{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T11:32:56Z","timestamp":1777894376067,"version":"3.51.4"},"reference-count":47,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Economics & Human Biology"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1016\/j.ehb.2025.101511","type":"journal-article","created":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T19:37:19Z","timestamp":1752608239000},"page":"101511","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Drivers of COVID-19 in U.S. counties: A wave-level analysis"],"prefix":"10.1016","volume":"58","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4766-3699","authenticated-orcid":false,"given":"Christopher F.","family":"Baum","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9617-6873","authenticated-orcid":false,"given":"Andr\u00e9s","family":"Garc\u00eda-Suaza","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miguel","family":"Henry","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jes\u00fas","family":"Otero","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.ehb.2025.101511_b1","series-title":"MIT election data and science lab. County presidential election returns","first-page":"2000","year":"2018"},{"key":"10.1016\/j.ehb.2025.101511_b2","first-page":"598","article-title":"Provisional mortality data \u2013 United States, 2021","volume":"vol. 71","author":"Ahmad","year":"2022"},{"key":"10.1016\/j.ehb.2025.101511_b3","first-page":"488","article-title":"Provisional mortality data - United States, 2022","volume":"vol. 72","author":"Ahmad","year":"2023"},{"issue":"2","key":"10.1016\/j.ehb.2025.101511_b4","doi-asserted-by":"crossref","first-page":"662","DOI":"10.1016\/j.ijforecast.2021.06.007","article-title":"Regional heterogeneity and u.s. presidential elections: real-time 2020 forecasts and evaluation","volume":"38","author":"Ahmed","year":"2022","journal-title":"Int. J. Forecast."},{"key":"10.1016\/j.ehb.2025.101511_b5","series-title":"What explains temporal and geographic variation in the early US coronavirus pandemic? Working paper","author":"Allcott","year":"2024"},{"issue":"142396","key":"10.1016\/j.ehb.2025.101511_b6","first-page":"1","article-title":"Analyzing the spatial determinants of local Covid-19 transmission in the United States","volume":"754","author":"Andersen","year":"2021","journal-title":"Sci. Total Environ."},{"issue":"2","key":"10.1016\/j.ehb.2025.101511_b7","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1111\/roiw.12570","article-title":"Excess mortality versus COVID-19 death rates: A spatial analysis of socioeconomic disparities and political allegiance across U.S. states","volume":"68","author":"Aron","year":"2022","journal-title":"Rev. Income Wealth"},{"key":"10.1016\/j.ehb.2025.101511_b8","first-page":"366","article-title":"Socio-economic and demographic factors influencing the spatial spread of COVID-19 in the USA","volume":"12","author":"Baum","year":"2022","journal-title":"Int. J. Comput. Econ. Econ."},{"key":"10.1016\/j.ehb.2025.101511_b9","doi-asserted-by":"crossref","first-page":"1341","DOI":"10.1016\/S0140-6736(23)00461-0","article-title":"Assessing COVID-19 pandemic policies and behaviours and their economic and educational trade-offs across US states from jan 1 2020, to july 31 2022: an observational analysis","volume":"401","author":"Bollyky","year":"2023","journal-title":"Lancet"},{"issue":"1","key":"10.1016\/j.ehb.2025.101511_b10","doi-asserted-by":"crossref","first-page":"239","DOI":"10.2307\/2297111","article-title":"The Lagrange multiplier test and its applications to model specification in econometrics","volume":"47","author":"Breusch","year":"1980","journal-title":"Rev. Econ. Stud."},{"key":"10.1016\/j.ehb.2025.101511_b11","series-title":"Inequality and the coronavirus: Socioeconomic covariates of behavioral responses and viral outcomes across US counties. NBER working papers 27549, national bureau of economic research, inc","author":"Brown","year":"2020"},{"issue":"1","key":"10.1016\/j.ehb.2025.101511_b12","doi-asserted-by":"crossref","DOI":"10.1016\/j.jeconom.2024.105787","article-title":"Bridging the covid-19 data and the epidemiological model using the time-varying parameter sird model","volume":"242","author":"\u00c7akmakl\u0131","year":"2024","journal-title":"J. Econometrics","ISSN":"https:\/\/id.crossref.org\/issn\/0304-4076","issn-type":"print"},{"key":"10.1016\/j.ehb.2025.101511_b13","article-title":"Urban density and COVID-19: understanding the US experience","author":"Carozzi","year":"2022","journal-title":"Ann. Reg. Sci."