Spatial variation of covid-19 morbidity status and identification of risk zone in Tamil Nadu (India) during first wave

• Published in: GeoJournal Vol. 88; no. 2; pp. 1341 - 1354
• Main Authors: Saravanabavan, V., Emayavaramban, V., Thangamani, V., Manonmani, I. K., Rose, R. S. Suja, Balaji, D., Nisha, R. Rahamath, Kannadasan, K., Vinothkanna, S., Vinothini, C.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 2023; Springer Nature B.V
• Subjects: Coronaviruses; Correlation analysis; COVID-19; Diseases; Environmental Management; Geography; Human Geography; Mapping; Morbidity; Pandemics; Respiratory diseases; Risk; Severe acute respiratory syndrome; Severe acute respiratory syndrome coronavirus 2; Social Sciences; Spatial variations; Standardization; Tertiary; Viral diseases; Tamil Nadu India; India; COVID-19; GIS; Correlation; Z score; LQ analysis; Tertiary workers; Tamil Nadu; Risk zone
• ISSN: 1572-9893; 0343-2521; 1572-9893
• DOI: 10.1007/s10708-022-10680-x

COVID-19 is a pandemic disease caused by severe acute respiratory syndrome corona virus 2 (SARS-CoV-2). The study area, Tamilnadu, is a southern state in India. The present study demonstrates the significance of mapping in identifying the risk zones of COVID-19 disease by taking a study of COVID-19 cases in Tamilnadu state. The main objective of the study was to identify the risk zone of COVID-19 disease in the first wave of Tamilnadu through geospatial mapping. Data on COVID-19 cases collected during March 2020 to March 2021 month wise in all 37 districts (unit area) of Tamilnadu in two-month interval wise was analysed. The study is based on secondary sources from respective office in Tamilnadu. Z-score techniques were used for standardizing data. Correlation analysis provided a measure of correlation between COVID-19 and working population. Location Quotient analysis aided the identification of COVID-19 risk zones in Tamilnadu. Present study indicates tertiary workers are more vulnerable to COVID-19 disease.