01783nam a22001697a 4500999001900000008004100019100003900060245009300099260004500192300003200237520108000269650007201349773004501421906003301466942000701499952010701506  c519225d519225220215b           ||||| |||| 00| 0 eng d  aChundeli, Faiz Ahmed et al 932271  aPopulation density and Covid spatial dynamics: A critical assessment of Indian districts  aIndian Journal of Public Administration   a67(3), Sep, 2021: p.425-439  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   aPopulation density, Geospatial analysis, City planning, GIS.929906  aIndian Journal of Public Administration   aCOVID-19 (DISEASE) – INDIA  cAR  00102ddc40709393276aIIPAbIIPAd2022-02-15h67(3), Sep, 2021: p.425-439pAR126257r2022-02-15yAR