disturbances
Each domain of the PSQI was negatively correlated with the HRQOL domains, but showed the strongest correlation with the HRQOL physical domain. The correlation between sleep quality and physical domain was the strongest (− 0.614), followed by daytime dysfunction (− 0.536), and sleep disturbances (− 0.503). Sleep quality, daytime dysfunction, and sleep disturbances also had a strong negative correlation with the HRQOL psychological domain; the correlation coefficients were − 0.477, − 0.508, and − 0.446, respectively. The correlation coefficient between the PSQI and HRQOL total score was − 0.557.(Table 3 ).
The SEM analysis results were as follows, which indicated that the model fit the data well: χ 2 = 483.013; p < 0.001; root mean square error of approximation (RMSEA), 0.096; and goodness of fit (GFI), 0.883. The SEM results also showed that within the mental health dimension, depression had the largest factor loading (0.93). Sleep quality had the largest factor loading (0.82) within the PSQI. The HRQOL psychological domain had the largest factor loading (0.89), followed by the physical and environmental domains (0.83 and 0.84, respectively). The path coefficients of mental health on HRQOL and PSQI were − 0.75 and 0.72, respectively, while the path coefficient of sleep status on HRQOL was only − 0.15(Fig. 1 ).
The structural equation model for the hypothesis that mental health domains and sleep status (PSQI) influence the health-related quality of life in people living with HIV/AIDS.
With the COVID-19 global pandemic, mental health has become a common issue for the general public. People in different regions or countries have been reported to experience severe mental health and sleep problems during the COVID-19 pandemic [ 29 , 30 ]. Although mental health and sleep status have been reported to impact the quality of life among PLWHA [ 31 , 32 ], with the implementation of strict preventive policies during the COVID-19 epidemic in China, PLWHA may not only experience the mental stress from HIV infection and treatment, but also face stress from life and work, which might cause severe mental health or sleep problems for PLWHA than usual. Our results showed a higher incidence of anxiety and depression than previous studies conducted involving Chinese PLWHA prior to the COVID-19 outbreak. More severe mental health and sleep problems among PLWHA existed during COVID-19 epidemic based on the findings in current study [ 28 , 33 , 34 ]. The same results were also found in other regions outside China [ 35 , 36 ]. More severe psychological and sleep problems during COVID-19 pandemic may result in more adverse effects on the HRQOL for PLWHA.
Correlation analysis showed that anxiety and depression had a strong positive correlation with sleep disturbances and sleep quality. Mental health status is usually considered to be a cause, rather than a consequence of sleep disturbance among HIV-infected patients [ 37 , 38 ]. Anxiety had a closer correlation with sleep disturbances and sleep quality than depression among PLWHA. Anxiety and depression also had a significant negative correlation with the psychological and physical domains of HRQOL, but depression was more significantly associated with psychological health. In brief, anxiety may lead to more adverse effects on sleep status, while depression may more affect the psychological health among PLWHA.
The present study showed that all domains of the PSQI exhibited the strongest negative correlativity with the HRQOL physical domain. The most notable correlation was between sleep quality and the physical domain (coefficient, − 0.614). Moreover, daytime dysfunction, sleep disturbances and sleep quality of the PSQI also had a significant correlation with the HRQOL psychological domain. Studies revealed that improved sleep quality promotes improvement in the HRQOL among patients with HIV, and better sleep helps reduce anxious personality and depressive symptoms [ 39 , 40 ]. Our study revealed that sleep quality, daytime dysfunction, and sleep disturbances can exert a greater effect on physical and psychological health among PLWHA. Intervention for sleep status is more effective in improving HRQOL, especially for taking measures to improve sleep quality, daytime dysfunction, and sleep disturbances not only benefit physical health, but also promote psychological health among PLWHA. Although some studies have identified influencing factors, such as social support and socioeconomic status on the quality of life among PLWHA [ 5 , 41 ], intervention targeting social support and economic status may not be an effective measure that can achieve a short-term effect. Intervention strategies to improve mental health and sleep are feasible methods to evaluate the intervening effect in anytime because implementing mental health and sleep status interventions are likely to be quick and facilitated to improve the quality of life among PLWHA.
