{"title":"COVID-19发病率和死亡率因素","authors":"Yuval Arbel, Chaim Fialkoff, A. Kerner, M. Kerner","doi":"10.18335/region.v10i3.455","DOIUrl":null,"url":null,"abstract":"This study investigates the scope of morbidity and mortality from SARS-COV2 virus at a country-wide level based on three central risk factors: population density, median age, and per capita hospital beds. Given that the relative weight following a change in equal units of measurement has not been examined on a country-wide level, we use empirical models with standardized coefficients. Information for this study was obtained from the World Health Organization (WHO) data base, which encompasses 162 countries, and spans five continents from January 22, 2020, to January 21, 2022. Referring to projected COVID-19 infection and mortality rates, and following a one standard deviation increase, the influence of these independent variables may be ranked as follows: Infection -- 1) the median age of the country's population; 2) number of hospital beds per thousand persons; 3) population density. Mortality -- 1) the median age of the country's population; 2) population density; 3) number of hospital beds per thousand persons. Findings may be of assistance to public policy planners. Given the dominance of the age variable in the context of the COVID-19 pandemic, on the one hand, the allocation of resources for future pandemics should grow in countries with older population profiles (European countries). On the other hand, the emphasis in countries with younger populations (African countries) should be on better medical infrastructure in sparser regions.","PeriodicalId":43257,"journal":{"name":"Baltic Region","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2023-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"COVID-19 Morbidity and Mortality Factors\",\"authors\":\"Yuval Arbel, Chaim Fialkoff, A. Kerner, M. Kerner\",\"doi\":\"10.18335/region.v10i3.455\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study investigates the scope of morbidity and mortality from SARS-COV2 virus at a country-wide level based on three central risk factors: population density, median age, and per capita hospital beds. Given that the relative weight following a change in equal units of measurement has not been examined on a country-wide level, we use empirical models with standardized coefficients. Information for this study was obtained from the World Health Organization (WHO) data base, which encompasses 162 countries, and spans five continents from January 22, 2020, to January 21, 2022. Referring to projected COVID-19 infection and mortality rates, and following a one standard deviation increase, the influence of these independent variables may be ranked as follows: Infection -- 1) the median age of the country's population; 2) number of hospital beds per thousand persons; 3) population density. Mortality -- 1) the median age of the country's population; 2) population density; 3) number of hospital beds per thousand persons. Findings may be of assistance to public policy planners. Given the dominance of the age variable in the context of the COVID-19 pandemic, on the one hand, the allocation of resources for future pandemics should grow in countries with older population profiles (European countries). On the other hand, the emphasis in countries with younger populations (African countries) should be on better medical infrastructure in sparser regions.\",\"PeriodicalId\":43257,\"journal\":{\"name\":\"Baltic Region\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2023-08-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Baltic Region\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18335/region.v10i3.455\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"AREA STUDIES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Baltic Region","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18335/region.v10i3.455","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AREA STUDIES","Score":null,"Total":0}
This study investigates the scope of morbidity and mortality from SARS-COV2 virus at a country-wide level based on three central risk factors: population density, median age, and per capita hospital beds. Given that the relative weight following a change in equal units of measurement has not been examined on a country-wide level, we use empirical models with standardized coefficients. Information for this study was obtained from the World Health Organization (WHO) data base, which encompasses 162 countries, and spans five continents from January 22, 2020, to January 21, 2022. Referring to projected COVID-19 infection and mortality rates, and following a one standard deviation increase, the influence of these independent variables may be ranked as follows: Infection -- 1) the median age of the country's population; 2) number of hospital beds per thousand persons; 3) population density. Mortality -- 1) the median age of the country's population; 2) population density; 3) number of hospital beds per thousand persons. Findings may be of assistance to public policy planners. Given the dominance of the age variable in the context of the COVID-19 pandemic, on the one hand, the allocation of resources for future pandemics should grow in countries with older population profiles (European countries). On the other hand, the emphasis in countries with younger populations (African countries) should be on better medical infrastructure in sparser regions.