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Background: Mansonella perstans is a widespread, but relatively unknown human filarial parasite transmitted by Culicoides biting midges. Although it is found in many parts of sub-Saharan Africa, only few studies have been carried out to deepen the understanding of its ecology, epidemiology, and health consequences. Hence, knowledge about ecological drivers of the vector and parasite distribution, integral to develop spatially explicit models for disease prevention, control, and elimination strategies, is limited. Methodology: We analyzed data from a comprehensive nationwide survey of M. perstans infection conducted in 76 schools across Uganda in 2000–2003, to identify environmental drivers. A suite of Bayesian geostatistical regression models was fitted, and the best fitting model based on the deviance information criterion was utilized to predict M. perstans infection risk for all of Uganda. Additionally, we investigated co-infection rates and co-distribution with Wuchereria bancrofti and Plasmodium spp. infections observed at the same survey by mapping geographically overlapping areas. Principal Findings: Several bioclimatic factors were significantly associated with M. perstans infection levels. A spatial Bayesian regression model showed the best fit, with diurnal temperature range, normalized difference vegetation index, and cattle densities identified as significant covariates. This model was employed to predict M. perstans infection risk at non-sampled locations. The level of co-infection with W. bancrofti was low (0.3%), due to limited geographic overlap. However, where the two infections did overlap geographically, a positive association was found. Conclusions/Significance: This study presents the first geostatistical risk map for M. perstans in Uganda. We confirmed a widespread distribution of M. perstans, and identified important potential drivers of risk. The results provide new insight about the ecologic preferences of this otherwise poorly known filarial parasite and its Culicoides vector species in Uganda, which might be relevant for other settings in sub-Saharan Africa. [ABSTRACT FROM AUTHOR]

Highlights: ▶ Investigation into micro-scale variations of gastropod community diversity. ▶ Bayesian multivariate modeling to predict Biomphalaria abundance. ▶ DNA sequence analysis of S. mansoni cercariae from wild-infected snails. ▶ Population genetics analysis of Biomphalaria at a micro-scale level. ▶ Comparison of micro-scale patterns to lake-wide observations. [Copyright &y& Elsevier]

Background: To reduce the under-five mortality (U5M), fine-gained spatial assessment of the effects of health interventions is critical because national averages can obscure important sub-national disparities. In turn, sub-national estimates can guide control programmes for spatial targeting. The purpose of our study is to quantify associations of interventions with U5M rate at national and sub-national scales in Uganda and to identify interventions associated with the largest reductions in U5M rate at the sub-national scale.Methods: Spatially explicit data on U5M, interventions and sociodemographic indicators were obtained from the 2011 Uganda Demographic and Health Survey (DHS). Climatic data were extracted from remote sensing sources. Bayesian geostatistical Weibull proportional hazards models with spatially varying effects at sub-national scales were utilized to quantify associations between all-cause U5M and interventions at national and regional levels. Bayesian variable selection was employed to select the most important determinants of U5M.Results: At the national level, interventions associated with the highest reduction in U5M were artemisinin-based combination therapy (hazard rate ratio (HRR) = 0.60; 95% Bayesian credible interval (BCI): 0.11, 0.79), initiation of breastfeeding within 1 h of birth (HR = 0.70; 95% BCI: 0.51, 0.86), intermittent preventive treatment (IPTp) (HRR = 0.74; 95% BCI: 0.67, 0.97) and access to insecticide-treated nets (ITN) (HRR = 0.75; 95% BCI: 0.63, 0.84). In Central 2, Mid-Western and South-West, largest reduction in U5M was associated with access to ITNs. In Mid-North and West-Nile, improved source of drinking water explained most of the U5M reduction. In North-East, improved sanitation facilities were associated with the highest decline in U5M. In Kampala and Mid-Eastern, IPTp had the largest associated with U5M. In Central1 and East-Central, oral rehydration solution and postnatal care were associated with highest decreases in U5M respectively.Conclusion: Sub-national estimates of the associations between U5M and interventions can guide control programmes for spatial targeting and accelerate progress towards mortality-related Sustainable Development Goals. [ABSTRACT FROM AUTHOR]

Background: Electronic reporting of routine health facility data in Uganda began with the adoption of the District Health Information Software System version 2 (DHIS2) in 2011. This has improved health facility reporting and overall data quality. In this study, the effects of case management with artemisinin-based combination therapy (ACT) and vector control interventions on space–time patterns of disease incidence were determined using DHIS2 data reported during 2013–2016. Methods: Bayesian spatio-temporal negative binomial models were fitted on district-aggregated monthly malaria cases, reported by two age groups, defined by a cut-off age of 5 years. The effects of interventions were adjusted for socio-economic and climatic factors. Spatial and temporal correlations were taken into account by assuming a conditional autoregressive and a first-order autoregressive AR(1) process on district and monthly specific random effects, respectively. Fourier trigonometric functions were incorporated in the models to take into account seasonal fluctuations in malaria transmission. Results: The temporal variation in incidence was similar in both age groups and depicted a steady decline up to February 2014, followed by an increase from March 2015 onwards. The trends were characterized by a strong bi-annual seasonal pattern with two peaks during May–July and September-December. Average monthly incidence in children < 5 years declined from 74.7 cases (95% CI 72.4–77.1) in 2013 to 49.4 (95% CI 42.9–55.8) per 1000 in 2015 and followed by an increase in 2016 of up to 51.3 (95% CI 42.9–55.8). In individuals ≥ 5 years, a decline in incidence from 2013 to 2015 was followed by an increase in 2016. A 100% increase in insecticide-treated nets (ITN) coverage was associated with a decline in incidence by 44% (95% BCI 28–59%). Similarly, a 100% increase in ACT coverage reduces incidence by 28% (95% BCI 11–45%) and 25% (95% BCI 20–28%) in children < 5 years and individuals ≥ 5 years, respectively. The ITN effect was not statistically important in older individuals. The space–time patterns of malaria incidence in children < 5 are similar to those of parasitaemia risk predicted from the malaria indicator survey of 2014–15. Conclusion: The decline in malaria incidence highlights the effectiveness of vector-control interventions and case management with ACT in Uganda. This calls for optimizing and sustaining interventions to achieve universal coverage and curb reverses in malaria decline. [ABSTRACT FROM AUTHOR]

