Modeling serological testing to inform relaxation of social distancing for COVID-19 control.

• Type of Material: Article
• Authors: Alicia N. M. Kraay, Emory University; Kristin Nelson, Emory University; Conan Y. Zhao, Georgia Institute of Technology; David Demory, Georgia Institute of Technology; Joshua S. Weitz, Georgia Institute of Technology; Benjamin Lopman, Emory University
• Language: English
• Date: 2020-11-17
• Publisher: National Institutes of Health
• Publication Version: Preprint (Prior to Peer Review)
• Copyright Statement: © The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1101/2020.04.24.20078576
• Title of Journal or Parent Work: medRxiv
• Grant/Funding Information: JSW and DD were supported by Simons Foundation (Scope Award ID 329108);; BAL and KNN were supported by NIH/NICHD R01 HD097175; BAL, KNN, and ANMK were supported by NIH/NIGMS R01 GM124280;; JSW and CYZ was supported by National Science Foundation (1806606, 1829636, and 2032082).; BAL and ANMK were supported by the Vaccine Impact Modelling Consortium;; BAL was supported by NSF 2032084; JSW was supported by the Army Research Office (W911NF1910384)
• Keywords: Public, Environmental & Occupational Health; Control; Modeling; Relaxation of social distancing; serological testing; COVID-19
• Research Categories: Health Sciences, Epidemiology; Biology, Biostatistics; Health Sciences, Public Health; Biology, Virology

Abstract

Serological testing remains a passive component of the current public health response to the COVID-19 pandemic. Using a transmission model, we examined how serology can be implemented to allow seropositive individuals to increase levels of social interaction while offsetting transmission risks. We simulated the use of widespread serological testing in three metropolitan areas with different initial outbreak timing and severity characteristics: New York City, South Florida, and Washington Puget Sound. In our model, we use realistic serological assay characteristics, in which tested seropositive individuals partially restore their social contacts and act as immunological 'shields'. Compared to a scenario with no intervention, beginning a mass serological testing program on November 1, 2020 was predicted to avert 15,000 deaths (28% reduction, 95% CrI: 0.4%-30.2%) in New York City, 3,000 (31.1% reduction, 95% CrI: 26.4%-33.3%) in South Florida and 10,000 (60.3% reduction, 95% CrI: 50.2%-60.7%) in Washington State by June 2021. In all three sites, widespread serological testing substantially blunted new waves of transmission. Serological testing has the potential to mitigate the impacts of the COVID-19 pandemic while also allowing a substantial number of individuals to safely return to social interactions and economic activity.