Effects of the COVID-19 pandemic on hospital admissions and inpatient mortality in Kenya

BackgroundThe impact of COVID-19 in Africa remains poorly defined. We sought to describe trends in hospitalisation due to all medical causes, pneumonia-specific admissions, and inpatient mortality in Kenya before and during the first five waves of the COVID-19 pandemic in Kenya. MethodsWe conducted a hospital-based, multi-site, longitudinal observational study of patients admitted to 13 public referral facilities in Kenya from January 2018 to December 2021. The pre-COVID population included patients admitted before 1 March 2020. We fitted time series models to compare observed and predicted trends for each outcome. To estimate the impact of the COVID-19 pandemic, we calculated incidence rate ratios (IRR) and corresponding 95% confidence intervals (CI) from negative binomial mixed-effects models. ResultsOut of 302,703 patients hospitalised across the 13 surveillance sites (range 11547 to 57011), 117642 (39%) were admitted to adult wards. Compared with the pre-COVID period, hospitalisations declined markedly among adult (IRR 0.68, 95% CI 0.63 to 0.73) and paediatric (IRR 0.67, 95% CI 0.62 to 0.73) patients. Adjusted in-hospital mortality also declined among both adult (IRR 0.83, 95% CI 0.77 to 0.89) and paediatric (IRR 0.85, 95% CI 0.77 to 0.94) admissions. Pneumonia-specific admissions among adults increased during the pandemic (IRR 1.75, 95% CI 1.18 to 2.59). Paediatric pneumonia cases were lower than pre-pandemic levels in the first year of the pandemic and elevated in late 2021 (IRR 0.78, 95% CI 0.51 to 1.20). ConclusionsContrary to initial predictions, the COVID-19 pandemic was associated with lower hospitalisation rates and in-hospital mortality, despite increased pneumonia admissions among adults. These trends were sustained after the withdrawal of containment measures that disrupted essential health services, suggesting a role for additional factors that warrant further investigation.

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

BackgroundUp-to-date SARS-CoV-2 antibody seroprevalence estimates are important for informing public health planning, including priorities for Coronavirus disease 2019 (COVID-19) vaccination programs. We sought to estimate infection- and vaccination-induced SARS-CoV-2 antibody seroprevalence within representative samples of the Kenyan population approximately two years into the COVID-19 pandemic and approximately one year after rollout of the national COVID-19 vaccination program. MethodsWe conducted cross-sectional serosurveys within random, age-stratified samples of Kilifi Health and Demographic Surveillance System (HDSS) and Nairobi Urban HDSS residents. Anti-spike (anti-S) immunoglobulin G (IgG) and anti-nucleoprotein (anti-N) IgG were measured using validated in-house ELISAs. Target-specific Bayesian population-weighted seroprevalence was calculated overall, by sex and by age, with adjustment for test performance as appropriate. Anti-S IgG concentrations were estimated with reference to the WHO International Standard (IS) for anti-SARS-CoV-2 immunoglobulin and their reverse cumulative distributions plotted. ResultsBetween February and June 2022, 852 and 851 individuals within the Kilifi HDSS and the Nairobi Urban HDSS, respectively, were sampled. Only 11.0% (95% confidence interval [CI] 9.0-13.3) of all Kilifi HDSS participants and 33.4% (95%CI 30.2-36.6) of all Nairobi Urban HDSS participants had received any doses of COVID-19 vaccine. Population-weighted anti-S IgG seroprevalence was 69.1% (95% credible interval [CrI] 65.8-72.3) within the Kilifi HDSS and 88.5% (95%CrI 86.1-90.6) within the Nairobi Urban HDSS. Among COVID-unvaccinated residents of the Kilifi HDSS and Nairobi Urban HDSS, it was 66.7% (95%CrI 63.3-70.0) and 85.3% (95%CrI 82.1-88.2), respectively. Population-weighted, test-adjusted anti-N IgG seroprevalence within the Kilifi HDSS was 53.5% (95%CrI 46.5-61.1) and 65.5% (95%CrI 56.0-75.6) within the Nairobi Urban HDSS. The prevalence of anti-N antibodies was similar in vaccinated and unvaccinated subgroups in both HDSS populations. Anti-S IgG concentrations were significantly lower among Kilifi HDSS residents than among Nairobi Urban HDSS residents (p< 0.001). ConclusionsApproximately, 7 in 10 Kilifi residents and 9 in 10 Nairobi residents were seropositive for anti-S IgG by May 2022 and June 2022, respectively. Given COVID-19 vaccination coverage, anti-S IgG seropositivity among COVID-unvaccinated individuals, and anti-N IgG seroprevalence, population-level anti-S IgG seroprevalence was predominantly derived from infection. Interventions to improve COVID-19 vaccination uptake should be targeted to individuals in rural Kenya who are at high risk of severe COVID-19.

