Areal Interpolation Approach for Covid -19 Cases in India: A Case of Geospatial Modelling

Abstract

Covid-19 ever since its attack on human has left no trace of breaking the chain in this World. India started its first Covid- 19 case in March first week and the positive cases has raised to a count of 380532. In this study, Areal Interpolation approach is performed to analysis the distribution of the confirmed cases. For this analysis, the dataset has been obtained from the Ministry of Health and Family Welfare Government of India. The aim of the paper is to analyze the spatial distribution and prediction using the cases as on March 15, April 12, May 12, and June 19, 2020. The results of the models obtained for the confirmed cases on March 15 (Model: 19.786 Spherical(30.018)); April 12 (Model: 118170 Spherical(30.018)), May 12 (Model : 1.475e7 Spherical(30.018)) and June 19, 2020 (Model: 2.4625e8 Spherical(30.018)). The highlight of this study is the state district wise spatial distribution in four states and their respective daywise increase of confirm cases graphs.