Merits and Demerits of Selective Isolation of Superspreaders: A Mathematical Modeling Study Based upon West Bengal (India) SARS-COV 2 Data

Ghoshdastidar, S and Sarkar, K and Ghoshdastidar, B (2021) Merits and Demerits of Selective Isolation of Superspreaders: A Mathematical Modeling Study Based upon West Bengal (India) SARS-COV 2 Data. In: Indian Journal of Community Medicine, 46 (3). pp. 515-519.

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Abstract

Context: All COVID cases and their contacts are considered highly infectious requiring isolation, which blocks the COVID isolation beds and disrupts life in the community. Aim: To find out the effect of selective isolation and contact tracing of superspreaders as compared with the conventional ongoing protocol. Settings and Design: A mathematical model was designed to look at the effect of isolation and contact tracing of only those with high viral loads (superspreaders) on COVID-19 bed occupancy and overall mortality, in comparison with conventional protocol of isolation and contact tracing of all cases. Materials and Methods: An agent-based model, calibrated to the ongoing West Bengal COVID-19 data, was run for a total of 178 days to find out the effect of the interventions on COVID-19 bed occupancy and mortality. Results: There is an impressive reduction in the occupancy of COVID isolation beds, even with the preintervention testing rate with no negative impact on mortality. Conclusions: Strict isolation of superspreaders only, maybe highly effective in reducing the burden on health care and solving the COVID isolation bed crises if the testing rate is significantly increased.

Item Type:	Journal Article
Publication:	Indian Journal of Community Medicine
Publisher:	Wolters Kluwer Medknow Publications
Additional Information:	The copyright for this article belongs to the Wolters Kluwer Medknow Publications.
Keywords:	Coronavirus disease 2019; mathematical modeling; severe acute respiratory syndrome coronavirus 2; superspreader; viral load
Department/Centre:	Division of Mechanical Sciences > Chemical Engineering
Date Deposited:	28 Nov 2023 03:51
Last Modified:	28 Nov 2023 03:51
URI:	https://eprints.iisc.ac.in/id/eprint/82955

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