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

BackgroundThe impact of COVID-19 on all-cause mortality in sub-Saharan Africa remains unknown. MethodsWe monitored mortality among 306,000 residents of Kilifi Health and Demographic Surveillance System, Kenya, through four COVID-19 waves from April 2020-September 2021. We calculated expected deaths using negative binomial regression fitted to baseline mortality data (2010-2019) and calculated excess mortality as observed-minus-expected deaths. We excluded deaths in infancy because of under-ascertainment of births during lockdown. In February 2021, after two waves of wild-type COVID-19, adult seroprevalence of anti-SARS-CoV-2 was 25.1%. We predicted COVID-19-attributable deaths as the product of age-specific seroprevalence, population size and global infection fatality ratios (IFR). We examined changes in cause of death by Verbal Autopsy (VA). ResultsBetween April 2020 and February 2021, we observed 1,000 deaths against 1,012 expected deaths (excess mortality -1.2%, 95% PI -6.6%, 5.8%). Based on SARS-CoV-2 seroprevalence, we predicted 306 COVID-19-attributable deaths (a predicted excess mortality of 30.6%) within this period. Monthly mortality analyses showed a significant excess among adults aged [≥]45 years in only two months, July-August 2021, coinciding with the fourth (Delta) wave of COVID-19. By September 2021, overall excess mortality was 3.2% (95% PI -0.6%, 8.1%) and cumulative excess mortality risk was 18.7/100,000. By VA, there was a transient reduction in deaths attributable to acute respiratory infections in 2020. ConclusionsNormal mortality rates during extensive transmission of wild-type SARS-CoV-2 through February 2021 suggests that the IFR for this variant is lower in Kenya than elsewhere. We found excess mortality associated with the Delta variant but the cumulative excess mortality risk remains low in coastal Kenya compared to global estimates.

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

BackgroundMost 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. We conducted population-based serosurveys at three Health and Demographic Surveillance Systems (HDSSs) to determine the cumulative incidence of infection with SARS-CoV-2. MethodsWe selected random age-stratified population-based samples at HDSSs in Kisumu, Nairobi and Kilifi, in Kenya. Blood samples were collected from participants between 01 Dec 2020 and 27 May 2021. No participant had received a COVID-19 vaccine. 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. We adjusted prevalence estimates using classical methods and Bayesian modelling to account for the sampling scheme and assay performance. ResultsWe recruited 2,559 individuals from the three HDSS sites, median age (IQR) 27 (10-78) years and 52% were female. Seroprevalence at all three sites rose steadily during the study period. In Kisumu, Nairobi and Kilifi, seroprevalences (95% CI) at the beginning of the study were 36.0% (28.2-44.4%), 32.4% (23.1-42.4%), and 14.5% (9.1-21%), and respectively; at the end they were 42.0% (34.7-50.0%), 50.2% (39.7-61.1%), and 24.7% (17.5-32.6%), respectively. Seroprevalence was substantially lower among children (<16 years) than among adults at all three sites (p[≤]0.001). ConclusionBy May 2021 in three broadly representative populations of unvaccinated individuals in Kenya, seroprevalence of anti-SARS-CoV-2 IgG was 25-50%. There was wide variation in cumulative incidence by location and age.

