• Nimalan Arinaminpathy, Jishnu Das, Tyler H McCormick, Partha Mukhopadhyay, and Neelanjan Sircar.
• MRC Centre for Global Infectious Disease Analysis, Imperial College, United Kingdom. Electronic address: nim.pathy@imperial.ac.uk.
• Epidemics. 2021 Sep 1; 36: 100477.

AbstractThe novel SARS-CoV-2 virus, as it manifested in India in April 2020, showed marked heterogeneity in its transmission. Here, we used data collected from contact tracing during the lockdown in response to the first wave of COVID-19 in Punjab, a major state in India, to quantify this heterogeneity, and to examine implications for transmission dynamics. We found evidence of heterogeneity acting at multiple levels: in the number of potentially infectious contacts per index case, and in the per-contact risk of infection. Incorporating these findings in simple mathematical models of disease transmission reveals that these heterogeneities act in combination to strongly influence transmission dynamics. Standard approaches, such as representing heterogeneity through secondary case distributions, could be biased by neglecting these underlying interactions between heterogeneities. We discuss implications for policy, and for more efficient contact tracing in resource-constrained settings such as India. Our results highlight how contact tracing, an important public health measure, can also provide important insights into epidemic spread and control.Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.

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