Risk Analysis of COVID‐19 Infections in Kolkata Metropolitan City: A GIS‐Based Study and Policy Implications

Abstract

The COVID‐19 pandemic has affected daily lives of people around the world. People have already started to live wearing masks, keeping a safe distance from others, and maintaining a high level of hygiene. This paper deals with an in‐depth analysis of riskness associated with COVID‐19 infections in Kolkata Municipal Corporation (KMC) at the subcity (ward) level. Attempts have been made to identify the areas with high or low risk of infections using GIS‐based geostatistical approach. Cosine Similarity Index has been used to rank different wards of KMC according to the degree of riskness. Four indices were computed to address intervention objectives and to determine “Optimized Prevention Rank” of wards for future policy decisions. The highest risk areas were located in the eastern and western part of the city, to a great extent overlapped with wards containing larger share of population living in slums and/or below poverty level. On the other hand, highly infected areas lie in central Kolkata and in several wards at the eastern and northeastern periphery of the KMC. The “Optimized Prevention Rank” have indicated that the lack of social awareness along with lack of social distancing have contributed to the increasing number of containments of COVID‐19 cases. The rankings of the wards would no doubt provide the policy makers a basis to control further spread of the disease. Since effective antiviral drugs are already in the market, the best application of our research would be in the ensuing vaccination drive against further COVID‐19 infections.

Optimizing Spatial Allocation of COVID‐19 Vaccine by Agent‐Based Spatiotemporal Simulations

“…Our results emphasized the existence of spatial heterogeneity in herd immunity. Previous studies also indicated that spatial heterogeneity may influence the implementation of interventions, and control strategies should aim at such heterogeneity (Dowdy et al., 2012; Nath et al., 2021; Shrestha et al., 2016; Yechezkel et al., 2020). Therefore, it is necessary to quantify the degree of spatial heterogeneity, identify the “hotspots” and apply intervention against the disease outbreak.…”

Geographical Analysis of COVID-19 Epidemiology: A Review

“…When analyzing the risk to COVID-19 infection using remote sensing and GIS, geographical analysis-based proximity analysis and census data of Jaipur city and socioeconomic parameters (population, population density, percentage of main workers, and percentages of literates) have been employed to identify the risk to COVID-19 infection. Also in India, with the aim of dealing with an in-depth analysis of riskness associated with COVID-19 infections in Kolkata Municipal Corporation at the subcity level, the areas with high or low risk of infections using GISbased geostatistical approach was identified in this area (54). The study results of (54) has shown that the highest risk areas were located in the eastern and western part of the city, to a great extent overlapped with wards containing larger share of population living in slums and/or below poverty level (54).…”

“…Also in India, with the aim of dealing with an in-depth analysis of riskness associated with COVID-19 infections in Kolkata Municipal Corporation at the subcity level, the areas with high or low risk of infections using GISbased geostatistical approach was identified in this area (54). The study results of (54) has shown that the highest risk areas were located in the eastern and western part of the city, to a great extent overlapped with wards containing larger share of population living in slums and/or below poverty level (54). Impacts of social and economic factors on the transmission of COVID-19 was also assessed in China (55).…”

Impact of COVID‐19 lockdown on the elemental profile of PM10 present in the ambient aerosol of an educational institute in Kolkata, India

“…The abrupt restriction of anthropogenic activities was implemented in India from March 24, 2020 (Kabiraj & Gavli, 2020 ; Srivastava et al., 2020 ), constraining the normal movement of the population (Gautam & Hens, 2020 ). Like the whole country, interstate and intrastate transportation from Kolkata were suspended till May 3, 2020, which was further extended till June 30, 2020 in areas with large COVID‐19 cases categorized as red zones (Banerji & Mitra, 2021 ; Nath et al., 2021 ). During the lockdown, the Indian railway was operating only freight services to transport necessary goods to various parts of the country.…”