{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T19:58:20Z","timestamp":1772135900790,"version":"3.50.1"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,11,16]],"date-time":"2020-11-16T00:00:00Z","timestamp":1605484800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,11,16]],"date-time":"2020-11-16T00:00:00Z","timestamp":1605484800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"UCSF Bakar Computational Health Sciences Institute"},{"DOI":"10.13039\/100006108","name":"U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","award":["UL1 TR001872"],"award-info":[{"award-number":["UL1 TR001872"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","award":["UL1 TR001872"],"award-info":[{"award-number":["UL1 TR001872"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","award":["UL1 TR001872"],"award-info":[{"award-number":["UL1 TR001872"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","award":["UL1 TR001872"],"award-info":[{"award-number":["UL1 TR001872"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","award":["UL1 TR001872"],"award-info":[{"award-number":["UL1 TR001872"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"name":"U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences"},{"name":"U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences"},{"name":"U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences"},{"name":"U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Data"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Management of the COVID-19 pandemic has proven to be a significant challenge to policy makers. This is in large part due to uneven reporting and the absence of open-access visualization tools to present local trends and infer healthcare needs. Here we report the development of CovidCounties.org, an interactive web application that depicts daily disease trends at the level of US counties using time series plots and maps. This application is accompanied by a manually curated dataset that catalogs all major public policy actions made at the state-level, as well as technical validation of the primary data. Finally, the underlying code for the site is also provided as open source, enabling others to validate and learn from this work.<\/jats:p>","DOI":"10.1038\/s41597-020-00731-8","type":"journal-article","created":{"date-parts":[[2020,11,16]],"date-time":"2020-11-16T06:04:49Z","timestamp":1605506689000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["CovidCounties is an interactive real time tracker of the COVID19 pandemic at the level of US counties"],"prefix":"10.1038","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9464-2586","authenticated-orcid":false,"given":"Douglas","family":"Arneson","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthew","family":"Elliott","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arman","family":"Mosenia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9364-7051","authenticated-orcid":false,"given":"Boris","family":"Oskotsky","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Samuel","family":"Solodar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rohit","family":"Vashisht","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Travis","family":"Zack","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3005-0864","authenticated-orcid":false,"given":"Paul","family":"Bleicher","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7433-2740","authenticated-orcid":false,"given":"Atul J.","family":"Butte","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1789-3004","authenticated-orcid":false,"given":"Vivek A.","family":"Rudrapatna","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,11,16]]},"reference":[{"key":"731_CR1","unstructured":"World Health Organization. Novel Coronavirus \u2013 China, https:\/\/www.who.int\/csr\/don\/12-january-2020-novel-coronavirus-china\/en\/ (2020)."},{"key":"731_CR2","unstructured":"Center for Systems Engineering and Science at Johns Hopkins. COVID-19 Dashboard, https:\/\/coronavirus.jhu.edu\/map.html (2020)."},{"key":"731_CR3","unstructured":"AP News. South Dakota COVID cases top 1,100; meat plant worker dies, https:\/\/apnews.com\/b20cd0c7c71b828eb164fbe069050aac (2020)."},{"key":"731_CR4","unstructured":"The New York Times. Coronavirus (Covid-19) Data in the United States, https:\/\/github.com\/nytimes\/covid-19-data (2020)."