SARS-CoV-2 Antibody Seroprevalence and Associated Risk Factors in an Urban District in Cameroon

Abstract

The extent of SARS-CoV-2 circulation in many African countries remains unclear, underlining the need for antibody sero-surveys to assess the cumulative attack rate. Here, we present the results of a cross-sectional sero-survey of a random sample of residents of a health district in Yaoundé, Cameroon, conducted from October 14 to November 26, 2020. Among the 971 participants, the test-adjusted seroprevalence of anti-SARS-CoV-2 IgG antibodies was 29•2% (95%CI 24•3-34•1). This is about 323 times greater than the 0.09% nationwide attack rate implied by COVID-19 case counts at the time. Men, obese individuals and those living in large households were significantly more likely to be seropositive, and the majority (64•2% [58•7-69•4]) of seropositive individuals reported no symptoms. Despite the high seroprevalence, most of the population had not been infected with SARS-CoV-2, highlighting the importance of continued measures to control viral spread and quick vaccine deployment to protect the vulnerable.

Retrospective mortality and prevalence of SARS-CoV-2 antibodies in greater Omdurman, Sudan: a population–based cross–sectional survey

“…Various factors have been proposed to explain the overall low numbers of COVID-19 cases and deaths reported from African countries, supporting the assumption that Africa might be less affected by the pandemic. 6 However, our data contradicts this notion, with the overall seroprevalence detected for Omdurman being amongst the highest compared to all compiled studies listed on the SeroTracker from Arora et al 1 Furthermore, considering the high seroprevalences from South Sudan, Cameroon and Mali, [24][25][26] the officially reported case numbers in Africa seem to be highly underreported. For example, a study in Zambia showed a 100 times higher number cases compared to the officially reported cases.…”

“…9 Compared to global observed trends of higher seroprevalence in the working age population (18-64 years), 23 we found a different SARS-CoV-2 infection pattern with a gradual increase by age (appendix p 26) up to highest adjusted estimates (adjustment 2) among individuals aged ≥50 years (80.7%). Studies from the neighbouring country's capital Juba in South Sudan 24 and from Cameroon 25 showed a similar, but less pronounced increase by age. Closest to our findings, an overall seroprevalence of 58.5% was found in Mali, which was equally associated with age.…”

High SARS-CoV-2 seroprevalence among health care workers in Bamako referral hospitals: a prospective multisite cross-sectional study (ANRS COV11)

“…In this study, we report a high seroprevalence of 51.8% among HCW in Bamako referral hospitals. These results are notably higher to what has been observed among the general population in Democratic Republic of Congo and Cameroon (2,3), but are in line with a recent work revealing a SARS-CoV-2 exposure rate of around 58% among three Malian communities after the first wave (4). Anti-nucleocapsid antibodies allow an estimation of viral spread by seroprevalence in the context of spike-based vaccination but vanish within several months.…”

Seroprevalence of anti‐SARS‐CoV‐2 antibodies in Africa: A systematic review and meta‐analysis

“… 17 , 18 , 19 Two were conducted in each of the following countries: Republic of South Africa, 20 , 21 Ethiopia, 22 , 23 Libya 24 , 25 Kenya 26 and Democratic Republic of Congo (DRC). 27 One study was conducted in each of the following countries: Malawi, 28 Togo, 29 Ivory Coast, 30 Zambia, 31 Egypt, 32 Gabon, 33 Congo Brazaville, 34 South Sudan, 35 Cameroon 36 , 37 and Guinea Bissau. 38 …”

“…[17][18][19] Two were conducted in each of the following countries: Republic of South Africa, 20,21 Ethiopia, 22,23 Libya 24,25 Kenya 26 and Democratic Republic of Congo (DRC). 27 One study was conducted in each of the following countries: Malawi, 28 Togo, 29 Ivory Coast, 30 Zambia, 31 Egypt, 32 Gabon, 33 Congo Brazaville, 34 South Sudan, 35 Cameroon 36,37 and Guinea Bissau. 38 The study participants in 10 studies were recruited from the general population, 18,[22][23][24][31][32][33][34][35][36] four studies were from health workers, 17,27,28,38 one study combined health workers and community, 25 one study combined health workers, air transport, police and drivers, 29 three studies recruited blood donors, 19,20,39 one study recruited water front workers, 21 one study involved travelers, 40 -3 of 10 study recruited drivers and their assistants, 26 while the other one recruited gold miners.…”