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How COVID-19 affects African population



EARLY predictions of the impact of the COVID-19 pandemic by some public health scientists painted a gloomy picture for Africa. The continent was expected to suffer a huge burden of disease and death. These predictions have not held true. The continent has experienced fewer deaths than predicted.

  In addition, it has been much less affected than many other parts of the world. For example, the total number of recorded deaths in the entire African continent is slightly less than those recorded in the UK alone. Even when under-reporting is accounted for, the mortality rate has been lower than in western Europe.

  There are several reasons why predictions of COVID-19 ravaging African countries were wrong – but two stand out. The first is limited scientific knowledge of how the virus behaves in different populations and environments. The second is an underestimation of Africa’s ability to respond to the pandemic.

  Despite having comparatively poor health infrastructure, African public health practitioners have amassed a wealth of experience of managing epidemics. The 2014-16 Ebola outbreak in west Africa showed local doctors using mitigation strategies available to them and the strong community based healthcare system.

  By September 2020, it was clear that the pandemic was following a different path on the continent than was predicted. This underscored the need for African countries to learn lessons for Africa from data collected from Africa.

  To do this, my colleagues and I at the National Institute for Health Research Global Health Unit Tackling Infections to Benefit Africa worked with partners at the Universities of Ghana and Edinburgh, as well as the World Health Organisation (WHO) regional office for Africa, to analyse data collected from member states.

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  We determined the factors that influenced the timing of the first COVID-19 cases as well as the number of COVID-19 deaths in the WHO’s African member states during the first and second pandemic waves.

  We also looked for associations between the preparedness of health systems and government pandemic responses.

  We found that countries with more urban populations detected their first cases of COVID-19 earlier than those with higher rural populations. Countries with high HIV prevalence reported the most COVID-19-related deaths. And countries with the most advanced health systems fared the worst in terms of COVID-19 cases and deaths.

  Our findings helped us to understand Africa’s epidemic and provided lessons for future pandemics.

  In our recent research we investigated factors that could potentially influence the spread and severity of the COVID-19 pandemic based on the knowledge of the virus’s transmission factors and potential risk factors. We tested the effect of 15 such factors.

  We found that the first case was detected earlier in countries with more urban populations, higher international connectivity and greater COVID-19 test capacity, but later in island nations. This finding is not surprising, given what we know about the transmission of the virus indoors, the introduction of SARS-CoV-2 into Africa from Europe and the importance of surveillance and testing.

  Egypt was the first of 47 African countries to report a case in February 2020. Most countries had recorded cases by late March 2020, with Lesotho being the last to report one, on 14 May 2020.

  Countries with high rates of HIV were also more likely to have higher mortality rates. This was also not surprising as people with HIV often have other health conditions that put them at greater risk from COVID-19.

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  Among 44 countries of the WHO African Region with available data, South Africa had the highest mortality rate during the first wave between May and August 2020, at 33.3 deaths recorded per 100,000 people. Cape Verde and Eswatini had the next highest rates at 17.5 and 8.6 deaths per 100,000 respectively. At 0.26 deaths recorded per 100,000, the lowest mortality rate was in Uganda.

  True numbers of deaths in Africa are thought to be over three times higher than officially reported, slightly higher than the global average, but even accounting for this, our findings are still valid.

  Our most important finding was that seemingly well-prepared, resilient countries such as South Africa have fared worst during the pandemic. This is not only true in Africa; the result is consistent with a global trend that more developed countries have often been particularly hard hit by COVID-19. This tells us that lack of preparedness and vulnerability are not the same thing.

  While health systems may have been less prepared for the pandemic, other factors such as demography and rural populations made the African population less vulnerable. We are also currently investigating the potential protective role of previous exposure to other pathogens that may induce COVID-19 protective cross-immunity or modify the immune phenotype and thus, disease progression and prognosis.

  Our analysis indicates the critical importance of using context-appropriate data in models to make predictions that guide control or mitigation policy. This would inform context-relevant interventions. The director of the WHO’s regional office for Africa, Matshidiso Moeti, remarked:

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  The study also highlighted unanticipated vulnerabilities. For example countries with strong health systems could still be vulnerable to pandemics. Therefore, assessing the impact of potential threats and future pandemic preparedness planning must be informed by the transmission dynamics and local risk factors for infection and disease.

  It is clear that other factors unique to Africa such as a younger population and less urbanisation have contributed to the comparatively lower COVID-19 cases and deaths on the continent. Moeti reiterated these when she said:

  Going forward, African researchers and governments need to do three things.

  First, African scientists must conduct more Africa-led analyses of Africa’s COVID-19 epidemic at national and continental level.   These analyses should include studies of the impact of Africa’s socio-ecological setting and the structure of the health delivery system, which is heavily community based.

  Second, we need to use these results to identify uniquely African strengths and vulnerabilities to emerging and epidemic disease to inform preparedness planning and ensure that epidemic preparedness indices such as the Global Health Security Index take these into account.

  Third, we need to accelerate open data sharing to ensure timely access to data to inform data-driven innovations and interventions.

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