Dataset Information

Face mask use in the general population and optimal resource allocation during the COVID-19 pandemic.

ABSTRACT: The ongoing novel coronavirus disease (COVID-19) pandemic has rapidly spread in early 2020, causing tens of thousands of deaths, over a million cases and widespread socioeconomic disruption. With no vaccine available and numerous national healthcare systems reaching or exceeding capacity, interventions to limit transmission are urgently needed. While there is broad agreement that travel restrictions and closure of non-essential businesses and schools are beneficial in limiting local and regional spread, and such measures have been adopted in countries around the world, recommendations around the use of face masks for the general population are less consistent internationally. In this study, we examined the role of face masks in mitigating the spread of COVID-19 in the general population, using epidemic models to estimate the total reduction of infections and deaths under various scenarios. In particular, we examined the optimal deployment of face masks when resources are limited. We found that face masks, even with a limited protective effect, can reduce infections and deaths, and can delay the peak time of the epidemic. We consistently found that a random distribution of masks in the population was a suboptimal strategy when resources were limited. Prioritizing coverage among the elderly was more beneficial, while allocating a proportion of available resources for diagnosed infected cases provided further mitigation under a range of scenarios. In summary, face mask use, particularly for a pathogen with relatively common asymptomatic carriage, can effectively provide some mitigation of transmission, while balancing provision between vulnerable healthy persons and symptomatic persons can optimize mitigation efforts when resources are limited.

SUBMITTER: Worby CJ

PROVIDER: S-EPMC7276053 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Face mask use in the general population and optimal resource allocation during the COVID-19 pandemic.

Worby Colin J CJ Chang Hsiao-Han HH

medRxiv : the preprint server for health sciences 20200407

The ongoing novel coronavirus disease (COVID-19) pandemic has rapidly spread in early 2020, causing tens of thousands of deaths, over a million cases and widespread socioeconomic disruption. With no vaccine available and numerous national healthcare systems reaching or exceeding capacity, interventions to limit transmission are urgently needed. While there is broad agreement that travel restrictions and closure of non-essential businesses and schools are beneficial in limiting local and regional ...[more]

PMID: 32511626

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Project description:The 2019 novel coronavirus (COVID-19) pandemic is associated with increases in psychiatric morbidity, including depression. It is unclear if people with depressive symptoms understand or apply COVID-19 information differently to the general population. Therefore, this study aimed to examine associations between depression, health beliefs, and face mask use during the COVID-19 pandemic among the general population in Hong Kong. This study gathered data from 11,072 Hong Kong adults via an online survey. Respondents self-reported their demographic characteristics, depressive symptoms (PHQ-9), face mask use, and health beliefs about COVID-19. Hierarchical logistic regression was used to identify independent variables associated with depression. The point-prevalence of probable depression was 46.5% (n = 5,150). Respondents reporting higher mask reuse (OR = 1.24, 95%CI 1.17-1.34), wearing masks for self-protection (OR = 1.03 95%CI 1.01-1.06), perceived high susceptibility (OR = 1.15, 95%CI 1.09-1.23), and high severity (OR = 1.33, 95%CI 1.28-1.37) were more likely to report depression. Depression was less likely in those with higher scores for cues to action (OR = 0.82, 95%CI 0.80-0.84), knowledge of COVID-19 (OR = 0.95, 95%CI 0.91-0.99), and self-efficacy to wear mask properly (OR = 0.90 95%CI 0.83-0.98). We identified a high point-prevalence of probable major depression and suicidal ideation during the COVID-19 outbreak in Hong Kong, but this should be viewed with caution due to the convenience sampling method employed. Future studies should recruit a representative probability sample in order to draw more reliable conclusions. The findings highlight that COVID-19 health information may be a protective factor of probable depression and suicidal ideation during the pandemic. Accurate and up-to-date health information should be disseminated to distressed and vulnerable subpopulations, perhaps using digital health technology, and social media platforms to prompt professional help-seeking behavior.

Project description:BackgroundThe world is currently confronting the first influenza pandemic of the 21(st) century. Influenza vaccination is an effective preventive measure, but the unique epidemiological features of swine-origin influenza A (H1N1) (pH1N1) introduce uncertainty as to the best strategy for prioritization of vaccine allocation. We sought to determine optimal prioritization of vaccine distribution among different age and risk groups within the Canadian population, to minimize influenza-attributable morbidity and mortality.Methodology/principal findingsWe developed a deterministic, age-structured compartmental model of influenza transmission, with key parameter values estimated from data collected during the initial phase of the epidemic in Ontario, Canada. We examined the effect of different vaccination strategies on attack rates, hospitalizations, intensive care unit admissions, and mortality. In all scenarios, prioritization of high-risk individuals (those with underlying chronic conditions and pregnant women), regardless of age, markedly decreased the frequency of severe outcomes. When individuals with underlying medical conditions were not prioritized and an age group-based approach was used, preferential vaccination of age groups at increased risk of severe outcomes following infection generally resulted in decreased mortality compared to targeting vaccine to age groups with higher transmission, at a cost of higher population-level attack rates. All simulations were sensitive to the timing of the epidemic peak in relation to vaccine availability, with vaccination having the greatest impact when it was implemented well in advance of the epidemic peak.Conclusions/significanceOur model simulations suggest that vaccine should be allocated to high-risk groups, regardless of age, followed by age groups at increased risk of severe outcomes. Vaccination may significantly reduce influenza-attributable morbidity and mortality, but the benefits are dependent on epidemic dynamics, time for program roll-out, and vaccine uptake.

Dataset Information

Face mask use in the general population and optimal resource allocation during the COVID-19 pandemic.

Publications

Face mask use in the general population and optimal resource allocation during the COVID-19 pandemic.

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