Search

Abstract Background Lymphatic filariasis (LF) is an infectious neglected tropical disease caused by mosquito-borne nematodes such as Wuchereria bancrofti, Brugia malayi, and Brugia timori. Globally, LF affects 51 million people, with approximately 863 million at risk in 47 countries. In Kenya, filariasis is endemic along the entire coastal strip, and more recently, at the Kenya–Ugandan border. The World Health Organization (WHO) recommends mass drug administration to reduce disease transmission and morbidity. Monitoring the effectiveness of such interventions relies on robust surveillance, achieved through microscopic examination of microfilariae in nighttime blood, detection of circulating filarial antigens (CFA), and molecular xenomonitoring. We focused on molecular xenomonitoring along the Kenyan coast due to its noninvasive nature and the opportunity to identify new vectors. Methods In 2022, mosquitoes were collected from Kilifi, Kwale, and Taita-Taveta counties located within the LF endemic region in Kenya. Subsequently, genomic deoxyribonucleic acid (gDNA) was extracted from these mosquitoes for speciation and analysis of Wuchereria bancrofti infection rates. The impact of sociodemographic and household attributes on infection rates was assessed using generalized estimating equations. Results A total of 18,121 mosquitoes belonging to Culicinae (63.0%, n = 11,414) and Anophelinae (37.0%, n = 6707) subfamilies were collected. Morphological identification revealed that Anopheline mosquitoes were dominated by An. funestus (45.4%, n = 3045) and An. gambiae (42.8%, n = 2873). Wuchereria bancrofti infection rates were highest in Kilifi (35.4%; 95% CI 28.0–43.3%, n = 57/161) and lowest in Taita Taveta (5.3%; 95% CI 3.3–8.0%, n = 22/412). The major vectors incriminated are An. rivulorum, An. funestus sensu stricto, and An. arabiensis. Mosquitoes of the An. funestus complex were significantly associated with LF transmission (OR 18.0; 95% CI 1.80–180; p = 0.014). Additionally, a higher risk of transmission was observed outdoors (OR 1.74; 95% CI 1.08–2.82; p = 0.024) and in homesteads that owned livestock (OR 2.00; 95% CI 1.09–3.66; p = 0.025). Conclusions In this study, we identified An. funestus s.l. sibling species, An. rivulorum and An. funestus s.s., as the primary vectors of lymphatic filariasis along the Kenyan coast. These findings also highlight that a significant portion of disease transmission potentially occurs outdoors where indoor-based vector control tools, including long-lasting insecticidal nets and indoor residual spray, may not be effective. Therefore, control measures targeting outdoor resting mosquitoes such as zooprophylaxis, larval source management, and attractive sugar baits may have potential for LF transmission reduction. Graphical Abstract

Background Anaemia and malaria are leading causes of paediatric hospitalisation and inpatient mortality in sub-Saharan Africa. However, there is limited empirical data on survival following hospital discharge. We aimed to estimate independent effects of anaemia and malaria parasitaemia on inpatient and 1 year postdischarge mortality among Kenyan children.Methods A retrospective cohort study among children admitted to Kilifi County Hospital (KCH) from 2010 to 2019 and followed-up for 1 year postdischarge in Kilifi Health and Demographic Surveillance System (KHDSS). The main exposures were anaemia and malaria parasitaemia at the time of hospital admission while inpatient and 1 year postdischarge mortality were the outcomes.Results We included 9431 admissions among 7578 children (43% girls), median (IQR) age 19 (9.9‒23) months. 2069 (22%), 3893 (41%) and 1140 (12%) admissions had mild, moderate and severe anaemia, whereas 366 (3.9%), 779 (8.3%) and 224 (2.4%) had low, medium and high malaria parasitaemia, respectively. Overall, there were 381 (4.0%) inpatient deaths: 317/381 (83%) and 47/381 (12%) among children with any level of anaemia and malaria parasitaemia, respectively. Moderate and severe, but not mild anaemia, were positively associated with inpatient death. Low and high level parasitaemia were positively associated with inpatient mortality, while medium level parasitaemia was negatively associated. There were 228 (3.1%) postdischarge deaths: 32.8 (95% CI 28.8‒37.3) deaths/1000 child-years. 180/228 (79%) deaths occurred within 6 months after index discharge and 99/228 (43%) occurred in the community. Overall, 180/228 (79%) and 10/228 (4.4%) postdischarge deaths occurred among children with any level of anaemia and malaria parasitaemia, respectively. Severe anaemia was positively associated with postdischarge mortality (adjusted HR 1.94 (95% CI 1.11‒3.40)), while medium level parasitaemia was negatively associated.Conclusion Interventions to create awareness of postdischarge risks, improve uptake of existing interventions and improved discharge processes targeting high-risk groups such as children admitted with severe anaemia, need to be prioritised.

