Mapping the probability of schistosomiasis and associated uncertainty, West Africa

Evaluating the impact of biannual school-based and community-wide treatment on urogenital schistosomiasis in Niger

Background

The Schistosomiasis Consortium for Operational Research and Evaluation (SCORE) coordinated a five-year study implemented in several countries, including Niger, to provide an evidence-base for programmatic decisions regarding cost-effective approaches to preventive chemotherapy for schistosomiasis control.

Methods

This was a cluster-randomised trial investigating six possible combinations of annual or biannual community-wide treatment (CWT), school-based treatment (SBT), and holidays from mass treatment over four years. The most intense arm involved two years of annual CWT followed by 2 years of biannual CWT, while the least intensive arm involved one year of annual SBT followed by a year without treatment and two more years of annual SBT. The primary outcome of interest was prevalence and intensity of Schistosoma haematobium among 100 children aged 9–12 years sampled each year. In addition, 100 children aged 5–8 years in their first year of school and 50 adults (aged 20–55 years) were tested in the first and final fifth year of the study.

Results

In total, data were collected from 167,500 individuals across 225 villages in nine districts within the Niger River valley, Western Niger. Overall, the prevalence of S. haematobium decreased from baseline to Year 5 across all study arms. The relative reduction of prevalence was greater in biannual compared with annual treatment across all arms; however, the only significant difference was seen in areas with a high starting prevalence. Although adults were not targeted for treatment in SBT arms, a statistically significant decrease in prevalence among adults was seen in moderate prevalence areas receiving biannual (10.7% to 4.8%) SBT (P < 0.001). Adults tested in the annual SBT group also showed a decrease in prevalence between Year 1 and Year 5 (12.2% to 11.0%), but this difference was not significant.

Conclusions

These findings are an important consideration for schistosomiasis control programmes that are considering elimination and support the idea that scaling up the frequency of treatment rounds, particularly in areas of low prevalence, will not eliminate schistosomiasis. Interestingly, the finding that prevalence decreased among adults in SBT arms suggests that transmission in the community can be reduced, even where only school children are being treated, which could have logistical and cost-saving implications for the national control programmes.

Mapping tuberculosis prevalence in Ethiopia: protocol for a geospatial meta-analysis

INTRODUCTION

Tuberculosis (TB), a major public health concern in Ethiopia, is distributed heterogeneously across the country. Mapping TB prevalence at national and subnational levels can provide information for designing and implementing control strategies. Data for spatial analysis can be obtained through systematic review of the literature, and spatial prediction can be done by meta-analysis of published data (geospatial meta-analysis). Geospatial meta-analysis can increase the power of spatial analytic models by making use of all available data. It can also provide a means for spatial prediction where new survey data in a given area are sparse or not available. In this report, we present a protocol for a geospatial meta-analysis to investigate the spatial patterns of TB prevalence in Ethiopia.

METHODS AND ANALYSIS

To conduct this study, a national TB prevalence survey, supplemented with data from a systematic review of published reports, will be used as the source of TB prevalence data. Systematic searching will be conducted in PubMed, Scopus and Web of Science for studies published up to 15 April 2020 to identify all potential publications reporting TB prevalence in Ethiopia. Data for covariates for multivariable analysis will be obtained from different, readily available sources. Extracted TB survey and covariate data will be georeferenced to specific locations or the centroids of small administrative areas. A binomial logistic regression model will be fitted to TB prevalence data using both fixed covariate effects and random geostatistical effects based on the approach of model-based geostatistics. Markov Chain Monte Carlo simulation will be conducted to obtained posterior parameter estimations, including spatially predicted prevalence.

ETHICS AND DISSEMINATION

Ethical approval will not be required for this study as it will be based on deidentified, aggregate published data. The final report of this review will be disseminated through publication in a peer-reviewed scientific journal and will also be presented at relevant conferences.

Environmental Predictors of Schistosomiasis Persistent Hotspots following Mass Treatment with Praziquantel

Schistosomiasis control programs rely heavily on mass drug administration (MDA) campaigns with praziquantel for preventative chemotherapy. Areas where the prevalence and/or intensity of schistosomiasis infection remains high even after several rounds of treatment, termed "persistent hotspots" (PHSs), have been identified in trials of MDA effectiveness conducted by the Schistosomiasis Consortium for Operational Research and Evaluation (SCORE) in Kenya, Mozambique, Tanzania, and Côte d'Ivoire. In this analysis, we apply a previously developed set of criteria to classify the PHS status of 531 study villages from five SCORE trials. We then fit logistic regression models to data from SCORE and publically available georeferenced datasets to evaluate the influence of local environmental and population features, pre-intervention infection burden, and treatment scheduling on PHS status in each trial. The frequency of PHS in individual trials ranged from 35.3% to 71.6% in study villages. Significant relationships between PHS status and MDA frequency, distance to freshwater, rainfall, baseline schistosomiasis burden, elevation, land cover type, and village remoteness were each observed in at least one trial, although the strength and direction of these relationships was not always consistent among study sites. These findings suggest that PHSs are driven in part by environmental conditions that modify the risk and frequency of reinfection.

Antibody response to Schistosoma haematobium and other helminth species in malaria-exposed populations from Burkina Faso

Infection with helminths in sub-Saharan Africa could modulate the immune response towards Plasmodium falciparum as well as susceptibility to malaria infection and disease. The aim of this study is to assess the antibody responses to helminths species in malaria-exposed populations from Burkina Faso. Plasma samples were collected in rural villages inhabited by Fulani, Mossi and Rimaibe communities, and IgG against parasitic helminths were measured by ELISA. The prevalence of IgG against antigens of Strongyloides stercoralis, Wuchereria bancrofti and Schistosoma haematobium (Soluble Egg Antigen, SEA) was 5%, 16% and 63% respectively, in line with estimates of infection prevalence in the region for the three parasites. Anti-SEA IgG prevalence was highest at 10-20 years of age, higher in males than females, and did not show differences between ethnic groups. However, the Fulani showed lower levels of anti-SEA IgG suggesting that lighter S. haematobium infections may occur in the ethnic group known for a marked lower susceptibility to P. falciparum. The present data support the use of serological methods for integrated surveillance of neglected tropical diseases such as soil-transmitted helminths, lymphatic filariasis and bilharzia. Furthermore, as helminth infections might promote downregulation of immune responses against intracellular pathogens, the observation of lower anti-SEA IgG levels in the malaria resistant Fulani population warrants further investigation into the immunological cross-talk between S. haematobium and P. falciparum in this geographical region.

The association between child Schistosoma spp. infections and morbidity in an irrigated rice region in Mali: A localized study

Background

Schistosomiasis is one of the neglected tropical diseases endemic to Mali. There has been insufficient investigation of the morbidity burden in highly endemic irrigated rice areas with the ongoing mass drug administration with praziquantel. In February 2005, a year after an initial mass drug administration in 2004, we performed the first cross-sectional survey of schistosomiasis in the Kokry-Bozo village in the Office du Niger rice irrigation region. In the fourteen years since this survey, there has been almost no research into schistosomiasis morbidity in Mali due to lack of funding. Therefore, the 2005 survey supplies near-baseline data for any future research into the treatment impacts in the area.

Methods

One hundred and ninety-four children aged 6–14 years from two schools were assessed for bladder pathology by ultrasound, and for anaemia and micro-haematuria by laboratory tests. Schistosoma eggs were examined microscopically in fresh stool and urine samples. Multivariate logistic regression analysis quantified the association of Schistosoma infections with anaemia, bladder pathology and micro-haematuria. Akaike’s information criterion was used to test the assumption of linear effects of infection intensity classes and used to compare across models.

Results

The overall prevalence of schistosomiasis in 189 school children was 97%; 17% (33/189) had a single infection (S. mansoni,13%, or S. haematobium, 4%) and 80% (156/189) were co-infected with S. mansoni and S. haematobium. The overall prevalence of S. mansoni with light infection was 27% (53/194), moderate infection was 24% (47/194) and heavy infection was 42% (81/194). Of the 194 of children investigated for S. haematobium 59% (114/194) had light infection and 26% (50/194) had heavy infection. No hookworm eggs were detected.

