets, including influenza and many forms of pneumonia . Transmission over distances greater than one meter is called airborne transmission .

Indirect contact transmission involves inanimate objects called fomites that become contaminated by pathogens from an infected individual or reservoir ( Figure 16.10 ). For example, an individual with the common cold may sneeze, causing droplets to land on a fomite such as a tablecloth or carpet, or the individual may wipe her nose and then transfer mucus to a fomite such as a doorknob or towel. Transmission occurs indirectly when a new susceptible host later touches the fomite and transfers the contaminated material to a susceptible portal of entry. Fomites can also include objects used in clinical settings that are not properly sterilized, such as syringes, needles, catheters, and surgical equipment. Pathogens transmitted indirectly via such fomites are a major cause of healthcare-associated infections (see Controlling Microbial Growth ).

Vehicle Transmission

The term vehicle transmission refers to the transmission of pathogens through vehicles such as water, food, and air. Water contamination through poor sanitation methods leads to waterborne transmission of disease. Waterborne disease remains a serious problem in many regions throughout the world. The World Health Organization (WHO) estimates that contaminated drinking water is responsible for more than 500,000 deaths each year. 10 Similarly, food contaminated through poor handling or storage can lead to foodborne transmission of disease ( Figure 16.11 ).

Dust and fine particles known as aerosols , which can float in the air, can carry pathogens and facilitate the airborne transmission of disease. For example, dust particles are the dominant mode of transmission of hantavirus to humans. Hantavirus is found in mouse feces, urine, and saliva, but when these substances dry, they can disintegrate into fine particles that can become airborne when disturbed; inhalation of these particles can lead to a serious and sometimes fatal respiratory infection.

Although droplet transmission over short distances is considered contact transmission as discussed above, longer distance transmission of droplets through the air is considered vehicle transmission. Unlike larger particles that drop quickly out of the air column, fine mucus droplets produced by coughs or sneezes can remain suspended for long periods of time, traveling considerable distances. In certain conditions, droplets desiccate quickly to produce a droplet nucleus that is capable of transmitting pathogens; air temperature and humidity can have an impact on effectiveness of airborne transmission.

Tuberculosis is often transmitted via airborne transmission when the causative agent, Mycobacterium tuberculosis , is released in small particles with coughs. Because tuberculosis requires as few as 10 microbes to initiate a new infection, patients with tuberculosis must be treated in rooms equipped with special ventilation, and anyone entering the room should wear a mask.

Clinical Focus

After identifying the source of the contaminated turduckens, the Florida public health office notified the CDC, which requested an expedited inspection of the facility by state inspectors. Inspectors found that a machine used to process the chicken was contaminated with Salmonella as a result of substandard cleaning protocols. Inspectors also found that the process of stuffing and packaging the turduckens prior to refrigeration allowed the meat to remain at temperatures conducive to bacterial growth for too long. The contamination and the delayed refrigeration led to vehicle (food) transmission of the bacteria in turduckens.

Based on these findings, the plant was shut down for a full and thorough decontamination. All turduckens produced in the plant were recalled and pulled from store shelves ahead of the December holiday season, preventing further outbreaks.

Go back to the previous Clinical Focus Box.

Vector Transmission

Diseases can also be transmitted by a mechanical or biological vector , an animal (typically an arthropod ) that carries the disease from one host to another. Mechanical transmission is facilitated by a mechanical vector , an animal that carries a pathogen from one host to another without being infected itself. For example, a fly may land on fecal matter and later transmit bacteria from the feces to food that it lands on; a human eating the food may then become infected by the bacteria, resulting in a case of diarrhea or dysentery ( Figure 16.12 ).

Biological transmission occurs when the pathogen reproduces within a biological vector that transmits the pathogen from one host to another ( Figure 16.12 ). Arthropods are the main vectors responsible for biological transmission ( Figure 16.13 ). Most arthropod vectors transmit the pathogen by biting the host, creating a wound that serves as a portal of entry. The pathogen may go through part of its reproductive cycle in the gut or salivary glands of the arthropod to facilitate its transmission through the bite. For example, hemipterans (called “kissing bugs” or “assassin bugs”) transmit Chagas disease to humans by defecating when they bite, after which the human scratches or rubs the infected feces into a mucous membrane or break in the skin.

Biological insect vectors include mosquitoes , which transmit malaria and other diseases, and lice , which transmit typhus . Other arthropod vectors can include arachnids, primarily ticks , which transmit Lyme disease and other diseases, and mites , which transmit scrub typhus and rickettsial pox . Biological transmission, because it involves survival and reproduction within a parasitized vector, complicates the biology of the pathogen and its transmission. There are also important non-arthropod vectors of disease, including mammals and birds. Various species of mammals can transmit rabies to humans, usually by means of a bite that transmits the rabies virus. Chickens and other domestic poultry can transmit avian influenza to humans through direct or indirect contact with avian influenza virus A shed in the birds’ saliva, mucous, and feces.

  • Describe how diseases can be transmitted through the air.
  • Explain the difference between a mechanical vector and a biological vector.

Eye on Ethics

Using gmos to stop the spread of zika.

In 2016, an epidemic of the Zika virus was linked to a high incidence of birth defects in South America and Central America. As winter turned to spring in the northern hemisphere, health officials correctly predicted the virus would spread to North America, coinciding with the breeding season of its major vector, the Aedes aegypti mosquito.

The range of the A. aegypti mosquito extends well into the southern United States ( Figure 16.14 ). Because these same mosquitoes serve as vectors for other problematic diseases ( dengue fever , yellow fever , and others), various methods of mosquito control have been proposed as solutions. Chemical pesticides have been used effectively in the past, and are likely to be used again; but because chemical pesticides can have negative impacts on the environment, some scientists have proposed an alternative that involves genetically engineering A. aegypti so that it cannot reproduce. This method, however, has been the subject of some controversy.

One method that has worked in the past to control pests, with little apparent downside, has been sterile male introductions. This method controlled the screw-worm fly pest in the southwest United States and fruit fly pests of fruit crops. In this method, males of the target species are reared in the lab, sterilized with radiation, and released into the environment where they mate with wild females, who subsequently bear no live offspring. Repeated releases shrink the pest population.

A similar method, taking advantage of recombinant DNA technology, 11 introduces a dominant lethal allele into male mosquitoes that is suppressed in the presence of tetracycline (an antibiotic) during laboratory rearing. The males are released into the environment and mate with female mosquitoes. Unlike the sterile male method, these matings produce offspring, but they die as larvae from the lethal gene in the absence of tetracycline in the environment. As of 2016, this method has yet to be implemented in the United States, but a UK company tested the method in Piracicaba, Brazil, and found an 82% reduction in wild A. aegypti larvae and a 91% reduction in dengue cases in the treated area. 12 In August 2016, amid news of Zika infections in several Florida communities, the FDA gave the UK company permission to test this same mosquito control method in Key West, Florida, pending compliance with local and state regulations and a referendum in the affected communities.

The use of genetically modified organisms (GMOs) to control a disease vector has its advocates as well as its opponents. In theory, the system could be used to drive the A. aegypti mosquito extinct—a noble goal according to some, given the damage they do to human populations. 13 But opponents of the idea are concerned that the gene could escape the species boundary of A. aegypti and cause problems in other species, leading to unforeseen ecological consequences. Opponents are also wary of the program because it is being administered by a for-profit corporation, creating the potential for conflicts of interest that would have to be tightly regulated; and it is not clear how any unintended consequences of the program could be reversed.

There are other epidemiological considerations as well. Aedes aegypti is apparently not the only vector for the Zika virus. Aedes albopictus , the Asian tiger mosquito, is also a vector for the Zika virus. 14 A. albopictus is now widespread around the planet including much of the United States ( Figure 16.14 ). Many other mosquitoes have been found to harbor Zika virus, though their capacity to act as vectors is unknown. 15 Genetically modified strains of A. aegypti will not control the other species of vectors. Finally, the Zika virus can apparently be transmitted sexually between human hosts, during pregnancy to a fetus or during birth, and possibly through blood transfusion. All of these factors must be considered in any approach to controlling the spread of the virus.