Abstract In malaria epidemiology, interpolation frameworks based on available observations are critical for policy decisions and interpreting disease burden. Updating our understanding of the empirical evidence across different populations, settings, and timeframes is crucial to improving inference for supporting public health. Here, via individual-based modeling, we evaluate a large, multicountry, contemporary Plasmodium falciparum severe malaria dataset to better understand the relationship between prevalence and incidence of malaria pediatric hospitalizations - a proxy of malaria severe outcomes- in East-Africa. We find that life-long exposure dynamics, and subsequent protection patterns in children, substantially determine the likelihood of malaria hospitalizations relative to ongoing prevalence at the population level. Unsteady transmission patterns over a lifetime in children -increasing or decreasing- lead to an exponential relationship of hospitalization rates versus prevalence rather than the asymptotic pattern observed under steady transmission. Addressing this increase in the complexity of malaria epidemiology is crucial to update burden assessments via inference models that guide current and future policy decisions.

IntroductionIn 2012, the World Health Organization revised treatment guidelines for childhood pneumonia with lower chest wall indrawing (LCWI) but no 'danger signs', to recommend home-based treatment. We analysed data from children hospitalized with LCWI pneumonia in the Pneumonia Etiology Research for Child Health (PERCH) study to identify sub-groups with high odds of mortality, who might continue to benefit from hospital management but may not be admitted by staff implementing the 2012 guidelines. We compare the proportion of deaths identified using the criteria in the 2012 guidelines, and the proportion of deaths identified using an alternative set of criteria from our model.MethodsPERCH enrolled a cohort of 2189 HIV-negative children aged 2-59 months who were admitted to hospital with LCWI pneumonia (without obvious cyanosis, inability to feed, vomiting, convulsions, lethargy or head nodding) between 2011-2014 in Kenya, Zambia, South Africa, Mali, The Gambia, Bangladesh, and Thailand. We analysed risk factors for mortality among these cases using predictive logistic regression. Malnutrition was defined as mid-upper-arm circumference ResultsAmong 2189 cases, 76 (3·6%) died. Mortality was associated with oxygen saturation ConclusionsAlthough it focuses on treatment failure in hospital, this study supports the proposal for better risk stratification of children with LCWI pneumonia. Those who have hypoxaemia, any malnutrition or those who were born to HIV positive mothers, experience poorer outcomes than other children with LCWI pneumonia. Consistent identification of these risk factors should be prioritised and children with at least one of these risk factors should not be managed in the community.

Abstract Background Understanding spatial variations in health outcomes is a fundamental component in the design of effective, efficient public health strategies. Here we analyse the spatial heterogeneity of low birthweight (LBW) hospital deliveries from a demographic surveillance site on the Kenyan coast. Methods A secondary data analysis on singleton livebirths that occurred between 2011 and 2021 within the rural areas of the Kilifi Health and demographic surveillance system (KHDSS) was undertaken. Individual-level data was aggregated at enumeration zone (EZ) and sub-location level to estimate the incidence of LBW adjusted for accessibility index using the Gravity model. Finally, spatial variations in LBW were assessed using Martin Kulldorf’s spatial scan statistic under Discrete Poisson distribution. Results Access adjusted LBW incidence was estimated as 87 per 1,000 person years in the under 1 population (95% CI: 80, 97) at the sub-location level similar to EZ. The adjusted incidence ranged from 35 to 159 per 1,000 person years in the under 1 population at sub-location level. There were six significant clusters identified at sub-location level and 17 at EZ level using the spatial scan statistic. Conclusions LBW is a significant health risk on the Kenya coast, possibly under-estimated from previous health information systems, and the risk of LBW is not homogenously distributed across areas served by the County hospital.

