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      Global perspective of COVID‐19 epidemiology for a full‐cycle pandemic

        1
      European Journal of Clinical Investigation
      Wiley

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Abstract As of October 2020, there are >1 million documented deaths with COVID‐19. Excess deaths can be caused by both COVID‐19 and the measures taken. COVID‐19 shows extremely strong risk stratification across age, socioeconomic factors, and clinical factors. Calculation of years‐of‐life‐lost from COVID‐19 is methodologically challenging and can yield misleading over‐estimates. Many early deaths may have been due to suboptimal management, malfunctional health systems, hydroxychloroquine, sending COVID‐19 patients to nursing homes, and nosocomial infections; such deaths are partially avoidable moving forward. About 10% of the global population may be infected by October 2020. Global infection fatality rate is 0.15‐0.20% (0.03‐0.04% in those <70 years), with large variability across locations with different age‐structure, institutionalization rates, socioeconomic inequalities, population‐level clinical risk profile, public health measures, and health care. There is debate on whether at least 60% of the global population must be infected for herd immunity, or, conversely, mixing heterogeneity and pre‐existing cross‐immunity may allow substantially lower thresholds. Simulations are presented with a total of 1.58‐8.76 million COVID‐19 deaths over 5‐years (1/2020‐12/2024) globally (0.5‐2.9% of total global deaths). The most favorable figures in that range would be feasible if high risk groups can be preferentially protected with lower infection rates than the remaining population. Death toll may also be further affected by potential availability of effective vaccines and treatments, optimal management and measures taken, COVID‐19 interplay with influenza and other health problems, reinfection potential, and any chronic COVID‐19 consequences. Targeted, precise management of the pandemic and avoiding past mistakes would help minimize mortality.

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          Most cited references11

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          The psychological impact of quarantine and how to reduce it: rapid review of the evidence

          Summary The December, 2019 coronavirus disease outbreak has seen many countries ask people who have potentially come into contact with the infection to isolate themselves at home or in a dedicated quarantine facility. Decisions on how to apply quarantine should be based on the best available evidence. We did a Review of the psychological impact of quarantine using three electronic databases. Of 3166 papers found, 24 are included in this Review. Most reviewed studies reported negative psychological effects including post-traumatic stress symptoms, confusion, and anger. Stressors included longer quarantine duration, infection fears, frustration, boredom, inadequate supplies, inadequate information, financial loss, and stigma. Some researchers have suggested long-lasting effects. In situations where quarantine is deemed necessary, officials should quarantine individuals for no longer than required, provide clear rationale for quarantine and information about protocols, and ensure sufficient supplies are provided. Appeals to altruism by reminding the public about the benefits of quarantine to wider society can be favourable.
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            Loneliness and social isolation as risk factors for mortality: a meta-analytic review.

            Actual and perceived social isolation are both associated with increased risk for early mortality. In this meta-analytic review, our objective is to establish the overall and relative magnitude of social isolation and loneliness and to examine possible moderators. We conducted a literature search of studies (January 1980 to February 2014) using MEDLINE, CINAHL, PsycINFO, Social Work Abstracts, and Google Scholar. The included studies provided quantitative data on mortality as affected by loneliness, social isolation, or living alone. Across studies in which several possible confounds were statistically controlled for, the weighted average effect sizes were as follows: social isolation odds ratio (OR) = 1.29, loneliness OR = 1.26, and living alone OR = 1.32, corresponding to an average of 29%, 26%, and 32% increased likelihood of mortality, respectively. We found no differences between measures of objective and subjective social isolation. Results remain consistent across gender, length of follow-up, and world region, but initial health status has an influence on the findings. Results also differ across participant age, with social deficits being more predictive of death in samples with an average age younger than 65 years. Overall, the influence of both objective and subjective social isolation on risk for mortality is comparable with well-established risk factors for mortality.
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              Losing life and livelihood: a systematic review and meta-analysis of unemployment and all-cause mortality.

              Unemployment rates in the United States remain near a 25-year high and global unemployment is rising. Previous studies have shown that unemployed persons have an increased risk of death, but the magnitude of the risk and moderating factors have not been explored. The study is a random effects meta-analysis and meta-regression designed to assess the association between unemployment and all-cause mortality among working-age persons. We extracted 235 mortality risk estimates from 42 studies, providing data on more than 20 million persons. The mean hazard ratio (HR) for mortality was 1.63 among HRs adjusted for age and additional covariates. The mean effect was higher for men than for women. Unemployment was associated with an increased mortality risk for those in their early and middle careers, but less for those in their late career. The risk of death was highest during the first 10 years of follow-up, but decreased subsequently. The mean HR was 24% lower among the subset of studies controlling for health-related behaviors. Public health initiatives could target unemployed persons for more aggressive cardiovascular screening and interventions aimed at reducing risk-taking behaviors. Copyright © 2011 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                European Journal of Clinical Investigation
                Eur J Clin Invest
                Wiley
                0014-2972
                1365-2362
                October 07 2020
                Affiliations
                [1 ]Departments of Medicine, of Epidemiology and Population Health of Biomedical Data Science, and of Statistics, and Meta‐Research Innovation Center at Stanford (METRICS) Stanford University Stanford CA USA
                Article
                10.1111/eci.13423
                4b922b99-b6a5-4c04-8fc6-51e5d8bc83bf
                © 2020

                http://onlinelibrary.wiley.com/termsAndConditions#vor

                http://doi.wiley.com/10.1002/tdm_license_1.1

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