{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T06:13:23Z","timestamp":1772172803468,"version":"3.50.1"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1008994","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2021,6,29]],"date-time":"2021-06-29T00:00:00Z","timestamp":1624924800000}}],"reference-count":82,"publisher":"Public Library of Science (PLoS)","issue":"6","license":[{"start":{"date-parts":[[2021,6,17]],"date-time":"2021-06-17T00:00:00Z","timestamp":1623888000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/publicdomain\/zero\/1.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01GM130668"],"award-info":[{"award-number":["R01GM130668"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01GM130668"],"award-info":[{"award-number":["R01GM130668"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Effectively designing and evaluating public health responses to the ongoing COVID-19 pandemic requires accurate estimation of the prevalence of COVID-19 across the United States (US). Equipment shortages and varying testing capabilities have however hindered the usefulness of the official reported positive COVID-19 case counts. We introduce four complementary approaches to estimate the cumulative incidence of symptomatic COVID-19 in each state in the US as well as Puerto Rico and the District of Columbia, using a combination of excess influenza-like illness reports, COVID-19 test statistics, COVID-19 mortality reports, and a spatially structured epidemic model. Instead of relying on the estimate from a single data source or method that may be biased, we provide multiple estimates, each relying on different assumptions and data sources. Across our four approaches emerges the consistent conclusion that on April 4, 2020, the estimated case count was 5 to 50 times higher than the official positive test counts across the different states. Nationally, our estimates of COVID-19 symptomatic cases as of April 4 have a likely range of 2.3 to 4.8 million, with possibly as many as 7.6 million cases, up to 25 times greater than the cumulative confirmed cases of about 311,000. Extending our methods to May 16, 2020, we estimate that cumulative symptomatic incidence ranges from 4.9 to 10.1 million, as opposed to 1.5 million positive test counts. The proposed combination of approaches may prove useful in assessing the burden of COVID-19 during resurgences in the US and other countries with comparable surveillance systems.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1008994","type":"journal-article","created":{"date-parts":[[2021,6,17]],"date-time":"2021-06-17T13:43:38Z","timestamp":1623937418000},"page":"e1008994","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":35,"title":["Estimating the cumulative incidence of COVID-19 in the United States using influenza surveillance, virologic testing, and mortality data: Four complementary approaches"],"prefix":"10.1371","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1026-5734","authenticated-orcid":true,"given":"Fred S.","family":"Lu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7131-6879","authenticated-orcid":true,"given":"Andre T.","family":"Nguyen","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4078-4842","authenticated-orcid":true,"given":"Nicholas B.","family":"Link","sequence":"additional","affiliation":[]},{"given":"Mathieu","family":"Molina","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0726-1855","authenticated-orcid":true,"given":"Jessica T.","family":"Davis","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5955-1929","authenticated-orcid":true,"given":"Matteo","family":"Chinazzi","sequence":"additional","affiliation":[]},{"given":"Xinyue","family":"Xiong","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3419-4205","authenticated-orcid":true,"given":"Alessandro","family":"Vespignani","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1504-9213","authenticated-orcid":true,"given":"Marc","family":"Lipsitch","sequence":"additional","affiliation":[]},{"given":"Mauricio","family":"Santillana","sequence":"additional","affiliation":[]}],"member":"340","published-online":{"date-parts":[[2021,6,17]]},"reference":[{"key":"pcbi.1008994.ref001","unstructured":"Organization WH. Report of the WHO-China Joint Mission on Coronavirus Disease 2019;. Available from: https:\/\/www.who.int\/publications-detail\/report-of-the-who-china-joint-mission-on-coronavirus-disease-2019-(covid-19)."