Geostatistical model-based estimates of Schistosomiasis prevalence among individuals aged ≤ 20 years in West Africa

Climate change could fuel urinary schistosomiasis transmission in Africa and Europe

The freshwater snail Bulinus truncatus is an important intermediate host for trematode parasites causing urogenital schistosomiasis, a tropical disease affecting over 150 million people. Despite its medical importance, uncertainty remains about its global distribution and the potential impacts of climate change on its future spread. Here, we investigate the distribution of B. truncatus, combining the outputs of correlative and mechanistic modelling methods to fully capitalize on both experimental and occurrence data of the species and to create a more reliable distribution forecast than ever constructed. We constructed ensemble correlative species distribution models using 273 occurrence points collected from different sources and a combination of climatic and (bio)physical environmental variables. Additionally, a mechanistic thermal suitability model was constructed, parameterized by recent life-history data obtained through extensive lab-based snail-temperature experiments and supplemented with an extensive literature review. Our findings reveal that the current suitable habitat for B. truncatus encompasses the Sahel region, the Middle East, and the Mediterranean segment of Africa, stretching from Southern Europe to Mozambique. Regions identified as suitable by both methods generally coincide with areas exhibiting high urogenital schistosomiasis prevalence. Model projections into the future suggest an overall net increase in suitable area of up to 17%. New suitable habitat is in Southern Europe, the Middle East, and large parts of Central Africa, while suitable habitat will be lost in the Sahel region. The change in snail habitat suitability may substantially increase the risk of urogenital schistosomiasis transmission in parts of Africa and Southern Europe while reducing it in the Sahel region.

Geostatistical analysis of active human cysticercosis: Results of a large-scale study in 60 villages in Burkina Faso

Cysticercosis is a neglected tropical disease caused by the larval stage of the zoonotic tapeworm (Taenia solium). While there is a clear spatial component in the occurrence of the parasite, no geostatistical analysis of active human cysticercosis has been conducted yet, nor has such an analysis been conducted for Sub-Saharan Africa, albeit relevant for guiding prevention and control strategies. The goal of this study was to conduct a geostatistical analysis of active human cysticercosis, using data from the baseline cross-sectional component of a large-scale study in 60 villages in Burkina Faso. The outcome was the prevalence of active human cysticercosis (hCC), determined using the B158/B60 Ag-ELISA, while various environmental variables linked with the transmission and spread of the disease were explored as potential explanatory variables for the spatial distribution of T. solium. A generalized linear geostatistical model (GLGM) was run, and prediction maps were generated. Analyses were conducted using data generated at two levels: individual participant data and grouped village data. The best model was selected using a backward variable selection procedure and models were compared using likelihood ratio testing. The best individual-level GLGM included precipitation (increasing values were associated with an increased odds of positive test result), distance to the nearest river (decreased odds) and night land temperature (decreased odds) as predictors for active hCC, whereas the village-level GLGM only retained precipitation and distance to the nearest river. The range of spatial correlation was estimated at 45.0 [95%CI: 34.3; 57.8] meters and 28.2 [95%CI: 14.0; 56.2] km for the individual- and village-level datasets, respectively. Individual- and village-level GLGM unravelled large areas with active hCC predicted prevalence estimates of at least 4% in the south-east, the extreme south, and north-west of the study area, while patches of prevalence estimates below 2% were seen in the north and west. More research designed to analyse the spatial characteristics of hCC is needed with sampling strategies ensuring appropriate characterisation of spatial variability, and incorporating the uncertainty linked to the measurement of outcome and environmental variables in the geostatistical analysis. Trial registration: ClinicalTrials.gov; NCT0309339.

Temporal modelling of Lymnaea natalensis (Krauss, 1848) in tropical aquatic habitats

Lymnaea natalensis is the only snail intermediate host of Fasciola gigantica, the causative agent of fascioliasis, in Nigeria. The species also serves as intermediate host for many other African trematode species of medical and veterinary importance, and it is found throughout the country. However, there is no detailed information on the factors that influence its distribution and seasonal abundance in the tropical aquatic habitats in Nigeria. This study used the geographic information system and remotely sensed data to develop models for predicting the distribution of L. natalensis in South-Western Nigeria. Both land surface temperature (LST) and normalised difference vegetation index (NDVI) were extracted from Landsat satellite imagery; other variables (slope and elevation) were extracted from a digital elevation model (DEM) while rainfall data were retrieved from the European Meteorology Research Programme (EMRP). These environmental variables were integrated into a geographic information system (GIS) to predict suitable habitats of L. natalensis using exploratory regression. A total of 1410 L. natalensis snails were collected vis-à-vis 22 sampling sites. Built-up areas recorded more L. natalensis compared with farmlands. There was no significant difference in the abundance of snails with season (p  0.05). The regression models showed that rainfall, NDVI, and slope were predictors of L. natalensis distribution. The habitats suitable for L. natalensis were central areas, while areas to the north and south were not suitable for L. natalensis.Contribution: The predictive risk models of L. natalensis in the study will be useful in mapping other areas where the snail sampling could not be conducted.

Distribution and Risk of Cutaneous Leishmaniasis in Khyber Pakhtunkhwa, Pakistan

Cutaneous leishmaniasis (CL) is a zoonotic infection caused by obligate intracellular protozoa of the genus Leishmania. This study aimed to investigate CL in Khyber Pakhtunkhwa, Pakistan and to estimate the risk of epidemics. Clinico-epidemiological data of 3188 CL patients were collected from health facilities in 2021. Risk factors were analyzed using the chi-square test. ArcGIS V.10.7.1 was applied for spatial analysis. The association between CL occurrence and climatic variables was examined by Bayesian geostatistical analysis. The clinical data revealed males or individuals younger than 20 years old were more affected. Most patients presented with a single lesion, and the face was the most attacked body part. CL was prevalent in the southern region in winter. A proportional symbol map, a choropleth map, and a digital elevation model map were built to show the distribution of CL. Focal transmission was predicted by inverse distance weighting interpolation. Cluster and outlier analysis identified clusters in Bannu, Dir Lower, and Mardan, and hotspot analysis suggested Bannu as a high-risk foci. Bayesian geostatistical analysis indicated that increasing precipitation and temperature as well as low altitudes were associated with CL infection. The study has provided important information for public health sectors to develop intervention strategies for future CL epidemics.

Effectiveness of Four Different Interventions against Schistosoma haematobium in a Seasonal Transmission Setting of Côte d'Ivoire: A Cluster Randomized Trial

BACKGROUND

Annual mass drug administration (MDA) using praziquantel is the cornerstone of schistosomiasis morbidity control, but is not sufficient to interrupt transmission. We implemented a cluster-randomized trial to compare the effectiveness of four different intervention packages to interrupt transmission of Schistosoma haematobium in a seasonal transmission setting of Côte d'Ivoire.

METHODS

Sixty-four localities with a S. haematobium prevalence in school children aged 13-14 years above 4% were randomly assigned to one of four intervention arms over a 3-year period: (1) the current standard strategy consisting of annual MDA before peak of transmission; (2) annual MDA after peak of transmission; (3) biannual MDA; and (4) standard MDA combined with snail control. The primary outcome was prevalence and intensity of S. haematobium infection in children aged 9-12 years 1 year after the final intervention, using urine filtration performed by experienced microscopists.

RESULTS

By study end, we observed the lowest S. haematobium prevalence in the biannual MDA, compared to the standard treatment arm (0.6% vs. 7.5%; odds ratio [OR] = 0.07, 95% confidence interval [CI] = 0.02 to 0.24). The prevalence in arms 2 and 4 was about 3.5%, which was not statistically significantly different from the standard strategy (both ORs 0.4, 95% CI = 0.1 to ~1.8). New cases of infection were still observed in all arms at study end.

CONCLUSIONS

Biannual MDA was the only regimen that outperformed the standard treatment. All strategies resulted in decreased prevalence of infection, however none of them was able to interrupt transmission of S. haematobium within a 3-year period.

Schistosomiasis with a Focus on Africa

Schistosomiasis is a common neglected tropical disease of impoverished people and livestock in many developing countries in tropical Africa, the Middle East, Asia, and Latin America. Substantial progress has been made in controlling schistosomiasis in some African countries, but the disease still prevails in most parts of sub-Saharan Africa with an estimated 800 million people at risk of infection. Current control strategies rely primarily on treatment with praziquantel, as no vaccine is available; however, treatment alone does not prevent reinfection. There has been emphasis on the use of integrated approaches in the control and elimination of the disease in recent years with the development of health infrastructure and health education. However, there is a need to evaluate the present status of African schistosomiasis, primarily caused by Schistosoma mansoni and S. haematobium, and the factors affecting the disease as the basis for developing more effective control and elimination strategies in the future. This review provides an historical perspective of schistosomiasis in Africa and discusses the current status of control efforts in those countries where the disease is endemic.