There is paucity of evidence for the role of health service delivery to the malaria decline in Uganda We developed a methodology to quantify health facility readiness and assessed its role on severe malaria outcomes among lower-level facilities (HCIIIs and HCIIs) in the country. Malaria data was extracted from the Health Management Information System (HMIS). General service and malaria-specific readiness indicators were obtained from the 2013 Uganda service delivery indicator survey. Multiple correspondence analysis (MCA) was used to construct a composite facility readiness score based on multiple factorial axes. Geostatistical models assessed the effect of facility readiness on malaria deaths and severe cases. Malaria readiness was achieved in one-quarter of the facilities. The composite readiness score explained 48% and 46% of the variation in the original indicators compared to 23% and 27%, explained by the first axis alone for HCIIIs and HCIIs, respectively. Mortality rate was 64% (IRR = 0.36, 95% BCI: 0.14-0.61) and 68% (IRR = 0.32, 95% BCI: 0.12-0.54) lower in the medium and high compared to low readiness groups, respectively. A composite readiness index is more informative and consistent than the one based on the first MCA factorial axis. In Uganda, higher facility readiness is associated with a reduced risk of severe malaria outcomes.

Background: In Uganda, malaria vector control interventions and case management with Artemisinin Combination Therapies (ACTs) have been scaled up over the last few years as a result of increased funding. Data on parasitaemia prevalence among children less than 5 years old and coverage of interventions was collected during the first two Malaria Indicator Surveys (MIS) conducted in 2009 and 2014, respectively. In this study, we quantify the effects of control interventions on parasitaemia risk changes between the two MIS in a spatio-temporal analysis., Methods: Bayesian geostatistical and temporal models were fitted on the MIS data of 2009 and 2014. The models took into account geographical misalignment in the locations of the two surveys and adjusted for climatic changes and socio-economic differentials. Parasitaemia risk was predicted over a 2 × 2 km 2 grid and the number of infected children less than 5 years old was estimated. Geostatistical variable selection was applied to identify the most important ITN coverage indicators. A spatially varying coefficient model was used to estimate intervention effects at sub-national level., Results: The coverage of Insecticide Treated Nets (ITNs) and ACTs more than doubled at country and sub-national levels during the period 2009-2014. The coverage of Indoor Residual Spraying (IRS) remained static at all levels. ITNs, IRS, and ACTs were associated with a reduction in parasitaemia odds of 19% (95% BCI: 18-29%), 78% (95% BCI: 67-84%), and 34% (95% BCI: 28-66%), respectively. Intervention effects varied with region. Higher socio-economic status and living in urban areas were associated with parasitaemia odds reduction of 46% (95% BCI: 0.51-0.57) and 57% (95% BCI: 0.40-0.53), respectively. The probability of parasitaemia risk decline in the country was 85% and varied from 70% in the North-East region to 100% in Kampala region. The estimated number of children infected with malaria declined from 2,480,373 in 2009 to 825,636 in 2014., Conclusions: Interventions have had a strong effect on the decline of parasitaemia risk in Uganda during 2009-2014, albeit with varying magnitude in the regions. This success should be sustained by optimizing ITN coverage to achieve universal coverage.

Background: In Uganda, malaria and lymphatic filariasis (causative agent Wuchereria bancrofti) are transmitted by the same vector species of Anopheles mosquitoes, and thus are likely to share common environmental risk factors and overlap in geographical space. In a comprehensive nationwide survey in 2000-2003 the geographical distribution of W. bancrofti was assessed by screening school-aged children for circulating filarial antigens (CFA). Concurrently, blood smears were examined for malaria parasites. In this study, the resultant malariological data are analysed for the first time and the CFA data re-analysed in order to identify risk factors, produce age-stratified prevalence maps for each infection, and to define the geographical patterns of Plasmodium sp. and W. bancrofti co-endemicity., Methods: Logistic regression models were fitted separately for Plasmodium sp. and W. bancrofti within a Bayesian framework. Models contained covariates representing individual-level demographic effects, school-level environmental effects and location-based random effects. Several models were fitted assuming different random effects to allow for spatial structuring and to capture potential non-linearity in the malaria- and filariasis-environment relation. Model-based risk predictions at unobserved locations were obtained via Bayesian predictive distributions for the best fitting models. Maps of predicted hyper-endemic malaria and filariasis were furthermore overlaid in order to define areas of co-endemicity., Results: Plasmodium sp. parasitaemia was found to be highly endemic in most of Uganda, with an overall population adjusted parasitaemia risk of 47.2% in the highest risk age-sex group (boys 5-9 years). High W. bancrofti prevalence was predicted for a much more confined area in northern Uganda, with an overall population adjusted infection risk of 7.2% in the highest risk age-group (14-19 year olds). Observed overall prevalence of individual co-infection was 1.1%, and the two infections overlap geographically with an estimated number of 212,975 children aged 5 - 9 years living in hyper-co-endemic transmission areas., Conclusions: The empirical map of malaria parasitaemia risk for Uganda presented in this paper is the first based on coherent, national survey data, and can serve as a baseline to guide and evaluate the continuous implementation of control activities. Furthermore, geographical areas of overlap with hyper-endemic W. bancrofti transmission have been identified to help provide a better informed platform for integrated control.