},{"key":"10.1016\/j.ehb.2025.101511_b14","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.jeconom.2020.09.003","article-title":"Causal impact of masks, policies, behavior on early covid-19 pandemic in the U.S.","volume":"220","author":"Chernozhukov","year":"2021","journal-title":"J. Econometrics"},{"issue":"9","key":"10.1016\/j.ehb.2025.101511_b15","doi-asserted-by":"crossref","DOI":"10.1136\/bmjopen-2020-039886","article-title":"US-county level variation in intersecting individual, household and community characteristics relevant to COVID-19 and planning an equitable response: a cross-sectional analysis","volume":"10","author":"Chin","year":"2020","journal-title":"BMJ Open","ISSN":"https:\/\/id.crossref.org\/issn\/2044-6055","issn-type":"print"},{"issue":"105900","key":"10.1016\/j.ehb.2025.101511_b16","first-page":"1","article-title":"Variable selection in high dimensional linear regressions with parameter instability","volume":"246","author":"Chudik","year":"2024","journal-title":"J. Econometrics"},{"issue":"4","key":"10.1016\/j.ehb.2025.101511_b17","doi-asserted-by":"crossref","first-page":"1479","DOI":"10.3982\/ECTA14176","article-title":"A one covariate at a time, multiple testing approach to variable selection in high-dimensional linear regression models","volume":"86","author":"Chudik","year":"2018","journal-title":"Econometrica"},{"key":"10.1016\/j.ehb.2025.101511_b18","series-title":"Large Panel Data Models with Cross-Sectional Dependence a Survey","author":"Chudik","year":"2015"},{"issue":"103332","key":"10.1016\/j.ehb.2025.101511_b19","first-page":"1","article-title":"Understanding spatial variation in covid-19 across the united states","volume":"127","author":"Desmet","year":"2022","journal-title":"J. Urban Econ."},{"issue":"1","key":"10.1016\/j.ehb.2025.101511_b20","first-page":"1","article-title":"A social vulnerability index for disaster management","volume":"8","author":"Flanagan","year":"2011","journal-title":"J. Homel. Secur. Emerg. Manag."},{"key":"10.1016\/j.ehb.2025.101511_b21","doi-asserted-by":"crossref","first-page":"S28","DOI":"10.1016\/j.eneco.2014.10.006","article-title":"Crude oil price differentials, product heterogeneity and institutional arrangements","volume":"46","author":"Giulietti","year":"2014","journal-title":"Energy Econ."},{"issue":"2","key":"10.1016\/j.ehb.2025.101511_b22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/econometrics11020010","article-title":"Modeling COVID-19 infection rates by regime-switching unobserved components models","volume":"11","author":"Haimerl","year":"2023","journal-title":"Econometrics"},{"key":"10.1016\/j.ehb.2025.101511_b23","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.jeconom.2021.01.001","article-title":"How to go viral: A COVID-19 model with endogenously time-varying parameters","volume":"232","author":"Ho","year":"2023","journal-title":"J. Econometrics"},{"issue":"3","key":"10.1016\/j.ehb.2025.101511_b24","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1016\/j.econlet.2012.03.027","article-title":"Usage of an estimated coefficient as a dependent variable","volume":"116","author":"Hornstein","year":"2012","journal-title":"Econom. Lett."},{"key":"10.1016\/j.ehb.2025.101511_b25","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1093\/biomet\/28.3-4.321","article-title":"Relations between two sets of variates","volume":"28","author":"Hotelling","year":"1936","journal-title":"Biometrika"},{"key":"10.1016\/j.ehb.2025.101511_b26","first-page":"185","article-title":"Random coefficient models","volume":"vol. 33","author":"Hsiao","year":"2008"},{"key":"10.1016\/j.ehb.2025.101511_b27","series-title":"COVID-19 Projections","author":"IHME","year":"2023"},{"issue":"C","key":"10.1016\/j.ehb.2025.101511_b28","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1016\/j.jebo.2021.04.037","article-title":"Testing the efficiency of inflation and exchange rate forecast revisions in a changing economic environment","volume":"187","author":"Iregui","year":"2021","journal-title":"J. Econ. Behav. Organ."},{"issue":"3","key":"10.1016\/j.ehb.2025.101511_b29","first-page":"2049","article-title":"The lag between daily reported Covid-19 cases and deaths and its relationship to age","volume":"10","author":"Jin","year":"2021","journal-title":"J. Public Heal. Res."},{"key":"10.1016\/j.ehb.2025.101511_b30","unstructured":"Jones, Bradley, The Changing Political Geography of Covid-19 over the Last Two Years. Technical report, Pew Research Center, 2022. Available at https:\/\/www.pewresearch.org\/politics\/2022\/03\/03\/the-changing-political-geography-of-covid-19-over-the-last-two-years\/."},{"key":"10.1016\/j.ehb.2025.101511_b31","series-title":"What does and does not correlate with COVID-19 death rates. NBER working papers 27391, national bureau of economic research, inc","author":"Knittel","year":"2020"},{"issue":"2022","key":"10.1016\/j.ehb.2025.101511_b32","first-page":"25","article-title":"Life expectancy by county, race, and ethnicity in the usa, 200019: a systematic analysis of health disparities","volume":"400","author":"Laura","year":"2000","journal-title":"Lancet"},{"issue":"1","key":"10.1016\/j.ehb.2025.101511_b33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1001\/jamanetworkopen.2020.34578","article-title":"Association of social and economic inequality with coronavirus disease 2019 incidence and mortality across us counties","volume":"4","author":"Liao","year":"2021","journal-title":"JAMA Netw. Open"},{"key":"10.1016\/j.ehb.2025.101511_b34","article-title":"Socioeconomic inequalities in COVID-19 incidence during the first six waves in Barcelona","volume":"68","author":"Martinez-Beneito","year":"2023","journal-title":"Int. J. Epidemiol."