{"title":"受人类发展不平等和疫苗接种率影响的全球COVID-19病例死亡率。","authors":"Kaamel Nuhu, Kamal Humagain, Genevieve Alorbi, Sabena Thomas, Alexis Blavos, Vierne Placide","doi":"10.1007/s44155-022-00022-0","DOIUrl":null,"url":null,"abstract":"<p><strong>Aim: </strong>COVID-19 has exerted distress on virtually every aspect of human life with disproportionate mortality burdens on older individuals and those with underlying medical conditions. Variations in COVID-19 incidence and case fatality rates (CFRs) across countries have incited a growing research interest regarding the effect of social factors on COVID-19 case-loads and fatality rates. We investigated the effect of population median age, inequalities in human development, healthcare capacity, and pandemic mitigation indicators on country-specific COVID-19 CFRs across countries and regions.</p><p><strong>Subject and methods: </strong>Using population secondary data from multiple sources, we conducted a cross-sectional study and used regional analysis to compare regional differences in COVID-19 CFRs as influenced by the selected indicators.</p><p><strong>Results: </strong>The analysis revealed wide variations in COVID-19 CFRs and the selected indicators across countries and regions. Mean CFR was highest for South America at 1.973% (± 0.742) and lowest for Oceania at 0.264% (± 0.107), while the Africa sub-region recorded the lowest scores for pandemic preparedness, vaccination rate, and other indicators. Population Median Age [0.073 (0.033 0.113)], Vaccination Rate [-3.3389 (-5.570.033 -1.208)], and Inequality-Adjusted Human Development Index (IHDI) [-0.014 (-0.023 -0.004)] emerged as statistically significant predictors of COVID-19 CFR, with directions indicating increasing Population Median Age, higher inequalities in human development and low vaccination rate are predictive of higher fatalities from COVID-19.</p><p><strong>Conclusion: </strong>Regional differences in COVID-19 CFR may be influenced by underlying differences in sociodemographic and pandemic mitigation indicators. Populations with wide social inequalities, increased population Median Age and low vaccination rates are more likely to suffer higher fatalities from COVID-19.</p>","PeriodicalId":29972,"journal":{"name":"Discover Social Science and Health","volume":" ","pages":"20"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9628401/pdf/","citationCount":"90","resultStr":"{\"title\":\"Global COVID-19 case fatality rates influenced by inequalities in human development and vaccination rates.\",\"authors\":\"Kaamel Nuhu, Kamal Humagain, Genevieve Alorbi, Sabena Thomas, Alexis Blavos, Vierne Placide\",\"doi\":\"10.1007/s44155-022-00022-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aim: </strong>COVID-19 has exerted distress on virtually every aspect of human life with disproportionate mortality burdens on older individuals and those with underlying medical conditions. Variations in COVID-19 incidence and case fatality rates (CFRs) across countries have incited a growing research interest regarding the effect of social factors on COVID-19 case-loads and fatality rates. We investigated the effect of population median age, inequalities in human development, healthcare capacity, and pandemic mitigation indicators on country-specific COVID-19 CFRs across countries and regions.</p><p><strong>Subject and methods: </strong>Using population secondary data from multiple sources, we conducted a cross-sectional study and used regional analysis to compare regional differences in COVID-19 CFRs as influenced by the selected indicators.</p><p><strong>Results: </strong>The analysis revealed wide variations in COVID-19 CFRs and the selected indicators across countries and regions. Mean CFR was highest for South America at 1.973% (± 0.742) and lowest for Oceania at 0.264% (± 0.107), while the Africa sub-region recorded the lowest scores for pandemic preparedness, vaccination rate, and other indicators. Population Median Age [0.073 (0.033 0.113)], Vaccination Rate [-3.3389 (-5.570.033 -1.208)], and Inequality-Adjusted Human Development Index (IHDI) [-0.014 (-0.023 -0.004)] emerged as statistically significant predictors of COVID-19 CFR, with directions indicating increasing Population Median Age, higher inequalities in human development and low vaccination rate are predictive of higher fatalities from COVID-19.</p><p><strong>Conclusion: </strong>Regional differences in COVID-19 CFR may be influenced by underlying differences in sociodemographic and pandemic mitigation indicators. Populations with wide social inequalities, increased population Median Age and low vaccination rates are more likely to suffer higher fatalities from COVID-19.</p>\",\"PeriodicalId\":29972,\"journal\":{\"name\":\"Discover Social Science and Health\",\"volume\":\" \",\"pages\":\"20\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9628401/pdf/\",\"citationCount\":\"90\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Discover Social Science and Health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s44155-022-00022-0\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/11/1 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Discover Social Science and Health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s44155-022-00022-0","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/11/1 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Global COVID-19 case fatality rates influenced by inequalities in human development and vaccination rates.
