Cohort profile : the Kilifi vaccine monitoring study

The Kilifi Vaccine Monitoring Study (KiVMS) is a long-term continuous cohort study set up to investigate effectiveness, impact, coverage, safety and indirect vaccine effects by recruiting birth cohorts and, where applicable, cohorts of older and adults. It is based in the area covered by the Kilifi Health and Demographic Surveillance System, Kilifi, Kenya, and currently has records of 33 962 children in the birth cohort database. A major strength of KiVMS is its unique integration of a vaccine registry, a morbidity surveillance system and the largest health and demographic surveillance system (HDSS) in Africa

Sero-surveillance for IgG to SARS-CoV-2 at antenatal care clinics in three Kenyan referral hospitals: Repeated cross-sectional surveys 2020-21.

INTRODUCTION: The high proportion of SARS-CoV-2 infections that have remained undetected presents a challenge to tracking the progress of the pandemic and estimating the extent of population immunity. METHODS: We used residual blood samples from women attending antenatal care services at three hospitals in Kenya between August 2020 and October 2021and a validated IgG ELISA for SARS-Cov-2 spike protein and adjusted the results for assay sensitivity and specificity. We fitted a two-component mixture model as an alternative to the threshold analysis to estimate of the proportion of individuals with past SARS-CoV-2 infection. RESULTS: We estimated seroprevalence in 2,981 women; 706 in Nairobi, 567 in Busia and 1,708 in Kilifi. By October 2021, 13% of participants were vaccinated (at least one dose) in Nairobi, 2% in Busia. Adjusted seroprevalence rose in all sites; from 50% (95%CI 42-58) in August 2020, to 85% (95%CI 78-92) in October 2021 in Nairobi; from 31% (95%CI 25-37) in May 2021 to 71% (95%CI 64-77) in October 2021 in Busia; and from 1% (95% CI 0-3) in September 2020 to 63% (95% CI 56-69) in October 2021 in Kilifi. Mixture modelling, suggests adjusted cross-sectional prevalence estimates are underestimates; seroprevalence in October 2021 could be 74% in Busia and 72% in Kilifi. CONCLUSIONS: There has been substantial, unobserved transmission of SARS-CoV-2 in Nairobi, Busia and Kilifi Counties. Due to the length of time since the beginning of the pandemic, repeated cross-sectional surveys are now difficult to interpret without the use of models to account for antibody waning

Association of diabetes, smoking, and alcohol use with subclinical-to-symptomatic spectrum of tuberculosis in 16 countries: an individual participant data meta-analysis of national tuberculosis prevalence surveys

Background Non-communicable diseases (NCDs) and NCD risk factors, such as smoking, increase the risk for tuberculosis (TB). Data are scarce on the risk of prevalent TB associated with these factors in the context of population-wide systematic screening and on the association between NCDs and NCD risk factors with different manifestations of TB, where ∼50% being asymptomatic but bacteriologically positive (subclinical). We did an individual participant data (IPD) meta-analysis of national and sub-national TB prevalence surveys to synthesise the evidence on the risk of symptomatic and subclinical TB in people with NCDs or risk factors, which could help countries to plan screening activities. Methods In this systematic review and IPD meta-analysis, we identified eligible prevalence surveys in low-income and middle-income countries that reported at least one NCD (e.g., diabetes) or NCD risk factor (e.g., smoking, alcohol use) through the archive maintained by the World Health Organization and by searching in Medline and Embase from January 1, 2000 to August 10, 2021. The search was updated on March 23, 2023. We performed a one-stage meta-analysis using multivariable multinomial models. We estimated the proportion of and the odds ratio for subclinical and symptomatic TB compared to people without TB for current smoking, alcohol use, and self-reported diabetes, adjusted for age and gender. Subclinical TB was defined as microbiologically confirmed TB without symptoms of current cough, fever, night sweats, or weight loss and symptomatic TB with at least one of these symptoms. We assessed heterogeneity using forest plots and I2 statistic. Missing variables were imputed through multi-level multiple imputation. This study is registered with PROSPERO (CRD42021272679). Findings We obtained IPD from 16 national surveys out of 21 national and five sub-national surveys identified (five in Asia and 11 in Africa, N = 740,815). Across surveys, 15.1%–56.7% of TB were subclinical (median: 38.1%). In the multivariable model, current smoking was associated with both subclinical (OR 1.67, 95% CI 1.27–2.40) and symptomatic TB (OR 1.49, 95% CI 1.34–1.66). Self-reported diabetes was associated with symptomatic TB (OR 1.67, 95% CI 1.17–2.40) but not with subclinical TB (OR 0.92, 95% CI 0.55–1.55). For alcohol drinking ≥ twice per week vs no alcohol drinking, the estimates were imprecise (OR 1.59, 95% CI 0.70–3.62) for subclinical TB and OR 1.43, 95% CI 0.59–3.46 for symptomatic TB). For the association between current smoking and symptomatic TB, I2 was high (76.5% (95% CI 62.0–85.4), while the direction of the point estimates was consistent except for three surveys with wide CIs. Interpretation Our findings suggest that current smokers are more likely to have both symptomatic and subclinical TB. These individuals can, therefore, be prioritised for intensified screening, such as the use of chest X-ray in the context of community-based screening. People with self-reported diabetes are also more likely to have symptomatic TB, but the association is unclear for subclinical TB

Respiratory viruses and atypical bacteria

This chapter considers the main viral and atypical bacterial causes of acute respiratory infectious disease with particular concern for the low- and middle-income settings. The chapter covers endemic and zoonotic pathogens, with an overview of the wide breadth of aetiological agents, the distinctive clinical syndromes, particularly pneumonia and bronchiolitis, co-infections, and the characteristic patterns of distribution in the host population, i.e. temporal spatial and age-related. It also describes methods of diagnosis, what treatments are available, and what measures are for prevention. We hope to convey something of the awesome nature of these respiratory pathogens, the magnitude of the burden on human health, their remarkable diversity in aetiology, origin and transmission, and the potential and challenges for control and prevention

Replication Data for: Revealing the extent of the COVID-19 pandemic in Kenya based on serological and PCR-test data

This is a replication dataset for the submitted manuscript "Ojal, J., Brand, S.P., Were, V., Okiro, E.A., Kombe, I.K., Mburu, C., Aziza, R., Ogero, M., Agweyu, A., Warimwe, G.M. and Uyoga, S., 2020. Revealing the extent of the COVID-19 pandemic in Kenya based on serological and PCR-test data. medRxiv.". The related study was conducted to estimate the SARS-CoV-2 pandemic peak and COVID-19 disease burden including reported severe cases and deaths in the major urban counties in Kenya. National surveillance PCR tests, serological surveys, and mobility data were used to develop and fit a county-specific transmission model in the country. These datasets presented contain the number of positive PCR-confirmed swab tests for each county by date of sample collection (21st Feb to 6th August), the number of positive and negative serological results for each county by date of sample collection (21st Feb to 6th August), number of deaths with a PCR-confirmed swab test for each county by recorded date of death (21st Feb to 6th August), the total number of swab samples collected in Mombasa county, and analyzed at Kemri-Wellcome Research Program testing center (21st Feb – 27th June), and summary data of Kenyan epidemic, including reported total number of test performed. The datasets are used for COVID-19 forecasts

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

These data contain anonymised residual donor serum samples used for screening of transfusion transmissible infections collected at the KNBTS regional centres which has been used to compute standardised SARS-CoV-2 seroprevalence by age, sex and region using KNBS population as the standard population