Abstract Background Understanding the age patterns of disease is necessary to target interventions to maximise cost-effective impact. New malaria chemoprevention and vaccine initiatives target young children attending routine immunisation services. Here we explore the relationships between age and severity of malaria hospitalisation versus malaria transmission intensity. Methods Clinical data from 21 surveillance hospitals in East Africa were reviewed. Malaria admissions aged 1 month to 14 years from discrete administrative areas since 2006 were identified. Each site-time period was matched to a model estimated community-based age-corrected parasite prevalence to provide predictions of prevalence in childhood (PfPR2–10). Admission with all-cause malaria, severe malaria anaemia (SMA), respiratory distress (RD) and cerebral malaria (CM) were analysed as means and predicted probabilities from Bayesian generalised mixed models. Results 52,684 malaria admissions aged 1 month to 14 years were described at 21 hospitals from 49 site-time locations where PfPR2–10 varied from

Abstract Background The over-distributed pattern of malaria transmission has led to attempts to define malaria “hotspots” that could be targeted for purposes of malaria control in Africa. However, few studies have investigated the use of routine health facility data in the more stable, endemic areas of Africa as a low-cost strategy to identify hotspots. Here the objective was to explore the spatial and temporal dynamics of fever positive rapid diagnostic test (RDT) malaria cases routinely collected along the Kenyan Coast. Methods Data on fever positive RDT cases between March 2018 and February 2019 were obtained from patients presenting to six out-patients health-facilities in a rural area of Kilifi County on the Kenyan Coast. To quantify spatial clustering, homestead level geocoded addresses were used as well as aggregated homesteads level data at enumeration zone. Data were sub-divided into quarterly intervals. Kulldorff’s spatial scan statistics using Bernoulli probability model was used to detect hotspots of fever positive RDTs across all ages, where cases were febrile individuals with a positive test and controls were individuals with a negative test. Results Across 12 months of surveillance, there were nine significant clusters that were identified using the spatial scan statistics among RDT positive fevers. These clusters included 52% of all fever positive RDT cases detected in 29% of the geocoded homesteads in the study area. When the resolution of the data was aggregated at enumeration zone (village) level the hotspots identified were located in the same areas. Only two of the nine hotspots were temporally stable accounting for 2.7% of the homesteads and included 10.8% of all fever positive RDT cases detected. Conclusion Taking together the temporal instability of spatial hotspots and the relatively modest fraction of the malaria cases that they account for; it would seem inadvisable to re-design the sub-county control strategies around targeting hotspots.

Abstract Background Understanding the relationship between malaria infection risk and disease outcomes represents a fundamental component of morbidity and mortality burden estimations. Contemporary data on severe malaria risks among populations of different parasite exposures are scarce. Using surveillance data, we compared rates of paediatric malaria hospitalisation in areas of varying parasite exposure levels. Methods Surveillance data at five public hospitals; Jinja, Mubende, Kabale, Tororo, and Apac were assembled among admissions aged 1 month to 14 years between 2017 and 2018. The address of each admission was used to define a local catchment population where national census data was used to define person-year-exposure to risk. Within each catchment, historical infection prevalence was assembled from previously published data and current infection prevalence defined using 33 population-based school surveys among 3400 children. Poisson regression was used to compute the overall and site-specific incidences with 95% confidence intervals. Results Both current and historical Plasmodium falciparum prevalence varied across the five sites. Current prevalence ranged from

Abstract Background Malaria transmission has recently fallen in many parts of Africa, but systematic descriptions of infection and disease across all age groups are rare. Here, an epidemiological investigation of parasite prevalence, the incidence of fevers associated with infection, severe hospitalized disease and mortality among children older than 6 months and adults on the Kenyan coast is presented. Methods A prospective fever surveillance was undertaken at 6 out-patients (OPD) health-facilities between March 2018 and February 2019. Four community-based, cross sectional surveys of fever history and infection prevalence were completed among randomly selected homestead members from the same communities. Paediatric and adult malaria at Kilifi county hospital was obtained for the 12 months period. Rapid Diagnostic Tests (CareStart™ RDT) to detect HRP2-specific to Plasmodium falciparum was used in the community and the OPD, and microscopy in the hospital. Crude and age-specific incidence rates were computed using Poisson regression. Results Parasite prevalence gradually increased from childhood, reaching 12% by 9 years of age then declining through adolescence into adulthood. The incidence rate of RDT positivity in the OPD followed a similar trend to that of infection prevalence in the community. The incidence of hospitalized malaria from the same community was concentrated among children aged 6 months to 4 years (i.e. 64% and 70% of all hospitalized and severe malaria during the 12 months of surveillance, respectively). Only 3.7% (12/316) of deaths were directly attributable to malaria. Malaria mortality was highest among children aged 6 months–4 years at 0.57 per 1000 person-years (95% CI 0.2, 1.2). Severe malaria and death from malaria was negligible above 15 years of age. Conclusion Under conditions of low transmission intensity, immunity to disease and the fatal consequences of infection appear to continue to be acquired in childhood and faster than anti-parasitic immunity. There was no evidence of an emerging significant burden of severe malaria or malaria mortality among adults. This is contrary to current modelled approaches to disease burden estimation in Africa and has important implications for the targeting of infection prevention strategies based on chemoprevention or vector control.

