000			01664nam a22001577a 4500
999			_c519225 _d519225
008			220215b ||||| |||| 00| 0 eng d
100			_aChundeli, Faiz Ahmed et al _932271
245			_aPopulation density and Covid spatial dynamics: A critical assessment of Indian districts
260			_aIndian Journal of Public Administration
300			_a67(3), Sep, 2021: p.425-439
520			_aIn this article, a critical assessment of urban density and Covid-19 incidences in Indian cities is explored. The top hundred Covid-19 reported districts are analysed. The ArcGIS 10.1 statistical tool Getis-Ord Gi* is used in the identification of statistically significant Covid-19 clusters across India. Attempts are made to empirically establish the correlation between the urban density, the number of reported cases, and their possible impact on health infrastructure in general and planning in specific. Based on the results from 164 out of 693 district datasets, analyses have shown high positive spatial autocorrelation, which is more than 24% of the districts analysed. Further, the results show that southern districts are more affected than the Central and northern districts of India. Although a positive association between reported cases and the urban density was found, in high-density urban areas, the relationship with infection rate varied, which should be looked at together with other variables such as people’s activities and behaviours. –Reproduced
650			_aPopulation density, Geospatial analysis, City planning, GIS. _929906
773			_aIndian Journal of Public Administration
906			_aCOVID-19 (DISEASE) – INDIA
942			_cAR