Demography, social contact patterns and the COVID-19 burden in different settings of Ethiopia: a modeling study

ABSTRACT

BackgroundCOVID-19 spread may have a dramatic impact in countries with vulnerable economies and limited availability of, and access to, healthcare resources and infrastructures. However, in sub-Saharan Africa a low prevalence and mortality have been observed so far. MethodsWe collected data on individuals social contacts in Ethiopia across geographical contexts characterized by heterogeneous population density, work and travel opportunities, and access to primary care. We assessed how socio-demographic factors and observed mixing patterns can influence the COVID-19 disease burden, by simulating SARS-CoV-2 transmission in remote settlements, rural villages, and urban neighborhoods, under the current school closure mandate. ResultsFrom national surveillance data, we estimated a net reproduction number of 1.62 (95%CI 1.55-1.70). We found that, at the end of an epidemic mitigated by school closure alone, 10-15% of the overall population would have been symptomatic and 0.3-0.4% of the population would require mechanical ventilation and/or possibly result in a fatal outcome. Higher infection attack rates are expected in more urbanized areas, but the highest incidence of critical disease is expected in remote subsistence farming settlements. ConclusionsThe relatively low burden of COVID-19 in Ethiopia can be explained by the estimated mixing patterns, underlying demography and the enacted school closures. Socio-demographic factors can also determine marked heterogeneities across different geographical contexts within the same country. Our findings can contribute to understand why sub-Saharan Africa is experiencing a relatively lower attack rate of severe cases compared to high income countries.