SARS-CoV-2 seroprevalence and implications for population immunity: Evidence from two Health and Demographic Surveillance System sites in Kenya, February-December 2022.

BACKGROUND: We sought to estimate SARS-CoV-2 antibody seroprevalence within representative samples of the Kenyan population during the third year of the COVID-19 pandemic and the second year of COVID-19 vaccine use. METHODS: We conducted cross-sectional serosurveys among randomly selected, age-stratified samples of Health and Demographic Surveillance System (HDSS) residents in Kilifi and Nairobi. Anti-spike (anti-S) immunoglobulin G (IgG) serostatus was measured using a validated in-house ELISA and antibody concentrations estimated with reference to the WHO International Standard for anti-SARS-CoV-2 immunoglobulin. RESULTS: HDSS residents were sampled in February-June 2022 (Kilifi HDSS N = 852; Nairobi Urban HDSS N = 851) and in August-December 2022 (N = 850 for both sites). Population-weighted coverage for ≥1 doses of COVID-19 vaccine were 11.1% (9.1-13.2%) among Kilifi HDSS residents by November 2022 and 34.2% (30.7-37.6%) among Nairobi Urban HDSS residents by December 2022. Population-weighted anti-S IgG seroprevalence among Kilifi HDSS residents increased from 69.1% (65.8-72.3%) by May 2022 to 77.4% (74.4-80.2%) by November 2022. Within the Nairobi Urban HDSS, seroprevalence by June 2022 was 88.5% (86.1-90.6%), comparable with seroprevalence by December 2022 (92.2%; 90.2-93.9%). For both surveys, seroprevalence was significantly lower among Kilifi HDSS residents than among Nairobi Urban HDSS residents, as were antibody concentrations (p < 0.001). CONCLUSION: More than 70% of Kilifi residents and 90% of Nairobi residents were seropositive for anti-S IgG by the end of 2022. There is a potential immunity gap in rural Kenya; implementation of interventions to improve COVID-19 vaccine uptake among sub-groups at increased risk of severe COVID-19 in rural settings is recommended

Primers used for molecular analysis for identification of bee populations, pathogens and parasites.

<p>Abbreviations: Israeli acute paralysis virus (IAPV), acute bee paralysis virus (ABPV), black queen cell virus, (BQCV), chronic bee paralysis virus (CBPV), deformed wing virus (DWV), kashmir bee virus (KBV), and sacbrood virus (SBV). References: Arias MC and WS Sheppard WS (1996) <i>Molecular Phylogenetics and Evolution</i> 5: 557–566; Benjeddou et al. (2001) <i>Applied and Environmental Microbiol</i>ogy 67:2384–2387; Chen et al. (2005) <i>Applied and Environmental Microbiol</i>ogy 71(1):436–441; Di Prisco et. al. (2011) <i>Journal of General Virology</i> 92: 151–15; Klee et al. (2007). Journal of Invertabrate Pathology 96: 1–10. Ribiere et al. (2002) <i>Apidologie</i> 33: 339–351; Stoltz et al. (1995) <i>Journal of Apicultural Research</i> 34: 153–160.</p

Geographic location of surveyed apiaries.

<p>Twenty-four apiaries were surveyed throughout Kenya with an additional three apiaries (25–27), see supplemenatry material, surveyed for ecological effects on colony health. The location and numerical designation of the apiaries is indicated on the map.</p

Association of viral diversity with colony size and <i>Varroa</i>.

<p><b>A</b>. Colony size (the number of frames of bees) was not affected by viral diversity (the number of viruses in a colony), H(2) = 2.74, p = 0.254. <b>B</b>. However, colonies with different number of viruses had significantly different numbers of <i>Varroa</i> (H(2) = 13.10; p = 0.0014). Colonies with 1 or 2 viruses had significantly higher <i>Varroa</i> loads than colonies that had no viruses (p<0.05, Wilcoxon pairwise tests, different letters denote significant differences). The number of colonies in each group is indicated at the bottom of each bar. <i>Varroa</i> counts were converted to logarithmic scale.</p

Association of <i>Varroa</i> infestation with elevation and colony size.

<p><b>A</b>. Levels of <i>Varroa</i> mites were positively correlated with elevation, with colonies at higher elevations having significantly higher average numbers of <i>Varroa</i> (r(53) = 0.44, p = 0.001). <b>B</b>. Levels were also positively correlated with colony size ((48) = 0.35, p = 0.013). <i>Varroa</i> counts were converted to logarithmic scale.</p