Hyperlocal Postcode Based Crowdsourced Surveillance Systems in the COVID-19 Pandemic Response

Hyperlocal Postcode Based Crowdsourced Surveillance Systems in the COVID-19 Pandemic Response

Ajay Hegde, Ramesh Masthi, Darshan Krishnappa

The SARS-CoV-2 pandemic has rapidly saturated healthcare resources across the globe and has led to a restricted screening process, hindering efforts at comprehensive case detection. This has not only facilitated community spread but has also resulted in an underestimation of the true incidence of disease, a statistic which is useful for policy making aimed at controlling the current pandemic and in preparing for future outbreaks. In this perspective, we present a crowdsourced platform developed by us for the true estimation of all SARS-CoV-2 infections in the community, through active self-reporting and layering other authentic datasets. The granularity of data captured by this system could prove to be useful in assisting governments to identify SARS-CoV-2 hotspots in the community facilitating lifting of restrictions in a controlled fashion.

2020

surveillance, covid-19, Digital health, pandemic response, crowdsource, post code map

10.3389/fpubh.2020.00286

Epidemiology and Health

Korean Society of Epidemiology

Public aspects of medicine