Spatial risk assessment of an emerging pandemic under data scarcity: A case of COVID-19 in Eswatini

Abstract

Coronavirus (COVID-19) has rapidly spread across many countries in pandemic proportions since the first case was reported in Hubei, China in December 2019. Understanding transmission, susceptibility and exposure risks is crucial for surveillance, control and response to the disease. Knowing the geographic distribution of health resource scarcity areas is necessary if a country is to adequately anticipate and prepare for the full impact of infections. We explored the potential to undertake a spatial risk assessment of an emerging pandemic under data scarcity in Eswatini. We used a set of socio-economic and demographic variables to identify epidemic risk prone areas in the country. Three risk zone levels for COVID-19 were identified in the country. The analysis showed that about 29% (320 818) of the population were located in the high risk zone and these were people who could potentially be infected with COVID-19 in the absence of mitigation measures. A majority of cases and deaths attributed to COVID-19 would likely remain unknown but our estimate could be used to gauge the full burden of the disease. Approximating and quantifying the number of people who may be potentially infected with COVID-19 remains impossible under data scarcity and limited healthcare capacity especially in sub-Saharan Africa. We provided an estimation method that could support the pandemic risk forecasting, preparedness and response measures in the midst of data scarcity. The resultant map products could be used to guide on-the-ground surveillance and response efforts.

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