The emergence of the novel Coronavirus in China’s Wuhan city, in late 2019, led to unprecedented health challenges globally. This COVID-19 outbreak prompted significant transformation and adaptation in healthcare systems worldwide. The foundation for administrative responses came primarily from diverse modelling and forecasting approaches that informed government interventions, including lockdowns and preventive strategies such as physical distancing. This resulted in mathematical modelling 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 modelling reports, necessitates a thorough yet focused examination of COVID-19 mathematical modelling approaches to address existing doubts. Limited literature exists examining mathematical modelling applications and their influence during India's COVID-19 outbreak. Therefore, this analysis aims to examine various mathematical modelling approaches employed in India during COVID-19, addressing underlying assumptions, their influence on policy decisions, and inherent model constraints.
Mehto et al. (2025) studied this question.