Clearly there are risks and unknowns involved in conducting an open-environment experiment of an as-yet poorly understood technology. But allowing the Zika virus to spread unchecked is also risky. Does the threat of a Zika epidemic justify the ecological risk of genetically engineering mosquitos? Are current methods of mosquito control sufficiently ineffective or harmful that we need to try untested alternatives? These are the questions being put to public health officials now.

Quarantining

Individuals suspected or known to have been exposed to certain contagious pathogens may be quarantined , or isolated to prevent transmission of the disease to others. Hospitals and other health-care facilities generally set up special wards to isolate patients with particularly hazardous diseases such as tuberculosis or Ebola ( Figure 16.15 ). Depending on the setting, these wards may be equipped with special air-handling methods, and personnel may implement special protocols to limit the risk of transmission, such as personal protective equipment or the use of chemical disinfectant sprays upon entry and exit of medical personnel.

The duration of the quarantine depends on factors such as the incubation period of the disease and the evidence suggestive of an infection. The patient may be released if signs and symptoms fail to materialize when expected or if preventive treatment can be administered in order to limit the risk of transmission. If the infection is confirmed, the patient may be compelled to remain in isolation until the disease is no longer considered contagious.

In the United States, public health authorities may only quarantine patients for certain diseases, such as cholera , diphtheria , infectious tuberculosis , and strains of influenza capable of causing a pandemic . Individuals entering the United States or moving between states may be quarantined by the CDC if they are suspected of having been exposed to one of these diseases. Although the CDC routinely monitors entry points to the United States for crew or passengers displaying illness, quarantine is rarely implemented.

During the COVID-19 pandemic, quarantine became a common practice, particularly related to international travel. Various countries implemented quarantine and isolation requirements based on the availability of testing and vaccinations. Initially, some nations required that all international travelers remain quarantined for a period after arrival; later on, they instituted quarantine only for those who tested positive.

Healthcare-Associated (Nosocomial) Infections

Hospitals, retirement homes, and prisons attract the attention of epidemiologists because these settings are associated with increased incidence of certain diseases. Higher rates of transmission may be caused by characteristics of the environment itself, characteristics of the population, or both. Consequently, special efforts must be taken to limit the risks of infection in these settings.

Infections acquired in health-care facilities, including hospitals, are called nosocomial infections or healthcare-associated infections (HAI) . HAIs are often connected with surgery or other invasive procedures that provide the pathogen with access to the portal of infection. For an infection to be classified as an HAI, the patient must have been admitted to the health-care facility for a reason other than the infection. In these settings, patients suffering from primary disease are often afflicted with compromised immunity and are more susceptible to secondary infection and opportunistic pathogens.

In 2011, more than 720,000 HAIs occurred in hospitals in the United States, according to the CDC. About 22% of these HAIs occurred at a surgical site, and cases of pneumonia accounted for another 22%; urinary tract infections accounted for an additional 13%, and primary bloodstream infections 10%. 16 Such HAIs often occur when pathogens are introduced to patients’ bodies through contaminated surgical or medical equipment, such as catheters and respiratory ventilators. Health-care facilities seek to limit nosocomial infections through training and hygiene protocols such as those described in Control of Microbial Growth .

  • Give some reasons why HAIs occur.
  • 8 Yves Thomas, Guido Vogel, Werner Wunderli, Patricia Suter, Mark Witschi, Daniel Koch, Caroline Tapparel, and Laurent Kaiser. “Survival of Influenza Virus on Banknotes.” Applied and Environmental Microbiology 74, no. 10 (2008): 3002–3007.
  • 9 Filio Marineli, Gregory Tsoucalas, Marianna Karamanou, and George Androutsos. “Mary Mallon (1869–1938) and the History of Typhoid Fever.” Annals of Gastroenterology 26 (2013): 132–134. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3959940/pdf/AnnGastroenterol-26-132.pdf.
  • 10 World Health Organization. Fact sheet No. 391 —Drinking Water. June 2005. http://www.who.int/mediacentre/factsheets/fs391/en.
  • 11 Blandine Massonnet-Bruneel, Nicole Corre-Catelin, Renaud Lacroix, Rosemary S. Lees, Kim Phuc Hoang, Derric Nimmo, Luke Alphey, and Paul Reiter. “Fitness of Transgenic Mosquito Aedes aegypti Males Carrying a Dominant Lethal Genetic System.” PLOS ONE 8, no. 5 (2013): e62711.
  • 12 Richard Levine. “Cases of Dengue Drop 91 Percent Due to Genetically Modified Mosquitoes.” Entomology Today. https://entomologytoday.org/2016/07/14/cases-of-dengue-drop-91-due-to-genetically-modified-mosquitoes.
  • 13 Olivia Judson. “A Bug’s Death.” The New York Times , September 25, 2003. http://www.nytimes.com/2003/09/25/opinion/a-bug-s-death.html.
  • 14 Gilda Grard, Mélanie Caron, Illich Manfred Mombo, Dieudonné Nkoghe, Statiana Mboui Ondo, Davy Jiolle, Didier Fontenille, Christophe Paupy, and Eric Maurice Leroy. “Zika Virus in Gabon (Central Africa)–2007: A New Threat from Aedes albopictus ?” PLOS Neglected Tropical Diseases 8, no. 2 (2014): e2681.
  • 15 Constância F.J. Ayres. “Identification of Zika Virus Vectors and Implications for Control.” The Lancet Infectious Diseases 16, no. 3 (2016): 278–279.
  • 16 Centers for Disease Control and Prevention. “HAI Data and Statistics.” 2016. http://www.cdc.gov/hai/surveillance. Accessed Jan 2, 2016.

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  • Biology Article

Diseases - Types of Diseases and their Symptoms

Over the years, science and technology have improved to such an extent that we have been able to identify the causes, symptoms and cures for various diseases with a high degree of success. And this is supported by a considerably long average lifespan and lower mortality rates. But what exactly is a disease?

Table of Contents

  • Classification
  • Degenerative

different types of infectious diseases essay

What is Disease?

“A disease is a condition that deteriorates the normal functioning of the cells, tissues, and organs.”

Diseases are often thought of as medical conditions that are characterized by their signs and symptoms.

The disease can also be defined as:

“Any dangerous divergence from a functional or normal state of an entity.”

When a person is inflicted with a disease, he exhibits a few symptoms and signs that range from normal to severe depending upon the medical condition. Hence, in order to identify different diseases, the normalcy of an entity needs to be studied and understood as a clear demarcation between disease and disease-free is not always apparent.

The diseases are usually caused by many factors rather than a single cause. When we have a disease, we eventually show some signs, such as headaches, cough, cold, or weakness. These signs are referred to as “symptoms.” In almost all diseases, symptoms are shown immediately after having been struck by the disease. However, it varies depending upon the seriousness of the disease.

Today, there are various ways to classify diseases.

Also Read:  Difference between disinfection and sterilization

Classification of Diseases

Anatomic Classification This type refers to the affected organ or tissue Heart disease
Topographical Classification Further classified into types such as vascular disease, chest disease, gastrointestinal disease, and abdominal diseases. These are then handled by specializations in medicine that follow these topographical classifications An ENT specialist (Ear-Nose-Throat)
A Gastroenterology specialist etc.
Physiological Classification This type includes diseases that affect a process or a function (such as metabolism, digestion or respiration) Diabetes
Pathological Classification This type considers the nature of the disease. For instance, cancer is associated with uncontrolled cell growth, and there are variations or types in the disease. Neoplastic diseases (uncontrolled cell growth that is characteristic of cancer)
Inflammatory diseases (autoimmunity)
Epidemiological Classification This classification refers to the rate of occurrence, distribution and the control of the disease in a population. Epidemic diseases such as the plague and Influenza pandemic of 1918–1919

Types of Diseases

Diseases can be of two types

  • Infectious diseases
  • Non-infectious diseases

Infectious Diseases

Diseases that spread from one person to another are called communicable diseases. They are usually caused by microorganisms called pathogens (fungi, rickettsia, bacteria, viruses, protozoans, and worms). When an infected person discharges bodily fluids, pathogens may exit the host and infect a new person (sneezing, coughing etc). Examples include Cholera, chickenpox, malaria etc.