The level of abnormal bladder pathology was 18% (35/189) with the highest found in 10–14 year old children. The prevalence of anaemia was 91% (172/189) and was twice as likely to be associated (OR 2.0, 95% CI 1.1–3.9) with S. mansoni infections than in children without infection. As infection intensity with S. mansoni increased the risk of anaemia (OR 2.0, 95% CI 1.1–3.9) also increased. As infection intensity with S. haematobium increased bladder pathology (OR 2.4, 95%CI 1.3–4.5), haematuria (OR 6.7, 95%CI 3.3–13.6) and micro-haematuria increased (OR 2.4, 95%CI 1.3–4.5).

Conclusion

Our research contributes an important micro-geographical assessment of the heavy burden of schistosomiasis and associated morbidity in children who live in the rice irrigation regions. Our literature review found that there has been very limited research conducted on the impact of the treatment to control morbidity in the ON. Therefore, there is a need to do a comparable, but more extensive, study to identify any changes in morbidity and to indicate current requirements for the control programme. Our results from 2005 called for routine integration of iron supplementation, food fortification and diet diversification into the deworming program.

Spatiotemporal distribution and population at risk of soil-transmitted helminth infections following an eight-year school-based deworming programme in Burundi, 2007-2014

Background

Investigating the effect of successive annual deworming rounds on the spatiotemporal distribution of infection prevalence and numbers at risk for soil-transmitted helminths (STHs) can help identify communities nearing elimination and those needing further interventions. In this study, we aim to quantify the impact of an 8-year mass drug administration (MDA) programme (from 2007 to 2014) on the spatiotemporal distribution of prevalence of STH infections and to estimate the number of school-aged children infected with STHs in Burundi.

Methods

During annual longitudinal school-based surveys in Burundi between 2007 and 2011, STH infection and anthropometric data for a total of 40,656 children were collected; these data were supplemented with data from a national survey conducted in 2014. Bayesian model based geostatistics (MBG) were used to generate predictive prevalence maps for each STH species and year. The numbers of children at-risk of infection per district between 2008 and 2014 were estimated as the product of the predictive prevalence maps and population density maps.

Results

Overall, the degree of spatial clustering of STH infections decreased between 2008 and 2011; in 2014 the geographical clusters of all STH infections reappeared. The reduction in prevalence was small for Ascaris lumbricoides and Trichuris trichiura in the centre and central north of the country. Our predictive prevalence maps for hookworm indicate a reduction in prevalence along the periphery of the country. The predicted number of children infected with any STH species decreased substantially between 2007 and 2011, but in 2014 there was an increase in the predicted number of children infected with A. lumbricoides and T. trichiura. In 2014, the districts with the highest predicted number of children infected with A. lumbricoides, T. trichiura and hookworms were Kibuye district (n = 128,903), Mabayi district (n = 35,302) and Kiremba (n = 87,511), respectively.

Conclusions

While the MDA programme in Burundi resulted in a reduction in STH prevalence, this reduction was spatiotemporally heterogeneous, with some pockets of high prevalence remaining, suggesting that treatment coverage and complementary interventions should be evaluated to improve impact.

Electronic supplementary material

The online version of this article (10.1186/s13071-017-2505-x) contains supplementary material, which is available to authorized users.

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.

Prevalence and intensity of genito-urinary schistosomiasis and associated risk factors among junior high school students in two local government areas around Zobe Dam in Katsina State, Nigeria

BACKGROUND

The national burden of genito-urinary schistosomiasis in Nigeria has been expressed by an estimate of 101.3 million people at risk with an alarming figure of 29 million infected. Report obtained from respondents about Praziquantel® distribution and the obviously prevalent haematuria without any control programme in place justified the need for data on the prevalence, intensity of infection and associated risk factors which were the objectives this cross-sectional survey sought to address.

METHODS

A total of 718 students aged 10-23 years from the study area were surveyed between May and August, 2015. Data on socio-demographic and risk factors were obtained using structured questionnaires. Clean universal bottles with corresponding labels were offered for sample collection between 10:00 am and 13:30 pm. Centrifuged samples were microscopically examined and intensity of infection was recorded per 10 ml of each sample.

RESULTS

Prevalence of genito-urinary schistosomiasis was 22.7 % with a mean intensity of 25.05 (± standard deviation, ± 71.51) eggs/10 ml of urine. Higher prevalence (19.5 %) and mean intensity (28.7 eggs/10 ml of urine) was recorded among boys. Sex (χ (2) = 77.065, P < 0.0001), age group 16-18 (χ (2) = 5.396, P = 0.0202), altitude (χ (2) = 8.083, P = 0.0045), unwholesome water sources (χ (2) = 27.148, P < 0.0001), human recreational activities (χ (2) = 122.437, P < 0.0001), mothers' occupation (χ (2) = 6.359, P = 0.0117), farming (χ (2) = 6.201, P = 0.0128) and other brown collar jobs (χ (2) = 4.842, P = 0.0278) in fathers' occupational category were found to be significantly associated with urogenital schistosomiasis. Boys were seven times more likely to be infected compared to girls [AOR (95 % CI): 7.3 (4.26-12.4)]. Age group 16-18 years was four times more likely to be infected compared to age group 10-12 years [AOR (95 % CI): 4.43 (2.62-7.49)]. Similarly, respondents with farming as fathers' occupation were twice more likely to be infected than those whose fathers were civil servants [AOR (95 % CI): 2.08 (1.2-3.59)].

CONCLUSIONS

Dutsin-Ma and Safana were classified as moderate-risk Local Government Areas (LGA). Sex, altitude, unwholesome water sources and mothers' occupation were identified as the determining epidemiological factors in the prevalence of the disease. Sustainable chemotherapeutic intervention with Praziquantel®, good network of treated pipe-borne water, health education and waste disposal facilities are highly recommended to reduce its prevalence below the threshold of public health significance.

China-Africa and China-Asia Collaboration on Schistosomiasis Control: A SWOT Analysis

Schistosomiasis, a disease caused by a trematode, parasitic worm, is a worldwide public health problem. In spite of great progress with regard to morbidity control, even elimination of this infection in recent decades, there are still challenges to overcome in sub-Saharan Africa and endemic areas in Southeast Asia. Regarded as one of the most successful countries with respect to schistosomiasis control, The People's Republic of China has accumulated considerable experience and learnt important lessons in various local settings that could benefit schistosomiasis control in other endemic countries. Based on an analysis of conceived strengths, weaknesses, opportunities and threats (SWOT) of potential collaborative activities with regard to schistosomiasis in Africa and Asia, this article addresses the importance of collaborative efforts and explores the priorities that would be expected to facilitate the transfer of Chinese experience to low- and middle-income countries in Africa and Asia.

The landscape epidemiology of echinococcoses

Echinococcoses are parasitic diseases of major public health importance globally. Human infection results in chronic disease with poor prognosis and serious medical, social and economic consequences for vulnerable populations. According to recent estimates, the geographical distribution of Echinococcus spp. infections is expanding and becoming an emerging and re-emerging problem in several regions of the world. Echinococcosis endemicity is geographically heterogeneous and over time it may be affected by global environmental change. Therefore, landscape epidemiology offers a unique opportunity to quantify and predict the ecological risk of infection at multiple spatial and temporal scales. Here, we review the most relevant environmental sources of spatial variation in human echinococcosis risk, and describe the potential applications of landscape epidemiological studies to characterise the current patterns of parasite transmission across natural and human-altered landscapes. We advocate future work promoting the use of this approach as a support tool for decision-making that facilitates the design, implementation and monitoring of spatially targeted interventions to reduce the burden of human echinococcoses in disease-endemic areas.

