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Population-scale longitudinal mapping of COVID-19 symptoms, behaviour and testing.
Allen, William E; Altae-Tran, Han; Briggs, James; Jin, Xin; McGee, Glen; Shi, Andy; Raghavan, Rumya; Kamariza, Mireille; Nova, Nicole; Pereta, Albert; Danford, Chris; Kamel, Amine; Gothe, Patrik; Milam, Evrhet; Aurambault, Jean; Primke, Thorben; Li, Weijie; Inkenbrandt, Josh; Huynh, Tuan; Chen, Evan; Lee, Christina; Croatto, Michael; Bentley, Helen; Lu, Wendy; Murray, Robert; Travassos, Mark; Coull, Brent A; Openshaw, John; Greene, Casey S; Shalem, Ophir; King, Gary; Probasco, Ryan; Cheng, David R; Silbermann, Ben; Zhang, Feng; Lin, Xihong.
Afiliação
  • Allen WE; The How We Feel Project, San Leandro, CA, USA. weallen@fas.harvard.edu.
  • Altae-Tran H; Society of Fellows, Harvard University, Cambridge, MA, USA. weallen@fas.harvard.edu.
  • Briggs J; Broad Institute of MIT and Harvard, Cambridge, MA, USA. weallen@fas.harvard.edu.
  • Jin X; The How We Feel Project, San Leandro, CA, USA.
  • McGee G; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Shi A; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Raghavan R; The How We Feel Project, San Leandro, CA, USA.
  • Kamariza M; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Nova N; Schmidt Science Fellows, Oxford, UK.
  • Pereta A; The How We Feel Project, San Leandro, CA, USA.
  • Danford C; Society of Fellows, Harvard University, Cambridge, MA, USA.
  • Kamel A; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Gothe P; The How We Feel Project, San Leandro, CA, USA.
  • Milam E; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Aurambault J; The How We Feel Project, San Leandro, CA, USA.
  • Primke T; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Li W; The How We Feel Project, San Leandro, CA, USA.
  • Inkenbrandt J; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Huynh T; Health Sciences and Technology Program, Massachusetts Institute of Technology and Harvard Medical School, Cambridge, MA, USA.
  • Chen E; The How We Feel Project, San Leandro, CA, USA.
  • Lee C; Society of Fellows, Harvard University, Cambridge, MA, USA.
  • Croatto M; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Bentley H; The How We Feel Project, San Leandro, CA, USA.
  • Lu W; Department of Biology, Stanford University, Stanford, CA, USA.
  • Murray R; The How We Feel Project, San Leandro, CA, USA.
  • Travassos M; The How We Feel Project, San Leandro, CA, USA.
  • Coull BA; The How We Feel Project, San Leandro, CA, USA.
  • Openshaw J; The How We Feel Project, San Leandro, CA, USA.
  • Greene CS; The How We Feel Project, San Leandro, CA, USA.
  • Shalem O; The How We Feel Project, San Leandro, CA, USA.
  • King G; The How We Feel Project, San Leandro, CA, USA.
  • Probasco R; The How We Feel Project, San Leandro, CA, USA.
  • Cheng DR; The How We Feel Project, San Leandro, CA, USA.
  • Silbermann B; The How We Feel Project, San Leandro, CA, USA.
  • Zhang F; The How We Feel Project, San Leandro, CA, USA.
  • Lin X; The How We Feel Project, San Leandro, CA, USA.
Nat Hum Behav ; 4(9): 972-982, 2020 09.
Article em En | MEDLINE | ID: mdl-32848231
ABSTRACT
Despite the widespread implementation of public health measures, coronavirus disease 2019 (COVID-19) continues to spread in the United States. To facilitate an agile response to the pandemic, we developed How We Feel, a web and mobile application that collects longitudinal self-reported survey responses on health, behaviour and demographics. Here, we report results from over 500,000 users in the United States from 2 April 2020 to 12 May 2020. We show that self-reported surveys can be used to build predictive models to identify likely COVID-19-positive individuals. We find evidence among our users for asymptomatic or presymptomatic presentation; show a variety of exposure, occupational and demographic risk factors for COVID-19 beyond symptoms; reveal factors for which users have been SARS-CoV-2 PCR tested; and highlight the temporal dynamics of symptoms and self-isolation behaviour. These results highlight the utility of collecting a diverse set of symptomatic, demographic, exposure and behavioural self-reported data to fight the COVID-19 pandemic.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pneumonia Viral / Infecções por Coronavirus / Técnicas de Laboratório Clínico / Betacoronavirus Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male País/Região como assunto: America do norte Idioma: En Revista: Nat Hum Behav Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pneumonia Viral / Infecções por Coronavirus / Técnicas de Laboratório Clínico / Betacoronavirus Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male País/Região como assunto: America do norte Idioma: En Revista: Nat Hum Behav Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos