key: cord-1040806-53prb4jy
authors: Soumah, Abou Aissata; Diallo, Mamadou Saliou Kalifa; Guichet, Emilande; Maman, David; Thaurignac, Guillaume; Keita, Alpha Kabinet; Bouillin, Julie; Diallo, Haby; Pelloquin, Raphael; Ayouba, Ahidjo; Kpamou, Cece; Peeters, Martine; Delaporte, Eric; Etard, Jean-Francois; Toure, Abdoulaye
title: High and rapid increase in seroprevalence for SARS-CoV-2 in Conakry, Guinea: results from three successive cross-sectional surveys (ANRS COV16-ARIACOV)
date: 2022-03-23
journal: Open Forum Infect Dis
DOI: 10.1093/ofid/ofac152
sha: 6eb3cc1bf8a4e571479b0367a6f037baa2418e87
doc_id: 1040806
cord_uid: 53prb4jy

We conducted three successive seroprevalence surveys, three months apart, using a multistage cluster sampling to measure the extent and dynamics of the SARS-CoV-2 epidemic in Conakry, the capital city of Guinea. Seroprevalence increased from 17.3% (95% CI: 12.4-23.8) in December 2020 during the first survey (S1) to 28.9% (95% CI: 25.6-32.4%) in March/April 2021 (S2) then to 42.4% (95% CI: 39.5-45.3%) in June 2021 (S3). This significant overall trend of increasing seroprevalence (p <0.0001) was also significant in every age class, illustrating a sustained transmission within the whole community. These data may contribute to defining cost-effective response strategies.

The first cases of COVID-19 were reported in late-December 2019 in Wuhan (China) and two years later, more than 280 million cases have been reported worldwide with almost 5.5 million deaths [1] . In Africa, as of January 21, 2021, approximately 8 million cases and 162,000 deaths have been reported [1] , representing less than 3% of cumulative cases and deaths worldwide making the African continent apparently the least affected in contrast to the bleak scenario initially predicted for Africa at the onset of the COVID-19 pandemic [2] .

Limited access to care and diagnostics, weak surveillance systems as well as a high proportion of the young population often associated with asymptomatic infections [3] may have masked the extent of the epidemic in Africa. Therefore, the World Health Organization (WHO) recommends to conduct repeated population seroprevalence surveys in order to measure the extent of the epidemic, to monitor its spread over time and to provide reasonable estimates of the cumulative incidence of infection to guide the public health response to COVID-19 [4] .

Seroprevalence studies around the world have established that a small proportion of the population had been infected by SARS-CoV-2 after the first epidemic wave in Spring 2020, with most seroprevalence estimates ranging from less than 0.1% to more than 20%, with a pooled estimate of 3.38% (95%CI 3.05-3.72%) in the general population [5] . Most of these studies have estimated infection levels several times higher than previously reported by surveillance systems based on confirmed cases [5] . In Africa, however, most seroprevalence surveys have focused on specific risk groups (such as health care workers, blood donors, etc.) rather than on the general population, and mostly with cross-sectional instead of repeated surveys that can better capture the dynamics of the epidemic [6] [7] [8] [9] [10] [11] [12] . Nevertheless, these studies showed that SARS-CoV-2 infections in Africa are much higher than observed by cases confirmed by PCR.

A c c e p t e d M a n u s c r i p t 5 In Guinea, the first SARS-CoV-2 infection was detected on March 12, 2020. As in many African countries, the capital city, Conakry, accounts for nearly 80% of reported COVID-19 cases in the country. In this study we evaluated the extent and dynamics of the COVID-19 epidemic and its dynamics in Conakry through three successive population-based surveys measuring the prevalence of IgG antibodies to SARS-CoV-2.