Schistosoma haematobium infection and environmental factors in Southwestern Tanzania: A cross-sectional, population-based study

Schistosomiasis is a leading cause of morbidity in Africa. Understanding the disease ecology and environmental factors that influence its distribution is important to guide control efforts. Geographic information systems have increasingly been used in the field of schistosomiasis environmental epidemiology. This study reports prevalences of Schistosoma haematobium infection and uses remotely sensed and questionnaire data from over 17000 participants to identify environmental and socio-demographic factors that are associated with this parasitic infection. Data regarding socio-demographic status and S. haematobium infection were obtained between May 2006 and May 2007 from 17280 participants (53% females, median age = 17 years) in the Mbeya Region, Tanzania. Combined with remotely sensed environmental data (vegetation cover, altitude, rainfall etc.) this data was analyzed to identify environmental and socio-demographic factors associated with S. haematobium infection, using mixed effects logistic regression and geostatistical modelling. The overall prevalence of S. haematobium infection was 5.3% (95% confidence interval (CI): 5.0-5.6%). Multivariable analysis revealed increased odds of infection for school-aged children (5-15 years, odds ratio (OR) = 7.8, CI: 5.9-10.4) and the age groups 15-25 and 25-35 years (15-25 years: OR = 5.8, CI: 4.3-8.0, 25-35 years: OR = 1.6, CI: 1.1-2.4) compared to persons above 35 years of age, for increasing distance to water courses (OR = 1.4, CI: 1.2-1.6 per km) and for proximity to Lake Nyasa (<1 km, OR = 4.5, CI: 1.8-11.4; 1-2 km, OR = 3.5, CI: 1.7-7.5; 2-4 km; OR = 3.3, CI: 1.7-6.6), when compared to distances >4 km. Odds of infection decreased with higher altitude (OR = 0.7, CI: 0.6-0.8 per 100 m increase) and with increasing enhanced vegetation index EVI (OR = 0.2, CI: 0.1-0.4 per 0.1 units). When additionally adjusting for spatial correlation population density became a significant predictor of schistosomiasis infection (OR = 1.3, CI: 1.1-1.5 per 1000 persons/km2) and altitude turned non-significant. We found highly focal geographical patterns of S. haematobium infection in Mbeya Region in Southwestern Tanzania. Despite low overall prevalence our spatially heterogeneous results show that some of the study sites suffer from a considerable burden of S. haematobium infection, which is related to various socio-demographic and environmental factors. Our results could help to design more effective control strategies in the future, especially targeting school-aged children living in low altitude sites and/or crowded areas as the persons at highest need for preventive chemotherapy.

Mapping the Geographic Distribution of Tungiasis in Sub-Saharan Africa

The geographic distribution of tungiasis is poorly understood, despite the frequent occurrence of the disease in marginalized populations of low socioeconomic status. To date, little work is available to define the geography of this neglected tropical disease (NTD). This exploratory study incorporated geostatistical modeling to map the suitability for tungiasis transmission in sub-Saharan Africa (SSA). In SSA, environmental suitability is predicted in 44 countries, including Angola, Nigeria, Ghana, Cameroon, Cote de Ivoire, Mali, Ethiopia, the Democratic Republic of the Congo, Kenya, Gabon, Uganda, Rwanda, Tanzania, Zambia, Zimbabwe, Madagascar, and South Africa. In total, an estimated 668 million people live in suitable areas, 46% (304 million) of which reside in East Africa. These evidence-based maps provide vital evidence of the potential geographic extent of SSA. They will help to guide disease control programs, inform policymakers, and raise awareness at the global level. Likewise, these results will hopefully provide decisionmakers with the pertinent information necessary to lessen morbidity and mortality in communities located in environmentally suitable areas.

Distribution of ascariasis, trichuriasis and hookworm infections in Ogun State, Southwestern Nigeria

BACKGROUND

Ascariasis, Trichuriasis and Hookworm infections poses a considerable public health burden in Sub-Saharan Africa, and a sound understanding of their spatial distribution facilitates to better target control interventions. This study, therefore, assessed the prevalence of the trio, and mapped their spatial distribution in the 20 administrative regions of Ogun State, Nigeria.

METHODS

Parasitological surveys were carried out in 1,499 households across 33 spatially selected communities. Fresh stool samples were collected from 1,027 consenting participants and processed using ether concentration method. The locations of the communities were georeferenced using a GPS device while demographic data were obtained using a standardized form. Data were analysed using SPSS software and visualizations and plotting maps were made in ArcGIS software.

RESULTS

Findings showed that 19 of the 20 regions were endemic for one or more kind of the three infections, with an aggregated prevalence of 17.2%. Ascariasis was the most frequently observed parasitic infection in 28 communities with a prevalence of 13.6%, followed by hookworm infections with a prevalence of 4.6% while Trichuriasis was the least encountered with a prevalence of 1.7%. The spatial distribution of infections ranges between 5.3-49.2% across the regions. The highest and lowest distribution of overall helminth infections was recorded in Egbado South and Egbado North respectively. Nine regions had infection status between 20.0%-49.2%, while 10 regions had infection status between 5.3%-15.8%.

CONCLUSION

This study provides epidemiological data on the prevalence and spatial distribution of ascariasis, trichuriasis and hookworm infections which will add to the baseline data and guide the public health officers in providing appropriate control strategies in the endemic communities.

A Scoping Review of Spatial Analysis Approaches Using Health Survey Data in Sub-Saharan Africa

Spatial analysis has become an increasingly used analytic approach to describe and analyze spatial characteristics of disease burden, but the depth and coverage of its usage for health surveys data in Sub-Saharan Africa are not well known. The objective of this scoping review was to conduct an evaluation of studies using spatial statistics approaches for national health survey data in the SSA region. An organized literature search for studies related to spatial statistics and national health surveys was conducted through PMC, PubMed/Medline, Scopus, NLM Catalog, and Science Direct electronic databases. Of the 4,193 unique articles identified, 153 were included in the final review. Spatial smoothing and prediction methods were predominant (n = 108), followed by spatial description aggregation (n = 25), and spatial autocorrelation and clustering (n = 19). Bayesian statistics methods and lattice data modelling were predominant (n = 108). Most studies focused on malaria and fever (n = 47) followed by health services coverage (n = 38). Only fifteen studies employed nonstandard spatial analyses (e.g., spatial model assessment, joint spatial modelling, accounting for survey design). We recommend that for future spatial analysis using health survey data in the SSA region, there must be an improve recognition and awareness of the potential dangers of a naïve application of spatial statistical methods. We also recommend a wide range of applications using big health data and the future of data science for health systems to monitor and evaluate impacts that are not well understood at local levels.

Estimating uncertainty in geospatial modelling at multiple spatial resolutions: the pattern of delivery via caesarean section in Tanzania

Visualising maternal and newborn health (MNH) outcomes at fine spatial resolutions is crucial to ensuring the most vulnerable women and children are not left behind in improving health. Disaggregated data on life-saving MNH interventions remain difficult to obtain, however, necessitating the use of Bayesian geostatistical models to map outcomes at small geographical areas. While these methods have improved model parameter estimates and precision among spatially correlated health outcomes and allowed for the quantification of uncertainty, few studies have examined the trade-off between higher spatial resolution modelling and how associated uncertainty propagates. Here, we explored the trade-off between model outcomes and associated uncertainty at increasing spatial resolutions by quantifying the posterior distribution of delivery via caesarean section (c-section) in Tanzania. Overall, in modelling delivery via c-section at multiple spatial resolutions, we demonstrated poverty to be negatively correlated across spatial resolutions, suggesting important disparities in obtaining life-saving obstetric surgery persist across sociodemographic factors. Lastly, we found that while uncertainty increased with higher spatial resolution input, model precision was best approximated at the highest spatial resolution, suggesting an important policy trade-off between identifying concealed spatial heterogeneities in health indicators.

Modelling the impact of MAUP on environmental drivers for Schistosoma japonicum prevalence

BACKGROUND

The modifiable areal unit problem (MAUP) arises when the support size of a spatial variable affects the relationship between prevalence and environmental risk factors. Its effect on schistosomiasis modelling studies could lead to unreliable parameter estimates. The present research aims to quantify MAUP effects on environmental drivers of Schistosoma japonicum infection by (i) bringing all covariates to the same spatial support, (ii) estimating individual-level regression parameters at 30 m, 90 m, 250 m, 500 m and 1 km spatial supports, and (iii) quantifying the differences between parameter estimates using five models.

METHODS

We modelled the prevalence of Schistosoma japonicum using sub-provinces health outcome data and pixel-level environmental data. We estimated and compared regression coefficients from convolution models using Bayesian statistics.

RESULTS

Increasing the spatial support to 500 m gradually increased the parameter estimates and their associated uncertainties. Abrupt changes in the parameter estimates occur at 1 km spatial support, resulting in loss of significance of almost all the covariates. No significant differences were found between the predicted values and their uncertainties from the five models. We provide suggestions to define an appropriate spatial data structure for modelling that gives more reliable parameter estimates and a clear relationship between risk factors and the disease.

CONCLUSIONS

Inclusion of quantified MAUP effects was important in this study on schistosomiasis. This will support helminth control programmes by providing reliable parameter estimates at the same spatial support and suggesting the use of an adequate spatial data structure, to generate reliable maps that could guide efficient mass drug administration campaigns.

Currently Available Monitoring and Surveillance Systems for Taenia spp., Echinococcus spp., Schistosoma spp., and Soil-Transmitted Helminths at the Control/Elimination Stage: A Systematic Review

An increasing global focus on neglected tropical diseases (NTDs) has resulted in the set up of numerous control and elimination activities worldwide. This is partly true for Taenia solium taeniasis/cysticercosis, the most important foodborne parasitic infection. Despite substantial progress, adequate monitoring and surveillance (M&S) are required to sustain a status of control/elimination. This is often lacking, especially for T. solium. Therefore, the objective was to conduct a systematic literature review of the currently available M&S systems at the control/elimination stage of the four top-ranked helminth NTDs. Specifically, Taenia spp., Echinococcus spp., Schistosoma spp., and soil-transmitted helminths (STHs) were considered to determine if there are any similarities between their M&S systems and whether certain approaches can be adopted from each other. The systematic review demonstrated that rigorous M&S systems have been designed for the control/elimination stage of both STHs and schistosomiasis, particularly in China. On the other hand, a concept of M&S for Taenia spp. and Echinococcus spp. has not been fully developed yet, due to a lack of epidemiological data and the fact that many endemic countries are far away from reaching control/elimination. Moreover, accurate diagnostic tools for all four diseases are still imperfect, which complicates proper M&S. Finally, there is an urgent need to develop and harmonize/standardize M&S activities in order to reliably determine and compare the epidemiological situation worldwide.