Non-infectious Diseases

These diseases are caused by pathogens, but other factors such as age, nutritional deficiency, gender of an individual, and lifestyle also influence the disease. Examples include hypertension , diabetes, and cancer. They do not spread to others and they restrain within a person who has contracted them. Alzheimer’s disease, asthma, cataract and heart diseases are other non-infectious diseases.

Read more: Infectious diseases

Based on these above classifications, a disease may fall into any number of these classifications.

Degenerative Diseases

They are mainly caused by the malfunctioning of vital organs in the body due to the deterioration of cells over time. Diseases such as osteoporosis show characteristics of degenerative diseases in the form of increased bone weakness. This increases the risk of bone fractures.

When degeneration happens to the cells of the central nervous system, such as neurons, the condition is termed as a neurodegenerative disorder. Alzheimer’s is a prominent example of this disorder. Degenerative diseases are usually caused by ageing and bodywear. Others are caused by lifestyle choices and some are hereditary.

An allergic reaction arises when the body becomes hypersensitive to certain foreign substances called allergens. This usually happens when the immune system reacts abnormally to any seemingly harmless substances. Common allergens include dust, pollen, animal dander, mites, feathers, latex and also certain food products like nuts and gluten. Peanuts and other nuts have the capability to cause severe allergic reactions that may induce life-threatening conditions such as difficulty in breathing, tissues swelling up and blocking the airways and anaphylaxis shock.

Other common and less life-threatening symptoms include coughing, sneezing, running nose, itchy and red eyes, and skin rashes. One of the best examples of this allergic reaction is asthma . Sometimes, bee stings and ant bites also trigger allergies. Consumption of shellfish and certain medications can induce allergic reactions.

Asthma is a chronic disease, that mainly affects the bronchi and bronchioles of the lungs. One of the factors responsible for this is airborne allergens such as pollens or dust. Symptoms include difficulty in breathing, wheezing, and coughing.

Deficiency Diseases

They occur due to the deficiencies of hormones, minerals, nutrients, and vitamins. For example, diabetes occurs due to an inability to produce or utilize insulin, goitre is mainly caused by iodine deficiency, and  kwashiorkor is caused by a lack of proteins in the diet. Vitamin B1 deficiency causes beriberi.

Read more:  Deficiency Diseases

It is an abnormal enlargement of the thyroid gland by blocking the oesophagus or other organs of the chest and neck. This causes difficulty in breathing and eating.

Blood Diseases

Blood contains plasma, white blood cells, platelets and red blood cells. When any of these components are affected, it can lead to blood disorders. For instance, red blood cells are destroyed when a person contracts sickle cell disease. The red blood cells are distorted into the shape of a sickle (hence, the name) and they lose their ability to carry oxygen. Consequently, this disease is characterized by symptoms similar to chronic anaemia, such as shortness of breath and tiredness.

Other diseases such as eosinophilic disorders, leukaemia, myeloma (cancer of plasma cells in bone marrow), Sickle Cell Anemia, Aplastic Anemia, Hemochromatosis and Von Miller and Disease (blood-clotting disorder) fall under this classification.

General Symptoms: Pale skin, swelling of lymph nodes, fever, bleeding, bruising, skin rashes, etc.

Disease-Causing Agents

We have seen the classification of different entities based on various characteristics, for simplification, we classify organisms to group them together and study about them as a class. Similarly, diseases are caused by different microorganisms and can be classified as diseases caused by bacteria, fungi, viruses etc. Some diseases are also caused by multicellular organisms such as worms.

Listed below are a few diseases and the disease-causing agents

Plague Pasteurella pestis
Cholera Vibrio comma (Vibrio cholera)
Tetanus Clostridium tetani
Anthrax Bacillus anthracis
Whooping cough Bordetella pertussis
Human papillomavirus infection Human papillomavirus
Acquired Immune Deficiency Syndrome (AIDS) Human Immunodeficiency Virus (HIV)
Hepatitis Hepatitis A, Hepatitis B, Hepatitis C, Hepatitis D, Hepatitis E viruses
Chickenpox Varicella-zoster virus (VZV)
Meningoencephalitis Naegleria fowleri (amoeba)

Also Read: Harmful Microorganisms

To know more about human diseases, their types, causes, symptoms and other related topics, keep visiting  BYJU’S Biology.

Frequently Asked Questions

What is meant by communicable diseases name any two communicable diseases., what are genetic diseases, what are the disease-causing organisms known as, name the disease caused by the deficiency of insulin hormone in the body., what is the difference between an infectious disease and a communicable disease.

Thus, All infectious diseases are not communicable but all communicable diseases are infectious.

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The Power and Potential of Gene Tuning

Modifying DNA, conceptual image

A fter a lifetime in the field of epigenetics, and nearly 20 years after my colleagues and I coined the term “genome editing,” I will be the first to admit that describing the “ epi genome”—a marvelous biological process that guides what our genes do—takes a bit of explaining. I find that thinking about the genome and epigenome in terms of music and sound-mixing can be helpful here. We experience all sorts of music as we go through life, from Bach and Brahms to Laufey and Lizzo. It is remarkable that you can do so many different things musically from just a few basic components. You have a defined set of notes , which can be played separately or together in an enormous number of combinations and time signatures. Those notes can be played at different volumes —some louder, some softer. And finally, those same notes can have different textures . The note of A as played on a violin sounds very different when played by a distorted, death-metal guitar. Each has the same number of vibrations per unit time, but our experience of them is not the same at all.

 So now, let’s turn to genes. Humans have around 20,000 of them—which is not many more than the total number of genes in a fruit fly. Initial estimates were far higher, at around 120,000, because we thought that more genes are needed to make more complicated organisms. Our thinking was wrong. The wondrous complexity we observe emerges out of combinations of genes, functioning with a certain order and timing—rather than all of your genes doing “everything, everywhere, all at once.” Our body consists of several hundred different cell types (red blood cell, skin fibroblast, neuron), and about 8,000 genes in a given human cell come together, each at a specific volume, timing, and texture to bring it to life. Scientists call this gene “expression”—a term aptly borrowed from the arts. What coordinates it? Consider a music score for a song—whether it’s Taylor Swift’s Love Story or Schubert’s Message of Love . In both, you would see notes on a musical stave, with specific markings for rhythm, volume, and pitch. For our genome, every four bars of music would be accompanied by four pages of guidance on how to play them correctly. Scientists have discovered that in addition to 20,000 genes, our genome contains about 3 million sets of instructions on how to express them (akin to dials on a soundboard); together, these cover a quarter of human DNA. Our body contains about 40 trillion cells and in each one the genes are expressing themselves in a distinct way (a blood cell makes different proteins than a liver cell than a lung cell). And now think of setting each dial on a soundboard to the exact position you need for the music to sound like Swift or like Schubert. The epigenome is the total set of “dial settings” for all the genes that are expressed in a given human cell and give it its biological identity.

Health from harmony, disease from distortion

On a fundamental level, health (or the lack of it) is created and maintained through a kind of epigenomically-mediated harmony. If you’ve ever heard a beginning violinist working through a simple piece, you’ll know it's sonically grating. We hear the lack of harmony, and it's painful.

But what is lack of harmony? It could simply be the wrong note played at the wrong time. But it can also arise from a failure of coordination. Any time you have more than one instrument on stage, if they're not coherent (you might picture a middle-school orchestra, here), it just hurts.

