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

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Africa is poorly described. The first case of SARS-CoV-2 in Kenya was reported on 12 March 2020, and an overwhelming number of cases and deaths were expected, but by 31 July 2020, there were only 20,636 cases and 341 deaths. However, the extent of SARS-CoV-2 exposure in the community remains unknown. We determined the prevalence of anti-SARS-CoV-2 immunoglobulin G among blood donors in Kenya in April-June 2020. Crude seroprevalence was 5.6% (174 of 3098). Population-weighted, test-performance-adjusted national seroprevalence was 4.3% (95% confidence interval, 2.9 to 5.8%) and was highest in urban counties Mombasa (8.0%), Nairobi (7.3%), and Kisumu (5.5%). SARS-CoV-2 exposure is more extensive than indicated by case-based surveillance, and these results will help guide the pandemic response in Kenya and across Africa

Malaria paediatric hospitalization between 1999 and 2008 across Kenya

<p>Abstract</p> <p>Background</p> <p>Intervention coverage and funding for the control of malaria in Africa has increased in recent years, however, there are few descriptions of changing disease burden and the few reports available are from isolated, single site observations or are of reports at country-level. Here we present a nationwide assessment of changes over 10 years in paediatric malaria hospitalization across Kenya.</p> <p>Methods</p> <p>Paediatric admission data on malaria and non-malaria diagnoses were assembled for the period 1999 to 2008 from in-patient registers at 17 district hospitals in Kenya and represented the diverse malaria ecology of the country. These data were then analysed using autoregressive moving average time series models with malaria and all-cause admissions as the main outcomes adjusted for rainfall, changes in service use and populations-at-risk within each hospital's catchment to establish whether there has been a statistically significant decline in paediatric malaria hospitalization during the observation period.</p> <p>Results</p> <p>Among the 17 hospital sites, adjusted paediatric malaria admissions had significantly declined at 10 hospitals over 10 years since 1999; had significantly increased at four hospitals, and remained unchanged in three hospitals. The overall estimated average reduction in malaria admission rates was 0.0063 cases per 1,000 children aged 0 to 14 years per month representing an average percentage reduction of 49% across the 10 hospitals registering a significant decline by the end of 2008. Paediatric admissions for all-causes had declined significantly with a reduction in admission rates of greater than 0.0050 cases per 1,000 children aged 0 to 14 years per month at 6 of 17 hospitals. Where malaria admissions had increased three of the four sites were located in Western Kenya close to Lake Victoria. Conversely there was an indication that areas with the largest declines in malaria admission rates were areas located along the Kenyan coast and some sites in the highlands of Kenya.</p> <p>Conclusion</p> <p>A country-wide assessment of trends in malaria hospitalizations indicates that all is not equal, important variations exist in the temporal pattern of malaria admissions between sites and these differences require more detailed investigation to understand what is required to promote a clinical transition across Africa.</p

Detecting Foci of Malaria Transmission with School Surveys: A Pilot Study in the Gambia.

BACKGROUND: In areas of declining malaria transmission such as in The Gambia, the identification of malaria infected individuals becomes increasingly harder. School surveys may be used to identify foci of malaria transmission in the community. METHODS: The survey was carried out in May-June 2011, before the beginning of the malaria transmission season. Thirty two schools in the Upper River Region of The Gambia were selected with probability proportional to size; in each school approximately 100 children were randomly chosen for inclusion in the study. Each child had a finger prick blood sample collected for the determination of antimalarial antibodies by ELISA, malaria infection by microscopy and PCR, and for haemoglobin measurement. In addition, a simple questionnaire on socio-demographic variables and the use of insecticide-treated bed nets was completed. The cut-off for positivity for antimalarial antibodies was obtained using finite mixture models. The clustered nature of the data was taken into account in the analyses. RESULTS: A total of 3,277 children were included in the survey. The mean age was 10 years (SD = 2.7) [range 4-21], with males and females evenly distributed. The prevalence of malaria infection as determined by PCR was 13.6% (426/3124) [95% CI = 12.2-16.3] with marked variation between schools (range 3-25%, p<0.001), while the seroprevalence was 7.8% (234/2994) [95%CI = 6.4-9.8] for MSP119, 11.6% (364/2997) [95%CI = 9.4-14.5] for MSP2, and 20.0% (593/2973) [95% CI = 16.5-23.2) for AMA1. The prevalence of all the three antimalarial antibodies positive was 2.7% (79/2920). CONCLUSIONS: This survey shows that malaria prevalence and seroprevalence before the transmission season were highly heterogeneous