The SEM showed that the HRQOL psychological, environmental, and physical domains exhibited the largest factor loadings, indicating psychological, environmental, and physical health status among PLWHA had the most significant influence on the overall HRQOL. The significant feature of the environmental domain influence on HRQOL suggests that improving the environmental health among PLWHA may also be an important measure to improve HRQOL. This viewpoint is in agreement with a previously published finding [ 4 ] that emphasized the important role of the environmental domain on influencing the quality of life among PLWHA. In addition, the results of the SEM analysis revealed that the path coefficient of the HRQOL mental health domain ( − 0.75 ) was far greater than the HRQOL sleep status domain (− 0.15). When compared with sleep status, intervention for mental health will have a greater effect on improving the quality of life among PLWHA. Moreover, considering that the depression and psychological domains had the largest loading factors in mental health and the HRQOL, and a strong positive correlation existed between depression and the psychological domain according to the results of correlation analysis, interventions for depression among PLWHA should be the most effective manner for improving HRQOL. Interventions for depression will have a direct role in improving the HRQOL psychological health domain, and can be regarded as the most effective way to improve the quality of life among PLWHA.
The present study was conducted using a web-based online survey. This online-based survey of PLWHA is very popular [ 30 , 42 , 43 ], and during the COVID-19 pandemic, this survey method was seemingly most appropriate and useful, because it was convenient for PLWHA to respond and reply using a web-based method under the COVID-19 strict control measures. Moreover, this method can also protect the privacy issues for this special population. Overall, it was possible to obtain accurate information compared to an off-line face-to-face mode; however, the obtained samples may have been subject to selection bias. During the survey, although the clinicians informed their patients to cooperate as much as possible to complete the questionnaires, some candidates may still not take part according to the principle of voluntary participation, leading to the study were more made up of voluntary samples. In conclusion, the results of this study showed the significance of mental health on sleep status and quality of life among PLWHA. Interventions for depression among PLWHA are the most effective manner to improve HRQOL and promote psychological health. Given the high incidence of depressive symptoms among Chinese PLWHA [ 34 , 44 ], treatment, if supplemented with mental health interventions, such as controlling or alleviating depression symptoms, will achieve a better treatment effect. Physicians should not only focus on the results of antiviral treatment of patients, but also pay more attention to their mental health status and take appropriate intervention measures, which will improve the quality of life among PLWHA, especially during the infectious disease pandemic such as COVID-19.
Below is the link to the electronic supplementary material.
The authors would like to thank all the subjects for their participation and cooperation.
Juan Du, Jin Li and Bing Shao analyzed and wrote the main manuscript text and prepared Tables 1 , ,2 2 and and3; 3 ; Fig. 1 ; .Han Liang, Fuxiang Wang and Yuanlong Lin explained and discussed the main analysis results; .Jin Li and Yuanlong Lin carried out the survey. All authors reviewed the manuscript.
This work is supported by National Natural Science Foundation of China(82272318 and 81602899), Jilin Provincial Health Youth Science and Technology Backbone Training Program (2019Q034), Jilin Provincial Department of Education “Thirteenth Five Year” Science and Technology Project (JJKH20200464KJ), and the Jilin Provincial Science and Technology Development Plan Project (20180520107JH).
Declarations.
The study was approved by the Medical Ethics Committee of Jilin Medical University. All methods were carried out in accordance with relevant guidelines and regulations. Participants were fully informed of the objective of this study as well as their information was for academic use only before completing the online questionnaires. Survey was based on the principles of voluntary participation, confidentiality, and respect. Respondents volunteered to participate in the study. If the respondents participated and completed the investigation meant informed consent was obtained automatically. Based on these principles, participants were not required to sign an informed consent document.
Not applicable.
The authors declare no competing interests.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Juan Du and Jin Li contributed equally to this work.
Yuanlong Lin, Email: moc.621@gnol_nauynil .
Bing Shao, Email: moc.621@9860yppah .
In 2022, the World Health Organization (WHO) introduced a new online course aimed at strengthening health systems resilience in the face of public health challenges. The course – available through OpenWHO – addresses both acute shocks, such as infectious disease outbreaks and environmental disasters, and chronic stressors like non-communicable diseases and antimicrobial resistance.