A high-efficiency superhydrophobic plasma separator

To meet stringent limit-of-detection specifications for low abundance target molecules, a relatively large volume of plasma is needed for many blood-based clinical diagnostics. Conventional centrifugation methods for plasma separation are not suitable for on-site testing or bedside diagnostics. Here, we report a simple, yet high-efficiency, clamshell-style, superhydrophobic plasma separator that is capable of separating a relatively large volume of plasma from several hundred microliters of whole blood (finger-prick blood volume). The plasma separator consists of a superhydrophobic top cover with a separation membrane and a superhydrophobic bottom substrate. Unlike previously reported membrane-based plasma separators, the separation membrane in our device is positioned at the top of the sandwiched whole blood film to increase the membrane separation capacity and plasma yield. In addition, the device's superhydrophobic characteristics (i) facilitates the formation of well-defined, contracted, thin blood film with a high contact angle; (ii) minimizes biomolecular adhesion to surfaces; (iii) increases blood clotting time; and (iv) reduces blood cell hemolysis. The device demonstrated a "blood in-plasma out" capability, consistently extracting 65 ± 21.5 μL of plasma from 200 μL of whole blood in less than 10 min without electrical power. The device was used to separate plasma from Schistosoma mansoni genomic DNA-spiked whole blood with a recovery efficiency of >84.5 ± 25.8%. The S. mansoni genomic DNA in the separated plasma was successfully tested on our custom-made microfluidic chip by using loop mediated isothermal amplification (LAMP) method.

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.

Schistosomiasis in school-age children in Burkina Faso after a decade of preventive chemotherapy

Objective

To assess the impact of a decade of biennial mass administration of praziquantel on schistosomiasis in school-age children in Burkina Faso.

Methods

In 2013, in a national assessment based on 22 sentinel sites, 3514 school children aged 7–11 years were checked for Schistosoma haematobium and Schistosoma mansoni infection by the examination of urine and stool samples, respectively. We analysed the observed prevalence and intensity of infections and compared these with the relevant results of earlier surveys in Burkina Faso.

Findings

S. haematobium was detected in 287/3514 school children (adjusted prevalence: 8.76%, range across sentinel sites: 0.0–56.3%; median: 2.5%). The prevalence of S. haematobium infection was higher in the children from the Centre-Est, Est and Sahel regions than in those from Burkina Faso’s other eight regions with sentinel sites (P < 0.001). The adjusted arithmetic mean intensity of S. haematobium infection, among all children, was 6.0 eggs per 10 ml urine. Less than 1% of the children in six regions had heavy S. haematobium infections – i.e. at least 50 eggs per 10 ml urine – but such infections were detected in 8.75% (28/320) and 11.56% (37/320) of the children from the Centre-Est and Sahel regions, respectively. Schistosoma mansoni was only detected in two regions and 43 children – i.e. 1 (0.31%) of the 320 from Centre-Sud and 42 (8.75%) of the 480 from Hauts Bassins.

Conclusion

By mass use of preventive chemotherapy, Burkina Faso may have eliminated schistosomiasis as a public health problem in eight regions and controlled schistosome-related morbidity in another three regions.

Where's the risk? Landscape epidemiology of gastrointestinal parasitism in Alberta beef cattle

Background

Gastrointenstinal nematodes (GIN) present a serious challenge to the health and productivity of grazing stock around the globe. However, the epidemiology of GIN transmission remains poorly understood in northern climates. Combining use of serological diagnostics, GIS mapping technology, and geospatial statistics, we evaluated ecological covariates of spatial and temporal variability in GIN transmission among bovine calves pastured in Alberta, Canada.

Methods

Sera were collected from 1000 beef calves across Alberta, Canada over three consecutive years (2008–2010) and analyzed for presence of anti-GIN antibodies using the SVANOVIR Ostertagia osteragi-Ab ELISA kit. Using a GIS and Bayesian multivariate spatial statistics, we evaluated the degree to which variation in specific environmental covariates (e.g. moisture, humidity, temperature) was associated with variation in spatial and temporal heterogeneity in exposure to GIN (Nematodirus and other trichostrongyles, primarily Ostertagia and Cooperia).

Results

Variation in growing degree days above a base temperature of 5 °C, humidity, air temperature, and accumulated precipitation were found to be significant predictors of broad–scale spatial and temporal variation in serum antibody concentrations. Risk model projections identified that while transmission in cattle from southeastern and northwestern Alberta was relatively low in all years, rate of GIN transmission was generally higher in the central region of Alberta.

Conclusions

The spatial variability in risk is attributed to higher average humidity, precipitation and moderate temperatures in the central region of Alberta in comparison with the hot, dry southeastern corner of the province and the cool, dry northwestern corner. Although more targeted sampling is needed to improve model accuracy, our projections represent an important step towards tying treatment recommendations to actual risk of infection.

Probability Mapping to Determine the Spatial Risk Pattern of Acute Gastroenteritis in Coimbatore District, India, Using Geographic Information Systems (GIS)

BACKGROUND

Maps show well the spatial configuration of information. Considerable effort is devoted to the development of geographical information systems (GIS) that increase understanding of public health problems and in particular to collaborate efforts among clinicians, epidemiologists, ecologists, and geographers to map and forecast disease risk.

OBJECTIVES

Small populations tend to give rise to the most extreme disease rates, even if the actual rates are similar across the areas. Such situations will follow the decision-maker's attention on these areas when they scrutinize the map for decision making or resource allocation. As an alternative, maps can be prepared using P-values (probabilistic values).

MATERIALS AND METHODS

The statistical significance of rates rather than the rates themselves are used to map the results. The incidence rates calculated for each village from 2000 to 2009 is used to estimate λ, the expected number of cases in the study area. The obtained results are mapped using Arc GIS 10.0.

RESULTS

The likelihood of infections from low to high is depicted in the map and it is observed that five villages namely, Odanthurai, Coimbatore Corporation, Ikkaraiboluvampatti, Puliakulam, and Pollachi Corporation are more likely to have significantly high incidences.

CONCLUSION

In the probability map, some of the areas with exceptionally high or low rates disappear. These are typically small unpopulated areas, whose rates are unstable due to the small numbers problem. The probability map shows more specific regions of relative risks and expected outcomes.

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.

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.

Geographical distribution of human Schistosoma japonicum infection in The Philippines: tools to support disease control and further elimination

Schistosoma japonicum infection is believed to be endemic in 28 of the 80 provinces of The Philippines and the most recent data on schistosomiasis prevalence have shown considerable variability between provinces. In order to increase the efficient allocation of parasitic disease control resources in the country, we aimed to describe the small-scale spatial variation in S. japonicum prevalence across The Philippines, quantify the role of the physical environment in driving the spatial variation of S. japonicum, and develop a predictive risk map of S. japonicum infection. Data on S. japonicum infection from 35,754 individuals across the country were geo-located at the barangay level and included in the analysis. The analysis was then stratified geographically for the regions of Luzon, the Visayas and Mindanao. Zero-inflated binomial Bayesian geostatistical models of S. japonicum prevalence were developed and diagnostic uncertainty was incorporated. Results of the analysis show that in the three regions, males and individuals aged ⩾20years had significantly higher prevalence of S. japonicum compared with females and children <5years. The role of the environmental variables differed between regions of The Philippines. Schistosoma japonicum infection was widespread in the Visayas whereas it was much more focal in Luzon and Mindanao. This analysis revealed significant spatial variation in the prevalence of S. japonicum infection in The Philippines. This suggests that a spatially targeted approach to schistosomiasis interventions, including mass drug administration, is warranted. When financially possible, additional schistosomiasis surveys should be prioritised for areas identified to be at high risk but which were under-represented in our dataset.

Predictive spatial risk model of poliovirus to aid prioritization and hasten eradication in Nigeria

BACKGROUND

One of the challenges facing the Global Polio Eradication Initiative is efficiently directing limited resources, such as specially trained personnel, community outreach activities, and satellite vaccinator tracking, to the most at-risk areas to maximize the impact of interventions. A validated predictive model of wild poliovirus circulation would greatly inform prioritization efforts by accurately forecasting areas at greatest risk, thus enabling the greatest effect of program interventions.

METHODS

Using Nigerian acute flaccid paralysis surveillance data from 2004-2013, we developed a spatial hierarchical Poisson hurdle model fitted within a Bayesian framework to study historical polio caseload patterns and forecast future circulation of type 1 and 3 wild poliovirus within districts in Nigeria. A Bayesian temporal smoothing model was applied to address data sparsity underlying estimates of covariates at the district level.

