Background: Across the world, the COVID-19 pandemic has disproportionately affected economically disadvantaged groups. This differential impact has numerous possible explanations, each with significantly different policy implications. We examine, for the first time in a low- or middle-income country, which mechanisms best explain the disproportionate impact of the virus on the poor.
Methods: We use primary data from the CoVIDA project, including the results of 59,770 RT-PCR tests in Bogotá, targeted on a mostly asymptomatic adult population June 2020 to March 3rd, 2021. This is combined with administrative data that covers all reported cases in Bogotá. We estimate a number of parameters that are likely to drive inequality in COVID-19 infection rates across socioeconomic groups, then use these estimates in an individual-level branching process model of the epidemic. We use counterfactual scenarios to estimate the relative importance of different channels for explaining inequality in infection rates.
Findings: Total infections and inequalities in infections are largely driven by inequalities in the ability to work remotely and in within-home secondary attack rates. Inequalities in isolation behavior are less important but non-negligible, while access to testing and contract-tracing plays practically no role. Interventions that mitigate transmission are found to be more effective when targeted on socioeconomically disadvantaged groups.
Interpretation: Socioeconomically disadvantaged groups are particularly vulnerable to COVID-19 infections, and this appears to be primarily driven by the need to work out of home, higher transmission within home, and to some extent, the ability to isolate when needed. Policies that can successfully reduce these channels of transmission among the poor are likely to have large benefits.