How accurate are modelled birth and pregnancy estimates? Comparison of four models using high resolution maternal health census data in southern Mozambique

Background

Existence of inequalities in quality and access to healthcare services at subnational levels has been identified despite a decline in maternal and perinatal mortality rates at national levels, leading to the need to investigate such conditions using geographical analysis. The need to assess the accuracy of global demographic distribution datasets at all subnational levels arises from the current emphasis on subnational monitoring of maternal and perinatal health progress, by the new targets stated in the Sustainable Development Goals.

Methods

The analysis involved comparison of four models generated using Worldpop methods, incorporating region-specific input data, as measured through the Community Level Intervention for Pre-eclampsia (CLIP) project. Normalised root mean square error was used to determine and compare the models’ prediction errors at different administrative unit levels.

Results

The models’ prediction errors are lower at higher administrative unit levels. All datasets showed the same pattern for both the live birth and pregnancy estimates. The effect of improving spatial resolution and accuracy of input data was more prominent at higher administrative unit levels.

Conclusion

The validation successfully highlighted the impact of spatial resolution and accuracy of maternal and perinatal health data in modelling estimates of pregnancies and live births. There is a need for more data collection techniques that conduct comprehensive censuses like the CLIP project. It is also imperative for such projects to take advantage of the power of mapping tools at their disposal to fill the gaps in the availability of datasets for populated areas.

The use of remotely sensed environmental parameters for spatial and temporal schistosomiasis prediction across climate zones in Ghana

Schistosomiasis control in sub-Saharan Africa is enacted primarily through preventive chemotherapy. Predictive models can play an important role in filling knowledge gaps in the distribution of the disease and help guide the allocation of limited resources. Previous modeling approaches have used localized cross-sectional survey data and environmental data typically collected at a discrete point in time. In this analysis, 8 years (2008-2015) of monthly schistosomiasis cases reported into Ghana's national surveillance system were used to assess temporal and spatial relationships between disease rates and three remotely sensed environmental variables: land surface temperature (LST), normalized difference vegetation index (NDVI), and accumulated precipitation (AP). Furthermore, the analysis was stratified by three major and nine minor climate zones, defined using a new climate classification method. Results showed a downward trend in reported disease rates (~ 1% per month) for all climate zones. Seasonality was present in the north with two peaks (March and September), and in the middle of the country with a single peak (July). Lowest disease rates were observed in December/January across climate zones. Seasonal patterns in the environmental variables and their associations with reported schistosomiasis infection rates varied across climate zones. Precipitation consistently demonstrated a positive association with disease outcome, with a 1-cm increase in rainfall contributing a 0.3-1.6% increase in monthly reported schistosomiasis infection rates. Generally, surveillance of neglected tropical diseases (NTDs) in low-income countries continues to suffer from data quality issues. However, with systematic improvements, our approach demonstrates a way for health departments to use routine surveillance data in combination with publicly available remote sensing data to analyze disease patterns with wide geographic coverage and varying levels of spatial and temporal aggregation.

Arsenicosis in bladder pathology and schistosomiasis in Eggua, Nigeria

Background

Chronic schistosomiasis and arsenic exposure through drinking water are some of the risk factors for bladder cancer. To determine the association of schistosomiasis and arsenicosis with bladder pathologies, 122 individuals from Eggua in southwest Nigeria were recruited for this study.

Methods

Prevalence of schistosomiasis was determined by urine microscopy and PCR. Total urinary arsenic concentration and arsenic levels in three different water sources in the community were assessed by flame atomic absorption spectrometry. Bladder pathologies were investigated by ultrasonography. The data collected were evaluated with chi-square (χ2) and ANOVA tests to examine the relationships among demographic factors, infection, bladder pathologies and urinary arsenic concentrations.

Results

The prevalence and mean intensity of schistosomiasis were 21.3% and 20.7 eggs/10 mL urine, respectively. Arsenic concentration in two of the water sources, River Yewa (0.46 mg/L) and borehole (0.52 mg/L), were above the WHO standard (0.01 mg/L); and the mean concentration in urine samples, 1.17 mg/L, was also above the WHO standard (0.2 mg/L). There was no evidence of an association between bladder pathology and arsenicosis, or between schistosomiasis associated-bladder pathology and arsenicosis (p=0.66).

Conclusions

Arsenicosis is a public health concern in the study population. At the moment no clear roles are envisaged for it in the development of bladder pathologies or urinary schistosomiasis-associated bladder pathologies in Eggua.

Urinary schistosomiasis in Nigeria: a 50 year review of prevalence, distribution and disease burden

We reviewed survey data deposited in the Global Neglected Tropical Diseases database and many other articles on the prevalence and distribution of Schistosoma haematobium in Nigeria. Schistosoma haematobium surveys conducted over the period of 50 years under review using different diagnostic tools revealed that Ogun State has the highest prevalence, followed by Ekiti state, while the lowest prevalence was recorded in Adamawa. No incidence of Schistosoma haematobium was recorded for states such as Akwa Ibom, Bayelsa, Nasarawa, Jigawa and Gombe. In terms of endemicity, this review has shown that Nigeria is divided into four zones: hyperendemic, moderately endemic, low endemic, and no endemic zones. A survey of 47 (15%) of the 323 dams in Nigeria revealed that 45 out of the 47 dams are located in the hyperendemic zone, while the remaining two are located in the moderately endemic zone. Twenty (43%) of the total surveyed dams harboured Bulinus globosus and/or Biomphalaria pfeifferi, the local intermediate hosts of schistosomes, and 18 of these are located in the hyperendemic zone, while the other two are in the moderately endemic zone. We conclude that there is an urgent need to carry out a nationwide survey to help in planning, coordinating, and evaluating schistosomiasis control activities.

Modeling Schistosoma japonicum Infection under Pure Specification Bias: Impact of Environmental Drivers of Infection

Uncertainties in spatial modeling studies of schistosomiasis (SCH) are relevant for the reliable identification of at-risk populations. Ecological fallacy occurs when ecological or group-level analyses, such as spatial aggregations at a specific administrative level, are carried out for an individual-level inference. This could lead to the unreliable identification of at-risk populations, and consequently to fallacies in the drugs’ allocation strategies and their cost-effectiveness. A specific form of ecological fallacy is pure specification bias. The present research aims to quantify its effect on the parameter estimates of various environmental covariates used as drivers for SCH infection. This is done by (i) using a spatial convolution model that removes pure specification bias, (ii) estimating group and individual-level covariate regression parameters, and (iii) quantifying the difference between the parameter estimates and the predicted disease outcomes from the convolution and ecological models. We modeled the prevalence of Schistosoma japonicum using group-level health outcome data, and city-level environmental data as a proxy for individual-level exposure. We included environmental data such as water and vegetation indexes, distance to water bodies, day and night land surface temperature, and elevation. We estimated and compared the convolution and ecological model parameter estimates using Bayesian statistics. Covariate parameter estimates from the convolution and ecological models differed between 0.03 for the nearest distance to water bodies (NDWB), and 0.28 for the normalized difference water index (NDWI). The convolution model presented lower uncertainties in most of the parameter estimates, except for NDWB. High differences in uncertainty were found in night land surface temperature (0.23) and elevation (0.13). No significant differences were found between the predicted values and their uncertainties from both models. The proposed convolution model is able to correct for a pure specification bias by presenting less uncertain parameter estimates. It shows a good predictive performance for the mean prevalence values and for a positive number of infected people. Further research is needed to better understand the spatial extent and support of analysis to reliably explore the role of environmental variables.

Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and local water access profiles

BACKGROUND

Schistosomiasis is a water-related neglected tropical disease. In many endemic low- and middle-income countries, insufficient surveillance and reporting lead to poor characterization of the demographic and geographic distribution of schistosomiasis cases. Hence, modeling is relied upon to predict areas of high transmission and to inform control strategies. We hypothesized that utilizing remotely sensed (RS) environmental data in combination with water, sanitation, and hygiene (WASH) variables could improve on the current predictive modeling approaches.

METHODOLOGY

Schistosoma haematobium prevalence data, collected from 73 rural Ghanaian schools, were used in a random forest model to investigate the predictive capacity of 15 environmental variables derived from RS data (Landsat 8, Sentinel-2, and Global Digital Elevation Model) with fine spatial resolution (10-30 m). Five methods of variable extraction were tested to determine the spatial linkage between school-based prevalence and the environmental conditions of potential transmission sites, including applying the models to known human water contact locations. Lastly, measures of local water access and groundwater quality were incorporated into RS-based models to assess the relative importance of environmental and WASH variables.

PRINCIPAL FINDINGS

Predictive models based on environmental characterization of specific locations where people contact surface water bodies offered some improvement as compared to the traditional approach based on environmental characterization of locations where prevalence is measured. A water index (MNDWI) and topographic variables (elevation and slope) were important environmental risk factors, while overall, groundwater iron concentration predominated in the combined model that included WASH variables.

