{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T19:17:01Z","timestamp":1791832621189,"version":"4.3.4"},"reference-count":76,"publisher":"Public Library of Science (PLoS)","issue":"6","license":[{"start":{"date-parts":[[2021,6,9]],"date-time":"2021-06-09T00:00:00Z","timestamp":1623196800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000193","name":"IDRC","doi-asserted-by":"crossref","award":["109559-001"],"award-info":[{"award-number":["109559-001"]}],"id":[{"id":"10.13039\/501100000193","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>\n                      To assess whether the basic reproduction number (\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>0<\/jats:italic>\n                      <\/jats:sub>\n                      ) of COVID-19 is different across countries and what national-level demographic, social, and environmental factors other than interventions characterize initial vulnerability to the virus.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We fit logistic growth curves to reported daily case numbers, up to the first epidemic peak, for 58 countries for which 16 explanatory covariates are available. This fitting has been shown to robustly estimate\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>0<\/jats:italic>\n                      <\/jats:sub>\n                      from the specified period. We then use a generalized additive model (GAM) to discern both linear and nonlinear effects, and include 5 random effect covariates to account for potential differences in testing and reporting that can bias the estimated\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>0<\/jats:italic>\n                      <\/jats:sub>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>\n                      We found that the mean R0 is 1.70 (S.D. 0.57), with a range between 1.10 (Ghana) and 3.52 (South Korea). We identified four factors\u2014population between 20\u201334 years old (youth), population residing in urban agglomerates over 1 million (city), social media use to organize offline action (social media), and GINI income inequality\u2014as having strong relationships with\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>0<\/jats:italic>\n                      <\/jats:sub>\n                      , across countries. An intermediate level of youth and GINI inequality are associated with high\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>0<\/jats:italic>\n                      <\/jats:sub>\n                      , (n-shape relationships), while high city population and high social media use are associated with high\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>0<\/jats:italic>\n                      <\/jats:sub>\n                      . Pollution, temperature, and humidity did not have strong relationships with\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>0<\/jats:italic>\n                      <\/jats:sub>\n                      but were positive.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec004\">\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Countries have different characteristics that predispose them to greater intrinsic vulnerability to COVID-19. Studies that aim to measure the effectiveness of interventions across locations should account for these baseline differences in social and demographic characteristics.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0252373","type":"journal-article","created":{"date-parts":[[2021,6,9]],"date-time":"2021-06-09T13:31:03Z","timestamp":1623245463000},"page":"e0252373","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":60,"title":["Social, economic, and environmental factors influencing the basic reproduction number of COVID-19 across countries"],"prefix":"10.1371","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7557-5672","authenticated-orcid":true,"given":"Jude Dzevela","family":"Kong","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2971-6128","authenticated-orcid":true,"given":"Eden","family":"Tekwa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarah A.","family":"Gignoux-Wolfsohn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2021,6,9]]},"reference":[{"key":"pone.0252373.ref001","doi-asserted-by":"crossref","first-page":"100464","DOI":"10.1016\/j.eclinm.2020.100464","article-title":"A country level analysis measuring the impact of government actions, country preparedness and socioeconomic factors on COVID-19 mortality and related health outcomes.","volume":"25","author":"R Chaudhry","year":"2020","journal-title":"EClinicalMedicine."},{"key":"pone.0252373.ref002","doi-asserted-by":"crossref","first-page":"110184","DOI":"10.1016\/j.envres.2020.110184","article-title":"How socio-economic and atmospheric variables impact COVID-19 and influenza outbreaks in tropical and subtropical regions of Brazil","volume":"191","author":"LD Martins","year":"2020","journal-title":"Environmental Research"},{"key":"pone.0252373.ref003","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1186\/s12942-020-00225-1","article-title":"A multimethod approach for county-scale geospatial analysis of emerging infectious diseases: a cross-sectional case study of COVID-19 incidence in Germany.","volume":"19","author":"C Scarpone","year":"2020","journal-title":"Int J Health Geogr."},{"key":"pone.0252373.ref004","article-title":"The temporal association of introducing and lifting non-pharmaceutical interventions with the time-varying reproduction number (R) of SARS-CoV-2: a modelling study across 131 countries.","author":"Y Li","year":"2020","journal-title":"The Lancet Infectious Diseases"},{"key":"pone.0252373.ref005","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1007\/s11538-013-9918-2","article-title":"Estimating Initial Epidemic Growth Rates.","volume":"76","author":"J Ma","year":"2014","journal-title":"Bull Math Biol."},{"key":"pone.0252373.ref006","doi-asserted-by":"crossref","DOI":"10.2105\/AJPH.2013.301704","article-title":"Unraveling R0: Considerations for Public Health Applications.","volume":"104","author":"B Ridenhour","year":"2014","journal-title":"American Journal of Public Health"},{"key":"pone.0252373.ref007","doi-asserted-by":"crossref","first-page":"1199","DOI":"10.1056\/NEJMoa2001316","article-title":"Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus\u2013Infected Pneumonia","volume":"382","author":"Q Li","year":"2020","journal-title":"N Engl J Med"},{"key":"pone.0252373.ref008","doi-asserted-by":"crossref","first-page":"1470","DOI":"10.3201\/eid2607.200282","article-title":"High Contagiousness and Rapid Spread of Severe Acute Respiratory Syndrome Coronavirus 2","volume":"26","author":"S Sanche","year":"2020","journal-title":"Emerg Infect Dis"},{"key":"pone.0252373.ref009","doi-asserted-by":"crossref","DOI":"10.1016\/S1473-3099(20)30484-9","article-title":"Comparing SARS-CoV-2 with SARS-CoV and influenza pandemics","volume":"20","author":"E Petersen","year":"2020","journal-title":"The Lancet Infectious Diseases"},{"key":"pone.0252373.ref010","article-title":"COVID-19 May Be Much More Contagious Than We Thought.","author":"J. 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