38 research outputs found

    Statistical Regression Model of Water, Sanitation, and Hygiene; Treatment Coverage; and Environmental Influences on School-Level Soil-Transmitted Helminths and Schistosome Prevalence in Kenya: Secondary Analysis of the National Deworming Program Data.

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    According to the Kenya National School-Based Deworming program launched in 2012 and implemented for the first 5 years (2012-2017), the prevalence of soil-transmitted helminths (STH) and schistosomiasis substantially reduced over the mentioned period among the surveyed schools. However, this reduction is heterogeneous. In this study, we aimed to determine the factors associated with the 5-year school-level infection prevalence and relative reduction (RR) in prevalence in Kenya following the implementation of the program. Multiple variables related to treatment, water, sanitation, and hygiene (WASH) and environmental factors were assembled and included in mixed-effects linear regression models to identify key determinants of the school location STH and schistosomiasis prevalence and RR. Reduced prevalence of Ascaris lumbricoides was associated with low ( 75%) reported coverage of a household improved water source. Reduced Schistosoma haematobium was associated with high aridity index. Analysis indicated that a combination of factors, including the number of treatment rounds, multiple related program interventions, community- and school-level WASH, and several environmental factors had a major influence on the school-level infection transmission and reduction

    Quantifying travel behavior for infectious disease research: a comparison of data from surveys and mobile phones.

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    Human travel impacts the spread of infectious diseases across spatial and temporal scales, with broad implications for the biological and social sciences. Individual data on travel patterns have been difficult to obtain, particularly in low-income countries. Travel survey data provide detailed demographic information, but sample sizes are often small and travel histories are hard to validate. Mobile phone records can provide vast quantities of spatio-temporal travel data but vary in spatial resolution and explicitly do not include individual information in order to protect the privacy of subscribers. Here we compare and contrast both sources of data over the same time period in a rural area of Kenya. Although both data sets are able to quantify broad travel patterns and distinguish regional differences in travel, each provides different insights that can be combined to form a more detailed picture of travel in low-income settings to understand the spread of infectious diseases

    Risk factors for Plasmodium falciparum infection in the Kenyan Highlands: a cohort study.

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    BACKGROUND: Malaria transmission in African highland areas can be prone to epidemics, with minor fluctuations in temperature or altitude resulting in highly heterogeneous transmission. In the Kenyan Highlands, where malaria prevalence has been increasing, characterising malaria incidence and identifying risk factors for infection is complicated by asymptomatic infection. METHODS: This all-age cohort study, one element of the Malaria Transmission Consortium, involved monthly follow-up of 3155 residents of the Kisii and Rachuonyo South districts during June 2009-June 2010. Participants were tested for malaria using rapid diagnostic testing at every visit, regardless of symptoms. RESULTS: The incidence of Plasmodium falciparum infection was 0.2 cases per person, although infections were clustered within individuals and over time, with the majority of infections detected in the last month of the cohort study. Overall, incidence was higher in the Rachuonyo district and infections were detected most frequently in 5-10-year-olds. The majority of infections were asymptomatic (58%). Travel away from the study area was a notable risk factor for infection. CONCLUSIONS: Identifying risk factors for malaria infection can help to guide targeting of interventions to populations most likely to be exposed to malaria

    Prevalence and Correlation Analysis of Soil-Transmitted Helminths Infections and Treatment Coverage for Preschool and School Aged Children in Kenya: Secondary Analysis of the National School Based Deworming Program Data

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    Background: Soil-transmitted helminths (STH) are among the most common parasitic infections globally, disproportionately affecting children. Treatment of STH in Kenya is often targeted at preschool (PSAC) and school aged (SAC) children delivered through annual mass drug administration (MDA) in primary schools. Understanding group-specific prevalence and dynamics between treatment and coverage is critical for continued treatment success. This study aims to provide detailed information on group-specific infection prevalence and relative reductions (RR), and their relationships with treatment coverage over time. Additionally, it aims to quantify the correlation between the observed school level infection prevalence and treatment coverage. Methods: Secondary analysis of existing data collected between 2012 and 2018 by the monitoring and evaluation (M&E) program of the National School-Based Deworming (NSBD) program was used. The M&E program conducted surveys utilizing cross-sectional study design, at four survey time points, in a nationally-representative sample of schoolchildren across counties in Kenya. In each participating school, the program randomly sampled 108 children per school, of both groups. Infection prevalence was estimated using binomial regression, RR in prevalence using multivariable mixed effects model, statistical correlations using structural equation modeling, and change-point-analysis using the binary segmentation algorithm. Results: Overall, STH prevalence for PSAC was 33.7, 20.2, 19.0, and 17.9% during Year 1 (Y1), Year 3 (Y3), Year 5 (Y5), and Year 6 (Y6) surveys, respectively with an overall RR of 46.9% (p = 0.001) from Y1 to Y6. Similarly, overall STH prevalence for SAC was 33.6, 18.4, 14.7, and 12.5% during Y1, Y3, Y5, and Y6 surveys, respectively with an overall RR of 62.6% (p < 0.001). An overall (all time points) significant but very weak negative correlation was found between treatment coverage and undifferentiated STH prevalence (r = -0.144, p = 0.002) among PSAC but not in SAC. Further, we observed inter-county heterogeneity variation in infection prevalence, RR, as well as correlations. Conclusion: The analysis showed that after six rounds of MDA, prevalence of STH has significantly declined among both groups of children, however not to a point where it is not a public health problem (below 1%). The analysis, additionally established an overall significant but weak negative correlation between treatment coverage and prevalence, indicating that the current treatment coverage might not be sufficient to drive the overall STH prevalence to below 1%. These findings will allow STH control programs in Kenya to make decisions that will accelerate the attainment of STH elimination as a public health problem