Music can also be ruined when the relative volumes within it are wrong. (“Why are the drums so loud in this mix? We need less vocal and more bass!”) In music, it seems intuitive to us that the various notes and instruments must come together at the correct volumes, and in the right rhythm. And so it is with gene expression in relation to health and disease.

Read More: The Gene-Editing Revolution Is Already Here

We have had access to the complete, human genome sequence since 2003 . Our DNA is long; reading one letter of human DNA per second, it would take you a century to read the whole genome. Think 500 textbooks, stacked one atop the other. Now imagine reading different versions of that text—each unique to different people and populations, and asking: where are the genes that make us sick? Where are the genes that lead to heart attacks, or irritable bowel syndrome? As it turns out, many of the genetic signatures that cause us to develop such common and degenerative conditions are not actually located inside the genes themselves .

Now if that statement inspires some confusion, then you are not alone. We scientists were just as confused at first. But what we've essentially figured out is this: Few of the common diseases we suffer from—be they cardiovascular, autoimmune, or neurodegenerative—are the direct result of broken or defective genes (or keeping within our musical metaphor, broken or defective instruments). The pianos are fine. The guitars are fine. They are simply being played in the wrong way.

Conducting the orchestra of gene expression

Soon after the first sequence of the human genome was determined, scientists started a large effort to compare DNA between individuals with and without certain diseases. This approach—called a Genome-Wide Association Study (or GWAS) has been applied thousands of times for every imaginable human trait difference, including whether someone is a “morning person” or whether a given individual is likely to get celiac disease. What these studies found was this: susceptibility to practically every, major, non-infectious disease rarely lies in the genetic “notes” themselves. Rather, about 90% of it lies in the instructions of how to play those notes .

Armed with this knowledge—and empowered by the development of CRISPR-based proteins that can edit both genome and epigenome—scientists across academia and industry have been racing toward the goal of a new class of genetic medicines . Medicines that can help patients retune the ill-timed notes or imbalanced volumes leading to disease.

The basic idea is this: if discord of gene expression leads to disease, could we not simply re-tune this orchestra of gene output to restore harmony in health?

We have a strong “yes” as an answer in the recent development of a cure for sickle cell disease . This medicine does not involve repairing the mutation that causes the disease –a mutation that breaks a gene that makes oxygen-carrying hemoglobin in our red blood cells. Instead, guided by a GWAS for genetic variants that protect against this disease, scientists figured out how to "wake up” a gene called fetal hemoglobin that normally goes silent after birth. In this work—a collaboration between Dr. Stuart Orkin, scientists at the University of Washington, and a group led by myself—altering one of the epigenetic switches in the “symphony” of how our body makes hemoglobin restored health to sickle red blood cells. In fact, to date, this has helped over 50 persons living with sickle cell disease!

Where this really gets exciting is that there are a vast number of diseases like this— in which otherwise healthy genes are being played at the wrong volume , at the wrong time , or in the wrong combinations. For each of these, we can move the sliders to shift the timing, volume, and texture of what each individual gene “sounds” like. And critically, we can do it without having to rewrite the music.

Gene tuning for common, chronic, and severe disease

The emergence of this new transformative therapeutic power begs the question: what are the areas of most need, and how could we put this to the best, possible use? It makes sense for the first focus to be on severe disease.  Take, for example, someone with devastatingly high cholesterol, at a high risk of early death from cardiovascular disease. If they do not respond to the usual medications, what are we to do? And what of chronic viral infections like Hepatitis B, for which there are treatments, but no effective cure? What options are there for those who face a lifetime of liver disease, a high risk of liver cancer, and no long-term prospects beyond liver transplant?

Read More: How Gene Editing Could Help Solve the Problem of Poor Cholesterol

 Could we just remove a gene, rip out the page wholesale? Yes. I'm a gene editor, and I firmly believe that gene editing has the potential to cure hundreds, if not thousands of rare, single-gene diseases—a potential recently demonstrated in several clinical trials. But I will be the first to admit that once you have gene-edited somebody, you’re done. There is no way back—you are gene-edited for life. If you are facing an otherwise untreatable condition, you might be fine with that. But for those with partly manageable conditions like high cholesterol or chronic viral infection, there may be less enthusiasm in some folks for this all-or-nothing approach.

With gene tuning, we can place an X mark over a precise part of the music score and say, “Don’t play this.” You can turn this gene up, turn that gene down, and observe the hoped-for benefit. And if something goes awry you can – at least in principle – reverse the effects. Besides the potential benefit of reversibility, gene tuning also offers control over duration of effect. For example, a remarkable new wave of cancer treatments has emerged recently from work by physicians and scientists at the University of Pennsylvania in which the patient’s own immune system cells are reprogrammed to attack a blood cancer. Once they have done their job, you may want those same cells to calm down and return to standby mode—lest they cause collateral damage through their persistent (albeit well-intentioned) hyperactivity. Gene tuning is built for precisely this kind of nuance, allowing you to raise or lower the volume of one or more genes gradually, or for a fixed, desired duration of time.

Same tune, less cowbell

Beyond this, there is another reason why gene tuning could transform the application of genetic medicine. Put simply: tweaking and editing single genes will only get you so far.

The majority of common and chronic diseases involve expression changes in multiple genes. To tackle these, we will have to re-tune not just one instrument, but a whole section of the orchestra.

Take the case of chronic, age-related autoimmune conditions. Imagine retuning multiple, immune-system genes to turn “attack yourself” music into “protect yourself” music. We actually know which genes to tune for that. And the ability to set their volume gauges to zero, to 10,000, or anywhere in between is ultimately where the next generation of therapeutics are headed. For the vast majority of disease, we don't need the genes to be off, we just need them to start performing at the right volume. Same tune, only less cowbell. Looking ahead at the next decade, I see it as an important window of opportunity for gene tuning to go after diseases where multiple levers need to be adjusted on the soundboard—and where the adjustment level needs to be a graded one, rather than all-or-none.  This is not to say that gene editing cannot do similar things. But sometimes you just need to match the problem to the solution best configured to solve it. You could play the intro to the Jaws theme on a flute – but it will sound better on a double bass. So when can we expect these gene-tuning therapeutics to actually become available to patients? In a time where genetic therapy for cancer is becoming the standard of care , and where we have an approved CRISPR medicine for the most common genetic disease on earth, we are closer than ever. The number one thing we have learned from that history is every new technology stands on the shoulders of previous ones,

The first clinical trials for gene tuning are likely to happen very soon - perhaps within the year.  Encouraged by the exponential growth in the broader gene therapy space, many academic scientists and biotech companies are working hard to bring therapeutic gene tuning to patients. Clinicians and regulators worldwide have learned to appreciate the power and potential of gene editing, and I am hopeful we will see a similar phenomenon for gene tuning as well. The second half of John Lennon’s classic Strawberry Fields Forever was sped up by the Beatles’ producer, George Martin, to sound right—one of countless examples in the history of music where small tweaks to the score made a big difference. Gene tuning is just getting started on a similar journey to bring harmony to human health—a big challenge, to be sure, but one, I sincerely hope, we can work out.

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A review of computer vision-based crack detection methods in civil infrastructure: progress and challenges.

different types of infectious diseases essay

1. Introduction

2. crack detection combining traditional image processing methods and deep learning, 2.1. crack detection based on image edge detection and deep learning, 2.2. crack detection based on threshold segmentation and deep learning, 2.3. crack detection based on morphological operations and deep learning, 3. crack detection based on multimodal data fusion, 3.1. multi-sensor fusion, 3.2. multi-source data fusion, 4. crack detection based on image semantic understanding, 4.1. crack detection based on classification networks, 4.2. crack detection based on object detection networks, 4.3. crack detection based on segmentation networks.

