Analyzing the impact of a real-life outbreak simulator on pandemic mitigation: An epidemiological modeling study

Ivan Specht; Kian Sani; Bryn C Loftness; Curtis Hoffman; Gabrielle Gionet; Amy Bronson; John Marshall; Craig Decker; Landen Bailey; Tomi Siyanbade; Molly Kemball; Brett E Pickett; William P Hanage; Todd Brown; Pardis C Sabeti; Andrés Colubri

doi:10.1016/j.patter.2022.100572

Analyzing the impact of a real-life outbreak simulator on pandemic mitigation: An epidemiological modeling study

Patterns (N Y). 2022 Aug 12;3(8):100572. doi: 10.1016/j.patter.2022.100572.

Authors

Ivan Specht^{1

2}, Kian Sani^{1

3}, Bryn C Loftness^{1

4}, Curtis Hoffman^{1

5}, Gabrielle Gionet¹, Amy Bronson⁴, John Marshall⁴, Craig Decker⁵, Landen Bailey⁵, Tomi Siyanbade^{1

2}, Molly Kemball^{1

3}, Brett E Pickett⁵, William P Hanage^{1

6}, Todd Brown¹, Pardis C Sabeti^{1

3

7

8

9}, Andrés Colubri^{1

10}

Affiliations

¹ The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
² Harvard College, Faculty of Arts and Sciences, Harvard University, Cambridge, MA 02138, USA.
³ FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Faculty of Arts and Sciences, Harvard University, Cambridge, MA 02138, USA.
⁴ Colorado Mesa University, Grand Junction, CO 81501, USA.
⁵ Department of Microbiology and Molecular Biology, College of Life Sciences, Brigham Young University, Provo, UT 84606, USA.
⁶ Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
⁷ Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA.
⁸ Massachusetts Consortium on Pathogen Readiness, Harvard Medical School, Harvard University, Boston, MA 02115, USA.
⁹ Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA.
¹⁰ Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA 01655, USA.

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.

Keywords: Bluetooth contact sensing; epidemiology; modeling; network analysis; outbreak science; outbreak simulation; pandemic mitigation.