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

Ajay Hegde, Ramesh Masthi, Darshan Krishnappa

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


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.

Original languageEnglish
Article number286
JournalFrontiers in Public Health
Publication statusPublished - 09-06-2020

All Science Journal Classification (ASJC) codes

  • Public Health, Environmental and Occupational Health


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