Abstract Background The most widely used measures of declining burden of malaria across sub-Saharan Africa are predictions from geospatial models. These models apply spatiotemporal autocorrelations and covariates to parasite prevalence data and then use a function of parasite prevalence to predict clinical malaria incidence. We attempted to assess whether trends in malaria cases, based on local surveillance, were similar to those captured by Malaria Atlas Project (MAP) incidence surfaces. Methods We undertook a systematic review (PROSPERO International Prospective Register of Systematic Reviews; ID = CRD42019116834) to identify empirical data on clinical malaria in Africa since 2000, where reports covered at least 5 continuous years. The trends in empirical data were then compared with the trends of time-space matched clinical malaria incidence from MAP using the Spearman rank correlation. The correlations (rho) between changes in empirically observed and modelled estimates of clinical malaria were displayed by forest plots and examined by meta-regression. Results Sixty-seven articles met our inclusion criteria representing 124 sites from 24 African countries. The single most important factor explaining the correlation between empirical observations and modelled predictions was the slope of empirically observed data over time (rho = − 0.989; 95% CI − 0.998, − 0.939; p

The High Burden High Impact (HBHI) strategy for malaria encourages countries to use multiple sources of available data to define the sub-national vulnerabilities to malaria risk, including parasite prevalence. Here, a modelled estimate of Plasmodium falciparum from an updated assembly of community parasite survey data in Kenya, mainland Tanzania, and Uganda is presented and used to provide a more contemporary understanding of the sub-national malaria prevalence stratification across the sub-region for 2019. Malaria prevalence data from surveys undertaken between January 2010 and June 2020 were assembled form each of the three countries. Bayesian spatiotemporal model-based approaches were used to interpolate space-time data at fine spatial resolution adjusting for population, environmental and ecological covariates across the three countries. A total of 18,940 time-space age-standardised and microscopy-converted surveys were assembled of which 14,170 (74.8%) were identified after 2017. The estimated national population-adjusted posterior mean parasite prevalence was 4.7% (95% Bayesian Credible Interval 2.6–36.9) in Kenya, 10.6% (3.4–39.2) in mainland Tanzania, and 9.5% (4.0–48.3) in Uganda. In 2019, more than 12.7 million people resided in communities where parasite prevalence was predicted ≥ 30%, including 6.4%, 12.1% and 6.3% of Kenya, mainland Tanzania and Uganda populations, respectively. Conversely, areas that supported very low parasite prevalence (

IntroductionMalaria surveillance is a key pillar in the control of malaria in Africa. The value of using routinely collected data from health facilities to define malaria risk at community levels remains poorly defined.MethodsFour cross-sectional parasite prevalence surveys were undertaken among residents at 36 enumeration zones in Kilifi county on the Kenyan coast and temporally and spatially matched to fever surveillance at 6 health facilities serving the same communities over 12 months. The age-structured functional form of the relationship between test positivity rate (TPR) and community-based parasite prevalence (PR) was explored through the development of regression models fitted by alternating the linear, exponential and polynomial terms for PR. The predictive ranges of TPR were explored for PR endemicity risk groups of control programmatic value using cut-offs of low (PR ResultsAmong 28,134 febrile patients encountered for malaria diagnostic testing in the health facilities, 12,143 (43.2%: 95% CI: 42.6%, 43.7%) were positive. The overall community PR was 9.9% (95% CI: 9.2%, 10.7%) among 6,479 participants tested for malaria. The polynomial model was the best fitting model for the data that described the algebraic relationship between TPR and PR. In this setting, a TPR of ≥ 49% in all age groups corresponded to an age-standardized PR of ≥ 30%, while a TPR of < 40% corresponded to an age-standardized PR of < 5%.ConclusionA non-linear relationship was observed between the relative change in TPR and changes in the PR, which is likely to have important implications for malaria surveillance programs, especially at the extremes of transmission. However, larger, more spatially diverse data series using routinely collected TPR data matched to community-based infection prevalence data are required to explore the more practical implications of using TPR as a replacement for community PR.