Prevalence of SARS-CoV-2 Antibodies from a one-year National Serosurveillance of Kenyan Blood Transfusion Donors

In tropical Africa, SARS-CoV-2 epidemiology is poorly described because of lack of access to testing and weak surveillance systems. Since April 2020, we followed SARS-CoV-2 seroprevalence in plasma samples across the Kenya National Blood Transfusion Service. We developed an IgG ELISA against full length spike protein. Validated in locally-observed, PCR-positive COVID-19 cases and in pre-pandemic sera, sensitivity was 92.7% and specificity was 99.0%. Using sera from 9,922 donors, we estimated national seroprevalence of SARS-CoV-2 antibodies at 4.3% in April-June 2020 and 9.1% in August-September 2020. Kenyas second COVID-19 wave peaked in November 2020. Here we estimate national seroprevalence in early 2021. Between January 3 and March 15, 2021, we collected 3,062 samples from donors aged 16-64 years. Among 3,018 samples that met our study criteria, 1,333 were seropositive (crude seroprevalence 44.2%, 95% CI 42.4-46.0%). After Bayesian test-performance adjustment and population weighting to represent the national population distribution, the national estimate of seroprevalence was 48.5% (95% CI 45.2-52.1%). Seroprevalence varied little by age or sex but was higher in Nairobi (61.8%), the capital city, and lower in two rural regions. Almost half of Kenyas adult donors had evidence of past SARS-CoV-2 infection by March 2021. Although high, the estimate is corroborated by other population-specific estimates in country. Between March and June, 2% of the population were vaccinated against COVID-19 and the country experienced a third epidemic wave. Natural infection is outpacing vaccine delivery substantially in Africa, and this reality needs to be considered as objectives of the vaccine programme are set.

COVID-19 Transmission Dynamics Underlying Epidemic Waves in Kenya

Policy decisions on COVID-19 interventions should be informed by a local, regional and national understanding of SARS-CoV-2 transmission. Epidemic waves may result when restrictions are lifted or poorly adhered to, variants with new phenotypic properties successfully invade, or when infection spreads to susceptible sub-populations. Three COVID-19 epidemic waves have been observed in Kenya. Using a mechanistic mathematical model we explain the first two distinct waves by differences in contact rates in high and low social-economic groups, and the third wave by the introduction of a new higher-transmissibility variant. Reopening schools led to a minor increase in transmission between the second and third waves. Our predictions of current population exposure in Kenya ([~]75% June 1st) have implications for a fourth wave and future control strategies. One Sentence SummaryCOVID-19 spread in Kenya is explained by mixing heterogeneity and a variant less constrained by high population exposure

Improving SARS-CoV-2 cumulative incidence estimation through mixture modelling of antibody levels

As countries decide on vaccination strategies and how to ease movement restrictions, estimates of cumulative incidence of SARS-CoV-2 infection are essential in quantifying the extent to which populations remain susceptible to COVID-19. Cumulative incidence is usually estimated from seroprevalence data, where seropositives are defined by an arbitrary threshold antibody level, and adjusted for sensitivity and specificity at that threshold. This does not account for antibody waning nor for lower antibody levels in asymptomatic or mildly symptomatic cases. Mixture modelling can estimate cumulative incidence from antibody-level distributions without requiring adjustment for sensitivity and specificity. To illustrate the bias in standard threshold-based seroprevalence estimates, we compared both approaches using data from several Kenyan serosurveys. Compared to the mixture model estimate, threshold analysis underestimated cumulative incidence by 31% (IQR: 11 to 41) on average. Until more discriminating assays are available, mixture modelling offers an approach to reduce bias in estimates of cumulative incidence. One-Sentence SummaryMixture models reduce biases inherent in the standard threshold-based analysis of SARS-CoV-2 serological data.