},{"key":"pcbi.1008994.ref002","unstructured":"Centers for Disease Control and Prevention. Locations with Confirmed COVID-19 Cases;. Available from: https:\/\/www.cdc.gov\/coronavirus\/2019-ncov\/cases-updates\/world-map.html."},{"key":"pcbi.1008994.ref003","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1007\/82_2019_172","article-title":"Enhancing Situational Awareness to Prevent Infectious Disease Outbreaks from Becoming Catastrophic","author":"M Lipsitch","year":"2019","journal-title":"Global Catastrophic Biological Risks"},{"key":"pcbi.1008994.ref004","unstructured":"D Shear M, Goodnough A, Kaplan S, Fink S, Thomas K, Weiland N. The Lost Month: How a Failure to Test Blinded the U.S. to Covid-19;. Available from: https:\/\/www.nytimes.com\/2020\/03\/28\/us\/testing-coronavirus-pandemic.html."},{"key":"pcbi.1008994.ref005","unstructured":"Manrai AK, Mandl KD. Covid-19 testing: overcoming challenges in the next phase of the epidemic;. Available from: https:\/\/www.statnews.com\/2020\/03\/31\/covid-19-overcoming-testing-challenges\/."},{"key":"pcbi.1008994.ref006","doi-asserted-by":"crossref","unstructured":"Byambasuren O, Cardona M, Bell K, Clark J, McLaws ML, Glasziou P. Estimating the extent of true asymptomatic COVID-19 and its potential for community transmission: systematic review and meta-analysis. Available at SSRN 3586675. 2020;.","DOI":"10.2139\/ssrn.3586675"},{"key":"pcbi.1008994.ref007","article-title":"The role of asymptomatic SARS-CoV-2 infections: rapid living systematic review and meta-analysis","author":"DC Buitrago-Garcia","year":"2020","journal-title":"medRxiv"},{"key":"pcbi.1008994.ref008","article-title":"Prevalence of Asymptomatic SARS-CoV-2 Infection: A Narrative Review","author":"DP Oran","year":"2020","journal-title":"Annals of Internal Medicine"},{"key":"pcbi.1008994.ref009","article-title":"Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2)","author":"R Li","year":"2020","journal-title":"Science"},{"key":"pcbi.1008994.ref010","doi-asserted-by":"crossref","unstructured":"Kaashoek J, Santillana M. COVID-19 positive cases, evidence on the time evolution of the epidemic or an indicator of local testing capabilities? A case study in the United States. Available at SSRN: https:\/\/ssrncom\/abstract=3574849, April. 2020;.","DOI":"10.2139\/ssrn.3574849"},{"key":"pcbi.1008994.ref011","unstructured":"Centers for Disease Control and Prevention. FluView;. Available from: https:\/\/gis.cdc.gov\/grasp\/fluview\/fluportaldashboard.html."},{"key":"pcbi.1008994.ref012","unstructured":"Centers for Disease Control and Prevention. U.S. Influenza Surveillance System: Purpose and Methods;. Available from: https:\/\/www.cdc.gov\/flu\/weekly\/overview.htm."},{"issue":"8","key":"pcbi.1008994.ref013","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0006852","article-title":"Early epidemiological assessment of the virulence of emerging infectious diseases: a case study of an influenza pandemic","volume":"4","author":"H Nishiura","year":"2009","journal-title":"PLoS One"},{"key":"pcbi.1008994.ref014","unstructured":"Russell T, Hellewell J, Abbott S, Jarvis C, van Zandvoort K, et al. Using a delay-adjusted case fatality ratio to estimate under-reporting. Centre for Mathematical Modeling of Infectious Diseases Repository. 2020;."},{"issue":"7820","key":"pcbi.1008994.ref015","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1038\/s41586-020-2405-7","article-title":"Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe","volume":"584","author":"S Flaxman","year":"2020","journal-title":"Nature"},{"key":"pcbi.1008994.ref016","article-title":"Forecasting COVID-19 impact on hospital bed-days, ICU-days, ventilator-days and deaths by US state in the next 4 months","author":"COVID I","year":"2020","journal-title":"medRxiv"},{"issue":"51","key":"pcbi.1008994.ref017","doi-asserted-by":"crossref","first-page":"21825","DOI":"10.1073\/pnas.0902958106","article-title":"Reconstructing influenza incidence by deconvolution of daily mortality time series","volume":"106","author":"E Goldstein","year":"2009","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"pcbi.1008994.ref018","article-title":"The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak","author":"M Chinazzi","year":"2020","journal-title":"Science"},{"key":"pcbi.1008994.ref019","unstructured":"Reich NG, Ray EL, Gibson GC, Cramer E, Rivers CM. Looking for evidence of a high burden of COVID-19 in the United States from influenza-like illness data;. Available from: https:\/\/github.com\/reichlab\/ncov\/blob\/master\/analyses\/ili-labtest-report.pdf."