ModelImprovement/InnovationBackbone/Feature Extraction ArchitectureEfficiencyResults
FCS-Net [ ]Integrating ResNet-50, ASPP, and BNResNet-50-MIoU = 74.08%
FCN-SFW [ ]Combining fully convolutional network (FCN) and structural forests with wavelet transform (SFW) for detecting tiny cracksFCNComputing time = 1.5826 sPrecision = 64.1%
Recall = 87.22%
F1 score = 68.28%
AFFNet [ ]Using ResNet101 as the backbone network, and incorporating two attention mechanism modules, namely VH-CAM and ECAUMResNet101Execution time = 52 msMIoU = 84.49%
FWIoU = 97.07%
PA = 98.36%
MPA = 92.01%
DeepLabv3+ [ ]Replacing ordinary convolution with separable convolution; improved SE_ASSP moduleXception-65-AP = 97.63%
MAP = 95.58%
MIoU = 81.87%
U-Net [ ]The parameters were optimized (the depths of the network, the choice of activation functions, the selection of loss functions, and the data augmentation)Encoder and decoderAnalysis speed (1024 × 1024 pixels) = 0.022 sPrecision = 84.6%
Recall = 72.5%
F1 score = 78.1%
IoU = 64%
KTCAM-Net [ ]Combined CAM and RCM; integrating classification network and segmentation networkDeepLabv3FPS = 28Accuracy = 97.26%
Precision = 68.9%
Recall = 83.7%
F1 score = 75.4%
MIoU = 74.3%
ADDU-Net [ ]Featuring asymmetric dual decoders and dual attention mechanismsEncoder and decoderFPS = 35Precision = 68.9%
Recall = 83.7%
F1 score = 75.4%
MIoU = 74.3%
CGTr-Net [ ]Optimized CG-Trans, TCFF, and hybrid loss functionsCG-Trans-Precision = 88.8%
Recall = 88.3%
F1 score = 88.6%
MIoU = 89.4%
PCSN [ ]Using Adadelta as the optimizer and categorical cross-entropy as the loss function for the networkSegNetInference time = 0.12 smAP = 83%
Accuracy = 90%
Recall = 50%
DEHF-Net [ ]Introducing dual-branch encoder unit, feature fusion scheme, edge refinement module, and multi-scale feature fusion moduleDual-branch encoder unit-Precision = 86.3%
Recall = 92.4%
Dice score = 78.7%
mIoU = 81.6%
Student model + teacher model [ ]Proposed a semi-supervised semantic segmentation networkEfficientUNet-Precision = 84.98%
Recall = 84.38%
F1 score = 83.15%

5. Datasets

6. evaluation index, 7. discussion, 8. conclusions, author contributions, data availability statement, acknowledgments, conflicts of interest.

AspectCombining Traditional Image Processing Methods and Deep LearningMultimodal Data Fusion
Processing speedModerate—traditional methods are usually fast, but deep learning models may be slower, and the overall speed depends on the complexity of the deep learning modelSlower—data fusion and processing speed can be slow, especially with large-scale multimodal data, involving significant computational and data transfer overhead
AccuracyHigh—combines the interpretability of traditional methods with the complex pattern handling of deep learning, generally resulting in high detection accuracyTypically higher—combining different data sources (e.g., images, text, audio) provides comprehensive information, improving overall detection accuracy
RobustnessStrong—traditional methods provide background knowledge, enhancing robustness, but deep learning’s risk of overfitting may reduce robustnessVery strong—fusion of multiple data sources enhances the model’s adaptability to different environments and conditions, better handling noise and anomalies
ComplexityHigh—integrating traditional methods and deep learning involves complex design and balancing, with challenges in tuning and interpreting deep learning modelsHigh—involves complex data preprocessing, alignment, and fusion, handling inconsistencies and complexities from multiple data sources
AdaptabilityStrong—can adapt to different types of cracks and background variations, with deep learning models learning features from data, though it requires substantial labeled dataVery strong—combines diverse data sources, adapting well to various environments and conditions, and handling complex backgrounds and variations effectively
InterpretabilityHigher—traditional methods provide clear explanations, while deep learning models often lack interpretability; combining them can improve overall interpretabilityLower—fusion models generally have lower interpretability, making it difficult to intuitively explain how different data sources influence the final results
Data requirementsHigh—deep learning models require a lot of labeled data, while traditional methods are more lenient, though deep learning still demands substantial dataVery high—requires large amounts of data from various modalities, and these data need to be processed and aligned effectively for successful fusion
FlexibilityModerate—combining traditional methods and deep learning handles various types of cracks, but may be limited in very complex scenariosHigh—handles multiple data sources and different crack information, improving performance in diverse conditions through multimodal fusion
Real-time capabilityPoor—deep learning models are often slow to train and infer, making them less suitable for real-time detection, though combining with traditional methods can helpPoor—multimodal data fusion processing is generally slow, making it less suitable for real-time applications
Maintenance costModerate to high—deep learning models require regular updates and maintenance, while traditional methods have lower maintenance costsHigh—involves ongoing maintenance and updates for multiple data sources, with complex data preprocessing and fusion processes
Noise handlingGood—traditional methods effectively handle noise under certain conditions, and deep learning models can mitigate noise effects through trainingStrong—multimodal fusion can complement information from different sources, improving robustness to noise and enhancing detection accuracy
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Click here to enlarge figure

