GIS-based geospatial analysis of COVID-19 in southern India

Abstract

ABSTRACT The general objective of this study was to compare first and second wave of the COVID - 19 - epidemic at district level in Karnataka, Tamil Nadu and Karnataka, the southern states of India. To achieve this, four specific objectives were set. COVID19-India API dataset was used to meet the objectives. To analyse the space time pattern, space time cube was created and statistically significant emerging hot spots were identified using space time cube as input. To model spatially varying relationships cases during second were given as dependent variable and cases during first wave were set as Explanatory Variables. The results obtained from space time cube for the first wave shows the overall increasing trend direction for conformed cases (trend statistics = 4.4572, Trend p-value = 0.000) and for death cases (trend statistics = 4.3201, Trend p-value = 0.000). In case of second wave the overall increasing trend direction was for conformed cases (trend statistics = 6.3112, Trend p-value = 0.000) and for death cases (trend statistics = 6.2508, Trend p-value = 0.000). Emerging Hot Spot Analysis shows in case of first wave 19 consecutive and 02 new hot spots of confirmed cases and 12 consecutive and 01 new hot spot of deaths cases. Moreover, in case of second wave 29 consecutive and 03 new hot spots were found of confirmed cases and 12 consecutive and 04 new hot spots were found of deaths cases. The results of the Ordinary Least Squares (OLS) linear regression show the strong positive relationship in between both the variables in confirmed as well as death cases. In case of confirmed cases there were 15 districts below - 0.5 Std. Dev (standard deviation) and 16 districts above + 0.5 Std. Deviation. In case of death cases there were 06 districts below - 0.5 Std. Dev (standard deviation) and 07 districts above + 0.5 Std. Deviation. The Spatial Pattern of the residuals of confirmed and death cases were found statistically significant and highly clustered. Results indicate the districts having high urban agglomeration in Kerala, Karnataka and parts of the Tamil Nadu got successive high no. of COVID – 19 confirmed cases and death cases.