Course overview
As demonstrated by the COVID-19 pandemic, health systems worldwide are under constant pressure from a range of public health threats, both acute and chronic. These challenges can severely impact the delivery of essential health services, leading to setbacks in achieving universal health coverage (UHC) and health security goals. WHO emphasizes the need for a renewed focus on building resilience by addressing critical vulnerabilities within health systems – before, during and after a shock event.
This course targets decision-makers in public health policy and health service managers at national, subnational and community levels. It promotes an integrated approach and actions to enhance health systems resilience across policymaking, planning, service delivery and monitoring and evaluation.
Course structure and certification
The course, which takes approximately five hours to complete, is divided into four modules:
Each module has short learning sessions with exercises, case scenarios, discussion points and quizzes. Participants who score at least 80% will receive a Record of Achievement certificate, while those who complete 80% of the course material will earn a Confirmation of Participation certificate. Additionally, a digital Open Badge is available for those who achieve a Record of Achievement.
Since the offline course materials were adapted for virtual learning and published on OpenWHO in 2022, there have been 6870 enrollments – a testament to the growing need for WHO’s support in this area.
This dedicated training package is part of WHO’s programme of work on health systems resilience and essential public health functions which is supported by the UHC Partnership as well as by other partners including the Korea International Cooperation Agency (KOICA), the United States Agency for International Development (USAID), the Public Health Agency of Canada (PHAC), and the Foreign, Commonwealth and Development Office (FCDO) of the United Kingdom.
Learning outcomes
By the end of the course, participants will be able to:
For more information and to enrol in the course, visit the course webpage .
About OpenWHO
OpenWHO , launched in 2017 by the Learning and Capacity Development Unit in the WHO Health Emergencies Programme, is a free open-access online learning platform covering a wide a variety of public health topics. It offers self-paced, multilingual courses based on WHO’s guidance and designed for frontline responders, health workers, policymakers and anyone interested in public health. The platform provides low-bandwidth, adaptable and translatable resources. It also offers CPD-accredited courses for ongoing professional development.
For more information, visit the publications , newsletters and FAQ section of the website. Join OpenWHO today to access high-quality learning programs and make a difference in public health.
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In a recent study published in PLoS Computational Biology , researchers used mathematical modelling to evaluate whether prioritizing older individuals for coronavirus disease 2019 (COVID-19) booster vaccinations consistently leads to optimal public health outcomes across diverse socio-economic settings.
In the early stages of the COVID-19 pandemic, non-pharmaceutical interventions (NPIs) were crucial in reducing transmission and protecting healthcare systems.
The introduction of vaccines, such as those from Pfizer-BioNTech, Oxford-AstraZeneca, and Moderna, significantly altered the pandemic's trajectory by reducing severe cases and relaxing NPIs.
However, immunity from these vaccines wanes over time, necessitating booster vaccinations, especially with emerging variants.
Further research is needed to refine booster vaccination strategies to address varying population structures and socio-economic contexts globally, ensuring the most effective public health outcomes.
The study extends a previously published age-structured compartmental model of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) transmission and vaccination.
This deterministic model, governed by ordinary differential equations, divides individuals into compartments based on age, current infection status, and immune status before any infection.
The model includes 16 age groups, with individuals classified as Susceptible, Exposed, Infectious (symptomatic or asymptomatic), or Recovered.
To more accurately represent the time spent in the exposed class, the model employs gamma distributions, which provide a realistic representation of epidemiological periods.
The model also tracks immune status, categorizing individuals into groups such as Vaccinated, Boosted, Partially Waned, Fully Waned, and Unvaccinated, reflecting their infection and vaccination history.
The effectiveness of vaccination is incorporated into the model, accounting for reduced risks of infection, symptoms, hospitalization, and death.
Using this model, the study examines the impacts of six different age-based booster vaccination strategies across eight countries. Strategy 1 prioritizes the oldest individuals first, while Strategy 6 explores vaccinating those with the most contacts to provide indirect protection to the elderly.