MethodFeaturesDomainDatasetImage Device/SourceResultsLimitations
Canny and YOLOv4 [ ]Crack detection and measurementBridges1463 images
256 × 256 pixels
Smartphone and DJI UAVAccuracy = 92%
mAP = 92%
The Canny edge detector is affected by the threshold
Canny and GM-ResNet [ ]Crack detection, measurement, and classificationRoad522 images
224 × 224 pixels
Concrete crack sub-datasetPrecision = 97.9%
Recall = 98.9%
F1 measure = 98.0%
Accuracy in shadow conditions = 99.3%
Accuracy in shadow-free conditions = 99.9%
Its detection performance for complex cracks is not yet perfect
Sobel and ResNet50 [ ]Crack detectionConcrete4500 images
100 × 100 pixels
FLIR E8Precision = 98.4%
Recall = 88.7%
F1 measure = 93.2%
-
Sobel and BARNet [ ]Crack detection and localizationRoad206 images
800 × 600 pixels
CrackTree200 datasetAIU = 19.85%
ODS = 79.9%
OIS = 81.4%
Hyperparameter tuning is needed to balance the penalty weights for different types of cracks
Canny and DeepLabV3+ [ ]Crack detectionRoad2000 × 1500 pixelsCrack500 datasetMIoU = 77.64%
MAE = 1.55
PA = 97.38%
F1 score = 63%
Detection performance deteriorating in dark environments or when interfering objects are present
Canny and RetinaNet [ ]Crack detection and measurementRoad850 images
256 × 256 pixels
SDNET 2018 datasetPrecision = 85.96%
Recall = 84.48%
F1 score = 85.21%
-
Canny and Transformer [ ]Crack detection and segmentationBuildings11298 images
450 × 450 pixels
UAVsGA = 83.5%
MIoU = 76.2%
Precision = 74.3%
Recall = 75.2%
F1 score = 74.7%
Resulting in a marginal increment in computational costs for various network backbones
Canny and Inception-ResNet-v2 [ ]Crack detection, measurement, and classificationHigh-speed railway4650 images
400 × 400 pixels
The track inspection vehicleHigh severity level:
Precision = 98.37%
Recall = 93.82%
F1 score = 95.99%
Low severity level:
Precision = 94.25%
Recall = 98.39%
F1 score = 96.23%
Only the average width was used to define the severity of the crack, and the influence of the length on the detection result was not considered
Canny and Unet [ ]Crack detectionBuildings165 images-SSIM = 14.5392
PSNR = 0.3206
RMSE = 0.0747
Relies on a large amount of mural data for training and enhancement
MethodFeaturesDomainDatasetImage Device/SourceResultsLimitations
Otsu and Keras classifier [ ]Crack detection, measurement, and classificationConcrete4000 images
227 × 227 pixels
Open dataset availableClassifiers accuracy = 98.25%, 97.18%, 96.17%
Length error = 1.5%
Width error = 5%
Angle of orientation error = 2%
Only accurately quantify one single crack per image
Otsu and TL MobileNetV2 [ ]Crack detection, measurement, and classificationConcrete11435 images
224 × 224 pixels
Mendeley data—crack detectionAccuracy = 99.87%
Recall = 99.74%
Precision = 100%
F1 score = 99.87%
Dependency on image quality
Otsu, YOLOv7, Poisson noise, and bilateral filtering [ ]Crack detection and classificationBridges500 images
640 × 640 pixels
DatasetTraining time = 35 min
Inference time = 8.9 s
Target correct rate = 85.97%
Negative sample misclassification rate = 42.86%
It does not provide quantified information such as length and area
Adaptive threshold and WSIS [ ]Crack detectionRoad320 images
3024 × 4032 pixels
Photos of cracksRecall = 90%
Precision = 52%
IoU = 50%
F1 score = 66%
Accuracy = 98%
For some small cracks (with a width of less than 3 pixels), model can only identify the existence of small cracks, but it is difficult to depict the cracks in detail
Adaptive threshold and U-GAT-IT [ ]Crack detectionRoad300 training images and237 test imagesDeepCrack datasetRecall = 79.3%
Precision = 82.2%
F1 score = 80.7%
Further research is needed to address the interference caused by factors such as small cracks, road shadows, and water stains
Local thresholding and DCNN [ ]Crack detectionConcrete125 images
227 × 227 pixels
CamerasAccuracy = 93%
Recall = 91%
Precision = 92%
F1 score = 91%
-
Otsu and Faster R-CNN [ ]Crack detection, localization, and quantificationConcrete100 images
1920 × 1080 pixels
Nikon d7200 camera and Galaxy s9 cameraAP = 95%
mIoU = 83%
RMSE = 2.6 pixels
Length accuracy = 93%
The proposed method is useful for concrete cracks only; its applicability for the detection of other crack materials might be limited
Adaptive Dynamic Thresholding
Module (ADTM) and Mask DINO [ ]
Crack detection and segmentationRoad395 images
2000 × 1500 pixels
Crack500mIoU = 81.3%
mAcc = 96.4%
gAcc = 85.0%
ADTM module can only handle binary classification problems
Dynamic Thresholding Branch and DeepCrack [ ]Crack detection and classificationBridges3648 × 5472 pixelsCrack500mIoU = 79.3%
mAcc = 98.5%
gAcc = 86.6%
Image-level thresholds lead to misclassification of the background
MethodFeaturesDomainDatasetImage Device/SourceResultsLimitations
Morphological closing operations and Mask R-CNN [ ]Crack detectionTunnel761 images
227 × 227 pixels
MTI-200aBalanced accuracy = 81.94%
F1 score = 68.68%
IoU = 52.72%
Relatively small compared to the needs of the required sample size for universal conditions
Morphological operations and Parallel ResNet [ ]Crack detection and measurementRoad206 images (CrackTree200)
800 × 600 pixels
and 118 images (CFD)
320 × 480 pixels
CrackTree200 dataset and CFD datasetCrackTree200:
Precision = 94.27%
Recall = 92.52%
F1 = 93.08%
CFD:
Precision = 96.21%
Recall = 95.12%
F1 = 95.63%
The method was only performed on accurate static images
Closing and CNN [ ]Crack detection, measurement, and classificationConcrete3208 images
256 × 256 pixels
or
128 × 128 pixels
Hand-held DSLR camerasRelative error = 5%
Accuracy > 95%
Loss < 0.1
The extraction of the cracks’ edge will have a larger influence on the results
Dilation and TunnelURes [ ]Crack detection, measurement, and classificationTunnel6810 images
image sizes vary 10441 × 2910 to 50739 × 3140
Night 4K line-scan camerasAUC = 0.97
PA = 0.928
IoU = 0.847
The medial-axis skeletonization algorithm created many errors because it was susceptible to the crack intersection and the image edges where the crack’s representation changed
Opening, closing, and U-Net [ ]Crack detection, measurement, and classificationConcrete200 images
512 × 512 pixels
Canon SX510 HS cameraPrecision = 96.52%
Recall = 93.73%
F measure = 96.12%
Accuracy = 99.74%
IoU = 78.12%
It can only detect the other type of cracks which have the same crack geometry as that of thermal cracks
Morphological operations and DeepLabV3+ [ ]Crack detection and measurementMasonry structure200 images
780 × 355 pixels
and
2880 × 1920 pixels
Internet, drones,
and smartphones
IoU = 0.97
F1 score = 98%
Accuracy = 98%
The model will not detect crack features that do not appear in the dataset (complicated cracks, tiny cracks, etc.)
Erosion, texture analysis techniques, and InceptionV3 [ ]Crack detection and classificationBridges1706 images
256 × 256 pixels
CamerasF1 score = 93.7%
Accuracy = 94.07%
-
U-Net, opening, and closing operations [ ]Crack detection and segmentationBridges244 images
512 × 512 pixels
CamerasmP = 44.57%
mR = 53.13%
Mf1 = 42.79%
mIoU = 64.79%
The model lacks generality, and there are cases of false detection
Sensor TypeFusion MethodAdvantagesDisadvantagesApplication Scenarios
Optical sensor [ ]Data-level fusionHigh resolution, rich in detailsSusceptible to light and occlusionSurface crack detection, general environments
Thermal sensor [ ]Feature level fusionSuitable for nighttime or low-light environments, detects temperature changesLow resolution, lack of detailNighttime detection, heat-sensitive areas, large-area surface crack detection
Laser sensor [ ]Data-level fusion and feature level fusionHigh-precision 3D point cloud data, accurately measures crack morphologyHigh equipment cost, complex data processingComplex structures, precise measurements
Strain sensor [ ]Feature level fusion and decision-level fusionHigh sensitivity to structural changes; durableRequires contact with the material; installation complexityMonitoring structural health in bridges and buildings; detecting early-stage crack development
Ultrasonic sensor [ ]Data-level fusion and feature level fusionDetects internal cracks in materials, strong penetrationAffected by material and geometric shape, limited resolutionInternal cracks, metal material detection
Optical fiber sensor [ ]Feature level fusionHigh sensitivity to changes in material properties, non-contact measurementAffected by environmental conditions, requires calibrationSurface crack detection, structural health monitoring
Vibration sensor [ ]Data-level fusionDetects structural vibration characteristics, strong adaptabilityAffected by environmental vibrations, requires complex signal processingDynamic crack monitoring, bridges and other structures
Multispectral satellite sensor [ ]Data-level fusionRich spectral informationLimited spectral resolution, weather- and lighting-dependent,
high cost
Pavement crack detection, bridge and infrastructure monitoring, building facade inspection
High-resolution satellite sensors [ ]Data-level fusion and feature level fusionHigh spatial resolution, wide coverage, frequent revisit times, rich information contentWeather dependency, high cost, data processing complexity, limited temporal resolutionRoad and pavement crack detection, bridge and infrastructure monitoring, urban building facade inspection, railway and highway crack monitoring
ScaleDataset/(Pixels × Pixels)References
Image-based227 × 227[ , , , ]
224 × 224[ ]
256 × 256[ ]
416 × 416[ ]
512 × 512[ ]
Patch-based128 × 128[ , ]
200 × 200[ ]
224 × 224[ , , , , ]
227 × 227[ ]
256 × 256[ , ]
300 × 300[ , ]
320 × 480[ , ]
544 × 384[ ]
512 × 512[ , , , ]
584 × 384[ ]
ModelImprovement/InnovationDatasetBackboneResults
Faster R-CNN [ ]Combined with drones for crack detection2000 images
5280 × 2970 pixels
VGG-16Precision = 92.03%
Recall = 96.26%
F1 score = 94.10%
Faster R-CNN [ ]Double-head structure is introduced, including an independent fully connected head and a convolution head1622 images
1612 × 1947 pixels
ResNet50AP = 47.2%
Mask R-CNN [ ]The morphological closing operation was incorporated into the M-R-101-FPN model to form an integrated model761 images
227 × 227 pixels
ResNets and VGGBalanced accuracy = 81.94%
F1 score = 68.68%
IoU = 52.72%
Mask R-CNN [ ]PAFPN module and edge detection branch was introduced9680 images
1500 × 1500 pixels
ResNet-FPNPrecision = 92.03%
Recall = 96.26%
AP = 94.10%
mAP = 90.57%
Error rate = 0.57%
Mask R-CNN [ ]FPN structure introduces side join method and combines FPN with ResNet-101 to change RoI-Pooling layer to RoI-Align layer3430 images
1024 × 1024 pixels
ResNet101AP = 83.3%
F1 score = 82.4%
Average error = 2.33%
mIoU = 70.1%
YOLOv3-tiny [ ]A structural crack detection and quantification method combined with structured light is proposed500 images
640 × 640 pixels
Darknet-53Accuracy = 94%
Precision = 98%
YOLOv4 [ ]Some lightweight networks were used instead of the original backbone feature extraction network, and DenseNet, MobileNet, and GhostNet were selected for the lightweight networks800 images
416 × 416 pixels
DenseNet, MobileNet v1, MobileNet v2, MobileNet v3, and GhostNetPrecision = 93.96%
Recall = 90.12%
F1 score = 92%
YOLOv4 [ ]-1463 images
256 × 256 pixels
Darknet-53Accuracy = 92%
mAP = 92%
Datasets NameNumber of ImagesImage ResolutionManual AnnotationScope of ApplicabilityLimitations
CrackTree200 [ ]206 images800 × 600 pixelsPixel-level annotations for cracksCrack classification and segmentationWith only 200 images, the dataset’s relatively small size can hinder the model’s ability to generalize across diverse conditions, potentially leading to overfitting on the specific examples provided
Crack500 [ ]500 images2000 × 1500 pixelsPixel-level annotations for cracksCrack classification and segmentationLimited number of images compared to larger datasets, which might affect the generalization of models trained on this dataset
SDNET 2018 [ ]56000 images256 × 256 pixelsPixel-level annotations for cracksCrack classification and segmentationThe dataset’s focus on concrete surfaces may limit the model’s performance when applied to different types of surfaces or structures
Mendeley data—crack detection [ ]40000 images227 × 227 pixelsPixel-level annotations for cracksCrack classificationThe dataset might not cover all types of cracks or surface conditions, which can limit its applicability to a wide range of real-world scenarios
DeepCrack [ ]2500 images512 × 512 pixelsAnnotations for cracksCrack segmentationThe resolution might limit the ability of models to capture very small or subtle crack features
CFD [ ]118 images320 × 480 pixelsPixel-level annotations for cracksCrack segmentationThe dataset contains a limited number of data samples, which may limit the generalization ability of the model
CrackTree260 [ ]260 images800 × 600 pixels
and
960 × 720 pixels
Pixel-level labeling, bounding boxes, or other crack markersObject detection and segmentationBecause the dataset is small, it can be easy for the model to overfit the training data, especially if you’re using a complex model
CrackLS315 [ ]315 images512 × 512 pixelsPixel-level segmentation mask or bounding boxObject detection and segmentationThe small size of the dataset may make the model perform poorly in complex scenarios, especially when encountering different types of cracks or uncommon crack features
Stone331 [ ]331 images512 × 512 pixelsPixel-level segmentation mask or bounding boxObject detection and segmentationThe relatively small number of images limits the generalization ability of the model, especially in deep learning tasks where smaller datasets tend to lead to overfitting
IndexIndex Value and Calculation FormulaCurve
True positive -
False positive -
True negative -
False negative -
Precision PRC
Recall PRC, ROC curve
F1 score F1 score curve
Accuracy Accuracy vs. threshold curve
Average precision PRC
Mean average precision -
IoU IoU distribution curve, precision-recall curve with IoU thresholds
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Yuan, Q.; Shi, Y.; Li, M. A Review of Computer Vision-Based Crack Detection Methods in Civil Infrastructure: Progress and Challenges. Remote Sens. 2024 , 16 , 2910. https://doi.org/10.3390/rs16162910