CONCLUSIONS/SIGNIFICANCE

The study helps to understand localized drivers of schistosomiasis transmission. Specifically, unsatisfactory water quality in boreholes perpetuates reliance on surface water bodies, indirectly increasing schistosomiasis risk and resulting in rapid reinfection (up to 40% prevalence six months following preventive chemotherapy). Considering WASH-related risk factors in schistosomiasis prediction can help shift the focus of control strategies from treating symptoms to reducing exposure.

Interrupting seasonal transmission of Schistosoma haematobium and control of soil-transmitted helminthiasis in northern and central Côte d'Ivoire: a SCORE study protocol

Background

To achieve a world free of schistosomiasis, the objective is to scale up control and elimination efforts in all endemic countries. Where interruption of transmission is considered feasible, countries are encouraged to implement a comprehensive intervention package, including preventive chemotherapy, information, education and communication (IEC), water, sanitation and hygiene (WASH), and snail control. In northern and central Côte d’Ivoire, transmission of Schistosoma haematobium is seasonal and elimination might be achieved. In a cluster-randomised trial, we will assess different treatment schemes to interrupt S. haematobium transmission and control soil-transmitted helminthiasis over a 3-year period. We will compare the impact of (i) arm A: annual mass drug administration (MDA) with praziquantel and albendazole before the peak schistosomiasis transmission season; (ii) arm B: annual MDA after the peak schistosomiasis transmission season; (iii) arm C: two yearly treatments before and after peak schistosomiasis transmission; and (iv) arm D: annual MDA before peak schistosomiasis transmission, coupled with chemical snail control using niclosamide.

Methods/design

The prevalence and intensity of S. haematobium and soil-transmitted helminth infections will be assessed using urine filtration and Kato-Katz thick smears, respectively, in six administrative regions in northern and central parts of Côte d’Ivoire. Once a year, urine and stool samples will be collected and examined from 50 children aged 5–8 years, 100 children aged 9–12 years and 50 adults aged 20–55 years in each of 60 selected villages. Changes in S. haematobium and soil-transmitted helminth prevalence and intensity will be assessed between years and stratified by intervention arm. In the 15 villages randomly assigned to intervention arm D, intermediate host snails will be collected three times per year, before niclosamide is applied to the selected freshwater bodies. The snail abundance and infection rates over time will allow drawing inference on the force of transmission.

Discussion

This cluster-randomised intervention trial will elucidate whether in an area with seasonal transmission, the four different treatment schemes can interrupt S. haematobium transmission and control soil-transmitted helminthiasis. Lessons learned will help to guide schistosomiasis control and elimination programmes elsewhere in Africa.

Trial registration

ISRCTNISRCTN10926858. Registered 21 December 2016. Retrospectively registered.

Emerging Schistosomiasis in Europe: A Need to Quantify the Risks

The recent recurrent outbreaks of urogenital schistosomiasis in the south of Europe were unanticipated and caught scientists and health authorities unprepared. It is now time to learn lessons from these outbreaks and to implement concrete procedures in order to better quantify the risks and prevent future outbreaks of schistosomiasis in Europe. In this context, we propose a reflection on the factors that currently hamper our ability to quantify these risks and argue that we are incapable of predicting future outbreaks. We base our reflexion on an ecological two-step filter concept that drives host-parasite interactions, namely the encounter and the compatibility filters.

Big-data-driven modeling unveils country-wide drivers of endemic schistosomiasis

Schistosomiasis is a parasitic infection that is widespread in sub-Saharan Africa, where it represents a major health problem. We study the drivers of its geographical distribution in Senegal via a spatially explicit network model accounting for epidemiological dynamics driven by local socioeconomic and environmental conditions, and human mobility. The model is parameterized by tapping several available geodatabases and a large dataset of mobile phone traces. It reliably reproduces the observed spatial patterns of regional schistosomiasis prevalence throughout the country, provided that spatial heterogeneity and human mobility are suitably accounted for. Specifically, a fine-grained description of the socioeconomic and environmental heterogeneities involved in local disease transmission is crucial to capturing the spatial variability of disease prevalence, while the inclusion of human mobility significantly improves the explanatory power of the model. Concerning human movement, we find that moderate mobility may reduce disease prevalence, whereas either high or low mobility may result in increased prevalence of infection. The effects of control strategies based on exposure and contamination reduction via improved access to safe water or educational campaigns are also analyzed. To our knowledge, this represents the first application of an integrative schistosomiasis transmission model at a whole-country scale.

Adaptive geostatistical sampling enables efficient identification of malaria hotspots in repeated cross-sectional surveys in rural Malawi

INTRODUCTION

In the context of malaria elimination, interventions will need to target high burden areas to further reduce transmission. Current tools to monitor and report disease burden lack the capacity to continuously detect fine-scale spatial and temporal variations of disease distribution exhibited by malaria. These tools use random sampling techniques that are inefficient for capturing underlying heterogeneity while health facility data in resource-limited settings are inaccurate. Continuous community surveys of malaria burden provide real-time results of local spatio-temporal variation. Adaptive geostatistical design (AGD) improves prediction of outcome of interest compared to current random sampling techniques. We present findings of continuous malaria prevalence surveys using an adaptive sampling design.

METHODS

We conducted repeated cross sectional surveys guided by an adaptive sampling design to monitor the prevalence of malaria parasitaemia and anaemia in children below five years old in the communities living around Majete Wildlife Reserve in Chikwawa district, Southern Malawi. AGD sampling uses previously collected data to sample new locations of high prediction variance or, where prediction exceeds a set threshold. We fitted a geostatistical model to predict malaria prevalence in the area.

FINDINGS

We conducted five rounds of sampling, and tested 876 children aged 6-59 months from 1377 households over a 12-month period. Malaria prevalence prediction maps showed spatial heterogeneity and presence of hotspots-where predicted malaria prevalence was above 30%; predictors of malaria included age, socio-economic status and ownership of insecticide-treated mosquito nets.

CONCLUSIONS

Continuous malaria prevalence surveys using adaptive sampling increased malaria prevalence prediction accuracy. Results from the surveys were readily available after data collection. The tool can assist local managers to target malaria control interventions in areas with the greatest health impact and is ready for assessment in other diseases.

The Role of Spatial Statistics in the Control and Elimination of Neglected Tropical Diseases in Sub-Saharan Africa: A Focus on Human African Trypanosomiasis, Schistosomiasis and Lymphatic Filariasis

Disease control and elimination programmes can benefit greatly from accurate information on the spatial variability of disease risk, particularly when risk is highly spatially heterogeneous. Due to advances in statistical methodology, coupled with the increased availability of geospatial technology, this information is becoming increasingly accessible. In this chapter we describe recent advancements in spatial methods associated with the analysis of disease data measured at the point-level and demonstrate their application to the control and elimination of neglected tropical diseases (NTDs). We further provide information on spatially referenced data sources and software that can be used to create NTD risk maps, concentrating on those that can be freely obtained. Examples relating to three NTDs affecting populations in sub-Saharan Africa are presented throughout the chapter, i.e., human African trypanosomiasis, schistosomiasis and lymphatic filariasis. These three diseases, with differing routes of transmission, control methods and level of spatial heterogeneity, demonstrate the flexibility and applicability of the methods described.

Mapping Soil Transmitted Helminths and Schistosomiasis under Uncertainty: A Systematic Review and Critical Appraisal of Evidence

BACKGROUND

Spatial modelling of STH and schistosomiasis epidemiology is now commonplace. Spatial epidemiological studies help inform decisions regarding the number of people at risk as well as the geographic areas that need to be targeted with mass drug administration; however, limited attention has been given to propagated uncertainties, their interpretation, and consequences for the mapped values. Using currently published literature on the spatial epidemiology of helminth infections we identified: (1) the main uncertainty sources, their definition and quantification and (2) how uncertainty is informative for STH programme managers and scientists working in this domain.

METHODOLOGY/PRINCIPAL FINDINGS

We performed a systematic literature search using the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) protocol. We searched Web of Knowledge and PubMed using a combination of uncertainty, geographic and disease terms. A total of 73 papers fulfilled the inclusion criteria for the systematic review. Only 9% of the studies did not address any element of uncertainty, while 91% of studies quantified uncertainty in the predicted morbidity indicators and 23% of studies mapped it. In addition, 57% of the studies quantified uncertainty in the regression coefficients but only 7% incorporated it in the regression response variable (morbidity indicator). Fifty percent of the studies discussed uncertainty in the covariates but did not quantify it. Uncertainty was mostly defined as precision, and quantified using credible intervals by means of Bayesian approaches.

CONCLUSION/SIGNIFICANCE

None of the studies considered adequately all sources of uncertainties. We highlighted the need for uncertainty in the morbidity indicator and predictor variable to be incorporated into the modelling framework. Study design and spatial support require further attention and uncertainty associated with Earth observation data should be quantified. Finally, more attention should be given to mapping and interpreting uncertainty, since they are relevant to inform decisions regarding the number of people at risk as well as the geographic areas that need to be targeted with mass drug administration.

Natural history of chronic HBV infection in West Africa: a longitudinal population-based study from The Gambia

BACKGROUND

The natural history of chronic HBV infection in sub-Saharan Africa is unknown. Data are required to inform WHO guidelines that are currently based on studies in Europe and Asia.

METHODS

Between 1974 and 2008, serosurveys were repeated in two Gambian villages, and an open cohort of treatment-naive chronic HBV carriers was recruited. Participants were followed to estimate the rates of hepatitis B e (HBeAg) and surface antigen (HBsAg) clearance and incidence of hepatocellular carcinoma (HCC). In 2012-2013, a comprehensive liver assessment was conducted to estimate the prevalence of severe liver disease.

