{"title":"在疫情爆发初期,美国县COVID-19病例和死亡发生率背后的社会和经济因素","authors":"Nivedita Mukherji","doi":"10.52324/001c.35255","DOIUrl":null,"url":null,"abstract":"This paper uncovers the socioeconomic and health/lifestyle factors that can explain the differential impact of the coronavirus pandemic on different parts of the United States during the initial outbreak phase of the pandemic. Using a dynamic panel representation of an epidemiological model of disease spread, the paper develops a Vulnerability Index for US counties from the daily reported number of cases over a 20-day period of rapid disease growth. County-level economic, demographic, and health factors are used to explain the differences in the values of this index and thereby the transmission and concentration of the disease across the country. These factors are also used to examine the number of reported deaths. The paper finds that counties with high median income have a high incidence of cases but reported lower deaths. Income inequality, as measured by the Gini coefficient, is found to be associated with more deaths and more cases. The remarkable similarity in the distribution of cases across the country and the distribution of distance-weighted international passengers served by the top international airports is evidence of the spread of the virus by way of international travel. The distributions of age, race and health risk factors such as obesity and diabetes are found to be particularly significant factors in explaining the differences in mortality across counties. Counties with better access to health care, as measured by the number of primary care physicians per capita, have lower deaths, and so do places with more health awareness as measured by flu vaccination prevalence. Environmental health conditions such as the amount of air pollution are found to be associated with counties with higher deaths from the virus. It is hoped that research such as these will help policymakers to develop risk factors for each region of the country to better contain the spread of infectious diseases in the future.","PeriodicalId":44865,"journal":{"name":"Review of Regional Studies","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"The Social and Economic Factors Underlying the Incidence of COVID-19 Cases and Deaths in US Counties During the Initial Outbreak Phase\",\"authors\":\"Nivedita Mukherji\",\"doi\":\"10.52324/001c.35255\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper uncovers the socioeconomic and health/lifestyle factors that can explain the differential impact of the coronavirus pandemic on different parts of the United States during the initial outbreak phase of the pandemic. Using a dynamic panel representation of an epidemiological model of disease spread, the paper develops a Vulnerability Index for US counties from the daily reported number of cases over a 20-day period of rapid disease growth. County-level economic, demographic, and health factors are used to explain the differences in the values of this index and thereby the transmission and concentration of the disease across the country. These factors are also used to examine the number of reported deaths. The paper finds that counties with high median income have a high incidence of cases but reported lower deaths. Income inequality, as measured by the Gini coefficient, is found to be associated with more deaths and more cases. The remarkable similarity in the distribution of cases across the country and the distribution of distance-weighted international passengers served by the top international airports is evidence of the spread of the virus by way of international travel. The distributions of age, race and health risk factors such as obesity and diabetes are found to be particularly significant factors in explaining the differences in mortality across counties. Counties with better access to health care, as measured by the number of primary care physicians per capita, have lower deaths, and so do places with more health awareness as measured by flu vaccination prevalence. Environmental health conditions such as the amount of air pollution are found to be associated with counties with higher deaths from the virus. It is hoped that research such as these will help policymakers to develop risk factors for each region of the country to better contain the spread of infectious diseases in the future.\",\"PeriodicalId\":44865,\"journal\":{\"name\":\"Review of Regional Studies\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2022-04-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Review of Regional Studies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52324/001c.35255\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Review of Regional Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52324/001c.35255","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ECONOMICS","Score":null,"Total":0}
The Social and Economic Factors Underlying the Incidence of COVID-19 Cases and Deaths in US Counties During the Initial Outbreak Phase
This paper uncovers the socioeconomic and health/lifestyle factors that can explain the differential impact of the coronavirus pandemic on different parts of the United States during the initial outbreak phase of the pandemic. Using a dynamic panel representation of an epidemiological model of disease spread, the paper develops a Vulnerability Index for US counties from the daily reported number of cases over a 20-day period of rapid disease growth. County-level economic, demographic, and health factors are used to explain the differences in the values of this index and thereby the transmission and concentration of the disease across the country. These factors are also used to examine the number of reported deaths. The paper finds that counties with high median income have a high incidence of cases but reported lower deaths. Income inequality, as measured by the Gini coefficient, is found to be associated with more deaths and more cases. The remarkable similarity in the distribution of cases across the country and the distribution of distance-weighted international passengers served by the top international airports is evidence of the spread of the virus by way of international travel. The distributions of age, race and health risk factors such as obesity and diabetes are found to be particularly significant factors in explaining the differences in mortality across counties. Counties with better access to health care, as measured by the number of primary care physicians per capita, have lower deaths, and so do places with more health awareness as measured by flu vaccination prevalence. Environmental health conditions such as the amount of air pollution are found to be associated with counties with higher deaths from the virus. It is hoped that research such as these will help policymakers to develop risk factors for each region of the country to better contain the spread of infectious diseases in the future.