RESULTS

We find that calculated vaccine-derived population immunity is significantly negatively associated with the probability and number of wild poliovirus case(s) within a district. Recent case information is significantly positively associated with probability of a case, but not the number of cases. We used lagged indicators and coefficients from the fitted models to forecast reported cases in the subsequent six-month periods. Over the past three years, the average predictive ability is 86 ± 2% and 85 ± 4% for wild poliovirus type 1 and 3, respectively. Interestingly, the predictive accuracy of historical transmission patterns alone is equivalent (86 ± 2% and 84 ± 4% for type 1 and 3, respectively). We calculate uncertainty in risk ranking to inform assessments of changes in rank between time periods.

CONCLUSIONS

The model developed in this study successfully predicts districts at risk for future wild poliovirus cases in Nigeria. The highest predicted district risk was 12.8 WPV1 cases in 2006, while the lowest district risk was 0.001 WPV1 cases in 2013. Model results have been used to direct the allocation of many different interventions, including political and religious advocacy visits. This modeling approach could be applied to other vaccine preventable diseases for use in other control and elimination programs.

High levels of urinary schistosomiasis among children in Bunuso, a rural community in Ghana: an urgent call for increased surveillance and control programs

We investigated the occurrence of urinary schistosomiasis and estimated predictors for risk of infection among children in the Bunuso community of Ashanti Region of Ghana, West Africa. The cross-sectional survey was conducted between June and December 2009. Information was obtained on socio-demographic characteristics, schistosomiasis symptoms and other risk factors through interviews and questionnaires. Urine samples were analysed for Schistosoma haematobium ova using centrifugation and sedimentation, filtration and microscopy. Bivariate estimations and multiple logistic regression modelling with odds ratios (OR) were used to assess risk factors for S. haematobium infections. Inspections at River Nanakwaw revealed snail vectors, Bulinus truncatus. Overall, 95 out of 100 (95 % confidence interval [CI] 88.8-97.6) children tested positive for S. haematobium infection. The mean ova density (eggs/10 ml of urine) of infections was 58.12 (95 % CI 31.3-71.6) and varied significantly between age-group distributions (P value = 0.001; Post Hoc, P > 0.05 for ≤8 vs 15-17 years, and 9-11 vs 12-14 years), sources of house-hold water (P value = 0.019; Post Hoc, P < 0.05 for Borehole vs River Nanakwaw), children activities in River Nanakwaw (P value = 0.001), and haematuria (P value = 0.007). Independent variables significantly associated with S. haematobium infections were the use of River Nanakwaw as source of household water (OR 12.54; 95 % CI 3.932-42.12, P value = 0.003), engaging activities in River Nanakwaw (OR 8.76; 95 % CI 1.759-31.871; P value = 0.008) and haematuria (OR 36.71; 95 % CI 10.18-48.47; P value = 0.001). The passage of blood urine was prognostic of urinary schistosomiasis with a positive predictive value of 97.5 %. Our results demonstrate the endemicity of urinary schistosomiasis in Bunuso. Schistosomiasis remains a disease of great public health importance in Ghana, and there is the urgent need to intensify surveillance and control programs in remote riparian communities.

A brief review of spatial analysis concepts and tools used for mapping, containment and risk modelling of infectious diseases and other illnesses

Fast response and decision making about containment, management, eradication and prevention of diseases, are increasingly important aspects of the work of public health officers and medical providers. Diseases and the agents causing them are spatially and temporally distributed, and effective countermeasures rely on methods that can timely locate the foci of infection, predict the distribution of illnesses and their causes, and evaluate the likelihood of epidemics. These methods require the use of large datasets from ecology, microbiology, health and environmental geography. Geodatabases integrating data from multiple sets of information are managed within the frame of geographic information systems (GIS). Many GIS software packages can be used with minimal training to query, map, analyse and interpret the data. In combination with other statistical or modelling software, predictive and spatio-temporal modelling can be carried out. This paper reviews some of the concepts and tools used in epidemiology and parasitology. The purpose of this review is to provide public health officers with the critical tools to decide about spatial analysis resources and the architecture for the prevention and surveillance systems best suited to their situations.

Further shrinking the malaria map: how can geospatial science help to achieve malaria elimination?

Malaria is one of the biggest contributors to deaths caused by infectious disease. More than 30 countries have planned or started programmes to target malaria elimination, often with explicit support from international donors. The spatial distribution of malaria, at all levels of endemicity, is heterogeneous. Moreover, populations living in low-endemic settings where elimination efforts might be targeted are often spatially heterogeneous. Geospatial methods, therefore, can help design, target, monitor, and assess malaria elimination programmes. Rapid advances in technology and analytical methods have allowed the spatial prediction of malaria risk and the development of spatial decision support systems, which can enhance elimination programmes by enabling accurate and timely resource allocation. However, no framework exists for assessment of geospatial instruments. Research is needed to identify measurable indicators of elimination progress and to quantify the effect of geospatial methods in achievement of elimination outcomes.

Spatially explicit Schistosoma infection risk in eastern Africa using Bayesian geostatistical modelling

Schistosomiasis remains one of the most prevalent parasitic diseases in the tropics and subtropics, but current statistics are outdated due to demographic and ecological transformations and ongoing control efforts. Reliable risk estimates are important to plan and evaluate interventions in a spatially explicit and cost-effective manner. We analysed a large ensemble of georeferenced survey data derived from an open-access neglected tropical diseases database to create smooth empirical prevalence maps for Schistosoma mansoni and Schistosoma haematobium for a total of 13 countries of eastern Africa. Bayesian geostatistical models based on climatic and other environmental data were used to account for potential spatial clustering in spatially structured exposures. Geostatistical variable selection was employed to reduce the set of covariates. Alignment factors were implemented to combine surveys on different age-groups and to acquire separate estimates for individuals aged ≤20 years and entire communities. Prevalence estimates were combined with population statistics to obtain country-specific numbers of Schistosoma infections. We estimate that 122 million individuals in eastern Africa are currently infected with either S. mansoni, or S. haematobium, or both species concurrently. Country-specific population-adjusted prevalence estimates range between 12.9% (Uganda) and 34.5% (Mozambique) for S. mansoni and between 11.9% (Djibouti) and 40.9% (Mozambique) for S. haematobium. Our models revealed that infection risk in Burundi, Eritrea, Ethiopia, Kenya, Rwanda, Somalia and Sudan might be considerably higher than previously reported, while in Mozambique and Tanzania, the risk might be lower than current estimates suggest. Our empirical, large-scale, high-resolution infection risk estimates for S. mansoni and S. haematobium in eastern Africa can guide future control interventions and provide a benchmark for subsequent monitoring and evaluation activities.

Predictive vs. empiric assessment of schistosomiasis: implications for treatment projections in Ghana

BACKGROUND

Mapping the distribution of schistosomiasis is essential to determine where control programs should operate, but because it is impractical to assess infection prevalence in every potentially endemic community, model-based geostatistics (MBG) is increasingly being used to predict prevalence and determine intervention strategies.

METHODOLOGY/PRINCIPAL FINDINGS

To assess the accuracy of MBG predictions for Schistosoma haematobium infection in Ghana, school surveys were evaluated at 79 sites to yield empiric prevalence values that could be compared with values derived from recently published MBG predictions. Based on these findings schools were categorized according to WHO guidelines so that practical implications of any differences could be determined. Using the mean predicted values alone, 21 of the 25 empirically determined 'high-risk' schools requiring yearly praziquantel would have been undertreated and almost 20% of the remaining schools would have been treated despite empirically-determined absence of infection - translating into 28% of the children in the 79 schools being undertreated and 12% receiving treatment in the absence of any demonstrated need.

CONCLUSIONS/SIGNIFICANCE

Using the current predictive map for Ghana as a spatial decision support tool by aggregating prevalence estimates to the district level was clearly not adequate for guiding the national program, but the alternative of assessing each school in potentially endemic areas of Ghana or elsewhere is not at all feasible; modelling must be a tool complementary to empiric assessments. Thus for practical usefulness, predictive risk mapping should not be thought of as a one-time exercise but must, as in the current study, be an iterative process that incorporates empiric testing and model refining to create updated versions that meet the needs of disease control operational managers.

