Abhishek Mallela , Yen Ting Lin , William S. Hlavacek
{"title":"美国各地呼吸道疾病的不同传染性。","authors":"Abhishek Mallela , Yen Ting Lin , William S. Hlavacek","doi":"10.1016/j.epidem.2023.100718","DOIUrl":null,"url":null,"abstract":"<div><p>The initial contagiousness of a communicable disease within a given population is quantified by the basic reproduction number, <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span>. This number depends on both pathogen and population properties. On the basis of compartmental models that reproduce Coronavirus Disease 2019 (COVID-19) surveillance data, we used Bayesian inference and the next-generation matrix approach to estimate region-specific <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> values for 280 of 384 metropolitan statistical areas (MSAs) in the United States (US), which account for 95% of the US population living in urban areas and 82% of the total population. We focused on MSA populations after finding that these populations were more uniformly impacted by COVID-19 than state populations. Our maximum a posteriori (MAP) estimates for <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> range from 1.9 to 7.7 and quantify the relative susceptibilities of regional populations to spread of respiratory diseases.</p></div><div><h3>One-Sentence Summary</h3><p>Initial contagiousness of Coronavirus Disease 2019 varied over a 4-fold range across urban areas of the United States.</p></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":"45 ","pages":"Article 100718"},"PeriodicalIF":3.0000,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Differential contagiousness of respiratory disease across the United States\",\"authors\":\"Abhishek Mallela , Yen Ting Lin , William S. Hlavacek\",\"doi\":\"10.1016/j.epidem.2023.100718\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The initial contagiousness of a communicable disease within a given population is quantified by the basic reproduction number, <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span>. This number depends on both pathogen and population properties. On the basis of compartmental models that reproduce Coronavirus Disease 2019 (COVID-19) surveillance data, we used Bayesian inference and the next-generation matrix approach to estimate region-specific <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> values for 280 of 384 metropolitan statistical areas (MSAs) in the United States (US), which account for 95% of the US population living in urban areas and 82% of the total population. We focused on MSA populations after finding that these populations were more uniformly impacted by COVID-19 than state populations. Our maximum a posteriori (MAP) estimates for <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> range from 1.9 to 7.7 and quantify the relative susceptibilities of regional populations to spread of respiratory diseases.</p></div><div><h3>One-Sentence Summary</h3><p>Initial contagiousness of Coronavirus Disease 2019 varied over a 4-fold range across urban areas of the United States.</p></div>\",\"PeriodicalId\":49206,\"journal\":{\"name\":\"Epidemics\",\"volume\":\"45 \",\"pages\":\"Article 100718\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2023-09-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Epidemics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1755436523000543\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epidemics","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1755436523000543","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
Differential contagiousness of respiratory disease across the United States
The initial contagiousness of a communicable disease within a given population is quantified by the basic reproduction number, . This number depends on both pathogen and population properties. On the basis of compartmental models that reproduce Coronavirus Disease 2019 (COVID-19) surveillance data, we used Bayesian inference and the next-generation matrix approach to estimate region-specific values for 280 of 384 metropolitan statistical areas (MSAs) in the United States (US), which account for 95% of the US population living in urban areas and 82% of the total population. We focused on MSA populations after finding that these populations were more uniformly impacted by COVID-19 than state populations. Our maximum a posteriori (MAP) estimates for range from 1.9 to 7.7 and quantify the relative susceptibilities of regional populations to spread of respiratory diseases.
One-Sentence Summary
Initial contagiousness of Coronavirus Disease 2019 varied over a 4-fold range across urban areas of the United States.
期刊介绍：
Epidemics publishes papers on infectious disease dynamics in the broadest sense. Its scope covers both within-host dynamics of infectious agents and dynamics at the population level, particularly the interaction between the two. Areas of emphasis include: spread, transmission, persistence, implications and population dynamics of infectious diseases; population and public health as well as policy aspects of control and prevention; dynamics at the individual level; interaction with the environment, ecology and evolution of infectious diseases, as well as population genetics of infectious agents.
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