Aim: COVID-19 has exerted distress on virtually every aspect of human life with disproportionate mortality burdens on older individuals and those with underlying medical conditions. Variations in COVID-19 incidence and case fatality rates (CFRs) across countries have incited a growing research interest regarding the effect of social factors on COVID-19 case-loads and fatality rates. We investigated the effect of population median age, inequalities in human development, healthcare capacity, and pandemic mitigation indicators on country-specific COVID-19 CFRs across countries and regions.
Subject and methods: Using population secondary data from multiple sources, we conducted a cross-sectional study and used regional analysis to compare regional differences in COVID-19 CFRs as influenced by the selected indicators.
Results: The analysis revealed wide variations in COVID-19 CFRs and the selected indicators across countries and regions. Mean CFR was highest for South America at 1.973% (± 0.742) and lowest for Oceania at 0.264% (± 0.107), while the Africa sub-region recorded the lowest scores for pandemic preparedness, vaccination rate, and other indicators. Population Median Age [0.073 (0.033 0.113)], Vaccination Rate [-3.3389 (-5.570.033 -1.208)], and Inequality-Adjusted Human Development Index (IHDI) [-0.014 (-0.023 -0.004)] emerged as statistically significant predictors of COVID-19 CFR, with directions indicating increasing Population Median Age, higher inequalities in human development and low vaccination rate are predictive of higher fatalities from COVID-19.
Conclusion: Regional differences in COVID-19 CFR may be influenced by underlying differences in sociodemographic and pandemic mitigation indicators. Populations with wide social inequalities, increased population Median Age and low vaccination rates are more likely to suffer higher fatalities from COVID-19.
期刊介绍：
Discover Social Science and Health is an interdisciplinary, international journal that publishes papers at the intersection of the social and biomedical sciences. Papers should integrate, in both theory and measures, a social perspective (reflecting anthropology, criminology, economics, epidemiology, policy, sociology, etc) and a concern for health (mental and physical). Health, broadly construed, includes biological and other indicators of overall health, symptoms, diseases, diagnoses, treatments, treatment adherence, and related concerns. Drawing on diverse, sound methodologies, submissions may include reports of new empirical findings (including important null findings) and replications, reviews and perspectives that construe prior research and discuss future research agendas, methodological research (including the evaluation of measures, samples, and modeling strategies), and short or long commentaries on topics of wide interest. All submissions should include statements of significance with respect to health and future research. Discover Social Science and Health is an Open Access journal that supports the pre-registration of studies.
Topics
Papers suitable for Discover Social Science and Health will include both social and biomedical theory and data. Illustrative examples of themes include race/ethnicity, sex/gender, socioeconomic, geographic, and other social disparities in health; migration and health; spatial distribution of risk factors and access to healthcare; health and social relationships; interactional processes in healthcare, treatments, and outcomes; life course patterns of health and treatment regimens; cross-national patterns in health and health policies; characteristics of communities and neighborhoods and health; social networks and treatment adherence; stigma and disease progression; methodological studies including psychometric properties of measures frequently used in health research; and commentary and analysis of key concepts, theories, and methods in studies of social science and biomedicine. The journal welcomes submissions that draw on biomarkers of health, genetically-informed and neuroimaging data, psychophysiological measures, and other forms of data that describe physical and mental health, access to health care, treatment, and related constructs.
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