Spatial parasite ecology and epidemiology: a review of methods and applications

The distributions of parasitic diseases are determined by complex factors, including many that are distributed in space. A variety of statistical methods are now readily accessible to researchers providing opportunities for describing and ultimately understanding and predicting spatial distributions. This review provides an overview of the spatial statistical methods available to parasitologists, ecologists and epidemiologists and discusses how such methods have yielded new insights into the ecology and epidemiology of infection and disease. The review is structured according to the three major branches of spatial statistics: continuous spatial variation; discrete spatial variation; and spatial point processes.

Bovine paramphistomosis in Galicia (Spain): prevalence, intensity, aetiology and geospatial distribution of the infection

The present study explored various basic aspects of the epidemiology of paramphistomosis in Galicia, the main cattle producing region in Spain. In total, 589 cows from different farms located across the region were selected at random in the slaughterhouse for examination of the rumens and reticula for the presence of Paramphistomidae flukes. Paramphistomes were found in 111 of 589 necropsied cows (18.8%; 95% CI: 15.7-21.9%), with higher prevalences of infection in beef cows than in dairy cows (29.2% vs 13.9%). Although the number of flukes per animal was generally low (median=266 flukes), some cows harboured large parasite burdens (up to 11,895 flukes), which may have harmful effects on their health or productivity. Cows with higher parasite burdens also excreted greater numbers of fluke eggs in their faeces, which suggests that heavily parasitized mature cows play an important role in the transmission of paramphistomosis. This role may be particularly important in Galicia, where the roe deer, which is the only wild ruminant in the study area, was found not to be a reservoir for the infection. The use of morpho-anatomical and molecular techniques applied to a large number of fluke specimens provided reliable confirmation that Calicophoron daubneyi is the only species of the family Paramphistomidae that parasitizes cattle in Galicia. The environmental data from the farms of origin of the necropsied cows were used in Bayesian geostatistical models to predict the probability of infection by C. daubneyi throughout the region. The results revealed the role of environmental risk factors in explaining the geographical heterogeneity in the probability of infection in beef and dairy cattle. These explanatory factors were used to construct predictive maps showing the areas with the highest predicted risk of infection as well as the uncertainty associated with the predictions.

Combined spatial prediction of schistosomiasis and soil-transmitted helminthiasis in Sierra Leone: a tool for integrated disease control

BACKGROUND

A national mapping of Schistosoma haematobium was conducted in Sierra Leone before the mass drug administration (MDA) with praziquantel. Together with the separate mapping of S. mansoni and soil-transmitted helminths, the national control programme was able to plan the MDA strategies according to the World Health Organization guidelines for preventive chemotherapy for these diseases.

METHODOLOGY/PRINCIPAL FINDINGS

A total of 52 sites/schools were selected according to prior knowledge of S. haematobium endemicity taking into account a good spatial coverage within each district, and a total of 2293 children aged 9-14 years were examined. Spatial analysis showed that S. haematobium is heterogeneously distributed in the country with significant spatial clustering in the central and eastern regions of the country, most prevalent in Bo (24.6% and 8.79 eggs/10 ml), Koinadugu (20.4% and 3.53 eggs/10 ml) and Kono (25.3% and 7.91 eggs/10 ml) districts. By combining this map with the previously reported maps on intestinal schistosomiasis using a simple probabilistic model, the combined schistosomiasis prevalence map highlights the presence of high-risk communities in an extensive area in the northeastern half of the country. By further combining the hookworm prevalence map, the at-risk population of school-age children requiring integrated schistosomiasis/soil-transmitted helminth treatment regimens according to the coendemicity was estimated.

CONCLUSIONS/SIGNIFICANCE

The first comprehensive national mapping of urogenital schistosomiasis in Sierra Leone was conducted. Using a new method for calculating the combined prevalence of schistosomiasis using estimates from two separate surveys, we provided a robust coendemicity mapping for overall urogenital and intestinal schistosomiasis. We also produced a coendemicity map of schistosomiasis and hookworm. These coendemicity maps can be used to guide the decision making for MDA strategies in combination with the local knowledge and programme needs.

Geographical analysis of the role of water supply and sanitation in the risk of helminth infections of children in West Africa

Globally, inadequate water supply, sanitation, and hygiene (WASH) are major contributors to mortality and burden of disease. We aimed to quantify the role of WASH in the risk of Schistosoma hematobium, Schistosoma mansoni, and hookworm infection in school-aged children; to estimate the population attributable fraction (PAF) of helminth infection due to WASH; and to spatially predict the risk of infection. We generated predictive maps of areas in West Africa without piped water, toilet facilities, and improved household floor types, using spatial risk models. Our maps identified areas in West Africa where the millennium development goal for water and sanitation is lagging behind. There was a generally better geographical coverage for toilets and improved household floor types compared with water supply. These predictions, and their uncertainty, were then used as covariates in Bayesian geostatistical models for the three helminth species. We estimated a smaller attributable fraction for water supply in S. mansoni (PAF 47%) compared with S. hematobium (PAF 71%). The attributable fraction of S. hematobium infection due to natural floor type (PAF 21%) was comparable to that of S. mansoni (PAF 16%), but was significantly higher for hookworm infection (PAF 86%). Five percent of hookworm cases could have been prevented if improved toilet facilities had been available. Mapping the distribution of infection risk adjusted for WASH allowed the identification of communities in West Africa where preventive chemotherapy integrated with interventions to improve WASH will yield the greatest health benefits.

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

Background

Schistosomiasis is a water-based disease that is believed to affect over 200 million people with an estimated 97% of the infections concentrated in Africa. However, these statistics are largely based on population re-adjusted data originally published by Utroska and colleagues more than 20 years ago. Hence, these estimates are outdated due to large-scale preventive chemotherapy programs, improved sanitation, water resources development and management, among other reasons. For planning, coordination, and evaluation of control activities, it is essential to possess reliable schistosomiasis prevalence maps.

Methodology

We analyzed survey data compiled on a newly established open-access global neglected tropical diseases database (i) to create smooth empirical prevalence maps for Schistosoma mansoni and S. haematobium for individuals aged ≤20 years in West Africa, including Cameroon, and (ii) to derive country-specific prevalence estimates. We used Bayesian geostatistical models based on environmental predictors to take into account potential clustering due to common spatially structured exposures. Prediction at unobserved locations was facilitated by joint kriging.

Principal Findings

Our models revealed that 50.8 million individuals aged ≤20 years in West Africa are infected with either S. mansoni, or S. haematobium, or both species concurrently. The country prevalence estimates ranged between 0.5% (The Gambia) and 37.1% (Liberia) for S. mansoni, and between 17.6% (The Gambia) and 51.6% (Sierra Leone) for S. haematobium. We observed that the combined prevalence for both schistosome species is two-fold lower in Gambia than previously reported, while we found an almost two-fold higher estimate for Liberia (58.3%) than reported before (30.0%). Our predictions are likely to overestimate overall country prevalence, since modeling was based on children and adolescents up to the age of 20 years who are at highest risk of infection.

Conclusion/Significance

We present the first empirical estimates for S. mansoni and S. haematobium prevalence at high spatial resolution throughout West Africa. Our prediction maps allow prioritizing of interventions in a spatially explicit manner, and will be useful for monitoring and evaluation of schistosomiasis control programs.

Schistosomiasis is a parasitic disease caused by a blood fluke that mainly occurs in Africa. Current prevalence estimates of schistosomiasis are based on historical data, and hence might be outdated due to control programs, improved sanitation, and water resources development and management (e.g., construction of large dams and irrigation systems). To help planning, coordination, and evaluation of control activities, reliable schistosomiasis prevalence estimates are needed. We analyzed compiled survey data from 1980 onwards for West Africa, including Cameroon, focusing on individuals aged ≤20 years. Bayesian geostatistical models were implemented based on environmental and climatic predictors to take into account potential spatial clustering within the data. We created the first smooth data-driven prevalence maps for Schistosoma mansoni and S. haematobium at high spatial resolution throughout West Africa. We found that an estimated 50.8 million West Africans aged ≤20 years are infected with schistosome blood flukes. Country prevalence estimates ranged between 0.5% (in The Gambia) and 37.1% (in Liberia) for S. mansoni and between 17.6% (in The Gambia) and 51.6% (in Sierra Leone) for S. haematobium. Our results allow prioritization of areas where interventions are needed, and to monitor and evaluate the impact of control activities.

