COVID-19 and Population Density

The article explores various methodologies of estimating the relation between population density and COVID-19 cases to suggest that deaths per million may not be a sound indicator as a guide to public policy. It also infers that population density alone may not suffice to explain the spread of the virus. Social and living conditions could play a more dominant role in explaining the spread.

The author would like to thank Ravi Duggal for references to relevant studies.

The data is clear that most COVID-19 infections and deaths are clustered in cities. Awasthi and Mavlankar (2020) estimated that 50.8% cases, and 53.2% of deaths of COVID-19 are concentrated in only five cities of India—Mumbai, Delhi, Ahmedabad, Chennai, and Thane—that constitute merely 4.4% of the Indian population.

This has naturally led to an interest in the relationship of the spread of COVID-19 infections with urban density. However, in doing so, many analysts are resorting to deaths per million (DPM) as the relevant indictor to be plotted against population density. For example, according to Awasthi and Malvankar (2020), “death per million population is a good indicator to measure health system response, containment measures and overall management of COVID-19.” Using this indicator, they inferred that DPM in 10 out of the 20 districts, with the highest concentration of infections and mortality, is greater than the national average of 3.4, while in megacities like Ahmedabad (87 DPM) and Mumbai (85 DPM), this is more than 25 times of the national average. Hence, this “may reflect that few cities have COVID-19 burden completely different from rest of the country” (Awasthi and Malyankar 2020).