Post-lockdown spatiotemporal pattern of COVID clustering in North 24 Parganas, West Bengal, India

Abstract

Many scholars and researchers have studied the CoVID-19 epidemic's spread using GIS technologies since it first appeared. The CoVID-19 pandemic is thought to be rife with unknowns, and many of them have a spatial component that makes the phenomenon understood as being spatially and possibly mappable. The majority of these efforts, though, have been made at the national, state, or district, levels. Very few studies primarily concentrate on the display of the CoVID-19 cluster at a local or neighborhood scale. From the perspective of micro-planning, analyzing the clustering, geographical direction, and heterogeneity of the CoVID-19 hotspots' spatial pattern is crucial specially when mass has returned to new normal living style. Using a case study on the North 24 Parganas of West Bengal, India, the most vulnerable district in West Bengal, we attempt to analyze the CoVID-19 diffusion at the block level in post-lockdown period. We assess the spatiotemporal distribution of CoVID-19 and map its hotspots based on the containment zones. This study demonstrates the patterns of geographical dispersion and the CoVID-19 pandemic spread in North 24 Parganas which is highly concentrated along the western boundaries of the state. We observed that the containment clusters of 2020 once more noted a higher density of CoVID cases in 2022 and validates the findings of the current study. It promises to corroborate the study into the geographic relation and spread of CoVID-19. By examining such spatial distribution patterns, the government might be able to track and predict the transmission of the infection in neighborhoods of blocks.