A Predictive Model of the Effects of Sustained Community Transmission of SARS-CoV-2 Infection Across the Countries of the WHO African Region

Background: The spread of SARS-CoV-2 has been unprecedented in its speed and effects, within and beyond health. It is driven by unique, country-specific socio-ecological factors, with different times and rates of impact. Predictive models have been designed to help countries focusing on different aspects of its patho-aetiology, with few attempting to provide medium-term comprehensive planning information for governments. In the African context, such planning is crucial given the limited resources countries have, compounded by the stress on the weak health systems. The differentiated start of the pandemic in the region has given it time to better understand how it spreads and affects people, allowing more efficient targeting of country resources. Response actions are not being uniformly and consistently applied, as there is absence of evidence on the impact this will have on countries of the region if it is not controlled. This model quantifies this impact for each country, quantifying the situation current interventions are aiming to avoid. Methods: A statistical model is used to derive transition states and their probabilities of occurring during sustained community transmission of SARS-COV-2 in a country. This was built around a stochastic Markov chain model parameterised to the COVID-19 outbreak, with ten (10) transition states representing where any member of a population could exist at a given time. Each of these Markov states is associated with probabilities of transitioning to the next allowable state. A country specific Risk of Exposure is calculated as the probability of being exposed, from which an attack rate is determined as the probability of an exposed person getting infected. Five probabilities are possible for infected persons, with a probability of each applied. Death and recovery represent the final states, with the probability of each adjusted for age, pre-existing disease burden for each country. These probabilities are based on current available knowledge, adjusted for country specificities. Findings: The overall risk of exposure in the region of 0.078 (7.8%) means in a situation of sustained community transmission, the sum of events by countries shows 150 million persons would be infected within the first year. Of these, 137,231 would have severe/critical infections and there would be 44,140 total deaths. There would be 88,227 additional hospital admissions and need for additional 5,184 ventilation capacity placing significant pressure on the health systems. Current low system resilience – the ability to absorb such shocks – means most health systems would be overwhelmed quite quickly. This is most critical in countries with high risk of exposure, but low resilience. Small and highly dense countries have higher risks of exposure – and so most of their populations are exposed – while many of the low-income countries have poor system resilience. Interpretation: The effects of sustained community transmission would go beyond the cases and deaths seen and the resources needed to respond to these but would also cripple many of the health systems due to health workers falling ill / being quarantined plus have wider social, economic and political effects. It is crucial for countries to avoid a scenario of sustained community transmission of the SARS-CoV-2 therefore. The effect of breaking community transmission, in terms of lives saved, admissions avoided, and the social economic benefits are significant, and most likely outweigh any costs of preventing this scenario. The effectiveness of distancing measures, and better hygiene practices need to be advocated for in all Countries as the most effective approach to managing the COVID-19 pandemic. Funding Statement: None. Declaration of Interests: None.