Summary: Background: Vitamin D deficiency is associated with non-communicable and infectious diseases, but the vitamin D status of African populations is not well characterised. We aimed to estimate the prevalence of vitamin D deficiency in children and adults living in Africa. Methods: For this systematic review and meta-analysis, we searched PubMed, Web of Science, Embase, African Journals Online, and African Index Medicus for studies on vitamin D prevalence, published from database inception to Aug 6, 2019, without language restrictions. We included all studies with measured serum 25-hydroxyvitamin D (25[OH]D) concentrations from healthy participants residing in Africa. We excluded case reports and case series, studies that measured 25(OH)D only after a clinical intervention, and studies with only a meeting abstract or unpublished material available. We used a standardised data extraction form to collect information from eligible studies; if the required information was not available in the published report, we requested raw data from the authors. We did a random-effects meta-analysis to obtain the pooled prevalence of vitamin D deficiency in African populations, with use of established cutoffs and mean 25(OH)D concentrations. We stratified meta-analyses by participant age group, geographical region, and residence in rural or urban areas. The study is registered with PROSPERO, number CRD42018112030. Findings: Our search identified 1692 studies, of which 129 studies with 21 474 participants from 23 African countries were included in the systematic review and 119 studies were included in the meta-analyses. The pooled prevalence of low vitamin D status was 18·46% (95% CI 10·66–27·78) with a cutoff of serum 25(OH)D concentration less than 30 nmol/L; 34·22% (26·22–43·68) for a cutoff of less than 50 nmol/L; and 59·54% (51·32–67·50) for a cutoff of less than 75 nmol/L. The overall mean 25(OH)D concentration was 67·78 nmol/L (95% CI 64·50–71·06). There was no evidence of publication bias, although heterogeneity was high (I2 ranged from 98·26% to 99·82%). Mean serum 25(OH)D concentrations were lower in populations living in northern African countries or South Africa compared with sub-Saharan Africa, in urban areas compared with rural areas, in women compared with men, and in newborn babies compared with their mothers. Interpretation: The prevalence of vitamin D deficiency is high in African populations. Public health strategies in Africa should include efforts to prevent, detect, and treat vitamin D deficiency, especially in newborn babies, women, and urban populations. Funding: Wellcome Trust and the DELTAS Africa Initiative.

Abstract Background Use of bednets reduces malaria morbidity and mortality. In Kilifi, Kenya, there was a mass distribution of free nets to children 2500 parasitemia per μl) among children

Abstract Background Malaria transmission intensity is heterogeneous, complicating the implementation of malaria control interventions. We provide a description of the spatial micro-epidemiology of symptomatic malaria and asymptomatic parasitaemia in multiple sites. Methods We assembled data from 19 studies conducted between 1996 and 2015 in seven countries of sub-Saharan Africa with homestead-level geospatial data. Data from each site were used to quantify spatial autocorrelation and examine the temporal stability of hotspots. Parameters from these analyses were examined to identify trends over varying transmission intensity. Results Significant hotspots of malaria transmission were observed in most years and sites. The risk ratios of malaria within hotspots were highest at low malaria positive fractions (MPFs) and decreased with increasing MPF (p

