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?:abstract
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Due to the outbreak of Coronavirus, humans all over the world are facing several health problems. The present study has explored the spatio‐temporal pattern of Coronavirus spread in India including spatial clustering, identification of hotspot, spatial heterogeneity, and homogeneity, spatial trend, and direction of COVID‐19 cases using spatial statistical analysis during the period of 30th January to 20 June 2020. Besides, the polynomial regression model has been used for predictions of COVID‐19 affected population and related deaths. The study found positive spatial heterogeneity in COVID‐19 cases in India. The study has also identified seventeen epicentres across the country with high incidence rates. The directional distribution of ellipse polygon shows that the spread of COVID‐19 now trending towards the east but the concentration of cases is mainly in the western part of the country. The country\'s trend of COVID‐19 follows a fourth‐order polynomial growth and is characterized by an increasing trend. The prediction results show that as on 14(th) October India will reach 14,660,400 COVID‐19 cases and the death toll will cross 152,945. Therefore, a ‘space‐specific’ policy strategy would be a more suitable strategy for reducing the spatial spread of the virus in India. Moreover, the study has broadly found out seven sectors, where Govt. of India lacks in terms of confronting the ongoing pandemic. The study has also recommended some appropriate policies which would be immensely useful for the administration to initiate strategic planning.
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