},{"key":"731_CR5","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1016\/S1473-3099(20)30120-1","volume":"20","author":"E Dong","year":"2020","unstructured":"Dong, E., Du, H. & Gardner, L. An interactive web-based dashboard to track COVID-19 in real time. Lancet Infect. Dis. 20, 533\u2013534 (2020).","journal-title":"Lancet Infect. Dis."},{"key":"731_CR6","unstructured":"Institute for Health Metrics and Evaluation (IHME). COVID-19 Projections, https:\/\/covid19.healthdata.org\/united-states-of-america (2020)."},{"key":"731_CR7","unstructured":"Ripley, B. Our COVID-19 forecasting model, otherwise known as \u201cthe Chris Murray Model\u201d, http:\/\/www.healthdata.org\/acting-data\/our-covid-19-forecasting-model-otherwise-known-chris-murray-model (2020)."},{"key":"731_CR8","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-020-0448-0","volume":"7","author":"B Xu","year":"2020","unstructured":"Xu, B. et al. Epidemiological data from the COVID-19 outbreak, real-time case information. Sci. Data 7, 106 (2020).","journal-title":"Sci. Data"},{"key":"731_CR9","unstructured":"IHME COVID-19 Health Service Utilization Forecasting Team & Murray, C. J. Forecasting COVID-19 impact on hospital bed-days, ICU-days, ventilator-days and deaths by US state in the next 4 months. Preprint at https:\/\/www.medrxiv.org\/content\/10.1101\/2020.1103.1127.20043752v20043751 (2020)."},{"key":"731_CR10","unstructured":"Anzilotti, E. How governments are using Tableau to keep you up-to-date on the coronavirus, https:\/\/www.tableau.com\/about\/blog\/2020\/4\/how-governments-are-using-tableau-keep-you-date-coronavirus (2020)."},{"key":"731_CR11","unstructured":"Tableau Public, https:\/\/public.tableau.com\/search\/all\/%23coronavirus (2020)."},{"key":"731_CR12","unstructured":"Maryland Department of Public Health. Coronavirus Disease 2019 (COVID-19) Outbreak, https:\/\/coronavirus.maryland.gov\/ (2020)."},{"key":"731_CR13","unstructured":"Arizona Department of Health Services. Confirmed Covid-19 Cases by Zip Code, https:\/\/adhsgis.maps.arcgis.com\/apps\/opsdashboard\/index.html#\/84b7f701060641ca8bd9ea0717790906 (2020)."},{"key":"731_CR14","unstructured":"South Carolina Department of Health and Environmental Control. SC Cases by County & ZIP Code (COVID-19), https:\/\/scdhec.gov\/infectious-diseases\/viruses\/coronavirus-disease-2019-covid-19\/sc-cases-county-zip-code-covid-19 (2020)."},{"key":"731_CR15","unstructured":"Johnson County Kansas AIMS. Johnson County, KS - COVID-19 Update, https:\/\/public.tableau.com\/profile\/mapper.of.the.day.mod.#!\/vizhome\/covid19_joco_public\/Dashboard (2020)."},{"key":"731_CR16","unstructured":"County of San Diego Health and Human Services Agency. County of San Diego Daily Coronavirus Disease 2019 (COVID-19) Summary of Cases by Zip Code of Residence, https:\/\/www.sandiegocounty.gov\/content\/dam\/sdc\/hhsa\/programs\/phs\/Epidemiology\/COVID-19%20Summary%20of%20Cases%20by%20Zip%20Code.pdf (2020)."},{"key":"731_CR17","unstructured":"Seattle and King County Public Health. King County COVID-19 outbreak summary, https:\/\/kingcounty.gov\/depts\/health\/communicable-diseases\/disease-control\/novel-coronavirus\/data-dashboard.aspx (2020)."},{"key":"731_CR18","doi-asserted-by":"crossref","unstructured":"Omori, R., Mizumoto, K. & Nishiura, H. Ascertainment rate of novel coronavirus disease (COVID-19) in Japan. Int. J. Infect. Dis., 673\u2013675 (2020).","DOI":"10.1016\/j.ijid.2020.04.080"},{"key":"731_CR19","unstructured":"The U.S. Census Bureau. U.S. Census Bureau\u2019s 2014-2018 American Community Survey 5-year estimates, https:\/\/www.census.gov\/data\/developers\/data-sets\/acs-5year.html (2020)."},{"key":"731_CR20","unstructured":"Walker, K. tidycensus: Load US Census Boundary and Attribute Data as \u2018tidyverse\u2019 and\u2019sf\u2019-Ready Data Frames, https:\/\/CRAN.R-project.org\/package=tidycensus (2020)."},{"key":"731_CR21","unstructured":"Kaiser Health News. Millions Of Older Americans Live In Counties With No ICU Beds As Pandemic Intensifies, https:\/\/khn.org\/news\/as-coronavirus-spreads-widely-millions-of-older-americans-live-in-counties-with-no-icu-beds\/ (2020)."},{"key":"731_CR22","doi-asserted-by":"publisher","DOI":"10.7272\/Q6VQ30VD","author":"D Arneson","year":"2020","unstructured":"Arneson, D. et al. CovidCounties is an interactive real time tracker of the COVID19 pandemic at the level of US counties. Dryad https:\/\/doi.org\/10.7272\/Q6VQ30VD (2020)."