Corresponding Author: Matthew Bonds
Summary provided by Michelle Evans
In the early months of the global COVID-19 pandemic, models predicted that countries in Sub-saharan Africa (SSA) would experience some of the highest burdens of COVID-19. It was expected that the same drivers of other infectious diseases (e.g. socio-economic conditions, lack of water and sanitation infrastructure, and weak health systems) would mean disaster for COVID-19 epidemics. However, by May 2020, this was clearly not the case; Madagascar had had less than 200 cumulative cases by this date. Together with colleagues from Madagascar and France, we used a simple model with age-structured contact and severity rates to explore what scenarios could explain the lower-than-expected cases in Madagascar. Could it be due to low testing rates, early and efficient implementation of non-pharmaceutical interventions, differences in the epidemiology of the disease, or a combination of all three?
There was strong evidence for the first two hypotheses. Access to healthcare in Madagascar is one of the lowest in the world (Global Burden of Disease 2018) and national testing rates for SARS-CoV-2 were low. Madagascar’s government implemented strict mobility and public health measures within three days after the first imported COVID-19 case, compared to the UK, which instituted its first partial-lockdown 52 days after its first case, or the US, which has yet to institute national restrictions. In contrast, there is little evidence for a difference in COVID epidemiology in SSA countries due to climate or trained immunity. Our simple model, combined with strong anecdotal evidence, illustrates that the lower-than-expected cases can be explained by a combination of low testing rates and the successful implementation of NPIs.
Now, several months later, there is further evidence that the epidemics in Madagascar and SSA will proceed differently than in other regions, likely due in part to NPIs and the high heterogeneity in connectivity throughout the country. Together, these may result in a much smaller epidemic peak than expected, with a longer tail sustained by asynchronous local outbreaks in less connected regions of the country. Initial expectations were grounded in commonly held deficit narratives about public health in SSA countries. As these countries successfully control their epidemics, it is time to shift the foreign gaze common in epidemiological modeling to one that recognizes countries’ abilities to control this global health crisis and includes the diverse contexts in which epidemics are unfolding.
(2020) Reconciling model predictions with low reported cases of COVID-19 in Sub-Saharan Africa: insights from Madagascar, Global Health Action, 13:1,
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