Mapping helminth co-infection and co-intensity: geostatistical prediction in ghana

Background

Morbidity due to Schistosoma haematobium and hookworm infections is marked in those with intense co-infections by these parasites. The development of a spatial predictive decision-support tool is crucial for targeting the delivery of integrated mass drug administration (MDA) to those most in need. We investigated the co-distribution of S. haematobium and hookworm infection, plus the spatial overlap of infection intensity of both parasites, in Ghana. The aim was to produce maps to assist the planning and evaluation of national parasitic disease control programs.

Methodology/Principal Findings

A national cross-sectional school-based parasitological survey was conducted in Ghana in 2008, using standardized sampling and parasitological methods. Bayesian geostatistical models were built, including a multinomial regression model for S. haematobium and hookworm mono- and co-infections and zero-inflated Poisson regression models for S. haematobium and hookworm infection intensity as measured by egg counts in urine and stool respectively. The resulting infection intensity maps were overlaid to determine the extent of geographical overlap of S. haematobium and hookworm infection intensity. In Ghana, prevalence of S. haematobium mono-infection was 14.4%, hookworm mono-infection was 3.2%, and S. haematobium and hookworm co-infection was 0.7%. Distance to water bodies was negatively associated with S. haematobium and hookworm co-infections, hookworm mono-infections and S. haematobium infection intensity. Land surface temperature was positively associated with hookworm mono-infections and S. haematobium infection intensity. While high-risk (prevalence >10–20%) of co-infection was predicted in an area around Lake Volta, co-intensity was predicted to be highest in foci within that area.

Conclusions/Significance

Our approach, based on the combination of co-infection and co-intensity maps allows the identification of communities at increased risk of severe morbidity and environmental contamination and provides a platform to evaluate progress of control efforts.

Urinary schistosomiasis and hookworm infections cause considerable morbidity in school age children in West Africa. Severe morbidity is predominantly observed in individuals infected with both parasite types and, in particular, with heavy infections. We investigated for the first time the distribution of S. haematobium and hookworm co-infections and distribution of co-intensity of these parasites in Ghana. Bayesian geostatistical models were developed to generate a national co-infection map and national intensity maps for each parasite, using data on S. haematobium and hookworm prevalence and egg concentration (expressed as eggs per 10 mL of urine for S. haematobium and expressed as eggs per gram of faeces for hookworm), collected during a pre-intervention baseline survey in Ghana, 2008. In contrast with previous findings from the East Africa region, we found that both S. haematobium and hookworm infections are highly focal, resulting in small, localized clusters of co-infection and areas of high co-intensity. Overlaying on a single map the co-infection and the intensity of multiple parasite infections allows identification of areas where parasite environmental contamination and morbidity are at its highest, while providing an evidence base for the assessment of the progress of successive rounds of mass drug administration (MDA) in integrated parasitic disease control programs.

Mapping the risk of anaemia in preschool-age children: the contribution of malnutrition, malaria, and helminth infections in West Africa

BACKGROUND

Childhood anaemia is considered a severe public health problem in most countries of sub-Saharan Africa. We investigated the geographical distribution of prevalence of anaemia and mean haemoglobin concentration (Hb) in children aged 1-4 y (preschool children) in West Africa. The aim was to estimate the geographical risk profile of anaemia accounting for malnutrition, malaria, and helminth infections, the risk of anaemia attributable to these factors, and the number of anaemia cases in preschool children for 2011.

METHODS AND FINDINGS

National cross-sectional household-based demographic health surveys were conducted in 7,147 children aged 1-4 y in Burkina Faso, Ghana, and Mali in 2003-2006. Bayesian geostatistical models were developed to predict the geographical distribution of mean Hb and anaemia risk, adjusting for the nutritional status of preschool children, the location of their residence, predicted Plasmodium falciparum parasite rate in the 2- to 10-y age group (Pf PR(2-10)), and predicted prevalence of Schistosoma haematobium and hookworm infections. In the four countries, prevalence of mild, moderate, and severe anaemia was 21%, 66%, and 13% in Burkina Faso; 28%, 65%, and 7% in Ghana, and 26%, 62%, and 12% in Mali. The mean Hb was lowest in Burkina Faso (89 g/l), in males (93 g/l), and for children 1-2 y (88 g/l). In West Africa, severe malnutrition, Pf PR(2-10), and biological synergisms between S. haematobium and hookworm infections were significantly associated with anaemia risk; an estimated 36.8%, 14.9%, 3.7%, 4.2%, and 0.9% of anaemia cases could be averted by treating malnutrition, malaria, S. haematobium infections, hookworm infections, and S. haematobium/hookworm coinfections, respectively. A large spatial cluster of low mean Hb (<80 g/l) and maximal risk of anaemia (>95%) was predicted for an area shared by Burkina Faso and Mali. We estimate that in 2011, approximately 6.7 million children aged 1-4 y are anaemic in the three study countries.

CONCLUSIONS

By mapping the distribution of anaemia risk in preschool children adjusted for malnutrition and parasitic infections, we provide a means to identify the geographical limits of anaemia burden and the contribution that malnutrition and parasites make to anaemia. Spatial targeting of ancillary micronutrient supplementation and control of other anaemia causes, such as malaria and helminth infection, can contribute to efficiently reducing the burden of anaemia in preschool children in Africa.

Survived infancy but still vulnerable: spatial-temporal trends and risk factors for child mortality in the Agincourt rural sub-district, South Africa, 1992-2007

Targeting of health interventions to poor children at highest risk of mortality are promising approaches for enhancing equity. Methods have emerged to accurately quantify excess risk and identify space-time disparities. This provides useful and detailed information for guiding policy. A spatio-temporal analysis was performed to identify risk factors associated with child (1-4 years) mortality in the Agincourt sub-district, South Africa, to assess temporal changes in child mortality patterns within the study site between 1992 and 2007, and to produce all-cause and cause-specific mortality maps to identify high risk areas. Demographic, maternal, paternal and fertility-related factors, household mortality experience, distance to health care facility and socio-economic status were among the examined risk factors. The analysis was carried out by fitting a Bayesian discrete time Bernoulli survival geostatistical model using Markov chain Monte Carlo simulation. Bayesian kriging was used to produce mortality risk maps. Significant temporal increase in child mortality was observed due to the HIV epidemic. A distinct spatial risk pattern was observed with higher risk areas being concentrated in poorer settlements on the eastern part of the study area, largely inhabited by former Mozambican refugees. The major risk factors for childhood mortality, following multivariate adjustment, were mother's death (especially when due to HIV and tuberculosis), greater number of children under 5 years living in the same household and winter season. This study demonstrates the use of Bayesian geostatistical models for accurately quantifying risk factors and producing maps of child mortality risk in a health and demographic surveillance system. According to the space-time analysis, the southeast and upper central regions of the site appear to have the highest mortality risk. The results inform policies to address health inequalities in the Agincourt sub-district and to improve access to health services. Targeted efforts to prevent vertical transmission of HIV in specific settings need to be undertaken as well as ensuring the survival of the mother and father in childhood.

The applications of model-based geostatistics in helminth epidemiology and control

Funding agencies are dedicating substantial resources to tackle helminth infections. Reliable maps of the distribution of helminth infection can assist these efforts by targeting control resources to areas of greatest need. The ability to define the distribution of infection at regional, national and subnational levels has been enhanced greatly by the increased availability of good quality survey data and the use of model-based geostatistics (MBG), enabling spatial prediction in unsampled locations. A major advantage of MBG risk mapping approaches is that they provide a flexible statistical platform for handling and representing different sources of uncertainty, providing plausible and robust information on the spatial distribution of infections to inform the design and implementation of control programmes. Focussing on schistosomiasis and soil-transmitted helminthiasis, with additional examples for lymphatic filariasis and onchocerciasis, we review the progress made to date with the application of MBG tools in large-scale, real-world control programmes and propose a general framework for their application to inform integrative spatial planning of helminth disease control programmes.