},{"key":"pcbi.1008994.ref020","article-title":"Using ILI surveillance to estimate state-specific case detection rates and forecast SARS-CoV-2 spread in the United States","author":"JD Silverman","year":"2020","journal-title":"medRxiv"},{"key":"pcbi.1008994.ref021","article-title":"Estimates of the severity of coronavirus disease 2019: a model-based analysis","author":"R Verity","year":"2020","journal-title":"The Lancet Infectious Diseases"},{"key":"pcbi.1008994.ref022","article-title":"A systematic review and meta-analysis of published research data on COVID-19 infection-fatality rates","author":"G Meyerowitz-Katz","year":"2020","journal-title":"International Journal of Infectious Diseases"},{"key":"pcbi.1008994.ref023","unstructured":"Centers for Disease Control and Prevention. COVID-19 Pandemic Planning Scenarios;."},{"key":"pcbi.1008994.ref024","unstructured":"Rothwell J. Estimating COVID-19 Prevalence in Symptomatic Americans;. Available from: https:\/\/news.gallup.com\/opinion\/gallup\/306458\/estimating-covid-prevalence-symptomatic-americans.aspx."},{"key":"pcbi.1008994.ref025","unstructured":"Geldsetzer P. Knowledge and Perceptions of COVID-19 Among the General Public in the United States and the United Kingdom: A Cross-sectional Online Survey;. Available from: https:\/\/annals.org\/aim\/fullarticle\/2763550\/knowledge-perceptions-covid-19-among-general-public-united-states-united."},{"issue":"10","key":"pcbi.1008994.ref026","doi-asserted-by":"crossref","DOI":"10.2807\/1560-7917.ES.2020.25.10.2000180","article-title":"Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020","volume":"25","author":"K Mizumoto","year":"2020","journal-title":"Eurosurveillance"},{"key":"pcbi.1008994.ref027","unstructured":"John T. Iceland lab\u2019s testing suggests 50% of coronavirus cases have no symptoms. CNN. 2020;."},{"key":"pcbi.1008994.ref028","doi-asserted-by":"crossref","unstructured":"Day M. Covid-19: identifying and isolating asymptomatic people helped eliminate virus in Italian village; 2020.","DOI":"10.1136\/bmj.m1165"},{"issue":"4","key":"pcbi.1008994.ref029","doi-asserted-by":"crossref","first-page":"e13403","DOI":"10.2196\/13403","article-title":"Differences in Regional Patterns of Influenza Activity Across Surveillance Systems in the United States: Comparative Evaluation","volume":"5","author":"K Baltrusaitis","year":"2019","journal-title":"JMIR Public Health and Surveillance"},{"key":"pcbi.1008994.ref030","doi-asserted-by":"crossref","DOI":"10.15585\/mmwr.mm6912e1","article-title":"COVID-19 in a long-term care facility\u2014King County, Washington, February 27\u2013March 9, 2020","volume":"69","author":"TM McMichael","year":"2020","journal-title":"MMWR Morbidity and Mortality Weekly Report"},{"issue":"47","key":"pcbi.1008994.ref031","doi-asserted-by":"crossref","first-page":"14473","DOI":"10.1073\/pnas.1515373112","article-title":"Accurate estimation of influenza epidemics using Google search data via ARGO","volume":"112","author":"S Yang","year":"2015","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"1","key":"pcbi.1008994.ref032","first-page":"1","article-title":"Improved state-level influenza nowcasting in the United States leveraging Internet-based data and network approaches","volume":"10","author":"FS Lu","year":"2019","journal-title":"Nature communications"},{"issue":"7","key":"pcbi.1008994.ref033","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1005607","article-title":"Advances in using Internet searches to track dengue","volume":"13","author":"S Yang","year":"2017","journal-title":"PLoS computational biology"},{"key":"pcbi.1008994.ref034","doi-asserted-by":"crossref","first-page":"25732","DOI":"10.1038\/srep25732","article-title":"Cloud-based electronic health records for real-time, region-specific influenza surveillance","volume":"6","author":"M Santillana","year":"2016","journal-title":"Scientific reports"},{"issue":"10","key":"pcbi.1008994.ref035","doi-asserted-by":"crossref","first-page":"1446","DOI":"10.1093\/cid\/ciu647","article-title":"Using clinicians\u2019 search query data to monitor influenza epidemics","volume":"59","author":"M Santillana","year":"2014","journal-title":"Clinical Infectious Diseases"},{"issue":"3","key":"pcbi.1008994.ref036","doi-asserted-by":"crossref","first-page":"388","DOI":"10.1093\/cid\/ciy073","article-title":"A smartphone-driven thermometer application for real-time population-and individual-level influenza surveillance","volume":"67","author":"AC Miller","year":"2018","journal-title":"Clinical Infectious Diseases"},{"key":"pcbi.1008994.ref037","unstructured":"Organization WH. 