Globally, the COVID-19 pandemic has become a threat to humans and to the socioeconomic systems they have developed since the industrial revolution . Hence, governments and stakeholders call for strategies to help restore normalcy while dealing with this pandemic effectively . Since till now, the disease is yet to have a cure; therefore, only risk-based decision making can help governments achieve a sustainable solution in the long term . To help the decisionmakers explore viable actions, we propose a risk-based assessment framework for analyzing COVID-19 risk to areas, using integrated hazard and vulnerability components associated with this pandemic for effective risk mitigation . The study is carried on a region administrated by Jaipur municipal corporation (JMC), India . Based on the current understanding of this disease, we hypothesized different COVID-19 risk indices (C19Ri) of the wards of JMC such as proximity to hotspots, total population, population density, availability of clean water, and associated land use/land cover, are related with COVID-19 contagion and calculated them in a GIS-based multicriteria risk reduction method . The results showed disparateness in COVID-19 risk areas with a higher risk in north-eastern and south-eastern zone wards within the boundary of JMC . We proposed prioritizing wards under higher risk zones for intelligent decision making regarding COVID-19 risk reduction through appropriate management of resources-related policy consequences . This study aims to serve as a baseline study to be replicated in other parts of the country or world to eradicate the threat of COVID-19 effectively.
Index: COVID-19, CRAM model, GIS, lockdown, risk assessment, spatial analysis