},{"key":"731_CR23","unstructured":"Ferguson, N. M. et al. Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand, https:\/\/www.imperial.ac.uk\/media\/imperial-college\/medicine\/sph\/ide\/gida-fellowships\/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf (2020)."},{"key":"731_CR24","unstructured":"Predictive Healthcare at Penn Medicine. COVID-19 Hospital Impact Model for Epidemics (CHIME), https:\/\/penn-chime.phl.io\/ (2020)."},{"key":"731_CR25","unstructured":"Enns, E. A. et al. Modeling the Impact of Social Distancing Measures on the Spread of SARS-CoV-2 in Minnesota, https:\/\/mn.gov\/covid19\/assets\/MNmodel_tech_doc_tcm1148-427724.pdf (2020)."},{"key":"731_CR26","unstructured":"Biocomplexity Institute & Initiative University of Virginia. Estimation of COVID-19 Impact in Virginia, https:\/\/covid19.biocomplexity.virginia.edu\/sites\/covid19.biocomplexity\/files\/COVID-19-UVA-MODEL-FINDINGS-Apr13-2020-FINAL%20PRESS.pdf (2020)."},{"key":"731_CR27","unstructured":"Centers for Disease Prevention and Control. COVID-NET: A Weekly Summary of U.S. COVID-19 Hospitalization Data, https:\/\/gis.cdc.gov\/grasp\/COVIDNet\/COVID19_3.html (2020)."},{"key":"731_CR28","unstructured":"R Core Team. 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Open Source Softw."},{"key":"731_CR32","unstructured":"Sievert, C. plotly for R, https:\/\/plotly-r.com (2018)."}],"container-title":["Scientific Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41597-020-00731-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41597-020-00731-8","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41597-020-00731-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,5]],"date-time":"2022-12-05T23:54:34Z","timestamp":1670284474000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41597-020-00731-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,16]]},"references-count":32,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2020,12]]}},"alternative-id":["731"],"URL":"https:\/\/doi.org\/10.1038\/s41597-020-00731-8","relation":{"references":[{"id-type":"doi","id":"10.7272\/Q6VQ30VD","asserted-by":"subject"}],"has-preprint":[{"id-type":"doi","id":"10.1101\/2020.04.28.20083279","asserted-by":"object"}]},"ISSN":["2052-4463"],"issn-type":[{"value":"2052-4463","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,16]]},"assertion":[{"value":"23 April 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 October 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 November 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Atul Butte is a co-founder and consultant to Personalis and NuMedii; consultant to Samsung, Mango Tree Corporation, and in the recent past, 10x Genomics, Helix, Pathway Genomics, and Verinata (Illumina); has served on paid advisory panels or boards for Geisinger Health, Regenstrief Institute, Gerson Lehman Group, AlphaSights, Covance, Novartis, Genentech, Merck, and Roche; is a shareholder in Personalis and NuMedii; is a minor shareholder in Apple, Facebook, Alphabet (Google), Microsoft, Amazon, Snap, 10x Genomics, Illumina, Nuna Health, Assay Depot, Vet24seven, Regeneron, Sanofi, Royalty Pharma, AstraZeneca, Moderna, Biogen, Paraxel, and Sutro, and several other non-health related companies and mutual funds; and has received honoraria and travel reimbursement for invited talks from Johnson and Johnson, Roche, Genentech, Pfizer, Merck, Lilly, Takeda, Varian, Mars, Siemens, Optum, Abbott, Celgene, AstraZeneca, AbbVie, Westat, and many academic institutions, medical or disease specific foundations and associations, and health systems. Atul Butte receives royalty payments through Stanford University, for several patents and other disclosures licensed to NuMedii and Personalis. Atul Butte\u2019s research has been funded by NIH, Northrup Grumman (as the prime on an NIH contract), Genentech, Johnson and Johnson, FDA, Robert Wood Johnson Foundation, Leon Lowenstein Foundation, Intervalien Foundation, Priscilla Chan and Mark Zuckerberg, the Barbara and Gerson Bakar Foundation, and in the recent past, the March of Dimes, Juvenile Diabetes Research Foundation, California Governor\u2019s Office of Planning and Research, California Institute for Regenerative Medicine, L\u2019Oreal, and Progenity. The remaining authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"405"}}