Spatio-temporal Analysis of COVID-19 Hotspots in India Using Geographic Information Systems

Abstract

The aim of this study is to identify hotspot regions of COVID-19 in India from March 2020 to August 2023. Identifying hotspots is essential for effective pandemic management, as it helps policymakers understand the dynamics of virus spread and allows for more precise public health campaigns. The present study is a district level analysis of India at five different points in time, where we calculate the cumulative incidence rate (CIR), cumulative fatality rate (CFR) and recovery rate (RR) for COVID-19. Further, we apply Global Moran's I, Getis-Ord Gi* and Anselin local Moran's I index to identify COVID-19 hotspots by using Geographic Information Systems (GIS) technology. The results show that the spatial and temporal variation of the CIR is very high across India. The CIR was recorded lower in May 2020 as the affected people were immobilized due to the lockdown. However, the CFR was high and RR was low due to inadequate medical facilities and treatment. The findings revealed that mainly two hotspot regions existed in India until May 2021, the National Capital Region, Haryana, Punjab, Rajasthan, Uttar Pradesh and Maharashtra in the south. However, this scenario has entirely changed since January 2022, when northern India has changed into a cold-spot and the southern coastal states have become the pandemic hot-spot region. Combining hot-spot analysis with Global & Anselin local Moran's I offers a precise method for locating statistically significant COVID-19 case cluster areas and identifying high-risk areas.