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Available from: https:\/\/www.who.int\/influenza\/global_influenza_strategy_2019_2030\/en\/."},{"key":"pcbi.1008994.ref038","article-title":"Effect of non-pharmaceutical interventions for containing the COVID-19 outbreak: an observational and modelling study","author":"S Lai","year":"2020","journal-title":"medRxiv"},{"issue":"10","key":"pcbi.1008994.ref039","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1004513","article-title":"Combining search, social media, and traditional data sources to improve influenza surveillance","volume":"11","author":"M Santillana","year":"2015","journal-title":"PLoS computational biology"},{"issue":"10","key":"pcbi.1008994.ref040","doi-asserted-by":"crossref","first-page":"2124","DOI":"10.2105\/AJPH.2015.302696","article-title":"Flu near you: crowdsourced symptom reporting spanning 2 influenza seasons","volume":"105","author":"MS Smolinski","year":"2015","journal-title":"American journal of public health"},{"issue":"4","key":"pcbi.1008994.ref041","doi-asserted-by":"crossref","first-page":"e83","DOI":"10.2196\/publichealth.7344","article-title":"Combining participatory influenza surveillance with modeling and forecasting: Three alternative approaches","volume":"3","author":"JS Brownstein","year":"2017","journal-title":"JMIR public health and surveillance"},{"key":"pcbi.1008994.ref042","unstructured":"Liu D, Clemente L, Poirier C, Ding X, Chinazzi M, Davis JT, et al. A machine learning methodology for real-time forecasting of the 2019-2020 COVID-19 outbreak using Internet searches, news alerts, and estimates from mechanistic models. arXiv preprint arXiv:200404019. 2020;."},{"key":"pcbi.1008994.ref043","article-title":"Early transmission dynamics in Wuhan, China, of novel coronavirus\u2013infected pneumonia","author":"Q Li","year":"2020","journal-title":"New England Journal of Medicine"},{"key":"pcbi.1008994.ref044","doi-asserted-by":"crossref","unstructured":"Gutierrez E, Rubli A, Tavares T. Delays in death reports and their implications for tracking the evolution of COVID-19. Available at SSRN 3645304. 2020;.","DOI":"10.2139\/ssrn.3645304"},{"issue":"9","key":"pcbi.1008994.ref045","doi-asserted-by":"crossref","first-page":"2723","DOI":"10.1073\/pnas.1415012112","article-title":"Inference of seasonal and pandemic influenza transmission dynamics","volume":"112","author":"W Yang","year":"2015","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"pcbi.1008994.ref046","article-title":"Estimation of SARS-CoV-2 mortality during the early stages of an epidemic: a modelling study in Hubei, China and northern Italy","author":"A Hauser","year":"2020","journal-title":"medRxiv"},{"key":"pcbi.1008994.ref047","article-title":"Assessing the age specificity of infection fatality rates for COVID-19: Meta-analysis & public policy implications","author":"AT Levin","year":"2020","journal-title":"National Bureau of Economic Research"},{"key":"pcbi.1008994.ref048","unstructured":"Centers for Disease Control and Prevention. COVID-19 Pandemic Planning Scenarios\u2014Updated July 10, 2020;."},{"key":"pcbi.1008994.ref049","unstructured":"Kliff S, Bosman J. Official Counts Understate the U.S. Coronavirus Death Toll. The New York Times. 2020;."},{"key":"pcbi.1008994.ref050","unstructured":"Health N. Confirmed and Probably COVID-19 Deaths Daily Report; 2020."},{"key":"pcbi.1008994.ref051","unstructured":"Times NY. Data from the New York Times, based on reports from state and local health agencies; 2020."},{"key":"pcbi.1008994.ref052","article-title":"An interactive web-based dashboard to track COVID-19 in real time","author":"E Dong","year":"2020","journal-title":"The Lancet infectious diseases"},{"key":"pcbi.1008994.ref053","unstructured":"The COVID Tracking Project;. https:\/\/covidtracking.com\/."