Background: Malaria elimination remains a priority research agenda with the need for interventions that reduce and/or block malaria transmission from humans to mosquitoes. Transmission-blocking vaccines (TBVs) are in development, most of which target the transmission stage (i.e., gametocyte) antigens Pfs230 and Pfs48/45. For these interventions to be implemented, there is a need to understand the naturally acquired immunity to gametocytes. Several studies have measured the prevalence of immune responses to Pfs230 and Pfs48/45 in populations in malaria-endemic areas.Methods: We conducted a systematic review of studies carried out in African populations that measured the prevalence of immune responses to the gametocyte antigens Pfs230 and Pfs48/45. We assessed seroprevalence of antibody responses to the two antigens and investigated the effects of covariates such as age, transmission intensity/endemicity, season, and parasite prevalence on the prevalence of these antibody responses by meta-regression.Results: We identified 12 studies covering 23 sites for inclusion in the analysis. We found that the range of reported seroprevalence to Pfs230 and Pfs48/45 varied widely across studies, from 0 to 64% for Pfs48/45 and from 6 to 72% for Pfs230. We also found a modest association between increased age and increased seroprevalence to Pfs230: adults were associated with higher seroprevalence estimates in comparison to children (β coefficient 0.21, 95% CI: 0.05–0.38, p = 0.042). Methodological factors were the most significant contributors to heterogeneity between studies which prevented calculation of pooled prevalence estimates.Conclusions: Naturally acquired sexual stage immunity, as detected by antibodies to Pfs230 and Pfs48/45, was present in most studies analyzed. Significant between-study heterogeneity was seen, and methodological factors were a major contributor to this, and prevented further analysis of epidemiological and biological factors. This demonstrates a need for standardized protocols for conducting and reporting seroepidemiological analyses.

Background: Insecticide treated nets (ITNs) protect humans against bites from the Anopheles mosquito vectors that transmit malaria, thereby reducing malaria morbidity and mortality. It has been noted that ITN use leads to a switch from indoor to outdoor feeding among these vectors. It might be expected that outdoor feeding would undermine the effectiveness of ITNs that target indoors vectors, but data are limited. Methods: We linked homestead level geospatial data to clinical surveillance data at a primary healthcare facility in Kilifi County in order to map geographical heterogeneity in ITN effectiveness and observed vector feeding behaviour using landing catches and CDC light traps in six selected areas of varying ITN effectiveness. We quantified the interaction between mosquitoes and humans to evaluate whether outdoor vector biting is a potential explanation for the variation in ITN effectiveness. Results: We observed 37% and 46% visits associated with positive malaria slides among ITN users and non-ITN-users, respectively; ITN use was associated with 32% protection from malaria (crude OR = 0.68, 95% CI: 0.64, 0.73). We obtained modification of ITN effectiveness by geographical area (p=0.016), and identified 6 hotspots using the spatial scan statistic. Majority of mosquitoes were caught outdoor (60%) and were of the An. funestus group (75%). The overall propensity to feed at times when most people were asleep was high; the vast majority of the Anopheles mosquitoes were caught at times when most people are indoors asleep. Estimates for the proportion of human-mosquito contact between the first and last hour when most humans were asleep was consistently high across all locations, ranging from 0.83 to 1.00. Conclusion: Our data do not provide evidence of an epidemiological association between microgeographical variations in ITN effectiveness and variations in the microgeographical distribution of outdoor biting.

Background. Malaria control, and finally malaria elimination, requires the identification and targeting of residual foci or hotspots of transmission. However, the level of parasite mixing within and between geographical locations is likely to impact the effectiveness and durability of control interventions and thus should be taken into consideration when developing control programs. Methods. In order to determine the geographic-genetic patterns of Plasmodium falciparum parasite populations at a sub-national level in Kenya, we used the Sequenom platform to genotype 111 genome-wide distributed single nucleotide polymorphic (SNP) positions in 2486 isolates collected from children in 95 primary schools in western Kenya. We analysed these parasite genotypes for genetic structure using principal component analysis and assessed local and global clustering using statistical measures of spatial autocorrelation. We further examined the region for spatial barriers to parasite movement as well as directionality in the patterns of parasite movement. Results. We found no evidence of population structure and little evidence of spatial autocorrelation of parasite genotypes (correlation coefficients

Background. Malaria control, and finally malaria elimination, requires the identification and targeting of residual foci or hotspots of transmission. However, the level of parasite mixing within and between geographical locations is likely to impact the effectiveness and durability of control interventions and thus should be taken into consideration when developing control programs. Methods. In order to determine the geographic-genetic patterns of Plasmodium falciparum parasite populations at a sub-national level in Kenya, we used the Sequenom platform to genotype 111 genome-wide distributed single nucleotide polymorphic (SNP) positions in 2486 isolates collected from children in 95 primary schools in western Kenya. We analysed these parasite genotypes for genetic structure using principal component analysis and assessed local and global clustering using statistical measures of spatial autocorrelation. We further examined the region for spatial barriers to parasite movement as well as directionality in the patterns of parasite movement. Results. We found no evidence of population structure and little evidence of spatial autocorrelation of parasite genotypes (correlation coefficients