Mathematical models and their Policy implications on COVID-19 Pandemic in India: A narrative review
Keywords:
COVID-19, Mathematical modeling, assumptions, policy, IndiaAbstract
The emergence of the novel Coronavirus in Wuhan, China, in December 2019 led to unprecedented global health challenges. The COVID-19 outbreak prompted significant transformation and adaptation in healthcare systems worldwide. The foundation for administrative responses came primarily from diverse modeling and forecasting approaches that informed government interventions, including lockdowns and preventive strategies such as physical distancing. This resulted in mathematical modeling gaining extraordinary prominence. Epidemiological experts have demonstrated exceptional dedication while facing considerable uncertainty, generating crucial understanding about SARS-CoV-2 transmission patterns to inform public health strategies.
The abundance of information, coupled with discrepancies among various mathematical modeling reports, necessitates a thorough yet focused examination of COVID-19 mathematical modeling approaches to address existing doubts. Limited literature exists examining mathematical modeling applications and their influence during India's COVID-19 outbreak. Therefore, this analysis aims to examine various mathematical modeling approaches employed in India during COVID-19, addressing underlying assumptions, their influence on policy decisions, and inherent model constraints.
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Copyright (c) 2026 Amit Kumar Mehto, Parmeshwar Satpathy, Pragya Chand , Deepak Ranjan Bhol
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