},{"key":"pcbi.1008994.ref054","unstructured":"Bureau USC. Annual Estimates of the Civilian Population by Single Year of Age and Sex for the United States and States: April 1, 2010 to July 1, 2018; 2019."},{"key":"pcbi.1008994.ref055","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1214\/14-AOAS788","article-title":"Inferring causal impact using Bayesian structural time-series models","volume":"9","author":"KH Brodersen","year":"2015","journal-title":"Annals of Applied Statistics"},{"issue":"490","key":"pcbi.1008994.ref056","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1198\/jasa.2009.ap08746","article-title":"Synthetic control methods for comparative case studies: Estimating the effect of California\u2019s tobacco control program","volume":"105","author":"A Abadie","year":"2010","journal-title":"Journal of the American statistical Association"},{"issue":"11","key":"pcbi.1008994.ref057","doi-asserted-by":"crossref","first-page":"2752","DOI":"10.1073\/pnas.1708856115","article-title":"Forecasting the spatial transmission of influenza in the United States","volume":"115","author":"S Pei","year":"2018","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"pcbi.1008994.ref058","unstructured":"Carlos Cinelli AF, Pearl J. A Crash Course in Good and Bad Control;. Available from: http:\/\/causality.cs.ucla.edu\/blog\/index.php\/category\/back-door-criterion\/."},{"key":"pcbi.1008994.ref059","first-page":"1","article-title":"18 F-FDG PET\/CT findings of COVID-19: a series of four highly suspected cases","author":"C Qin","year":"2020","journal-title":"European Journal of Nuclear Medicine and Molecular Imaging"},{"key":"pcbi.1008994.ref060","article-title":"Laboratory diagnosis and monitoring the viral shedding of 2019-nCoV infections","author":"Y Yang","year":"2020","journal-title":"medRxiv"},{"issue":"2","key":"pcbi.1008994.ref061","doi-asserted-by":"crossref","first-page":"538","DOI":"10.3390\/jcm9020538","article-title":"Incubation period and other epidemiological characteristics of 2019 novel coronavirus infections with right truncation: a statistical analysis of publicly available case data","volume":"9","author":"NM Linton","year":"2020","journal-title":"Journal of clinical medicine"},{"key":"pcbi.1008994.ref062","article-title":"Incidence, clinical outcomes, and transmission dynamics of hospitalized 2019 coronavirus disease among 9,596,321 individuals residing in California and Washington, United States: a prospective cohort study","author":"JA Lewnard","year":"2020","journal-title":"medRxiv"},{"issue":"2","key":"pcbi.1008994.ref063","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1109\/TMI.1982.4307558","article-title":"Maximum likelihood reconstruction for emission tomography","volume":"1","author":"LA Shepp","year":"1982","journal-title":"IEEE transactions on medical imaging"},{"key":"pcbi.1008994.ref064","unstructured":"Ferguson N, Laydon D, Nedjati Gilani G, Imai N, Ainslie K, Baguelin M, et al. Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand. Imperial College London. 2020;."},{"key":"pcbi.1008994.ref065","article-title":"Estimating the early death toll of COVID-19 in the United States","author":"D Weinberger","year":"2020","journal-title":"medRxiv"},{"key":"pcbi.1008994.ref066","unstructured":"Brown E, Reinhard B, Davis A. Coronavirus death toll: Americans are almost certainly dying of covid-19 but being left out of the official count. the Washington Post. 2020;."},{"issue":"5","key":"pcbi.1008994.ref067","doi-asserted-by":"crossref","first-page":"863","DOI":"10.1111\/irv.12096","article-title":"Mortality burden of the 2009-10 influenza pandemic in the United States: improving the timeliness of influenza severity estimates using inpatient mortality records","volume":"7","author":"V Charu","year":"2013","journal-title":"Influenza and other respiratory viruses"},{"issue":"9","key":"pcbi.1008994.ref068","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1016\/S1473-3099(12)70121-4","article-title":"Estimated global mortality associated with the first 12 months of 2009 pandemic influenza A H1N1 virus circulation: a modelling study","volume":"12","author":"FS Dawood","year":"2012","journal-title":"The Lancet infectious diseases"},{"key":"pcbi.1008994.ref069","unstructured":"Centers for Disease Control and Prevention. Weekly counts of death by jurisdiction and cause of death;."