GIS-BASED GEOSPATIAL ANALYSIS OF COVID-19 IN SOUTH STATES IN INDIA

This study analyse the space-time pattem of COVID-19 cases and therefore a space-time cube was created of spatiotemporal COVID-19 data. Statistically significant emerging hotspots were identified using space-time cube as input. The time period of the first wave was determined from 22nd April 2020 to 31st December 2020, and of the second wave from 15th April 2021 to 15th June 2021. The results obtained from the space-time cube show that the overall increasing trend direction was obtained for confirmed cases and deceased cases in both the first and second waves. In the first wave, 19 consecutive and two new hotspots of confirmed cases and 12 consecutive and one new hotspot of death cases were identified. In the second wave, 29 consecutive and three new hotspots of confirmed cases and 12 consecutive and four new hotspots of death cases were found. The study found a strong positive relationship between the variables in confirmed and death cases, as shown by the results of the Ordinaw Least Squares (OLS) linear regression. The districts having high urban agglomeration in Kerala, Kamataka, and pmts of Tamil Nadu got successive high numbers of COVID-19 confirmed cases and deceased cases. Additionally, the spatial pattern of the residuals of confirmed and death cases are statistically significant and highly clustered. The study provides valuable insights into the spatiotemporal trends and patterns of COVID-19 confirmed and death cases during the first and second wave in southern India. The findings can aid policymakers and healthcare professionals in developing effective strategies to manage and control the spread of COVID-19 in these regions