    Factors associated with high heterogeneity of malaria at fine spatial scale in the Western Kenyan highlands.

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    BACKGROUND: The East African highlands are fringe regions between stable and unstable malaria transmission. What factors contribute to the heterogeneity of malaria exposure on different spatial scales within larger foci has not been extensively studied. In a comprehensive, community-based cross-sectional survey an attempt was made to identify factors that drive the macro- and micro epidemiology of malaria in a fringe region using parasitological and serological outcomes. METHODS: A large cross-sectional survey including 17,503 individuals was conducted across all age groups in a 100 km(2) area in the Western Kenyan highlands of Rachuonyo South district. Households were geo-located and prevalence of malaria parasites and malaria-specific antibodies were determined by PCR and ELISA. Household and individual risk-factors were recorded. Geographical characteristics of the study area were digitally derived using high-resolution satellite images. RESULTS: Malaria antibody prevalence strongly related to altitude (1350-1600 m, p < 0.001). A strong negative association with increasing altitude and PCR parasite prevalence was found. Parasite carriage was detected at all altitudes and in all age groups; 93.2 % (2481/2663) of malaria infections were apparently asymptomatic. Malaria parasite prevalence was associated with age, bed net use, house construction features, altitude and topographical wetness index. Antibody prevalence was associated with all these factors and distance to the nearest water body. CONCLUSION: Altitude was a major driver of malaria transmission in this study area, even across narrow altitude bands. The large proportion of asymptomatic parasite carriers at all altitudes and the age-dependent acquisition of malaria antibodies indicate stable malaria transmission; the strong correlation between current parasite carriage and serological markers of malaria exposure indicate temporal stability of spatially heterogeneous transmission

    'A bite before bed': exposure to malaria vectors outside the times of net use in the highlands of western Kenya.

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    BACKGROUND: The human population in the highlands of Nyanza Province, western Kenya, is subject to sporadic epidemics of Plasmodium falciparum. Indoor residual spraying (IRS) and long-lasting insecticide treated nets (LLINs) are used widely in this area. These interventions are most effective when Anopheles rest and feed indoors and when biting occurs at times when individuals use LLINs. It is therefore important to test the current assumption of vector feeding preferences, and late night feeding times, in order to estimate the extent to which LLINs protect the inhabitants from vector bites. METHODS: Mosquito collections were made for six consecutive nights each month between June 2011 and May 2012. CDC light-traps were set next to occupied LLINs inside and outside randomly selected houses and emptied hourly. The net usage of residents, their hours of house entry and exit and times of sleeping were recorded and the individual hourly exposure to vectors indoors and outdoors was calculated. Using these data, the true protective efficacy of nets (P*), for this population was estimated, and compared between genders, age groups and from month to month. RESULTS: Primary vector species (Anopheles funestus s.l. and Anopheles arabiensis) were more likely to feed indoors but the secondary vector Anopheles coustani demonstrated exophagic behaviour (p < 0.05). A rise in vector biting activity was recorded at 19:30 outdoors and 18:30 indoors. Individuals using LLINs experienced a moderate reduction in their overall exposure to malaria vectors from 1.3 to 0.47 bites per night. The P* for the population over the study period was calculated as 51% and varied significantly with age and season (p < 0.01). CONCLUSIONS: In the present study, LLINs offered the local population partial protection against malaria vector bites. It is likely that P* would be estimated to be greater if the overall suppression of the local vector population due to widespread community net use could be taken into account. However, the overlap of early biting habit of vectors and human activity in this region indicates that additional methods of vector control are required to limit transmission. Regular surveillance of both vector behaviour and domestic human-behaviour patterns would assist the planning of future control interventions in this region

    The Impact of Hotspot-Targeted Interventions on Malaria Transmission in Rachuonyo South District in the Western Kenyan Highlands: A Cluster-Randomized Controlled Trial.