RESULTS

405 chronic carriers (95% genotype E), recruited at a median age of 10.8 years, were followed for a median length of 28.4 years. Annually, 7.4% (95% CI 6.3% to 8.8%) cleared HBeAg and 1.0% (0.8% to 1.2%) cleared HBsAg. The incidence of HCC was 55.5/100 000 carrier-years (95% CI 24.9 to 123.5). In the 2012-2013 survey (n=301), 5.5% (95% CI 3.4% to 9.0%) had significant liver fibrosis. HBV genotype A (versus E), chronic aflatoxin B1 exposure and an HBsAg-positive mother, a proxy for mother-to-infant transmission, were risk factors for liver fibrosis. A small proportion (16.0%) of chronic carriers were infected via mother-to-infant transmission; however, this population represented a large proportion (63.0%) of the cases requiring antiviral therapy.

CONCLUSIONS

The incidence of HCC among chronic HBV carriers in West Africa was higher than that in Europe but lower than rates in East Asia. High risk of severe liver disease among the few who are infected by their mothers underlines the importance of interrupting perinatal transmission in sub-Saharan Africa.

Assessment of the national schistosomiasis control program in a typical region along the Yangtze River, China

Schistosomiasis remains a major public health problem in eastern China, particularly along the Yangtze River Basin. The latest national schistosomiasis control program (NSCP) was implemented in 2005 with the main goal of reducing the rate of infection to less than 5% by 2008 and 1% by 2015. To assess the progress, we applied a Bayesian spatio-temporal model to describe dynamics of schistosomiasis in Guichi, Anhui Province, China, using annual parasitological and environmental data collected within 41 sample villages for the period 2005-2011. Predictive maps of schistosomiasis showed that the disease prevalence remains constant and low. Results of uncertainty analysis, in the form of probability contour maps (PCMs), indicated that the first goal of "infection rate less than 5% by 2008" was fully achieved in the study area. More longitudinal data for schistosomiasis are needed for the assessment of the second goal of "infection rate less than 1% by 2015". Compared with the traditional way of mapping uncertainty (e.g., variance or mean-square error), our PCMs provide more realistic information for schistosomiasis control.

Hepatitis C in HIV-infected individuals: a systematic review and meta-analysis of estimated prevalence in Africa

INTRODUCTION

Although hepatitis C virus (HCV) screening is recommended for all HIV-infected patients initiating antiretroviral therapy, data on epidemiologic characteristics of HCV infection in resource-limited settings are scarce.

METHODS

We searched PubMed and EMBASE for studies assessing the prevalence of HCV infection among HIV-infected individuals in Africa and extracted data on laboratory methods used. Prevalence estimates from individual studies were combined for each country using random-effects meta-analysis. The importance of study design, population and setting as well as type of test (anti-HCV antibody tests and polymerase chain reactions) was examined with meta-regression.

RESULTS

Three randomized controlled trials, 28 cohort studies and 121 cross-sectional analyses with 108,180 HIV-infected individuals from 35 countries were included. The majority of data came from outpatient populations (55%), followed by blood donors (15%) and pregnant women (14%). Based on estimates from 159 study populations, anti-HCV positivity prevalence ranged between 3.3% (95% confidence interval (CI) 1.8-4.7) in Southern Africa and 42.3% (95% CI 4.1-80.5) in North Africa. Study design, type of setting and age distribution did not influence this prevalence significantly. The prevalence of replicating HCV infection, estimated from data of 29 cohorts, was 2.0% (95% CI 1.5-2.6). Ten studies from nine countries reported the HCV genotype of 74 samples, 53% were genotype 1, 24% genotype 2, 14% genotype 4 and 9% genotypes 3, 5 or 6.

CONCLUSIONS

The prevalence of anti-HCV antibodies is high in HIV-infected patients in Africa, but replicating HCV infection is rare and varies widely across countries.

Outbreak of urogenital schistosomiasis in Corsica (France): an epidemiological case study

BACKGROUND

Schistosomiasis is a snail-borne parasitic disease endemic in several tropical and subtropical countries. However, in the summer of 2013, an unexpected outbreak of urogenital schistosomiasis occurred in Corsica, with more than 120 local people or tourists infected. We used a multidisciplinary approach to investigate the epidemiology of urogenital schistosomiasis in Corsica, aiming to elucidate the origin of the outbreak.

METHODS

We did parasitological and malacological surveys at nine potential sites of infection. With the snails found, we carried out snail-parasite compatibility experiments by exposing snails to schistosome larvae recovered from the urine of a locally infected Corsican patient. Genetic analysis of both mitochondrial (cox1) and nuclear (internal transcribed spacer) DNA data from the Schistosoma eggs or miracidia recovered from the infected patients was conducted to elucidate the epidemiology of this outbreak.

FINDINGS

We identified two main infection foci along the Cavu River, with many Bulinus truncatus snails found in both locations. Of the 3544 snails recovered across all sites, none were naturally infected, but laboratory-based experimental infections confirmed their compatibility with the schistosomes isolated from patients. Molecular characterisation of 73 eggs or miracidia isolated from 12 patients showed infection with Schistosoma haematobium, S haematobium-Schistosoma bovis hybrids, and S bovis. Further sequence data analysis also showed that the Corsican schistosomes were closely related to those from Senegal in west Africa.

INTERPRETATION

The freshwater swimming pools of the Cavu River harbour many B truncatus snails, which are capable of transmitting S haematobium-group schistosomes. Our molecular data suggest that the parasites were imported into Corsica by individuals infected in west Africa, specifically Senegal. Hybridisation between S haematobium and the cattle schistosome S bovis had a putative role in this outbreak, showing how easily and rapidly urogenital schistosomiasis can be introduced and spread into novel areas where Bulinus snails are endemic, and how hybridisation could increase the colonisation potential of schistosomes. Furthermore our results show the potential risk of schistosomiasis outbreaks in other European areas, warranting close monitoring and surveillance of all potential transmission foci.

FUNDING

WHO, ANSES, RICET, and the Ministry of Health and Consumption.

Bayesian risk profiling of soil-transmitted helminth infections and estimates of preventive chemotherapy for school-aged children in Côte d'Ivoire

Background

Soil-transmitted helminthiasis affects more than a billion people in the world and accounts for a global burden of 5.1 million disability-adjusted life years. The objectives of this study were (i) to map and predict the risk of soil-transmitted helminth infections among school-aged children in Côte d’Ivoire; (ii) to estimate school-aged children population-adjusted risk; and (iii) to estimate annual needs for preventive chemotherapy.

Methods

In late 2011/early 2012, a cross-sectional survey was carried out among school-aged children in 92 localities of Côte d’Ivoire. Children provided a single stool sample that was subjected to duplicate Kato-Katz thick smears for the diagnosis of soil-transmitted helminths. A Bayesian geostatistical variable selection approach was employed to identify environmental and socioeconomic risk factors for soil-transmitted helminth infections. Bayesian kriging was used to predict soil-transmitted helminth infections on a grid of 1 × 1 km spatial resolution. The number of school-aged children infected with soil-transmitted helminths and the amount of doses needed for preventive chemotherapy according to World Health Organization guidelines were estimated.

Results

Parasitological data were available from 5246 children aged 5–16 years. Helminth infections with hookworm were predominant (17.2 %). Ascaris lumbricoides and Trichuris trichiura were rarely found; overall prevalences were 1.9 % and 1.2 %, respectively. Bayesian geostatistical variable selection identified rural setting for hookworm, soil acidity and soil moisture for A. lumbricoides, and rainfall coefficient of variation for T. trichiura as main predictors of infection. The estimated school-aged children population-adjusted risk of soil-transmitted helminth infection in Côte d’Ivoire is 15.5 % (95 % confidence interval: 14.2–17.0 %). We estimate that approximately 1.3 million doses of albendazole or mebendazole are required for school-based preventive chemotherapy, and we provide school-aged children-adjusted risk aggregated at health district level.

Conclusion

We provide the first soil-transmitted helminthiasis risk profile for entire Côte d’Ivoire, based on a robust Bayesian geostatistical framework. Our model-based estimates of treatment needs and risk maps on health district level may guide the national control program in spatial targeting of annual interventions.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-016-1446-0) contains supplementary material, which is available to authorized users.

Co-endemicity of Pulmonary Tuberculosis and Intestinal Helminth Infection in the People's Republic of China

Both pulmonary tuberculosis (PTB) and intestinal helminth infection (IHI) affect millions of individuals every year in China. However, the national-scale estimation of prevalence predictors and prevalence maps for these diseases, as well as co-endemic relative risk (RR) maps of both diseases' prevalence are not well developed. There are co-endemic, high prevalence areas of both diseases, whose delimitation is essential for devising effective control strategies. Bayesian geostatistical logistic regression models including socio-economic, climatic, geographical and environmental predictors were fitted separately for active PTB and IHI based on data from the national surveys for PTB and major human parasitic diseases that were completed in 2010 and 2004, respectively. Prevalence maps and co-endemic RR maps were constructed for both diseases by means of Bayesian Kriging model and Bayesian shared component model capable of appraising the fraction of variance of spatial RRs shared by both diseases, and those specific for each one, under an assumption that there are unobserved covariates common to both diseases. Our results indicate that gross domestic product (GDP) per capita had a negative association, while rural regions, the arid and polar zones and elevation had positive association with active PTB prevalence; for the IHI prevalence, GDP per capita and distance to water bodies had a negative association, the equatorial and warm zones and the normalized difference vegetation index had a positive association. Moderate to high prevalence of active PTB and low prevalence of IHI were predicted in western regions, low to moderate prevalence of active PTB and low prevalence of IHI were predicted in north-central regions and the southeast coastal regions, and moderate to high prevalence of active PTB and high prevalence of IHI were predicted in the south-western regions. Thus, co-endemic areas of active PTB and IHI were located in the south-western regions of China, which might be determined by socio-economic factors, such as GDP per capita.