Changing malaria intervention coverage, transmission and hospitalization in Kenya

<p>Abstract</p> <p>Background</p> <p>Reports of declining incidence of malaria disease burden across several countries in Africa suggest that the epidemiology of malaria across the continent is in transition. Whether this transition is directly related to the scaling of intervention coverage remains a moot point.</p> <p>Methods</p> <p>Paediatric admission data from eight Kenyan hospitals and their catchments have been assembled across two three-year time periods: September 2003 to August 2006 (pre-scaled intervention) and September 2006 to August 2009 (post-scaled intervention). Interrupted time series (ITS) models were developed adjusting for variations in rainfall and hospital use by surrounding communities to show changes in malaria hospitalization over the two periods. The temporal changes in factors that might explain changes in disease incidence were examined sequentially for each hospital setting, compared between hospital settings and ranked according to plausible explanatory factors.</p> <p>Results</p> <p>In six out of eight sites there was a decline in Malaria admission rates with declines between 18% and 69%. At two sites malaria admissions rates increased by 55% and 35%. Results from the ITS models indicate that before scaled intervention in September 2006, there was a significant month-to-month decline in the mean malaria admission rates at four hospitals (trend P < 0.05). At the point of scaled intervention, the estimated mean admission rates for malaria was significantly less at four sites compared to the pre-scaled period baseline. Following scaled intervention there was a significant change in the month-to-month trend in the mean malaria admission rates in some but not all of the sites. Plausibility assessment of possible drivers of change pre- versus post-scaled intervention showed inconsistent patterns however, allowing for the increase in rainfall in the second period, there is a suggestion that starting transmission intensity and the scale of change in ITN coverage might explain some but not all of the variation in effect size. At most sites where declines between observation periods were documented admission rates were changing before free mass ITN distribution and prior to the implementation of ACT across Kenya.</p> <p>Conclusion</p> <p>This study provides evidence of significant within and between location heterogeneity in temporal trends of malaria disease burden. Plausible drivers for changing disease incidence suggest a complex combination of mechanisms, not easily measured retrospectively.</p

Serum immunoglobulin G and mucosal immunoglobulin A antibodies from prepandemic samples collected in Kilifi, Kenya, neutralize SARS-CoV-2 in vitro

Objectives: Many regions of Africa have experienced lower COVID-19 morbidity and mortality than Europe. Pre-existing humoral responses to endemic human coronaviruses (HCoV) may cross-protect against SARS-CoV-2. We investigated the neutralizing capacity of SARS-CoV-2 spike reactive and nonreactive immunoglobulin (Ig)G and IgA antibodies in prepandemic samples. Methods: To investigate the presence of pre-existing immunity, we performed enzyme-linked immunosorbent assay using spike antigens from reference SARS-CoV-2, HCoV HKU1, OC43, NL63, and 229E using prepandemic samples from Kilifi in coastal Kenya. In addition, we performed neutralization assays using pseudotyped reference SARS-CoV-2 to determine the functionality of the identified reactive antibodies. Results: We demonstrate the presence of HCoV serum IgG and mucosal IgA antibodies, which cross-react with the SARS-CoV-2 spike. We show pseudotyped reference SARS-CoV-2 neutralization by prepandemic serum, with a mean infective dose 50 of 1: 251, which is 10-fold less than that of the pooled convalescent sera from patients with COVID-19 but still within predicted protection levels. The prepandemic naso-oropharyngeal fluid neutralized pseudo-SARS-CoV-2 at a mean infective dose 50 of 1: 5.9 in the neutralization assay. Conclusion: Our data provide evidence for pre-existing functional humoral responses to SARS-CoV-2 in Kilifi, coastal Kenya and adds to data showing pre-existing immunity for COVID-19 from other regions

School-based surveys of malaria in Oromia Regional State, Ethiopia: a rapid survey method for malaria in low transmission settings