Modelling the geographical distribution of co-infection risk from single-disease surveys

BACKGROUND

The need to deliver interventions targeting multiple diseases in a cost-effective manner calls for integrated disease control efforts. Consequently, maps are required that show where the risk of co-infection is particularly high. Co-infection risk is preferably estimated via Bayesian geostatistical multinomial modelling, using data from surveys screening for multiple infections simultaneously. However, only few surveys have collected this type of data.

METHODS

Bayesian geostatistical shared component models (allowing for covariates, disease-specific and shared spatial and non-spatial random effects) are proposed to model the geographical distribution and burden of co-infection risk from single-disease surveys. The ability of the models to capture co-infection risk is assessed on simulated data sets based on multinomial distributions assuming light- and heavy-dependent diseases, and a real data set of Schistosoma mansoni-hookworm co-infection in the region of Man, Côte d'Ivoire. The data were restructured as if obtained from single-disease surveys. The estimated results of co-infection risk, together with independent and multinomial model results, were compared via different validation techniques.

RESULTS

The results showed that shared component models result in more accurate estimates of co-infection risk than models assuming independence in settings of heavy-dependent diseases. The shared spatial random effects are similar to the spatial co-infection random effects of the multinomial model for heavy-dependent data.

CONCLUSIONS

In the absence of true co-infection data geostatistical shared component models are able to estimate the spatial patterns and burden of co-infection risk from single-disease survey data, especially in settings of heavy-dependent diseases.

Spatial modelling of soil-transmitted helminth infections in Kenya: a disease control planning tool

BACKGROUND

Implementation of control of parasitic diseases requires accurate, contemporary maps that provide intervention recommendations at policy-relevant spatial scales. To guide control of soil transmitted helminths (STHs), maps are required of the combined prevalence of infection, indicating where this prevalence exceeds an intervention threshold of 20%. Here we present a new approach for mapping the observed prevalence of STHs, using the example of Kenya in 2009.

METHODS AND FINDINGS

Observed prevalence data for hookworm, Ascaris lumbricoides and Trichuris trichiura were assembled for 106,370 individuals from 945 cross-sectional surveys undertaken between 1974 and 2009. Ecological and climatic covariates were extracted from high-resolution satellite data and matched to survey locations. Bayesian space-time geostatistical models were developed for each species, and were used to interpolate the probability that infection prevalence exceeded the 20% threshold across the country for both 1989 and 2009. Maps for each species were integrated to estimate combined STH prevalence using the law of total probability and incorporating a correction factor to adjust for associations between species. Population census data were combined with risk models and projected to estimate the population at risk and requiring treatment in 2009. In most areas for 2009, there was high certainty that endemicity was below the 20% threshold, with areas of endemicity ≥ 20% located around the shores of Lake Victoria and on the coast. Comparison of the predicted distributions for 1989 and 2009 show how observed STH prevalence has gradually decreased over time. The model estimated that a total of 2.8 million school-age children live in districts which warrant mass treatment.

CONCLUSIONS

Bayesian space-time geostatistical models can be used to reliably estimate the combined observed prevalence of STH and suggest that a quarter of Kenya's school-aged children live in areas of high prevalence and warrant mass treatment. As control is successful in reducing infection levels, updated models can be used to refine decision making in helminth control.

Geographical information systems and tropical medicine

In terms of their applicability to the field of tropical medicine, geographical information systems (GIS) have developed enormously in the last two decades. This article reviews some of the pertinent and representative applications of GIS, including the use of such systems and remote sensing for the mapping of Chagas disease and human helminthiases, the use of GIS in vaccine trials, and the global applications of GIS for health-information management, disease epidemiology, and pandemic planning. The future use of GIS as a decision-making tool and some barriers to the widespread implementation of such systems in developing settings are also discussed.

Targeting trachoma control through risk mapping: the example of Southern Sudan

BACKGROUND

Trachoma is a major cause of blindness in Southern Sudan. Its distribution has only been partially established and many communities in need of intervention have therefore not been identified or targeted. The present study aimed to develop a tool to improve targeting of survey and control activities.

METHODS/PRINCIPAL FINDINGS

A national trachoma risk map was developed using Bayesian geostatistics models, incorporating trachoma prevalence data from 112 geo-referenced communities surveyed between 2001 and 2009. Logistic regression models were developed using active trachoma (trachomatous inflammation follicular and/or trachomatous inflammation intense) in 6345 children aged 1-9 years as the outcome, and incorporating fixed effects for age, long-term average rainfall (interpolated from weather station data) and land cover (i.e. vegetation type, derived from satellite remote sensing), as well as geostatistical random effects describing spatial clustering of trachoma. The model predicted the west of the country to be at no or low trachoma risk. Trachoma clusters in the central, northern and eastern areas had a radius of 8 km after accounting for the fixed effects.

CONCLUSION

In Southern Sudan, large-scale spatial variation in the risk of active trachoma infection is associated with aridity. Spatial prediction has identified likely high-risk areas to be prioritized for more data collection, potentially to be followed by intervention.

Risk factors for Schistosoma haematobium infection and morbidity in two villages with different transmission patterns in Niger

A better control of major neglected tropical diseases such as schistosomiasis is urgently needed to reduce their impact on public health in developing countries. To optimize the efficiency of intervention campaigns, we assessed the influence of individual human factors on the level of Schistosoma haematobium infection and morbidity in a typical Sahelian country (Niger). Random samples of 246 and 257 individuals were selected from general census in two villages with distinct patterns of schistosome transmission. One village (Lossa) is located in an area of perennial transmission whereas transmission is seasonal in the other village (Tara). Despite comparable levels of both egg excretion and lower tract pathology in the two villages, the inhabitants of Lossa had a higher risk (OR: 2.1, 95% CI: 1.1-3.9) of developing upper tract lesions compared to those living in Tara. In both villages, bladder lesions were more serious in males than in females. Children between 7 and 15 years old were the most at risk to experience heavy infections (OR: 3.4, 95% CI: 2.1-5.7), bladder (OR: 4.5, 95% CI: 2.6-7.8) and upper tract (OR: 10.4, 95% CI: 2.4-45.0) lesions, independently of gender and village. These results confirm that targeted intervention campaigns should include foci regardless of their schistosome transmission pattern and focus on the school-aged population.

Spatial prediction of malaria prevalence in an endemic area of Bangladesh

BACKGROUND

Malaria is a major public health burden in Southeastern Bangladesh, particularly in the Chittagong Hill Tracts region. Malaria is endemic in 13 districts of Bangladesh and the highest prevalence occurs in Khagrachari (15.47%).

METHODS

A risk map was developed and geographic risk factors identified using a Bayesian approach. The Bayesian geostatistical model was developed from previously identified individual and environmental covariates (p < 0.2; age, different forest types, elevation and economic status) for malaria prevalence using WinBUGS 1.4. Spatial correlation was estimated within a Bayesian framework based on a geostatistical model. The infection status (positives and negatives) was modeled using a Bernoulli distribution. Maps of the posterior distributions of predicted prevalence were developed in geographic information system (GIS).

RESULTS

Predicted high prevalence areas were located along the north-eastern areas, and central part of the study area. Low to moderate prevalence areas were predicted in the southwestern, southeastern and central regions. Individual age and nearness to fragmented forest were associated with malaria prevalence after adjusting the spatial auto-correlation.

CONCLUSION

A Bayesian analytical approach using multiple enabling technologies (geographic information systems, global positioning systems, and remote sensing) provide a strategy to characterize spatial heterogeneity in malaria risk at a fine scale. Even in the most hyper endemic region of Bangladesh there is substantial spatial heterogeneity in risk. Areas that are predicted to be at high risk, based on the environment but that have not been reached by surveys are identified.