Ecological Drivers of Mansonella perstans Infection in Uganda and Patterns of Co-endemicity with Lymphatic Filariasis and Malaria

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.

Local spatial clustering of stunting and wasting among children under the age of 5 years: implications for intervention strategies

OBJECTIVE

The present study aimed to evaluate the clustering of undernutrition indicators of children under the age of 5 years in relation to different scales.

DESIGN

A community-based cross-sectional study design was employed. We collected anthropometric data, geographic locations/elevations of households and other data from visited households. We used a retrospective purely spatial Poisson probability model to identify and locate clusters (high rates) of stunting and wasting using the software SaTScan™ version 9·1·1. We ran a logistic regression model to help evaluate the causes of clustering. Settings Six villages in the Meskane Mareko District (38·45763°E, 8·042144°N) of southern Ethiopia.

SUBJECTS

We surveyed 2371 children aged <5 years, who were found in 1744 households.

RESULTS

We found a micro-level variation in the risk of stunting and wasting within the studied district. We found the most likely significant clusters for wasting and severe wasting in two of the six villages. For stunting, a single large cluster size of 390 cases (304·19 expected) in 756 households was identified (relative risk=1·48, P<0·01). For severe stunting, a single cluster size of 106 cases (69·39 expected) in 364 households was identified (relative risk=1·69, P=0·035).

CONCLUSIONS

We conclude that the distribution of wasting and stunting was partly spatially structured. We identified distinct areas within and between villages that have a higher risk than the underlying at-risk population. Our analysis identified the spatial locations of high-risk areas for stunting that could be an input for geographically targeting and optimizing nutritional interventions.

Earth Observation, Spatial Data Quality, and Neglected Tropical Diseases

Earth observation (EO) is the use of remote sensing and in situ observations to gather data on the environment. It finds increasing application in the study of environmentally modulated neglected tropical diseases (NTDs). Obtaining and assuring the quality of the relevant spatially and temporally indexed EO data remain challenges. Our objective was to review the Earth observation products currently used in studies of NTD epidemiology and to discuss fundamental issues relating to spatial data quality (SDQ), which limit the utilization of EO and pose challenges for its more effective use. We searched Web of Science and PubMed for studies related to EO and echinococossis, leptospirosis, schistosomiasis, and soil-transmitted helminth infections. Relevant literature was also identified from the bibliographies of those papers. We found that extensive use is made of EO products in the study of NTD epidemiology; however, the quality of these products is usually given little explicit attention. We review key issues in SDQ concerning spatial and temporal scale, uncertainty, and the documentation and use of quality information. We give examples of how these issues may interact with uncertainty in NTD data to affect the output of an epidemiological analysis. We conclude that researchers should give careful attention to SDQ when designing NTD spatial-epidemiological studies. This should be used to inform uncertainty analysis in the epidemiological study. SDQ should be documented and made available to other researchers.

Modeling and Validation of Environmental Suitability for Schistosomiasis Transmission Using Remote Sensing

BACKGROUND

Schistosomiasis is the most widespread water-based disease in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and human water contact patterns. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. We investigated the potential of remote sensing to characterize habitat conditions of parasite and intermediate host snails and discuss the relevance for public health.

METHODOLOGY

We employed high-resolution remote sensing data, environmental field measurements, and ecological data to model environmental suitability for schistosomiasis-related parasite and snail species. The model was developed for Burkina Faso using a habitat suitability index (HSI). The plausibility of remote sensing habitat variables was validated using field measurements. The established model was transferred to different ecological settings in Côte d'Ivoire and validated against readily available survey data from school-aged children.

PRINCIPAL FINDINGS

Environmental suitability for schistosomiasis transmission was spatially delineated and quantified by seven habitat variables derived from remote sensing data. The strengths and weaknesses highlighted by the plausibility analysis showed that temporal dynamic water and vegetation measures were particularly useful to model parasite and snail habitat suitability, whereas the measurement of water surface temperature and topographic variables did not perform appropriately. The transferability of the model showed significant relations between the HSI and infection prevalence in study sites of Côte d'Ivoire.

CONCLUSIONS/SIGNIFICANCE

A predictive map of environmental suitability for schistosomiasis transmission can support measures to gain and sustain control. This is particularly relevant as emphasis is shifting from morbidity control to interrupting transmission. Further validation of our mechanistic model needs to be complemented by field data of parasite- and snail-related fitness. Our model provides a useful tool to monitor the development of new hotspots of potential schistosomiasis transmission based on regularly updated remote sensing data.

Fine resolution mapping of population age-structures for health and development applications

The age-group composition of populations varies considerably across the world, and obtaining accurate, spatially detailed estimates of numbers of children under 5 years is important in designing vaccination strategies, educational planning or maternal healthcare delivery. Traditionally, such estimates are derived from population censuses, but these can often be unreliable, outdated and of coarse resolution for resource-poor settings. Focusing on Nigeria, we use nationally representative household surveys and their cluster locations to predict the proportion of the under-five population in 1 × 1 km using a Bayesian hierarchical spatio-temporal model. Results showed that land cover, travel time to major settlements, night-time lights and vegetation index were good predictors and that accounting for fine-scale variation, rather than assuming a uniform proportion of under 5 year olds can result in significant differences in health metrics. The largest gaps in estimated bednet and vaccination coverage were in Kano, Katsina and Jigawa. Geolocated household surveys are a valuable resource for providing detailed, contemporary and regularly updated population age-structure data in the absence of recent census data. By combining these with covariate layers, age-structure maps of unprecedented detail can be produced to guide the targeting of interventions in resource-poor settings.

Case-Control Study of Posttreatment Regression of Urinary Tract Morbidity Among Adults in Schistosoma haematobium-Endemic Communities in Kwale County, Kenya

Previous population-based studies have examined treatment impact on Schistosoma-associated urinary tract disease among children, but much less is known about longer-term treatment benefits for affected adult populations in areas where risk of recurrent infection is high. In communities in Msambweni, along the Kenya coast, we identified, using a portable ultrasound, 77 adults (aged 17-85) with moderate-to-severe obstructive uropathy or bladder disease due to Schistosoma haematobium. Treatment response was assessed by repeat ultrasound 1-2 years after praziquantel (PZQ) therapy and compared with interval changes among age- and sex-matched infected/treated control subjects who did not have urinary tract abnormalities at the time of initial examination. Of the 77 affected adults, 62 (81%) had improvement in bladder and/or kidney scores after treatment, 14 (18%) had no change, and one (1.3%) had progression of disease. Of the 77 controls, 75 (97%) remained disease free by ultrasound, while two (3%) had apparent progression with abnormal findings on follow-up examination. We conclude that PZQ therapy for S. haematobium is effective in significantly reducing urinary tract morbidity from urogenital schistosomiasis among adult age groups, and affected adults stand to benefit from inclusion in mass treatment campaigns.

Taenia solium taeniosis/cysticercosis and the co-distribution with schistosomiasis in Africa

Background

This study aimed to map the distribution of Taenia solium taeniosis/cysticercosis and the co-distribution with schistosomiasis in Africa. These two major neglected tropical diseases are presumed to be widely distributed in Africa, but currently the level of co-distribution is unclear.

Methods

A literature search on T. solium taeniosis/cysticercosis was performed to compile all known studies on the presence of T. solium and apparent prevalence of taeniosis and porcine cysticercosis in Africa. Studies were geo-referenced using an online gazetteer. A Bayesian framework was used to combine the epidemiological data on the apparent prevalence with external information on test characteristics to estimate informed district-level prevalence of taeniosis and porcine cysticercosis. Districts with T. solium taeniosis/cysticercosis presence were cross-referenced with the Global Neglected Tropical Diseases Database for schistosomiasis presence.

Results

The search strategies identified 141 reports of T. solium in Africa from 1985 to 2014 from a total of 476 districts in 29 countries, 20 with porcine cysticercosis, 22 with human cysticercosis, and 16 with taeniosis, in addition to 2 countries identified from OIE reports. All 31 countries were considered, on national scale, to have co-distribution with schistosomiasis. Presence of both parasites was confirmed in 124 districts in 17 countries. The informed prevalence of taeniosis and porcine cysticercosis were estimated for 14 and 41 districts in 10 and 13 countries, respectively.

Conclusions

With the paucity of data, T. solium infection is grossly under-reported and expected to be more widespread than this study suggests. In areas where co-distribution occurs there is a need for increased emphasis on evaluation of integrated intervention approaches for these two helminth infections and allocation of resources for evaluating the extent of adverse effects caused by mass drug administration.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-015-0938-7) contains supplementary material, which is available to authorized users.

Spatial distribution of schistosomiasis and treatment needs in sub-Saharan Africa: a systematic review and geostatistical analysis

BACKGROUND

Schistosomiasis affects more than 200 million individuals, mostly in sub-Saharan Africa, but empirical estimates of the disease burden in this region are unavailable. We used geostatistical modelling to produce high-resolution risk estimates of infection with Schistosoma spp and of the number of doses of praziquantel treatment needed to prevent morbidity at different administrative levels in 44 countries.