Yuan Q, Shi Y, Li M. A Review of Computer Vision-Based Crack Detection Methods in Civil Infrastructure: Progress and Challenges. Remote Sensing . 2024; 16(16):2910. https://doi.org/10.3390/rs16162910

Yuan, Qi, Yufeng Shi, and Mingyue Li. 2024. "A Review of Computer Vision-Based Crack Detection Methods in Civil Infrastructure: Progress and Challenges" Remote Sensing 16, no. 16: 2910. https://doi.org/10.3390/rs16162910

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NCBI Bookshelf. A service of the National Library of Medicine, National Institutes of Health.

Janeway CA Jr, Travers P, Walport M, et al. Immunobiology: The Immune System in Health and Disease. 5th edition. New York: Garland Science; 2001.

By agreement with the publisher, this book is accessible by the search feature, but cannot be browsed.

Cover of Immunobiology

Immunobiology: The Immune System in Health and Disease. 5th edition.

Infectious agents and how they cause disease.

Infectious disease can be devastating, and sometimes fatal, to the host. In this part of the chapter we will briefly examine the stages of infection, and the various types of infectious agents.

10-1. The course of an infection can be divided into several distinct phases

The process of infection can be broken down into stages, each of which can be blocked by different defense mechanisms. In the first stage, a new host is exposed to infectious particles shed by an infected individual. The number, route, mode of transmission, and stability of an infectious agent outside the host determines its infectivity. Some pathogens, such as anthrax, are spread by spores that are highly resistant to heat and drying, while others, such as the human immunodeficiency virus ( HIV ), are spread only by the exchange of bodily fluids or tissues because they are unable to survive as infectious agents outside the body.

The first contact with a new host occurs through an epithelial surface. This may be the skin or the internal mucosal surfaces of the respiratory, gastro-intestinal, and urogenital tracts. After making contact, an infectious agent must establish a focus of infection. This involves adhering to the epithelial surface, and then colonizing it, or penetrating it to replicate in the tissues ( Fig. 10.2 , left-hand panels). Many microorganisms are repelled at this stage by innate immunity . We have discussed the innate immune defense mediated by epithelia and by phagocytes and complement in the underlying tissues in Chapter 2. Chapter 2 also discusses how NK cells are activated in response to intracellular infections, and how a local inflammatory response and induced cytokines and chemokines can bring more effector cells and molecules to the site of an infection while preventing pathogen spread into the blood. These innate immune responses use a variety of germline-encoded receptors to discriminate between microbial and host cell surfaces, or infected and normal cells. They are not as effective as adaptive immune responses, which can afford to be more powerful on account of their antigen specificity . However, they can prevent an infection being established, or failing that, contain it while an adaptive immune response develops.

Figure 10.2

Infections and the responses to them can be divided into a series of stages. These are illustrated here for an infectious microorganism entering across an epithelium, the commonest route of entry. The infectious organism must first adhere to epithelial (more...)

Only when a microorganism has successfully established a site of infection in the host does disease occur, and little damage will be caused unless the agent is able to spread from the original site of infection or can secrete toxins that can spread to other parts of the body. Extracellular pathogens spread by direct extension of the focus of infection through the lymphatics or the bloodstream. Usually, spread by the bloodstream occurs only after the lymphatic system has been overwhelmed by the burden of infectious agent. Obligate intracellular pathogens must spread from cell to cell; they do so either by direct transmission from one cell to the next or by release into the extracellular fluid and reinfection of both adjacent and distant cells. Many common food poisoning organisms cause pathology without spreading into the tissues. They establish a site of infection on the epithelial surface in the lumen of the gut and cause no direct pathology themselves, but they secrete toxins that cause damage either in situ or after crossing the epithelial barrier and entering the circulation.