Strategies 2-5 test variations of these approaches, generally focusing on prioritizing older individuals for booster vaccination. The analysis assumes limited vaccine availability, with a 10% population coverage baseline and a 90% maximum uptake per age group.
The population's age structure varies significantly across countries, with high-income countries generally having a larger proportion of older individuals compared to low-income countries.
This demographic difference influences the distribution of booster vaccines under different vaccination strategies. In the UK, for instance, strategies 1-4 that prioritize older individuals for booster vaccination result in a substantial number of individuals aged 50-74 receiving vaccines. However, the oldest individuals (75+) may not be fully covered due to the limited vaccine supply.
On the other hand, Strategies focused on vaccinating younger individuals, particularly those aged 20-49, who typically have more contacts and, therefore, could potentially contribute to indirect protection of older populations.
However, the age distribution of vaccinated individuals under each strategy varies between countries. For example, in Sierra Leone, where the proportion of older individuals is relatively small, Strategies 1-4 effectively vaccinate almost all older individuals, leading to identical outcomes for these strategies.
This contrasts with the situation in the UK, where a larger elderly population means that not all older individuals can be vaccinated under these strategies due to vaccine constraints.
When considering the impact of these strategies on public health outcomes during a wave of infections caused by a novel SARS-CoV-2 variant, the model projections indicated that Strategy 1 consistently resulted in the fewest deaths across all countries analyzed.
This outcome is particularly evident in high-income countries, where a large proportion of older individuals contribute to a higher projected number of deaths if they are not prioritized for booster vaccination.
In contrast, in countries like Sierra Leone, the small number of older individuals allows nearly all of them to receive booster vaccines under Strategy 1, leading to fewer deaths overall.
The analysis also examined the projected Years of Life Lost (YLL), which accounts for the number of deaths and the ages at which they occur.
While it might be expected that vaccinating younger individuals could reduce YLL, the model consistently showed that Strategy 1, which prioritizes the oldest individuals, was optimal in minimizing YLL. This is due to the higher risk of severe outcomes and mortality associated with SARS-CoV-2 infection in older populations.
Sensitivity analyses further supported these findings, showing that Strategy 1 led to fewer deaths and YLL under various assumptions, including different levels of vaccine availability, uptake rates, and timing of booster administration.
Even when the outbreak began 150 days after booster vaccines were administered, resulting in some immunity waning, Strategy 1 remained the most effective approach in reducing deaths and YLL.
To summarize, future SARS-CoV-2 transmission will be influenced by novel variants, booster vaccinations, and immunity dynamics. Unlike the pandemic's early stages, many individuals globally are now infected or vaccinated, impacting immunity and transmission.
In this evolving scenario, it is essential to reassess the effectiveness of past interventions and explore new strategies.
This study evaluated different age-based booster vaccination strategies and found that prioritizing older individuals consistently leads to better public health outcomes, regardless of varying population structures.
Bouros I, Hill EM, Keeling MJ, et al. (2024) Prioritizing older individuals for COVID-19 booster vaccination leads to optimal public health outcomes in a range of socio-economic settings. PLoS Comput Biol . doi : https://doi.org/10.1371/journal. pcbi.1012309 . https://journals.plos.org/ploscompbiol/article?
Posted in: Medical Science News | Medical Research News | Medical Condition News | Disease/Infection News
Tags: Coronavirus , Coronavirus Disease COVID-19 , covid-19 , Healthcare , immunity , Mortality , Pandemic , Public Health , Research , Respiratory , SARS , SARS-CoV-2 , Severe Acute Respiratory , Severe Acute Respiratory Syndrome , Syndrome , Vaccine
Vijay holds a Ph.D. in Biotechnology and possesses a deep passion for microbiology. His academic journey has allowed him to delve deeper into understanding the intricate world of microorganisms. Through his research and studies, he has gained expertise in various aspects of microbiology, which includes microbial genetics, microbial physiology, and microbial ecology. Vijay has six years of scientific research experience at renowned research institutes such as the Indian Council for Agricultural Research and KIIT University. He has worked on diverse projects in microbiology, biopolymers, and drug delivery. His contributions to these areas have provided him with a comprehensive understanding of the subject matter and the ability to tackle complex research challenges.
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