Based on the WHO population-based sero-epidemiological investigation protocol for COVID-19 [4] , three repeated cross-sectional household-based and age-stratified seroprevalence surveys were conducted in Conakry, Guinea just before ( 2 to 26 December 2020; first survey : S1), during the peak (19 March to 3 April, 2021 ; second survey : S2) and after the second wave of the COVID-19 epidemic ( 04 to 19 June, 2021 ; third survey : S3) (Supplementary Figure S1 ).

For each survey, a stratified two-stage random cluster sampling design was used to select households with a first stage probability to be selected proportional to the population number in each enumeration area. At the second stage, all residents above 40 years were invited to participate while residents under 40 years were invited to participate in half of the selected households. The samples for the three surveys were independent and representative of the general population of Conakry, stratified by age.

After consent, household and individual questionnaires were used to collect general demographic characteristics (sex, age, education, marital status, occupation), symptoms related to SARS-CoV-2 infection, previous testing and Covid-19 vaccination, other health-promoting behaviour and previous contact with a confirmed or probable COVID-19 patient. PCR testing was offered to all individuals A c c e p t e d M a n u s c r i p t 6 with suspicion of COVID-19 infection. All staff involved in the study were tested by PCR prior to the survey and followed infection prevention and control recommendations.

Blood samples were collected as dried blood spot (DBS) on a Whatman 903 filter paper. DBS were eluted and 100 μl of diluted eluate, adjusted at a final plasma dilution of 1/200, taken into account the hematocrit, was used to test for the presence of antibodies to SARS-CoV-2 with a previously developed, highly sensitive and specific Luminex-based assay (Luminex Corp, Austin, TX, USA) using recombinant nucleocapsid (NC) and spike (SP) SARS-CoV-2 proteins [13] . Samples were considered positive for SARS-CoV-2 IgG antibodies when they reacted simultaneously with NC and SP proteins, samples reacting with only one antigen were considered as "indeterminate" because this could be related either to antibody decline or lower specificity of single-antigen reaction especially on samples from Africa [14] . The test has been previously evaluated on a panel of 1197 samples from Africa before the COVID-19 pandemic from Guinea, Cameroun and the DRC, with 99.7% specificity [13] .

Socio-demographic characteristics were described as proportion or mean and were weighted to take into account the probability of selection from cluster sampling. For the calculation of seroprevalence 

A total of 596 individuals from 174 households were included in the first survey (S1), 1207 from 227 households in the second survey (S2) and 1082 from 193 households in the third survey S3 (Table1).

Of these, 535/596 (89.7%) participants of S1 were tested for anti-SARS-CoV-2 IgG antibodies, A c c e p t e d M a n u s c r i p t 8

The overall weighted and age-standardized SARS-CoV-2 IgG seroprevalence was 17.3% (95% CI: 12.4-23.8) in S1 (December 2020). Seroprevalence increased to 28.9% (95% CI: 25.6-32.4) in S2 three months later and to 42.4% (95% CI: 39.5-45.3) six months after S1 with a significant increase throughout the three surveys (p <0.0001) (Table1, Figure 1) Across the three consecutive surveys, seroprevalence increased significantly in each age category. In S2 and S3, seroprevalence differed significantly by marital status (p<0.0001), with highest prevalence observed in single individuals. Seroprevalence did not differ by sex and by reported symptoms in the three surveys.In general, whatever the socio-demographic characteristics considered, a significant increase in seroprevalence was observed between S1 and S3 (Table1). Among seropositive participants, 19/362 (5.2%) in S2 and 86/474 (18.1%) in S3 were vaccinated. The proportion of individuals with SP antibodies only was 17.9% in S1, 36.1% in S2 and 27.2% in S3, whereas the proportion of individuals with NC antibodies only was 6.6% in S1, 2.7% in S2 and 3.2% in S3) Tables S3 and S4 ).

