| Autor: |
Ajay Hegde, Ramesh Masthi, Darshan Krishnappa |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Frontiers in Public Health, Vol 8 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2296-2565 |
| DOI: |
10.3389/fpubh.2020.00286 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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