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    BACKGROUND: Malaria transmission is highly heterogeneous, generating malaria hotspots that can fuel malaria transmission across a wider area. Targeting hotspots may represent an efficacious strategy for reducing malaria transmission. We determined the impact of interventions targeted to serologically defined malaria hotspots on malaria transmission both inside hotspots and in surrounding communities. METHODS AND FINDINGS: Twenty-seven serologically defined malaria hotspots were detected in a survey conducted from 24 June to 31 July 2011 that included 17,503 individuals from 3,213 compounds in a 100-km2 area in Rachuonyo South District, Kenya. In a cluster-randomized trial from 22 March to 15 April 2012, we randomly allocated five clusters to hotspot-targeted interventions with larviciding, distribution of long-lasting insecticide-treated nets, indoor residual spraying, and focal mass drug administration (2,082 individuals in 432 compounds); five control clusters received malaria control following Kenyan national policy (2,468 individuals in 512 compounds). Our primary outcome measure was parasite prevalence in evaluation zones up to 500 m outside hotspots, determined by nested PCR (nPCR) at baseline and 8 wk (16 June-6 July 2012) and 16 wk (21 August-10 September 2012) post-intervention by technicians blinded to the intervention arm. Secondary outcome measures were parasite prevalence inside hotpots, parasite prevalence in the evaluation zone as a function of distance from the hotspot boundary, Anopheles mosquito density, mosquito breeding site productivity, malaria incidence by passive case detection, and the safety and acceptability of the interventions. Intervention coverage exceeded 87% for all interventions. Hotspot-targeted interventions did not result in a change in nPCR parasite prevalence outside hotspot boundaries (p ≥ 0.187). We observed an average reduction in nPCR parasite prevalence of 10.2% (95% CI -1.3 to 21.7%) inside hotspots 8 wk post-intervention that was statistically significant after adjustment for covariates (p = 0.024), but not 16 wk post-intervention (p = 0.265). We observed no statistically significant trend in the effect of the intervention on nPCR parasite prevalence in the evaluation zone in relation to distance from the hotspot boundary 8 wk (p = 0.27) or 16 wk post-intervention (p = 0.75). Thirty-six patients with clinical malaria confirmed by rapid diagnostic test could be located to intervention or control clusters, with no apparent difference between the study arms. In intervention clusters we caught an average of 1.14 female anophelines inside hotspots and 0.47 in evaluation zones; in control clusters we caught an average of 0.90 female anophelines inside hotspots and 0.50 in evaluation zones, with no apparent difference between study arms. Our trial was not powered to detect subtle effects of hotspot-targeted interventions nor designed to detect effects of interventions over multiple transmission seasons. CONCLUSIONS: Despite high coverage, the impact of interventions targeting malaria vectors and human infections on nPCR parasite prevalence was modest, transient, and restricted to the targeted hotspot areas. Our findings suggest that transmission may not primarily occur from hotspots to the surrounding areas and that areas with highly heterogeneous but widespread malaria transmission may currently benefit most from an untargeted community-wide approach. Hotspot-targeted approaches may have more validity in settings where human settlement is more nuclear. TRIAL REGISTRATION: ClinicalTrials.gov NCT01575613

    Using a model-based geostatistical approach to design and analyse the prevalence of schistosomiasis in Kenya

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    BackgroundInfections caused by both Schistosoma mansoni and Schistosoma haematobium are endemic in Kenya, with over six million children at risk. A national school-based deworming programme was launched in 2012 with the goal of eliminating parasitic worms as a public health problem. This study used a model-based geostatistical (MBG) approach to design and analyse the impact of the programme and inform treatment strategy changes for schistosomiasis (SCH).MethodsA cross-sectional survey of 200 schools across 27 counties of Kenya was utilised. The study design, selection of the schools, and analysis followed the MBG approach, which incorporated historical data on treatment, morbidity, and environmental covariates.ResultsThe overall SCH prevalence was 5.0% (95% CI 4.9%–5.2%) and was estimated, with a high predictive probability of 0.999, to be between 1% and&lt; 10%. The predictive probabilities at county level revealed county heterogeneity, with that of four counties estimated to be between 0% and&lt; 1%, that of 20 counties estimated to be between 1% and&lt; 10%, that of two counties estimated to be between 10% and&lt; 20%, and that of one county estimated to be between 20% and&lt; 50%.ConclusionSCH treatment requirements can now be confidently refined based on the World Health Organization’s guidelines. The four counties with prevalences of between 0% and&lt; 1% may consider suspending treatment only in areas (i.e., sub-counties and wards) where the prevalence is&lt; 1%
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