Schistosomiasis and neglected tropical diseases: towards integrated and sustainable control and a word of caution

In May 2001, the World Health Assembly (WHA) passed a resolution which urged member states to attain, by 2010, a minimum target of regularly administering anthelminthic drugs to at least 75% and up to 100% of all school-aged children at risk of morbidity. The refined global strategy for the prevention and control of schistosomiasis and soil-transmitted helminthiasis was issued in the following year and large-scale administration of anthelminthic drugs endorsed as the central feature. This strategy has subsequently been termed 'preventive chemotherapy'. Clearly, the 2001 WHA resolution led the way for concurrently controlling multiple neglected tropical diseases. In this paper, we recall the schistosomiasis situation in Africa in mid-2003. Adhering to strategic guidelines issued by the World Health Organization, we estimate the projected annual treatment needs with praziquantel among the school-aged population and critically discuss these estimates. The important role of geospatial tools for disease risk mapping, surveillance and predictions for resource allocation is emphasised. We clarify that schistosomiasis is only one of many neglected tropical diseases and that considerable uncertainties remain regarding global burden estimates. We examine new control initiatives targeting schistosomiasis and other tropical diseases that are often neglected. The prospect and challenges of integrated control are discussed and the need for combining biomedical, educational and engineering strategies and geospatial tools for sustainable disease control are highlighted. We conclude that, for achieving integrated and sustainable control of neglected tropical diseases, a set of interventions must be tailored to a given endemic setting and fine-tuned over time in response to the changing nature and impact of control. Consequently, besides the environment, the prevailing demographic, health and social systems contexts need to be considered.

Spatial co-distribution of neglected tropical diseases in the east African great lakes region: revisiting the justification for integrated control

OBJECTIVE

To determine spatial patterns of co-endemicity of schistosomiasis mansoni and the soil-transmitted helminths (STHs) Ascaris lumbricoides, Trichuris trichiura and hookworm in the Great Lakes region of East Africa, to help plan integrated neglected tropical disease programmes in this region.

METHOD

Parasitological surveys were conducted in Uganda, Tanzania, Kenya and Burundi in 28 213 children in 404 schools. Bayesian geostatistical models were used to interpolate prevalence of these infections across the study area. Interpolated prevalence maps were overlaid to determine areas of co-endemicity.

RESULTS

In the Great Lakes region, prevalence was 18.1% for Schistosoma mansoni, 50.0% for hookworm, 6.8% for A. lumbricoides and 6.8% for T. trichiura. Hookworm infection was ubiquitous, whereas S. mansoni, A. lumbricoides and T. trichiura were highly focal. Most areas were endemic (prevalence >or=10%) or hyperendemic (prevalence >or=50%) for one or more STHs, whereas endemic areas for schistosomiasis mansoni were restricted to foci adjacent large perennial water bodies.

CONCLUSION

Because of the ubiquity of hookworm, treatment programmes are required for STH throughout the region but efficient schistosomiasis control should only be targeted at limited high-risk areas. Therefore, integration of schistosomiasis with STH control is only indicated in limited foci in East Africa.

Remote sensing, geographical information system and spatial analysis for schistosomiasis epidemiology and ecology in Africa

Beginning in 1970, the potential of remote sensing (RS) techniques, coupled with geographical information systems (GIS), to improve our understanding of the epidemiology and control of schistosomiasis in Africa, has steadily grown. In our current review, working definitions of RS, GIS and spatial analysis are given, and applications made to date with RS and GIS for the epidemiology and ecology of schistosomiasis in Africa are summarised. Progress has been made in mapping the prevalence of infection in humans and the distribution of intermediate host snails. More recently, Bayesian geostatistical modelling approaches have been utilized for predicting the prevalence and intensity of infection at different scales. However, a number of challenges remain; hence new research is needed to overcome these limitations. First, greater spatial and temporal resolution seems important to improve risk mapping and understanding of transmission dynamics at the local scale. Second, more realistic risk profiling can be achieved by taking into account information on people's socio-economic status; furthermore, future efforts should incorporate data on domestic access to clean water and adequate sanitation, as well as behavioural and educational issues. Third, high-quality data on intermediate host snail distribution should facilitate validation of infection risk maps and modelling transmission dynamics. Finally, more emphasis should be placed on risk mapping and prediction of multiple species parasitic infections in an effort to integrate disease risk mapping and to enhance the cost-effectiveness of their control.

Integrated mapping of neglected tropical diseases: epidemiological findings and control implications for northern Bahr-el-Ghazal State, Southern Sudan

Background

There are few detailed data on the geographic distribution of most neglected tropical diseases (NTDs) in post-conflict Southern Sudan. To guide intervention by the recently established national programme for integrated NTD control, we conducted an integrated prevalence survey for schistosomiasis, soil-transmitted helminth (STH) infection, lymphatic filariasis (LF), and loiasis in Northern Bahr-el-Ghazal State. Our aim was to establish which communities require mass drug administration (MDA) with preventive chemotherapy (PCT), rather than to provide precise estimates of infection prevalence.

Methods and Findings

The integrated survey design used anecdotal reports of LF and proximity to water bodies (for schistosomiasis) to guide selection of survey sites. In total, 86 communities were surveyed for schistosomiasis and STH; 43 of these were also surveyed for LF and loiasis. From these, 4834 urine samples were tested for blood in urine using Hemastix reagent strips, 4438 stool samples were analyzed using the Kato-Katz technique, and 5254 blood samples were tested for circulating Wuchereria bancrofti antigen using immunochromatographic card tests (ICT). 4461 individuals were interviewed regarding a history of ‘eye worm’ (a proxy measure for loiasis) and 31 village chiefs were interviewed regarding the presence of clinical manifestations of LF in their community. At the village level, prevalence of Schistosoma haematobium and S. mansoni ranged from 0 to 65.6% and from 0 to 9.3%, respectively. The main STH species was hookworm, ranging from 0 to 70% by village. Infection with LF and loiasis was extremely rare, with only four individuals testing positive or reporting symptoms, respectively. Questionnaire data on clinical signs of LF did not provide a reliable indication of endemicity. MDA intervention thresholds recommended by the World Health Organization were only exceeded for urinary schistosomiasis and hookworm in a few, yet distinct, communities.

Conclusion

This was the first attempt to use an integrated survey design for this group of infections and to generate detailed results to guide their control over a large area of Southern Sudan. The approach proved practical, but could be further simplified to reduce field work and costs. The results show that only a few areas need to be targeted with MDA of PCT, thus confirming the importance of detailed mapping for cost-effective control.

Integrated control of neglected tropical diseases (NTDs) is being scaled up in a number of developing countries, because it is thought to be more cost-effective than stand-alone control programmes. Under this approach, treatments for onchocerciasis, lymphatic filariasis (LF), schistosomiasis, soil-transmitted helminth (STH) infection, and trachoma are administered through the same delivery structure and at about the same time. A pre-requisite for implementation of integrated NTD control is information on where the targeted diseases are endemic and to what extent they overlap. This information is generated through surveys that can be labour-intensive and expensive. In Southern Sudan, all of the above diseases except onchocerciasis require further mapping before a comprehensive integrated NTD control programme can be implemented. To determine where treatment for which disease is required, integrated surveys were conducted for schistosomiasis, STH infection, LF, and loiasis, throughout one of ten states of the country. Our results show that treatment is only required for urinary schistosomiasis and STH in a few, yet separate, geographical area. This illustrates the importance of investing in disease mapping to minimize overall programme costs by being able to target interventions. Integration of survey methodologies for the above disease was practical and efficient, and minimized the effort required to collect these data.

The Schistosomiasis Control Initiative (SCI): rationale, development and implementation from 2002-2008

Schistosomiasis remains one of the most prevalent parasitic diseases in developing countries. After malaria, schistosomiasis is the most important tropical disease in terms of human morbidity with significant economic and public health consequences. Although schistosomiasis has recently attracted increased focus and funding for control, it has been estimated that less than 20% of the funding needed to control the disease in Africa is currently available. In this article the following issues are discussed: the rationale, development and objectives of the Schistosomiasis Control Initiative (SCI)-supported programmes; the management approaches followed to achieve implementation by each country; mapping, monitoring and evaluation activities with quantifiable impact of control programmes; monitoring for any potential drug resistance; and finally exit strategies within each country. The results have demonstrated that morbidity due to schistosomiasis has been reduced by the control programmes. While challenges remain, the case for the control of schistosomiasis has been strengthened by research by SCI teams and the principle that a national programme using 'preventive chemotherapy' can be successfully implemented in sub-Saharan Africa, whenever the resources are available. SCI and partners are now actively striving to raise further funds to expand the coverage of integrated control of neglected tropical diseases (NTDs) in sub-Saharan Africa.