METHODS

We did a systematic review to identify surveys including schistosomiasis prevalence data in sub-Saharan Africa via PubMed, ISI Web of Science, and African Journals Online, from inception to May 2, 2014, with no restriction of language, survey date, or study design. We used Bayesian geostatistical meta-analysis and rigorous variable selection to predict infection risk over a grid of 1 155 818 pixels at 5 × 5 km, on the basis of environmental and socioeconomic predictors and to calculate the number of doses of praziquantel needed for prevention of morbidity.

FINDINGS

The literature search identified Schistosoma haematobium and Schistosoma mansoni surveys done in, respectively, 9318 and 9140 unique locations. Infection risk decreased from 2000 onwards, yet estimates suggest that 163 million (95% Bayesian credible interval [CrI] 155 million to 172 million; 18·5%, 17·6-19·5) of the sub-Saharan African population was infected in 2012. Mozambique had the highest prevalence of schistosomiasis in school-aged children (52·8%, 95% CrI 48·7-57·8). Low-risk countries (prevalence among school-aged children lower than 10%) included Burundi, Equatorial Guinea, Eritrea, and Rwanda. The numbers of doses of praziquantel needed per year were estimated to be 123 million (95% CrI 121 million to 125 million) for school-aged children and 247 million (239 million to 256 million) for the entire population.

INTERPRETATION

Our results will inform policy makers about the number of treatments needed at different levels and will guide the spatial targeting of schistosomiasis control interventions.

FUNDING

European Research Council, China Scholarship Council, UBS Optimus Foundation, and Swiss National Science Foundation.

Bayesian geostatistical model-based estimates of soil-transmitted helminth infection in Nigeria, including annual deworming requirements

Background

The acceleration of the control of soil-transmitted helminth (STH) infections in Nigeria, emphasizing preventive chemotherapy, has become imperative in light of the global fight against neglected tropical diseases. Predictive risk maps are an important tool to guide and support control activities.

Methodology

STH infection prevalence data were obtained from surveys carried out in 2011 using standard protocols. Data were geo-referenced and collated in a nationwide, geographic information system database. Bayesian geostatistical models with remotely sensed environmental covariates and variable selection procedures were utilized to predict the spatial distribution of STH infections in Nigeria.

Principal Findings

We found that hookworm, Ascaris lumbricoides, and Trichuris trichiura infections are endemic in 482 (86.8%), 305 (55.0%), and 55 (9.9%) locations, respectively. Hookworm and A. lumbricoides infection co-exist in 16 states, while the three species are co-endemic in 12 states. Overall, STHs are endemic in 20 of the 36 states of Nigeria, including the Federal Capital Territory of Abuja. The observed prevalence at endemic locations ranged from 1.7% to 51.7% for hookworm, from 1.6% to 77.8% for A. lumbricoides, and from 1.0% to 25.5% for T. trichiura. Model-based predictions ranged from 0.7% to 51.0% for hookworm, from 0.1% to 82.6% for A. lumbricoides, and from 0.0% to 18.5% for T. trichiura. Our models suggest that day land surface temperature and dense vegetation are important predictors of the spatial distribution of STH infection in Nigeria. In 2011, a total of 5.7 million (13.8%) school-aged children were predicted to be infected with STHs in Nigeria. Mass treatment at the local government area level for annual or bi-annual treatment of the school-aged population in Nigeria in 2011, based on World Health Organization prevalence thresholds, were estimated at 10.2 million tablets.

Conclusions/Significance

The predictive risk maps and estimated deworming needs presented here will be helpful for escalating the control and spatial targeting of interventions against STH infections in Nigeria.

Infections with three kinds of parasitic worms—hookworm, roundworm, and whipworm—are collectively known as soil-transmitted helminths (STHs). These parasitic worm infections are widespread in Nigeria, but the exact distribution is poorly understood. In view of the global commitment to control STH infections, there is a need to accelerate the mapping of STH infections to guide control interventions, such as large-scale administration of deworming drugs. In this study, we collated survey data from the year 2011 for Nigeria. The data were utilized to predict the distribution of STH infection based on environmental and socioeconomic covariates, and employing a Bayesian geostatistical modeling approach. Our results indicated that STH infections are widely distributed across Nigeria with prevalence estimates as high as 83% for roundworm, 50% for hookworm, and 19% for whipworm infections at specific survey locations. We predict that 5.7 million school-aged children were infected with STHs. The numbers of deworming tablets for annual or bi-annual treatment of the school-aged population at local government areas level in Nigeria for 2011 were estimated to be 10.2 million.

Risk profiling of schistosomiasis using remote sensing: approaches, challenges and outlook

BACKGROUND

Schistosomiasis is a water-based disease that affects an estimated 250 million people, mainly in sub-Saharan Africa. The transmission of schistosomiasis is spatially and temporally restricted to freshwater bodies that contain schistosome cercariae released from specific snails that act as intermediate hosts. Our objective was to assess the contribution of remote sensing applications and to identify remaining challenges in its optimal application for schistosomiasis risk profiling in order to support public health authorities to better target control interventions.

METHODS

We reviewed the literature (i) to deepen our understanding of the ecology and the epidemiology of schistosomiasis, placing particular emphasis on remote sensing; and (ii) to fill an identified gap, namely interdisciplinary research that bridges different strands of scientific inquiry to enhance spatially explicit risk profiling. As a first step, we reviewed key factors that govern schistosomiasis risk. Secondly, we examined remote sensing data and variables that have been used for risk profiling of schistosomiasis. Thirdly, the linkage between the ecological consequence of environmental conditions and the respective measure of remote sensing data were synthesised.

RESULTS

We found that the potential of remote sensing data for spatial risk profiling of schistosomiasis is - in principle - far greater than explored thus far. Importantly though, the application of remote sensing data requires a tailored approach that must be optimised by selecting specific remote sensing variables, considering the appropriate scale of observation and modelling within ecozones. Interestingly, prior studies that linked prevalence of Schistosoma infection to remotely sensed data did not reflect that there is a spatial gap between the parasite and intermediate host snail habitats where disease transmission occurs, and the location (community or school) where prevalence measures are usually derived from.

CONCLUSIONS

Our findings imply that the potential of remote sensing data for risk profiling of schistosomiasis and other neglected tropical diseases has yet to be fully exploited.

In Ivorian school-age children, infection with hookworm does not reduce dietary iron absorption or systemic iron utilization, whereas afebrile Plasmodium falciparum infection reduces iron absorption by half

BACKGROUND

In sub-Saharan Africa, parasitic diseases and low bioavailable iron intake are major causes of anemia. Anemia results from inflammation, preventing iron recycling and decreasing dietary iron absorption. Hookworm, Plasmodium, and Schistosoma infections contribute to anemia, but their influence on dietary iron absorption and recycling is unknown.

OBJECTIVE

The objective was to measure inflammation biomarkers, hepcidin, iron absorption, and utilization pre- and posttreatment in children with afebrile malaria, hookworm, and Schistosoma haematobium infection.

DESIGN

Ivorian children aged 11-17 y with afebrile Plasmodium falciparum (n = 17), hookworm (n = 16), or S. haematobium infection (n = 8) consumed a syrup containing 3 mg ⁵⁷Fe as ferrous sulfate and received an intravenous infusion of 50 μg ⁵⁸Fe as ferrous citrate. Children were treated for their respective infection, and the iron studies were repeated 4 wk later. Iron and inflammation biomarkers and hepcidin were measured.

RESULTS

Geometric mean iron absorptions in the afebrile malaria and hookworm groups were 12.9% and 32.2% (P < 0.001) before treatment and 23.6% and 30.0% (P = 0.113) after treatment, respectively. Treatment of afebrile malaria reduced inflammation (P < 0.001) and serum hepcidin (P = 0.004) and improved iron absorption (P = 0.003). Treatment of hookworm infection neither affected inflammation biomarkers nor altered iron absorption. Similarly, there was a lack of treatment effects in the S. haematobium-infected group; however, the small sample size limits conclusions. Geometric mean iron utilization ranged between 79.1% and 88.0% in the afebrile malaria and hookworm groups with no significant differences pre- and posttreatment.

CONCLUSIONS

In school-age children, hookworm infection does not produce inflammation or increase serum hepcidin, and it does not influence iron absorption or utilization. In contrast, afebrile malaria causes inflammation, increases hepcidin, and reduces iron absorption but not utilization. These findings provide insights into the iron metabolism and the etiology of anemia in parasitic infections.

Geostatistical modelling of soil-transmitted helminth infection in Cambodia: do socioeconomic factors improve predictions?