These three consecutive cross-sectional surveys, showed that the proportion of the population in Conakry with antibodies to SARS-CoV-2 increased sharply from 17.3% to 42.4% between December 2020 and June 2021, just before and after the second wave of the COVID-19 epidemic, respectively. This 2.4-fold increase in seroprevalence over 6 months shows intense community transmission during the second wave and the increase concerns all age categories and all socio-demographic parameters studied. Like almost all previous studies in Africa [7] [8] [9] [10] 12] , we showed that seroprevalence is significantly associated with age but does not differ by sex and reported symptoms A c c e p t e d M a n u s c r i p t 9 associated with COVID-19. More precisely seroprevalence was constantly higher in individuals above 40 years similarly to studies in Kenya [7] and Sudan [8] which have shown that participants aged 50 years or more were among the most affected. A study using a similar population based approach in Kinshasa, DRC, showed also the same trend [10] .

An increase in seroprevalence after the second wave, has been reported in other African countries, for example in Mali [11] , Zimbabwe [12] and Kenya [7] . Our results also suggest that the virus has spread widely in the community during the second wave of COVID-19 wave in Conakry. Indeed, at the end of the third survey, the cumulative number of positive cases reported in Guinea was 23,543 but seroprevalence suggests that by June 2021, around 42% of the population of Conakry had already been in contact with the SARS-CoV-2 virus, which corresponds to at least 700,000 individuals on the total population of Conakry which is estimated to be around 1.7 million inhabitants. Similarly as in other reports from Africa, our data show thus clearly that the vast majority of cases went underreported, with only one case detected by the surveillance system, based on PCR confirmation, for 30 infections in the community based on serology. Interestingly, this infection-to-case ratio was the same at the end of S1 and S2 (respectively 30 and 33), implying that diagnostic capacities were maintained similar over time. Another estimation from a systematic review reported that the seroprevalence was on average 18.1 times (IQR 5.9 to 38.7) higher than the corresponding cumulative incidence of PCR-confirmed SARS-CoV-2 infection [15] . These results suggest that most of the SARS-CoV-2 infections were pauci-or asymptomatic, had limited access to diagnostic, and that serological surveys are the best way to monitor the true extent of the spread of the pandemic.

These repeated surveys have the advantage of having included a large number of people using a rigorous sampling methodology. Moreover, while many studies have used rapid diagnostic tests or A c c e p t e d M a n u s c r i p t 10 ELISA, this study used the same serological test throughout the three surveys with a strict interpretation criteria and therefore reported seroprevalences were likely to be underestimated. It cannot be excluded that some participants seroconverted during the survey and that the antibody profile was not complete yet to both antigens. On the other hand, presence of antibodies to a single antigen can also be due to waning of antibodies over time. Given the retrospective reporting of the COVID-19-related symptoms, a non-differential recall bias is likely, resulting in a dilution of the association between symptoms and seropositivity.

It is important to note that in S1 vaccination had not yet started, and had just started during S2.

Among seropositive participants, 5 % in S2 and 18% in S3 were vaccinated.

The vaccines deployed in Guinea were Sputnik or Sinopharm, and the majority received only the first dose. Although 12% of participants in S3 received at least the first vaccine dose part of the antibody responses can thus be due to the recent introduction of vaccines. Lastly, given the socio-political situation in December, 2020, several people refused to participate in S1 and certain enumeration areas could not be visited, which may have had an impact of the representativeness of S1, compared to S2 and S3.

Taken together, these population-based studies provide an estimation of the extension of the epidemic and its dynamics. This study in Guinea is, to our knowledge, the first that combined three successive population-based surveys, to evaluate the level of SARS-CoV-2 dissemination in the general population in a large sub-Saharan capital, illustrating a sustained community transmission.

These results also contribute to guide cost-effective public health responses to the COVID-19 epidemic . 

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We thank the study participants, the investigation teams, the community health staff, the logistical support of Guinea and the national institute of statistics of Guinea, the health D-department of Conakry, Caroline Coulon and René Ecochard.

A c c e p t e d M a n u s c r i p t