Most infectious agents show a significant degree of host specificity , causing disease only in one or a few related species. What determines host specificity for every agent is not known, but the requirement for attachment to a particular cell-surface molecule is one critical factor. As other interactions with host cells are also commonly needed to support replication, most pathogens have a limited host range. The molecular mechanisms of host specificity comprise an area of research known as molecular pathogenesis, which falls outside the scope of this book.

While most microorganisms are repelled by innate host defenses, an initial infection, once established, generally leads to perceptible disease followed by an effective host adaptive immune response . This is initiated in the local lymphoid tissue, in response to antigens presented by dendritic cells activated during the course of the innate immune response ( Fig. 10.2 , third and fourth panels). Antigen-specific effector T cells and antibody -secreting B cells are generated by clonal expansion and differentiation over the course of several days, during which time the induced responses of innate immunity continue to function. Eventually, antigen -specific T cells and then antibodies are released into the blood and recruited to the site of infection ( Fig. 10.2 , last panel). A cure involves the clearance of extracellular infectious particles by antibodies and the clearance of intracellular residues of infection through the actions of effector T cells.

After many types of infection there is little or no residual pathology following an effective primary response. In some cases, however, the infection or the response to it causes significant tissue damage. In other cases, such as infection with cytomegalovirus or Mycobacterium tuberculosis , the infection is contained but not eliminated and can persist in a latent form. If the adaptive immune response is later weakened, as it is in acquired immune deficiency syndrome ( AIDS ), these diseases reappear as virulent systemic infections. We will focus on the strategies used by certain pathogens to evade or subvert adaptive immunity and thereby establish a persistent infection in the first part of Chapter 11.

In addition to clearing the infectious agent, an effective adaptive immune response prevents reinfection. For some infectious agents, this protection is essentially absolute, while for others infection is reduced or attenuated upon reexposure.

10-2. Infectious diseases are caused by diverse living agents that replicate in their hosts

The agents that cause disease fall into five groups: viruses, bacteria , fungi, protozoa, and helminths (worms). Protozoa and worms are usually grouped together as parasites, and are the subject of the discipline of parasitology, whereas viruses, bacteria, and fungi are the subject of microbiology. In Fig. 10.3 , the classes of microorganisms and parasites that cause disease are listed, with typical examples of each. The remarkable variety of these pathogens has caused the natural selection of two crucial features of adaptive immunity. First, the advantage of being able to recognize a wide range of different pathogens has driven the development of receptors on B and T cells of equal or greater diversity. Second, the distinct habitats and life cycles of pathogens have to be countered by a range of distinct effector mechanisms. The characteristic features of each pathogen are its mode of transmission, its mechanism of replication, its pathogenesis or the means by which it causes disease, and the response it elicits. We will focus here on the immune responses to these pathogens.

Figure 10.3

A variety of microorganisms can cause disease. Pathogenic organisms are of five main types: viruses, bacteria, fungi, protozoa, and worms. Some common pathogens in each group are listed in the column on the right.

Infectious agents can grow in various body compartments, as shown schematically in Fig. 10.4 . We have already seen that two major compartments can be defined—intracellular and extracellular. Intracellular pathogens must invade host cells in order to replicate, and so must either be prevented from entering cells or be detected and eliminated once they have done so. Such pathogens can be subdivided further into those that replicate freely in the cell, such as viruses and certain bacteria (species of Chlamydia and Rickettsia as well as Listeria ), and those, such as the mycobacteria, that replicate in cellular vesicles. Viruses can be prevented from entering cells by neutralizing antibodies whose production relies on T H 2 cells (see Section 9-14 ), while once within cells they are dealt with by virus-specific cytotoxic T cells , which recognize and kill the infected cell (see Section 8-21 ). Intravesicular pathogens, on the other hand, mainly infect macrophages and can be eliminated with the aid of pathogen-specific T H 1 cells , which activate infected macrophages to destroy the pathogen (see Section 8-26 ).

Figure 10.4

Pathogens can be found in various compartments of the body, where they must be combated by different host defense mechanisms. Virtually all pathogens have an extracellular phase where they are vulnerable to antibody-mediated effector mechanisms. However, intracellular (more...)

Many microorganisms replicate in extracellular spaces, either within the body or on the surface of epithelia. Extracellular bacteria are usually susceptible to killing by phagocytes and thus pathogenic species have developed means of resisting engulfment. The encapsulated gram-positive cocci, for instance, grow in extracellular spaces and resist phagocytosis by means of their polysaccharide capsule. This means they are not immediately eliminated by tissue phagocytes on infecting a previously unexposed host. However, if this mechanism of resistance is overcome by opsonization by complement and specific antibody , they are readily killed after ingestion by phagocytes. Thus, these extracellular bacteria are cleared by means of the humoral immune response (see Chapter 9).

Different infectious agents cause markedly different diseases, reflecting the diverse processes by which they damage tissues ( Fig. 10.5 ). Many extracellular pathogens cause disease by releasing specific toxic products or protein toxins (see Fig. 9.23 ), which can induce the production of neutralizing antibodies (see Section 9-14 ). Intracellular infectious agents frequently cause disease by damaging the cells that house them. The specific killing of virus-infected cells by cytotoxic T cells thus not only prevents virus spread but removes damaged cells. The immune response to the infectious agent can itself be a major cause of pathology in several diseases (see Fig. 10.5 ). The pathology caused by a particular infectious agent also depends on the site in which it grows; Streptococcus pneumoniae in the lung causes pneumonia, whereas in the blood it causes a rapidly fatal systemic illness.

Figure 10.5

Pathogens can damage tissues in a variety of different ways. The mechanisms of damage, representative infectious agents, and the common names of the diseases associated with each are shown. Exotoxins are released by microorganisms and act at the surface (more...)

As we learned in Chapter 2, for a pathogen to invade the body, it must first bind to or cross the surface of an epithelium. When the infection is due to intestinal pathogens such as Salmonella typhi , the causal agent of typhoid fever, or Vibrio cholerae , which causes cholera, the adaptive immune response occurs in the specialized mucosal immune system associated with the gastrointestinal tract, as described later in this chapter. Some intestinal pathogens even target the M cells of the gut mucosal immune system, which are specialized to transport antigens across the epithelium, as a means of entry.

Many pathogens cannot be entirely eliminated by the immune response . But neither are most pathogens universally lethal. Those pathogens that have persisted for many thousands of years in the human population are highly evolved to exploit their human hosts, and cannot alter their pathogenicity without upsetting the compromise they have achieved with the human immune system . Rapidly killing every host it infects is no better for the long-term survival of a pathogen than being wiped out by the immune response before it has had time to infect another individual. In short, we have learned to live with our enemies, and they with us. However, we must be on the alert at all times for new pathogens and new threats to health. The human immunodeficiency virus that causes AIDS serves as a warning to mankind that we remain constantly vulnerable to the emergence of new infectious agents.

The mammalian body is susceptible to infection by many pathogens, which must first make contact with the host and then establish a focus of infection in order to cause infectious disease. To establish an infection, the pathogen must first colonize the skin or the internal mucosal surfaces of the respiratory, gastrointestinal, or urogenital tracts and then overcome or bypass the innate immune defenses associated with the epithelia and underlying tissues. If it succeeds in doing this, it will provoke an adaptive immune response that will take effect after several days and will usually clear the infection. Pathogens differ greatly in their lifestyles and means of pathogenesis, requiring an equally diverse set of defensive responses from the host immune system .

  • Cite this Page Janeway CA Jr, Travers P, Walport M, et al. Immunobiology: The Immune System in Health and Disease. 5th edition. New York: Garland Science; 2001. Infectious agents and how they cause disease.
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