Modelling Interconnected Factors for Mitigating Infectious Disease Transmission: Lessons for Health and Sustainability

In the light of COVID-19, which has been announced as a global pandemic by the world health organization, it becomes paramount to take the necessary measures to control the possible spread of this highly spread contagious virus in Indian context. The present research aims to discuss the factors that help in deciding the strategies for reducing/elimination chain transmission. For this, an attempt has been made on the identified factors and to rank them according to their impacts on causing the chain transmission with the help of the total interpretive structural modelling (TISM) approach. Further, the factor categorization among the clusters is done by using MICMAC analysis to reveal the nature of factors that further helps in discussing the conclusion. The study advocates that there is rapid growth in increasing the cases of COVID-19 in the crowded cities and, mostly detected in the persons travelling from the other countries to India from February 2020 to September 2020. The factors CoF1 and CoF5 are concluded as significant and responsible for the rising number of COVID-19 and it is proposed that these factors should be addressed first to have the better control on the possible transmission. Further, the report also reveals that the asymptomatic cases (CoF7) have a high dependence power which states that this factor is influenced by the presence of other factors. In these extreme conditions, this study aptly reports the precautionary measures to prevent the increasing active cases of COVID-19.