BACKGROUND: In Ethiopia, malaria transmission is seasonal and unstable, with both Plasmodium falciparum and Plasmodium vivax endemic. Such spatial and temporal clustering of malaria only serves to underscore the importance of regularly collecting up-to-date malaria surveillance data to inform decision-making in malaria control. Cross-sectional school-based malaria surveys were conducted across Oromia Regional State to generate up-to-date data for planning malaria control interventions, as well as monitoring and evaluation of operational programme implementation. METHODS: Two hundred primary schools were randomly selected using a stratified and weighted sampling frame; 100 children aged five to 18 years were then randomly chosen within each school. Surveys were carried out in May 2009 and from October to December 2009, to coincide with the peak of malaria transmission in different parts of Oromia. Each child was tested for malaria by expert microscopy, their haemoglobin measured and a simple questionnaire completed. Satellite-derived environmental data were used to assess ecological correlates of Plasmodium infection; Bayesian geostatistical methods and Kulldorff's spatial scan statistic were employed to investigate spatial heterogeneity. RESULTS: A total 20,899 children from 197 schools provided blood samples, two selected schools were inaccessible and one school refused to participate. The overall prevalence of Plasmodium infection was found to be 0.56% (95% CI: 0.46-0.67%), with 53% of infections due to P. falciparum and 47% due to P. vivax. Of children surveyed, 17.6% (95% CI: 17.0-18.1%) were anaemic, while 46% reported sleeping under a mosquito net the previous night. Malaria was found at 30 (15%) schools to a maximum elevation of 2,187 metres, with school-level Plasmodium prevalence ranging between 0% and 14.5%. Although environmental variables were only weakly associated with P. falciparum and P. vivax infection, clusters of infection were identified within Oromia. CONCLUSION: These findings demonstrate the marked spatial heterogeneity of malaria in Oromia and, in general, Ethiopia, and provide a strong epidemiological basis for planning as well as monitoring and evaluating malaria control in a setting with seasonal and unstable malaria transmission

Cost analysis of school-based intermittent screening and treatment of malaria in Kenya

<p>Abstract</p> <p>Background</p> <p>The control of malaria in schools is receiving increasing attention, but there remains currently no consensus as to the optimal intervention strategy. This paper analyses the costs of intermittent screening and treatment (IST) of malaria in schools, implemented as part of a cluster-randomized controlled trial on the Kenyan coast.</p> <p>Methods</p> <p>Financial and economic costs were estimated using an ingredients approach whereby all resources required in the delivery of IST are quantified and valued. Sensitivity analysis was conducted to investigate how programme variation affects costs and to identify potential cost savings in the future implementation of IST.</p> <p>Results</p> <p>The estimated financial cost of IST per child screened is US$6.61 (economic cost US$ 6.24). Key contributors to cost were salary costs (36%) and malaria rapid diagnostic tests (RDT) (22%). Almost half (47%) of the intervention cost comprises redeployment of existing resources including health worker time and use of hospital vehicles. Sensitivity analysis identified changes to intervention delivery that can reduce programme costs by 40%, including use of alternative RDTs and removal of supervised treatment. Cost-effectiveness is also likely to be highly sensitive to the proportion of children found to be RDT-positive.</p> <p>Conclusion</p> <p>In the current context, school-based IST is a relatively expensive malaria intervention, but reducing the complexity of delivery can result in considerable savings in the cost of intervention.</p> <p>(Costs are reported in US$ 2010).</p

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 higher-transmissibility variants. Reopening schools led to a minor increase in transmission between the second and third waves. Socio-economic and urban/rural population structure are critical determinants of viral transmission in Kenya

Temporal trends of SARS-CoV-2 seroprevalence during the first wave of the COVID-19 epidemic in Kenya.

Observed SARS-CoV-2 infections and deaths are low in tropical Africa raising questions about the extent of transmission. We measured SARS-CoV-2 IgG by ELISA in 9,922 blood donors across Kenya and adjusted for sampling bias and test performance. By 1st September 2020, 577 COVID-19 deaths were observed nationwide and seroprevalence was 9.1% (95%CI 7.6-10.8%). Seroprevalence in Nairobi was 22.7% (18.0-27.7%). Although most people remained susceptible, SARS-CoV-2 had spread widely in Kenya with apparently low associated mortality

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