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Allen WE, Altae-Tran H, Briggs J, Jin X, McGee G, Shi A, Raghavan R, Kamariza M, Nova N, Pereta A, Danford C, Kamel A, Gothe P, Milam E, Aurambault J, Primke T, Li W, Inkenbrandt J, Huynh T, Chen E, Lee C, Croatto M, Bentley H, Lu W, Murray R, Travassos M, Coull BA, Openshaw J, Greene CS, Shalem O, King G, Probasco R, Cheng DR, Silbermann B, Zhang F, Lin X. Population-scale longitudinal mapping of COVID-19 symptoms, behaviour and testing. Nat Hum Behav 2020; 4:972-982. [PMID: 32848231 PMCID: PMC7501153 DOI: 10.1038/s41562-020-00944-2] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 08/05/2020] [Indexed: 12/03/2022]
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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Affiliation(s)
- William E Allen
- The How We Feel Project, San Leandro, CA, USA.
- Society of Fellows, Harvard University, Cambridge, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Han Altae-Tran
- The How We Feel Project, San Leandro, CA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - James Briggs
- The How We Feel Project, San Leandro, CA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Schmidt Science Fellows, Oxford, UK
| | - Xin Jin
- The How We Feel Project, San Leandro, CA, USA
- Society of Fellows, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Glen McGee
- The How We Feel Project, San Leandro, CA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Andy Shi
- The How We Feel Project, San Leandro, CA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Rumya Raghavan
- The How We Feel Project, San Leandro, CA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Health Sciences and Technology Program, Massachusetts Institute of Technology and Harvard Medical School, Cambridge, MA, USA
| | - Mireille Kamariza
- The How We Feel Project, San Leandro, CA, USA
- Society of Fellows, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nicole Nova
- The How We Feel Project, San Leandro, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
| | | | | | - Amine Kamel
- The How We Feel Project, San Leandro, CA, USA
| | | | | | | | | | - Weijie Li
- The How We Feel Project, San Leandro, CA, USA
| | | | - Tuan Huynh
- The How We Feel Project, San Leandro, CA, USA
| | - Evan Chen
- The How We Feel Project, San Leandro, CA, USA
| | | | | | | | - Wendy Lu
- The How We Feel Project, San Leandro, CA, USA
| | | | - Mark Travassos
- The How We Feel Project, San Leandro, CA, USA
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Brent A Coull
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - John Openshaw
- The How We Feel Project, San Leandro, CA, USA
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Casey S Greene
- The How We Feel Project, San Leandro, CA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ophir Shalem
- The How We Feel Project, San Leandro, CA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Gary King
- The How We Feel Project, San Leandro, CA, USA
- Albert J. Weatherhead III University Professor, Institute for Quantitative Social Sciences, Harvard University, Cambridge, MA, USA
| | | | | | | | - Feng Zhang
- The How We Feel Project, San Leandro, CA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
| | - Xihong Lin
- The How We Feel Project, San Leandro, CA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Department of Statistics, Harvard University, Cambridge, MA, USA.
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Allen WE, Altae-Tran H, Briggs J, Jin X, McGee G, Raghavan R, Shi A, Kamariza M, Nova N, Pereta A, Danford C, Kamel A, Gothe P, Milam E, Aurambault J, Primke T, Li C, Inkenbrandt J, Huynh T, Chen E, Lee C, Croatto M, Bentley H, Lu W, Murray R, Travassos M, Openshaw J, Coull B, Greene C, Shalem O, King G, Probasco R, Cheng D, Silbermann B, Zhang F, Lin X. Population-scale Longitudinal Mapping of COVID-19 Symptoms, Behavior, and Testing Identifies Contributors to Continued Disease Spread in the United States. medRxiv 2020:2020.06.09.20126813. [PMID: 32577674 PMCID: PMC7302230 DOI: 10.1101/2020.06.09.20126813] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Despite social distancing and shelter-in-place policies, COVID-19 continues to spread in the United States. A lack of timely information about factors influencing COVID-19 spread and testing has hampered agile responses to the pandemic. We developed How We Feel, an extensible web and mobile application that aggregates self-reported survey responses, to fill gaps in the collection of COVID-19-related data. How We Feel collects longitudinal and geographically localized information on users' health, behavior, and demographics. Here we report results from over 500,000 users in the United States from April 2, 2020 to May 12, 2020. We show that self- reported surveys can be used to build predictive models of COVID-19 test results, which may aid in identification of likely COVID-19 positive individuals. We find evidence among our users for asymptomatic or presymptomatic presentation, as well as for household and community exposure, occupation, and demographics being strong risk factors for COVID-19. We further reveal factors for which users have been SARS-CoV-2 PCR tested, as well as the temporal dynamics of self- reported symptoms and self-isolation behavior in positive and negative users. These results highlight the utility of collecting a diverse set of symptomatic, demographic, and behavioral self- reported data to fight the COVID-19 pandemic.
