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Analyzing the impact of a real-life outbreak simulator on pandemic mitigation: An epidemiological modeling study.
Specht, Ivan; Sani, Kian; Loftness, Bryn C; Hoffman, Curtis; Gionet, Gabrielle; Bronson, Amy; Marshall, John; Decker, Craig; Bailey, Landen; Siyanbade, Tomi; Kemball, Molly; Pickett, Brett E; Hanage, William P; Brown, Todd; Sabeti, Pardis C; Colubri, Andrés.
  • Specht I; The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
  • Sani K; Harvard College, Faculty of Arts and Sciences, Harvard University, Cambridge, MA 02138, USA.
  • Loftness BC; The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
  • Hoffman C; FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Faculty of Arts and Sciences, Harvard University, Cambridge, MA 02138, USA.
  • Gionet G; The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
  • Bronson A; Colorado Mesa University, Grand Junction, CO 81501, USA.
  • Marshall J; The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
  • Decker C; Department of Microbiology and Molecular Biology, College of Life Sciences, Brigham Young University, Provo, UT 84606, USA.
  • Bailey L; The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
  • Siyanbade T; Colorado Mesa University, Grand Junction, CO 81501, USA.
  • Kemball M; Colorado Mesa University, Grand Junction, CO 81501, USA.
  • Pickett BE; Department of Microbiology and Molecular Biology, College of Life Sciences, Brigham Young University, Provo, UT 84606, USA.
  • Hanage WP; Department of Microbiology and Molecular Biology, College of Life Sciences, Brigham Young University, Provo, UT 84606, USA.
  • Brown T; The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
  • Sabeti PC; Harvard College, Faculty of Arts and Sciences, Harvard University, Cambridge, MA 02138, USA.
  • Colubri A; The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Patterns (N Y) ; 3(8): 100572, 2022 Aug 12.
Article in English | MEDLINE | ID: covidwho-2015904
ABSTRACT
An app-based educational outbreak simulator, Operation Outbreak (OO), seeks to engage and educate participants to better respond to outbreaks. Here, we examine the utility of OO for understanding epidemiological dynamics. The OO app enables experience-based learning about outbreaks, spreading a virtual pathogen via Bluetooth among participating smartphones. Deployed at many colleges and in other settings, OO collects anonymized spatiotemporal data, including the time and duration of the contacts among participants of the simulation. We report the distribution, timing, duration, and connectedness of student social contacts at two university deployments and uncover cryptic transmission pathways through individuals' second-degree contacts. We then construct epidemiological models based on the OO-generated contact networks to predict the transmission pathways of hypothetical pathogens with varying reproductive numbers. Finally, we demonstrate that the granularity of OO data enables institutions to mitigate outbreaks by proactively and strategically testing and/or vaccinating individuals based on individual social interaction levels.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Observational study / Prognostic study Topics: Vaccines Language: English Journal: Patterns (N Y) Year: 2022 Document Type: Article Affiliation country: J.patter.2022.100572

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Observational study / Prognostic study Topics: Vaccines Language: English Journal: Patterns (N Y) Year: 2022 Document Type: Article Affiliation country: J.patter.2022.100572