Spread of Covid-19 in urban neighbourhoods and slums of the developing world
Anand Sahasranaman, Henrik Jeldtoft Jensen

TL;DR
This study analyzes Covid-19 spread in developing world urban neighborhoods, revealing high concentration in slums, and introduces a stochastic network model that reproduces empirical patterns, highlighting slums as critical hotspots for outbreaks.
Contribution
The paper provides empirical evidence of inequality in Covid-19 distribution across neighborhoods and develops a stochastic model to simulate epidemic spread in slum and non-slum areas.
Findings
Slums contain the highest density of Covid-19 cases.
A small number of neighborhoods account for most cases (~70%).
Epidemic severity is greater in slums, with worse peak and total cases.
Abstract
We study the spread of Covid-19 across neighbourhoods of cities in the developing world and find that small numbers of neighbourhoods account for a majority of cases (k-index~0.7). We also find that the countrywide distribution of cases across states/provinces in these nations also displays similar inequality, indicating self-similarity across scales. Neighbourhoods with slums are found to contain the highest density of cases across all cities under consideration, revealing that slums constitute the most at-risk urban locations in this epidemic. We present a stochastic network model to study the spread of a respiratory epidemic through physically proximate and accidental daily human contacts in a city, and simulate outcomes for a city with two kinds of neighbourhoods - slum and non-slum. The model reproduces observed empirical outcomes for a broad set of parameter values - reflecting…
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