Seroprevalence of Antibodies to SARS-CoV-2 among Health Care Workers in Kenya

BackgroundFew studies have assessed the seroprevalence of antibodies against SARS-CoV-2 among Health Care Workers (HCWs) in Africa. We report findings from a survey among HCWs in three counties in Kenya. MethodsWe recruited 684 HCWs from Kilifi (rural), Busia (rural) and Nairobi (urban) counties. The serosurvey was conducted between 30th July 2020 and 4th December 2020. We tested for IgG antibodies to SARS-CoV-2 spike protein using ELISA. Assay sensitivity and specificity were 93% (95% CI 88-96%) and 99% (95% CI 98-99.5%), respectively. We adjusted prevalence estimates using Bayesian modeling to account for assay performance. ResultsCrude overall seroprevalence was 19.7% (135/684). After adjustment for assay performance seroprevalence was 20.8% (95% CI 17.5-24.4%). Seroprevalence varied significantly (p<0.001) by site: 43.8% (CI 35.8-52.2%) in Nairobi, 12.6% (CI 8.8-17.1%) in Busia and 11.5% (CI 7.2-17.6%) in Kilifi. In a multivariable model controlling for age, sex and site, professional cadre was not associated with differences in seroprevalence. ConclusionThese initial data demonstrate a high seroprevalence of antibodies to SARS-CoV-2 among HCWs in Kenya. There was significant variation in seroprevalence by region, but not by cadre.

Seroprevalence of anti-SARS-CoV-2 IgG antibodies among truck drivers and assistants in Kenya

In October 2020, anti-SARS-CoV-2 IgG seroprevalence among truck drivers and their assistants (TDA) in Kenya was 42.3%, higher than among other key populations. TDA transport essential supplies during the COVID-19 pandemic, placing them at increased risk of being infected and of transmitting SARS-CoV-2 infection over a wide geographical area.

Seroprevalence of anti-SARS-CoV-2 IgG antibodies in Kenyan blood donors

BackgroundThere are no data on SARS-CoV-2 seroprevalence in Africa though the COVID-19 epidemic curve and reported mortality differ from patterns seen elsewhere. We estimated the anti-SARS-CoV-2 antibody prevalence among blood donors in Kenya. MethodsWe measured anti-SARS-CoV-2 spike IgG prevalence by ELISA on residual blood donor samples obtained between April 30 and June 16, 2020. Assay sensitivity and specificity were 83% (95% CI 59-96%) and 99.0% (95% CI 98.1-99.5%), respectively. National seroprevalence was estimated using Bayesian multilevel regression and post-stratification to account for non-random sampling with respect to age, sex and region, adjusted for assay performance. ResultsComplete data were available for 3098 of 3174 donors, aged 15-64 years. By comparison with the Kenyan population, the sample over- represented males (82% versus 49%), adults aged 25-34 years (40% versus 27%) and residents of coastal Counties (49% versus 9%). Crude overall seroprevalence was 5.6% (174/3098). Population-weighted, test- adjusted national seroprevalence was 5.2% (95% CI 3.7- 7.1%). Seroprevalence was highest in the 3 largest urban Counties - Mombasa (9.3% [95% CI 6.4-13.2%)], Nairobi (8.5% [95% CI 4.9-13.5%]) and Kisumu (6.5% [95% CI 3.3-11.2%]). ConclusionsWe estimate that 1 in 20 adults in Kenya had SARS-CoV-2 antibodies during the study period. By the median date of our survey, only 2093 COVID-19 cases and 71 deaths had been reported through the national screening system. This contrasts, by several orders of magnitude, with the numbers of cases and deaths reported in parts of Europe and America when seroprevalence was similar.