Soil-transmitted helminth infections are intimately connected with poverty. Yet, there is a paucity of using socioeconomic proxies in spatially explicit risk profiling. We compiled household-level socioeconomic data pertaining to sanitation, drinking-water, education and nutrition from readily available Demographic and Health Surveys, Multiple Indicator Cluster Surveys and World Health Surveys for Cambodia and aggregated the data at village level. We conducted a systematic review to identify parasitological surveys and made every effort possible to extract, georeference and upload the data in the open source Global Neglected Tropical Diseases database. Bayesian geostatistical models were employed to spatially align the village-aggregated socioeconomic predictors with the soil-transmitted helminth infection data. The risk of soil-transmitted helminth infection was predicted at a grid of 1×1km covering Cambodia. Additionally, two separate individual-level spatial analyses were carried out, for Takeo and Preah Vihear provinces, to assess and quantify the association between soil-transmitted helminth infection and socioeconomic indicators at an individual level. Overall, we obtained socioeconomic proxies from 1624 locations across the country. Surveys focussing on soil-transmitted helminth infections were extracted from 16 sources reporting data from 238 unique locations. We found that the risk of soil-transmitted helminth infection from 2000 onwards was considerably lower than in surveys conducted earlier. Population-adjusted prevalences for school-aged children from 2000 onwards were 28.7% for hookworm, 1.5% for Ascaris lumbricoides and 0.9% for Trichuris trichiura. Surprisingly, at the country-wide analyses, we did not find any significant association between soil-transmitted helminth infection and village-aggregated socioeconomic proxies. Based also on the individual-level analyses we conclude that socioeconomic proxies might not be good predictors at an aggregated large-scale analysis due to their large between- and within-village heterogeneity. Specific information of both the infection risk and potential predictors might be needed to obtain any existing association. The presented soil-transmitted helminth infection risk estimates for Cambodia can be used for guiding and evaluating control and elimination efforts.

Bayesian risk mapping and model-based estimation of Schistosoma haematobium-Schistosoma mansoni co-distribution in Côte d'Ivoire

Background

Schistosoma haematobium and Schistosoma mansoni are blood flukes that cause urogenital and intestinal schistosomiasis, respectively. In Côte d′Ivoire, both species are endemic and control efforts are being scaled up. Accurate knowledge of the geographical distribution, including delineation of high-risk areas, is a central feature for spatial targeting of interventions. Thus far, model-based predictive risk mapping of schistosomiasis has relied on historical data of separate parasite species.

Methodology

We analyzed data pertaining to Schistosoma infection among school-aged children obtained from a national, cross-sectional survey conducted between November 2011 and February 2012. More than 5,000 children in 92 schools across Côte d′Ivoire participated. Bayesian geostatistical multinomial models were developed to assess infection risk, including S. haematobium–S. mansoni co-infection. The predicted risk of schistosomiasis was utilized to estimate the number of children that need preventive chemotherapy with praziquantel according to World Health Organization guidelines.

Principal Findings

We estimated that 8.9% of school-aged children in Côte d′Ivoire are affected by schistosomiasis; 5.3% with S. haematobium and 3.8% with S. mansoni. Approximately 2 million annualized praziquantel treatments would be required for preventive chemotherapy at health districts level. The distinct spatial patterns of S. haematobium and S. mansoni imply that co-infection is of little importance across the country.

Conclusions/Significance

We provide a comprehensive analysis of the spatial distribution of schistosomiasis risk among school-aged children in Côte d′Ivoire and a strong empirical basis for a rational targeting of control interventions.

Two types of blood-dwelling parasitic worms that cause schistosomiasis (i.e., Schistosoma haematobium and Schistosoma mansoni) are endemic in Côte d′Ivoire, West Africa. Reliable information on their geographical distribution is needed to plan and guide the national control program. Recently, control efforts have been intensified. There is a need to update risk maps that, historically, have been based on data specific to each type of parasite. In late 2011 and early 2012, we conducted a cross-sectional survey in 92 schools all over Côte d′Ivoire. We used Bayesian geostatistical multinomial models to estimate the risk for each infection, as well as co-infection. We estimated that slightly less than 10% of school-aged children are affected by schistosomiasis (5.3% with S. haematobium and 3.8% with S. mansoni). To control schistosomiasis with the deworming drug praziquantel, approximately 2 million treatments would be necessary each year. The distinct spatial patterns of S. haematobium and S. mansoni imply that co-infection with these two types of parasitic worms is rare across the country. Our results provide a detailed analysis of the spatial distribution of schistosomiasis risk among school-aged children in Côte d′Ivoire, which will inform the national control program for targeted interventions.

Maternal schistosomiasis: a growing concern in sub-Saharan Africa

Schistosomiasis remains one of the most important tropical parasitic infections threatening millions of lives in endemic areas. Cases of infections due to Schistosoma spp, the diecious digenetic trematodes have been on the increase over the last decades. While considerable efforts have been made to reduce infections and morbidities in most endemic areas, these efforts seem to be tailored only towards a specific group (school-based resources). This bias towards school children in epidemiological studies has also been observed in various research efforts in sub-Saharan Africa, thus making it difficult to produce a reliable estimate of the extent of infection in other strata of the population at risk. In recent times, attention has been drawn to Schistosoma spp infections in infants and preschool children, while studies on epidemiology of maternal schistosomiasis still suffer neglect. Considering the potential morbidity of Schistosoma infections on the mothers, fetuses, and neonates, as evidenced in some animal models and human case studies, more attention is solicited in all areas of observational studies and clinical trials, for maternal schistosomiasis with the aim of providing relevant data and information for effective management of the disease during pregnancy.

A cross-sectional study on urogenital schistosomiasis in children; haematuria and proteinuria as diagnostic indicators in an endemic rural area of Nigeria

BACKGROUND

Rapid and accurate diagnosis is necessary for the management of schistosomiasis in endemic areas.

OBJECTIVE

To assess the burden of urogenital schistosomiasis and the diagnostic efficiency of morbidity indicators of the disease in an endemic rural community of Nigeria.

METHODS

A cross-sectional school-based study was conducted. Urine samples of 487 pupils were screened microscopically for S. haematobium and tested for haematuria and proteinuria using chemical reagent strips.

RESULTS

The prevalence and intensity of infection were 57.1% and 45.0 eggs/10 mL urine respectively. Prevalence of infection in male (54.1%) and female (60.3%) individuals showed no significant variation (P>0.05). However, prevalence of infection was age dependent with those in age groups 3-5 and 12-14 years having the least and highest prevalence of infection respectively (P<0.05). Microhaematuria and proteinuria varied significantly with ages of the pupils with least (14.0, 40.0%) and highest (60.0, 80.0%) prevalence recorded in age groups 3-5 and 15-19 years respectively (P<0.05). Proteinuria showed higher sensitivity (80.3%) compared to microhaematuria (73.3%).

CONCLUSION

Schistosomiasis is highly endemic in the study area and the use of microhaematuria and proteinuria for mapping the infected population prior treatment could be adopted.

Schistosomiasis transmission; socio-demographic, knowledge and practices as transmission risk factors in pregnant women

Schistosoma transmission is influenced by the interplay between various factors ranging from parasite to host associated factors. While many studies have focused on mass chemotherapy to reduce transmission in other populations, no study has examined the impact of social factors that favour transmission in pregnant women in Nigeria. The study was conducted to assess the impact of knowledge, attitudes and sociodemographic factors on schistosomiasis burden in pregnant women of rural communities of Nigeria. A cross sectional community-based field study was conducted to assess the association between Schistosoma haematobium burden and the associated risk factors among pregnant women in rural endemic communities of Nigeria. Structured questionnaire was used to gather information on participants' socio-demographic data, knowledge on schistosomiasis and water contact activities. Of the 237 respondents examined microscopically for infection, 50 (21.1 %) were infected with overall mean infection intensity of 69.6 ± 165.2 eggs/10 mL urine. Multivariate logistic analysis showed occupation of the women to be associated with infection with the artisans having the highest risk (OR 3.34, CI 1.67-6.69, P = 0.022). Contact with water and water usage patterns are also associated with prevalence of disease with fetching (OR 2.04, CI 0.19-3.51, P = 0.003) and multipurpose water usage (OR 4.31, CI 2.17-8.57, P = 0.0002) being the most predisposing variables respectively. Awareness about water borne diseases showed no association with infection (P = 0.382) with typhoid (23.7 %) and fever (2.6 %) constituting the most and least common water borne diseases mentioned by the women. Health education and provision of good water supply should be integrated into the control strategies in order reduce transmission in endemic areas.

Geographical inequalities in use of improved drinking water supply and sanitation across Sub-Saharan Africa: mapping and spatial analysis of cross-sectional survey data

BACKGROUND

Understanding geographic inequalities in coverage of drinking-water supply and sanitation (WSS) will help track progress towards universal coverage of water and sanitation by identifying marginalized populations, thus helping to control a large number of infectious diseases. This paper uses household survey data to develop comprehensive maps of WSS coverage at high spatial resolution for sub-Saharan Africa (SSA). Analysis is extended to investigate geographic heterogeneity and relative geographic inequality within countries.

METHODS AND FINDINGS

Cluster-level data on household reported use of improved drinking-water supply, sanitation, and open defecation were abstracted from 138 national surveys undertaken from 1991-2012 in 41 countries. Spatially explicit logistic regression models were developed and fitted within a Bayesian framework, and used to predict coverage at the second administrative level (admin2, e.g., district) across SSA for 2012. Results reveal substantial geographical inequalities in predicted use of water and sanitation that exceed urban-rural disparities. The average range in coverage seen between admin2 within countries was 55% for improved drinking water, 54% for use of improved sanitation, and 59% for dependence upon open defecation. There was also some evidence that countries with higher levels of inequality relative to coverage in use of an improved drinking-water source also experienced higher levels of inequality in use of improved sanitation (rural populations r = 0.47, p = 0.002; urban populations r = 0.39, p = 0.01). Results are limited by the quantity of WSS data available, which varies considerably by country, and by the reliability and utility of available indicators.

CONCLUSIONS

This study identifies important geographic inequalities in use of WSS previously hidden within national statistics, confirming the necessity for targeted policies and metrics that reach the most marginalized populations. The presented maps and analysis approach can provide a mechanism for monitoring future reductions in inequality within countries, reflecting priorities of the post-2015 development agenda. Please see later in the article for the Editors' Summary.