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Russell LJ, Enshaei A, Jones L, Erhorn A, Masic D, Bentley H, Laczko KS, Fielding AK, Goldstone AH, Goulden N, Mitchell CD, Wade R, Vora A, Moorman AV, Harrison CJ. IGH@ translocations are prevalent in teenagers and young adults with acute lymphoblastic leukemia and are associated with a poor outcome. J Clin Oncol 2014; 32:1453-62. [PMID: 24711557 DOI: 10.1200/jco.2013.51.3242] [Citation(s) in RCA: 65] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
PURPOSE To determine the prevalence and prognostic association of immunoglobulin heavy chain (IGH@) translocations in acute lymphoblastic leukemia (ALL). PATIENTS AND METHODS The cohort comprised 3,269 patients treated on either the UKALL2003 trial for children and adolescents (1 to 24 years old) or the UKALLXII trial for adolescents and adults (15 to 59 years old). High-throughput fluorescent in situ hybridization was used to detect IGH@ translocations. RESULTS We identified IGH@ translocations in 5% of patients with ALL (159 of 3,269 patients), in patients with both B-cell (148 of 2,863 patients) and T-cell (11 of 408 patients) disease. Multiple partner genes were identified including CRLF2 (n = 35), five members of the CEPB gene family (n = 17), and ID4 (n = 11). The level of the IGH@-positive clone varied and indicated that some IGH@ translocations were primary events, whereas others were secondary aberrations often associated with other established aberrations. The age profile of patients with IGH@ translocations was distinctive, with a median age of 16 years and peak incidence of 11% among 20- to 24-year-old patients. Among patients with B-cell precursor ALL who were Philadelphia chromosome negative, those with an IGH@ translocation had an inferior overall survival compared with other patients (UKALL2003: hazard ratio, 2.37; 95% CI, 1.34 to 4.18; P = .003; UKALLXII: hazard ratio, 1.73; 95% CI, 1.22 to 2.47; P = .002). However, this adverse effect was not independent of age or minimal residual disease status and did not seem to be driven by an increased risk of relapse. CONCLUSION IGH@ translocations define a genetic feature that is frequent among adolescents and young adults with ALL. Although associated with an adverse outcome in adults, it is not an independent prognostic factor in children and adolescents.
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Affiliation(s)
- Lisa J Russell
- Lisa J. Russell, Amir Enshaei, Lisa Jones, Amy Erhorn, Dino Masic, Helen Bentley, Anthony V. Moorman, and Christine J. Harrison, Leukaemia Research Cytogenetics Group, Northern Institute for Cancer Research, Newcastle University, Newcastle-upon-Tyne; Karl S. Laczko, Leica Microsystems, Gateshead; Adele K. Fielding, Royal Free and University College London Medical School; Anthony H. Goldstone, University College London Hospital; Nicholas Goulden, Great Ormond St Hospital, London; Christopher D. Mitchell, John Radcliffe Hospital; Rachel Wade, Clinical Trial Service Unit, University of Oxford, Oxford; and Ajay Vora, Sheffield Children's Hospital, Sheffield, United Kingdom
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