},{"issue":"52","key":"10.1016\/j.ehb.2025.101511_b35","first-page":"127","article-title":"The social and economic factors underlying the incidence of COVID-19 cases and deaths in US counties during the initial outbreak phase","volume":"52","author":"Mukherji","year":"2022","journal-title":"Rev. Reg. Stud."},{"key":"10.1016\/j.ehb.2025.101511_b36","series-title":"BIMAP: Stata Module To Produce Bivariate Maps. Statistical Software Components","author":"Naqvi","year":"2022"},{"issue":"6","key":"10.1016\/j.ehb.2025.101511_b37","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1002\/jae.2850","article-title":"A one covariate at a time, multiple testing approach to variable selection in high-dimensional linear regression models: A replication in a narrow sense","volume":"36","author":"N\u00fa\u00f1ez","year":"2021","journal-title":"J. Appl. Econometrics"},{"issue":"3","key":"10.1016\/j.ehb.2025.101511_b38","doi-asserted-by":"crossref","first-page":"579","DOI":"10.2307\/1911792","article-title":"A general procedure for obtaining maximum likelihood estimates in generalized regression models","volume":"42","author":"Oberhofer","year":"1974","journal-title":"Econometrica"},{"issue":"9","key":"10.1016\/j.ehb.2025.101511_b39","doi-asserted-by":"crossref","first-page":"2791","DOI":"10.1007\/s11606-020-05971-3","article-title":"Association between state-level income inequality and COVID-19 cases and mortality in the USA","volume":"35","author":"Oronce","year":"2020","journal-title":"J. Gen. Intern. Med."},{"key":"10.1016\/j.ehb.2025.101511_b40","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1007\/s00148-020-00818-x","article-title":"Socio-demographic factors associated with self-protecting behavior during the covid-19 pandemic","volume":"34","author":"Papageorge","year":"2021","journal-title":"J. Popul. Econ."},{"key":"10.1016\/j.ehb.2025.101511_b41","series-title":"Severe COVID-19 Health Risk Index","author":"PolicyMap","year":"2020"},{"key":"10.1016\/j.ehb.2025.101511_b42","series-title":"Multilevel and Longitudinal Modeling using Stata, Volume I: Continuous Responses","author":"Rabe-Hesketh","year":"2022"},{"key":"10.1016\/j.ehb.2025.101511_b43","series-title":"COVID-19 US State Policy Database","author":"Raifman","year":"2020"},{"issue":"1","key":"10.1016\/j.ehb.2025.101511_b44","first-page":"178","article-title":"Estimated parameters as dependent variables","volume":"66","author":"Saxonhouse","year":"1976","journal-title":"Am. Econ. Rev."},{"key":"10.1016\/j.ehb.2025.101511_b45","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1515\/bejeap-2021-0157","article-title":"The impact of mask usage on COVID-19 deaths: Evidence from US Counties using a quasi-experimental approach","volume":"22","author":"Welsch","year":"2022","journal-title":"B. E. J. Econ. Anal. & Policy"},{"issue":"45","key":"10.1016\/j.ehb.2025.101511_b46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1126\/sciadv.abd4049","article-title":"Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis","volume":"6","author":"Wu","year":"2020","journal-title":"Sci. Adv."},{"key":"10.1016\/j.ehb.2025.101511_b47","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1080\/01621459.1962.10480664","article-title":"An efficient method of estimating seemingly unrelated regressions and tests of aggregation bias","volume":"57","author":"Zellner","year":"1962","journal-title":"J. Amer. Statist. Assoc."}],"container-title":["Economics & Human Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1570677X25000449?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1570677X25000449?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T07:19:32Z","timestamp":1777619972000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1570677X25000449"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":47,"alternative-id":["S1570677X25000449"],"URL":"https:\/\/doi.org\/10.1016\/j.ehb.2025.101511","relation":{},"ISSN":["1570-677X"],"issn-type":[{"value":"1570-677X","type":"print"}],"subject":[],"published":{"date-parts":[[2025,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Drivers of COVID-19 in U.S. counties: A wave-level analysis","name":"articletitle","label":"Article Title"},{"value":"Economics & Human Biology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ehb.2025.101511","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"101511"}}