TITLE:
Investigation on the COVID-19 Outbreak in India: Lockdown Impact and Vulnerability Analysis
AUTHORS:
Nilay Nishant, Avinash Chouhan, Dibyajyoti Chutia, Puyam S. Singh, Sanjiv Ojah, Sanjiban Roy, P. L. N. Raju
KEYWORDS:
COVID-19, Corona India, Time Series Analysis, SIR Model, Vulnerability Analysis
JOURNAL NAME:
Journal of Geographic Information System,
Vol.12 No.4,
August
12,
2020
ABSTRACT: Coronavirus (COVID-19) disease is a major pandemic which has taken the world by storm. More than 524,000 citizens of the globe have succumbed to the disease as on 3rd July, 2020. Accurate modeling of the dynamics of the disease spread is required to curb the virus. With the availability of large amount of data made available publicly by the Government agency as well as the other live crowdsourcing media, it is possible to develop an accurate local prediction tool. In this study, we analyze the dynamics of local outbreaks of COVID-19 for few states of India with major outbreaks and for India as a whole. The large amount of data available from the COVID-19 Tracker India platform was utilized to estimate the impact of lockdown in the country and the states with major outbreaks. The effectiveness of the lockdown implementation by the respective states is studied for the analysis. The lockdown was categorized into strict, moderate, and lenient. The model is deployed on a web based platform to disseminate the alert to the public. We further extend the ordinary differential Equation (ODE) based model to generate district level vulnerability index for the whole country based on the rate of change of infected people, breach in social distancing, and population. Around 47% of districts of the country were not found vulnerable; however, 13% of the districts were identified as high risk for the disease outbreak.