High SARS-CoV-2 IgG/IGM seroprevalence in asymptomatic Congolese in Brazzaville, the Republic of Congo

Abstract

Introduction: The Republic of the Congo detected its first case of coronavirus disease 2019 (COVID-19) on March 14, 2020, and within several weeks, the country had introduced protective measures that were still in force in July 2020. Over the course of time, the progression in the number of clinical cases has appeared to be lower than expected, although reverse transcription polymerase chain reaction (RT-PCR) testing has been somewhat limited. In order to evaluate the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within the Congolese population, a seroprevalence study was conducted on healthy individuals from different districts of Brazzaville who were willing to know their COVID-19 infection status. Methods: Oropharyngeal swab and blood samples were collected from 754 healthy volunteers between April 2020 and July 2020. The samples were analyzed for SARS-CoV-2 using a qualitative RT-PCR assay, and Immunoglobulin G (IgG) and Immunoglobulin M (IgM) antibodies were detected using two different rapid tests. Results: A total of 56 participants (7.4%) tested positive for SARS-CoV-2. The remaining 698 participants (92.6%) had negative RT-PCR results; of these, 117 were found to have anti-SARS-CoV-2 antibodies using serological tests. For these RT-PCR-negative subjects, the seroprevalence of IgG and IgM was found to increase over time: from 1.7% and 2.5% in April, up to 14.2% and 17.6% in July, respectively. In April 2020, 5% of the women were found to have IgG or IgM antibodies, whereas the antibodies were not detected in any of the men. The seroprevalence in RT-PCR negative subjects was significantly higher in women within IgG (P = 0.012) and IgM (P = 0.045) over the first three months. Conclusion: The proportion of the population who seroconvert over the course of the first wave is an important data to predict the risk of future COVID-19 waves and this will facilitate the efficient use of limited resources in a low income country like the Republic of the Congo.

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 …”

“…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 one study recruited drivers and their assistants, 26 while the other one recruited gold miners. 30 All studies were conducted in the period between April 2020 and April 2021 except one study by Olayanju et al.…”

Determinants of having severe acute respiratory syndrome coronavirus 2 neutralizing antibodies in Egypt

“…In a serosurvey conducted in Brazzaville, Congo, in the period April-July 2020, anti-SARS-CoV-2 antibodies were detected in 15% of the sampled adults. 13 In Guilan region of Iran, 22% of study participants enrolled in April 2020 had antibodies. 14 A larger national study in Iran conducted between April and June 2020 reported a 17% seroprevalence rate.…”

Regional comparisons of COVID reporting rates, burden, and mortality age-structure using auxiliary data sources

“…National case rates were obtained from Our World in Data (16). Sub-national case rates were calculated from sub-national reported case counts and population data (14,15,19,(23)(24)(25)(26)(27)(28)(29)(30)(31).…”

“…Because serostudy data in AFRO are sparse, both national estimates and sub-national estimates were included (14,(18)(19)(20)(21)(22). National case rates were obtained from Our World in Data (16).…”