},{"key":"pcbi.1008994.ref070","doi-asserted-by":"crossref","unstructured":"Mistry D, Litvinova M, Chinazzi M, Fumanelli L, Gomes MF, Haque SA, et al. Inferring high-resolution human mixing patterns for disease modeling. arXiv preprint arXiv:200301214. 2020;.","DOI":"10.1038\/s41467-020-20544-y"},{"key":"pcbi.1008994.ref071","unstructured":"International Air Transportation Association https:\/\/www.iata.org\/;."},{"key":"pcbi.1008994.ref072","unstructured":"Official Aviation Guide https:\/\/www.oag.com\/;."},{"issue":"51","key":"pcbi.1008994.ref073","doi-asserted-by":"crossref","first-page":"21484","DOI":"10.1073\/pnas.0906910106","article-title":"Multiscale mobility networks and the spatial spreading of infectious diseases","volume":"106","author":"D Balcan","year":"2009","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"3","key":"pcbi.1008994.ref074","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.jocs.2010.07.002","article-title":"Modeling the spatial spread of infectious diseases: The GLobal Epidemic and Mobility computational model","volume":"1","author":"D Balcan","year":"2010","journal-title":"Journal of computational science"},{"issue":"22","key":"pcbi.1008994.ref075","doi-asserted-by":"crossref","first-page":"E4334","DOI":"10.1073\/pnas.1620161114","article-title":"Spread of Zika virus in the Americas","volume":"114","author":"Q Zhang","year":"2017","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"pcbi.1008994.ref076","unstructured":"Klein B, LaRock T, McCabe S, et al. Assessing changes in commuting and individual mobility in major metropolitan areas in the United States during COVID-19 outbreak;. Available from: https:\/\/www.mobslab.org\/uploads\/6\/7\/8\/7\/6787877\/assessing_mobility_changes_in_the_united_states_during_the_covid_19_outbreak.pdf."},{"issue":"9","key":"pcbi.1008994.ref077","doi-asserted-by":"crossref","first-page":"e1005697","DOI":"10.1371\/journal.pcbi.1005697","article-title":"Projecting social contact matrices in 152 countries using contact surveys and demographic data","volume":"13","author":"K Prem","year":"2017","journal-title":"PLoS computational biology"},{"issue":"1","key":"pcbi.1008994.ref078","first-page":"1","article-title":"The impact of regular school closure on seasonal influenza epidemics: a data-driven spatial transmission model for Belgium","volume":"18","author":"G De Luca","year":"2018","journal-title":"BMC infectious diseases"},{"key":"pcbi.1008994.ref079","unstructured":"The New York Times, \u201cSee which states and cities have told their residents to stay at home.\u201d; (2020). https:\/\/www.nytimes.com\/interactive\/2020\/us\/coronavirus-stay-at-home-order.html."},{"key":"pcbi.1008994.ref080","article-title":"A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker)","author":"T Hale","year":"2021","journal-title":"Nature Human Behaviour"},{"key":"pcbi.1008994.ref081","unstructured":"Google LLC. \u201cGoogle COVID-19 Community Mobility Reports\u201d;. https:\/\/www.google.com\/covid19\/mobility\/."},{"issue":"4","key":"pcbi.1008994.ref082","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1038\/s41591-020-0822-7","article-title":"Estimating clinical severity of COVID-19 from the transmission dynamics in Wuhan, China","volume":"26","author":"JT Wu","year":"2020","journal-title":"Nature Medicine"}],"updated-by":[{"DOI":"10.1371\/journal.pcbi.1008994","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2021,6,29]],"date-time":"2021-06-29T00:00:00Z","timestamp":1624924800000}}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1008994","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,6,29]],"date-time":"2021-06-29T13:42:59Z","timestamp":1624974179000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1008994"}},"subtitle":[],"editor":[{"given":"Cecile","family":"Viboud","sequence":"first","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2021,6,17]]},"references-count":82,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2021,6,17]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pcbi.1008994","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2020.04.18.20070821","asserted-by":"object"}]},"ISSN":["1553-7358"],"issn-type":[{"value":"1553-7358","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6,17]]}}}