SARS-CoV-2 Seroprevalence in three Kenyan Health and Demographic Surveillance Sites, December 2020-May 2021

Abstract

Importance Most of the studies that have informed the public health response to the COVID-19 pandemic in Kenya have relied on samples that are not representative of the general population. Objective To determine the cumulative incidence of infection with SARS-CoV-2, from a randomly selected sample of individuals normally resident at three Health and Demographic Surveillance Systems (HDSSs) in Kenya. Design This was a cross-sectional population-based serosurvey conducted at Kilifi HDSS, Nairobi Urban HDSS, and Manyatta HDSS in Kenya. We selected age-stratified samples at HDSSs in Kilifi, Kisumu and Nairobi, in Kenya. Blood samples were collected from participants between 01 Dec 2020 and 27 May 2021. Setting Kilifi HDSS comprises a predominantly rural population, Manyatta HDSS comprises a predominantly semi-urban population, while Nairobi Urban HDSS comprises an urban population. The total population under regular surveillance at the three sites is ~470,000. Exposure We tested for IgG antibodies to SARS-CoV-2 spike protein using ELISA. Locally validated assay sensitivity and specificity were 93% (95% CI 88-96%) and 99% (95% CI 98-99.5%), respectively. Main Outcome and Measures The primary outcome measure was cumulative incidence of infection with SARS-COV-2 virus as evidenced by seropositivity to SARS-CoV-2 whole spike protein. We adjusted our estimates using classical methods and Bayesian modelling to account for assay performance. We performed multivariable logistic regression to test associations between seropositivity and age category, time period and sex. Results We recruited 2,559 individuals from the three HDSS sites, median age (IQR) 27years (10-78) and 52% were female. Seroprevalence at all three sites rose steadily during the study period. In Kilifi, Kisumu and Nairobi, seroprevalences at the beginning of the study were 14.5 % (9.1-21), 36.0 (28.2-44.4) and 32.4 % (23.1-42.4) respectively; at the end they were 27.6 % (21.4-33.9), 42.0 % (34.7-50.0) and 50.2 % (39.7-61.1), respectively. In multivariable logistic regression models that adjusted for sex and period of sample collections, age category was strongly associated with seroprevalence (p<0.001), with the highest seroprevalences being observed in the 35-44 and ≥65 year age categories. Conclusion There has been substantial unobserved transmission of SARS-CoV-2 in the general population in Kenya. There is wide variation in cumulative incidence by location and age category.

Impact of the COVID-19 epidemic on mortality in rural coastal Kenya

“…We have analyzed hospital admissions, community deaths and the seroprevalence of SARS-CoV-2 19 within a single large HDSS population in rural Kenya during the first 18 months of the COVID-19 pandemic. Despite two waves of COVID-19 wild-type infections over 11 months and serological evidence indicating SARS-CoV-2 infection in 25.1% of adults and 14.5% of children in the same population, we were unable to identify any signal of increased hospital utilization, either for pneumonia or all other diagnoses combined, in the principal public hospital serving this population.…”

“…The cumulative incidence of SARS-CoV-2 was derived from a serosurvey of a random sample of 850 KHDSS residents between 1 st December 2020 and 28 th April 2021 (median sample date 17 th Feb 2021). The serosurvey sampled 100 individuals in each 5-year age stratum from 0-14 years, 50 individuals in each 5-year age stratum between 15-64 years and 50 individuals aged 65 or greater 19 . We compared deaths predicted by this calculation with the total number of excess deaths observed in all KHDSS residents aged 1 year or more between 1 st April 2020 and 17 th February 2021.…”

“…In a random population survey in the KHDSS between December 2020 and April 2021, 14.5% of children (0-15 years) and 25.1% of adults (≥16 years) were anti-SARS-Cov-2 IgG positive, suggesting widespread transmission by early 2021 19 . We examine mortality trends up to 23 rd September 2021 and investigate the impact of the pandemic on morbidity using a hospital surveillance system linked to the KHDSS.…”

Epidemiological impact and cost-effectiveness analysis of COVID-19 vaccination in Kenya

“…Cross-sectional serological surveys of (a) donor samples from the Kenyan National Blood and Transfusion Service (KNBTS)[10] and (b) demographic surveillance systems (between 1 st January 2021 and 27 th May 2021). [11]…”

“…• Cross-sectional serological surveys of (a) donor samples from the Kenyan National Blood and Transfusion Service (KNBTS) [10] and (b) demographic surveillance systems (between 1 st January 2021 and 27 th May 2021). [11] We used a Bayesian hierarchical inference approach aimed at allowing inference on reporting fraction in counties with higher numbers of serological tests to influence inference of reporting fraction in counties with lower numbers of serological tests (see supplementary information for details on underlying data for age-specific effects and details on inference methodology).…”