New Index: A Young Population Has Been Africa’s Best Defense Against COVID-19 Deaths So Far, But Several Regions Are Dangerously Vulnerable Africa COVID-19 Community Vulnerability Index shows the 10 most vulnerable regions in Africa are found in six countries: Democratic Republic of Congo, Malawi, Ethiopia, Uganda, Cameroon, and Madagascar A new index designed to fill a critical information gap and help African governments, health officials, non-governmental organizations, and others respond to the coronavirus pandemic finds that although Africa has not yet been overwhelmed by COVID-19, several regions are showing troubling signs of vulnerability to the social, economic, and health impacts of an outbreak that should not be ignored.
The Africa COVID-19 Community Vulnerability Index (CCVI), developed by Surgo Foundation, was modeled after Surgo’s U.
COVID-19 Community Vulnerability Index, which is featured as a resource by the U.
Centers for Disease Control and Prevention.
It is the first Pan-African index to assess vulnerability to COVID-19 not just across, but within countries.
“By showing us the different ways African regions can be vulnerable to COVID-19 beyond just mortality, this index gives us predictive power we’ve never had before,” said Dr.
Sema Sgaier, executive director of Surgo Foundation.
“While it does not predict which regions are at risk of having outbreaks, it does predict whether a region in Africa is able to mitigate the health, economic, and social impacts of COVID-19 and what downstream consequences each region should plan for.
” The Africa CCVI ranks 751 regions across 48 African countries in terms of vulnerability to COVID-19 based on seven key themes: socioeconomic status, population density, access to transportation and housing, epidemiological factors, health system factors, fragility, and age of population.
It is the only index to measure vulnerability to COVID-19 across the African continent at a subnational level.
“The Africa COVID-19 Community Vulnerability Index fills an information gap that has challenged the global development community for too long,” said Magdalena Banasiak, Senior Innovation Adviser at DFID, who manages the COVIDAction programme, which co-funded the index.
“Until now, limited COVID-19 data in Africa has not provided a true reflection of where this pandemic could have the greatest impact--partly due to low scale-up of testing, and partly due to incomplete reporting.
Now we can better understand and prioritise pandemic response efforts not just across, but within African countries.
” Key Findings 1) Africa’s relatively young population is so far proving to be its best defense against COVID-19 deaths.
Regions with low age-related vulnerability--Nairobi, Mandera, and Kajiado in Kenya, or Lusaka in Zambia--will fare better in terms of COVID-19 hospitalizations, people needing critical care, and fatality rates.
Limited health systems in poor African countries like Mozambique and Mali are in part offset by their younger populations, which have several times lower projected hospitalization rates compared to rich countries like South Africa and Egypt.
These wealthier countries in North and South Africa have older populations, which are far more vulnerable to hospitalizations and poor COVID-19 outcomes.
Projected infection fatality rate (IFR) based on the age and gender distribution in the continent is relatively low in most regions of Africa--between 0.
10% and 0.
This is four times lower than in the US, where a greater proportion of the population is old (fatality rate of 0.
2) Vulnerability to COVID-19 is not distributed evenly across the continent, with drivers of vulnerability varying by region.
The Top 10 most vulnerable regions across Africa are found across six countries: Democratic Republic of Congo (with four of the most vulnerable regions), Malawi (with two of the most vulnerable regions), Ethiopia, Uganda, Cameroon, and Madagascar.
Some countries have similar levels of vulnerability, but for different reasons.
For example, in South Africa there is widespread vulnerability due to epidemiological risk factors and fragility, but the primary driver of vulnerability in Chad is socioeconomic factors, while the primary driver of vulnerability in Cameroon is fragility.
There are many regions with similar levels of vulnerability within a country, like Sahel and Sud-Ouest in Burkina Faso, where different underlying reasons account for that vulnerability.
Sahel’s vulnerability derives from its position as the epicenter of humanitarian violence in the country, while Sud-Ouest contains the greatest percentage of Burkina Faso’s elderly population.
3) Many kinds of vulnerability co-exist within regions, and seem to be correlated to some extent: Many regions that experience vulnerability due to socioeconomic factors are also experiencing vulnerability due to the strength of their health systems and the quality of their housing.
This is the case in the Somalia region of Ethiopia, Tahoua region of Niger, and Manyara region of Tanzania.
Regions with high socioeconomic vulnerability tend to have low vulnerability in terms of population density and epidemiological factors, as is the case with the Thaba-Tseka region of Lesotho or the Alibori region of Benin.
High epidemiological vulnerability tends to mean low vulnerability due to age, as is the case in the Abidjan region of Côte d'Ivoire or the Lilongwe region of Malawi, where many people die before reaching old age.
4) Mobility has by and large decreased across the continent over the last few months, but the most vulnerable areas are the least likely to practice social distancing.
Across 16 countries in Africa with available mobility data, there was an overall reduction in mobility of ~12.
2% since mid-February relative to pre-COVID-19 movement, which is encouraging for virus control.
People in more vulnerable regions such as Yobe, Zamfara, and Bauchi, Nigeria have not been social distancing as much as their counterparts in less vulnerable regions such as Lagos, Federal Capital Territory, and Osun, Nigeria--which increases their probability for infection and compounds those regions’ challenges in fending off the virus.
On average, the more vulnerable a region is due to health system factors, the less social distancing they are doing (even though poor health systems especially need a “flattening of the curve” through social distancing).
This is the case in regions like Al Wadi al Jadid, Egypt, Kavango, Namibia, and Mara, Tanzania.
On average, the more vulnerable an area is due to population density and epidemiological factors, the more social distancing they are doing--as is the case in regions like Dakar, Senegal and Western Cape, South Africa.
To explore the index and learn more, visit precisionforcovid.
The Africa CCVI is made possible in part through support by the #COVIDAction Data Challenge, via an award from the UKAID Department for International Development (DFID)’s Frontier Technologies Hub.
Technical Notes: Countries excluded due to lack of data: Cape Verde, Equatorial Guinea, Guinea-Bissau, Mauritius, Mayotte (France), Réunion (France), São Tomé and Príncipe, Seychelles, and Western Sahara.
Data Sources: Demographic and Health (DHS) Surveys, Institutes of Health Metric and Evaluation (IHME), Malaria Atlas Project, Uppsala Conflict Data Program, UNHCR, World Bank, Open data for Africa, Multiple Indicator Cluster Surveys (MICS), Armed Conflict Location & Event Data Project (ACLED), Global Roads Inventory Project, World Pop, and Global Data Lab.
Mobility data are from Google.
Fatality and hospitalization rates are from Salje et al.
(2020) in Science and kindly provided by Dr Mumtaz and Prof.
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About COVIDaction COVIDaction is a partnership between DFID’s Frontier Technology Hub, Global Disability Innovation Hub (GDI Hub), and UCL’s Institute of Healthcare Engineering along with other collaborators, designed to explore these questions.
The partnership is working with a range of partners to build a technology and innovation pipeline to support action related to the COVID-19 pandemic across key thematic areas.
Together we plan to scan the globe for promising ideas, evaluate and make sense of what we find, support the very best ideas with grant funding and venture support and share what we learn along the way.
The partnership seeks to support ideas across data, local production and solutions, and resilient health systems.
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