An integrated approach for risk profiling and spatial prediction of Schistosoma mansoni-hookworm coinfection

Enabling targeted mass drug administration for schistosomiasis in north-western Tanzania: Exploring the use of geostatistical modeling to inform planning at sub-district level

INTRODUCTION

Schistosomiasis is a parasitic disease in Tanzania affecting over 50% of the population. Current control strategies involve mass drug administration (MDA) campaigns at the district level, which have led to problems of over- and under-treatment in different areas. WHO guidelines have called for more targeted MDA to circumvent these problems, however a scarcity of prevalence data inhibits decision makers from prioritizing sub-district areas for MDA. This study demonstrated how geostatistics can be used to inform planning for targeted MDA.

METHODS

Geostatistical sub-district (ward-level) prevalence estimates were generated through combining a zero-inflated poisson model and kriging approach (regression kriging). To make predictions, the model used prevalence survey data collected in 2021 of 17,400 school children in six regions of Tanzania, along with several open source ecological and socio-demographic variables with known associations with schistosomiasis.

RESULTS

The model results show that regression kriging can be used to effectively predict the ward level parasite prevalence of the two species of Schistosoma endemic to the study area. Kriging was found to further improve the regression model fit, with an adjusted R-squared value of 0.51 and 0.32 for intestinal and urogenital schistosomiasis, respectively. Targeted treatment based on model predictions would represent a shift in treatment away from 193 wards estimated to be over-treated to 149 wards that would have been omitted from the district level MDA.

CONCLUSIONS

Geostatistical models can help to support NTD program efficiency and reduce disease transmission by facilitating WHO recommended targeted MDA treatment through provision of prevalence estimates where data is scarce.

Geospatial Overlap of Undernutrition and Tuberculosis in Ethiopia

Undernutrition is a key driver of the global tuberculosis (TB) epidemic, yet there is limited understanding regarding the spatial overlap of both diseases. This study aimed to determine the geographical co-distribution and socio-climatic factors of undernutrition and TB in Ethiopia. Data on undernutrition were found from the Ethiopian Demographic and Health Survey (EDHS). Data on TB were obtained from the Ethiopia national TB prevalence survey. We applied a geostatistical model using a Bayesian framework to predict the prevalence of undernutrition and TB. Spatial overlap of undernutrition and TB prevalence was detected in the Afar and Somali regions. Population density was associated with the spatial distribution of TB [β: 0.008; 95% CrI: 0.001, 0.014], wasting [β: -0.017; 95% CrI: -0.032, -0.004], underweight [β: -0.02; 95% CrI: -0.031, -0.011], stunting [β: -0.012; 95% CrI: -0.017, -0.006], and adult undernutrition [β: -0.007; 95% CrI: -0.01, -0.005]. Distance to a health facility was associated with the spatial distribution of stunting [β: 0.269; 95% CrI: 0.08, 0.46] and adult undernutrition [β: 0.176; 95% CrI: 0.044, 0.308]. Healthcare access and demographic factors were associated with the spatial distribution of TB and undernutrition. Therefore, geographically targeted service integration may be more effective than nationwide service integration.

Spatial parasitology and the unmapped human helminthiases

Helminthiases are a class of neglected tropical diseases that affect at least 1 billion people worldwide, with a disproportionate impact on resource-poor areas with limited disease surveillance. Geospatial methods can offer valuable insights into the burden of these infections, particularly given that many are subject to strong ecological influences on the environmental, vector-borne or zoonotic stages of their life cycle. In this study, we screened 6829 abstracts and analysed 485 studies that use maps to document, infer or predict transmission patterns for over 200 species of parasitic worms. We found that quantitative mapping methods are increasingly used in medical parasitology, drawing on One Health surveillance data from the community scale to model geographic distributions and burdens up to the regional or global scale. However, we found that the vast majority of the human helminthiases may be entirely unmapped, with research effort focused disproportionately on a half-dozen infections that are targeted by mass drug administration programmes. Entire regions were also surprisingly under-represented in the literature, particularly southern Asia and the Neotropics. We conclude by proposing a shortlist of possible priorities for future research, including several neglected helminthiases with a burden that may be underestimated.

Opisthorchis viverrini and Strongyloides stercoralis mono- and co-infections: Bayesian geostatistical analysis in an endemic area, Thailand

Parasitic infections caused by Opisthorchis viverrini and Strongyloides stercoralis remain a major public health threat in the Greater Mekong Sub-region. An understanding of climate and other environmental influences on the geographical distribution and emergence of parasitic diseases is a crucial step to guide targeted control and prevention programs. A parasitological survey was conducted from 2008 to 2013 and included 12,554 individuals (age between 20 and 60 years) from 142 villages in five districts in Khon Kaen Province, Thailand. Geographical information systems, remote sensing technologies and a Bayesian geostatistical framework were used to develop models for O. viverrini and S. stercoralis mono- and co-infections in areas where both parasites are known to co-occur. The results indicate that male sex, increased age, altitude, precipitation, and land surface temperature have influenced the infection rate and geographical distribution of mono- and co-infections of O. viverrini and S. stercoralis in this area. Males were 6.69 times (95% CrI: 5.26-8.58) more likely to have O. viverrini - S. stercoralis co-infection. We observed that O. viverrini and S. stercoralis mono-infections display distinct spatial pattern, while co-infection is predicted in the center and southeast of the study area. The observed spatial clustering of O. viverrini and S. stercoralis provides valuable information for the spatial targeting of prevention interventions in this area.

Assessing expanded community wide treatment for schistosomiasis: Baseline infection status and self-reported risk factors in three communities from the Greater Accra region, Ghana

BACKGROUND

This paper reports on the baseline prevalence and associated risk factor findings of a pilot, longitudinal study exploring community-wide treatment of schistosomiasis and soil-transmitted helminthiasis, using albendazole plus praziquantel in the Greater Accra region of Ghana.

METHOD

From three communities, at least, 658 individuals were enrolled into the study via random household selection. Prevalence and intensity of schistosomiasis and STH infection were determined from stool and urine samples with a questionnaire being administered in order to explore other morbidities and risk factors. Factor analysis of household demographic variables was undertaken to generate a socioeconomic score; this was then further categorised into tertiles. Proportional-odds cumulative logit generalised estimating equation (GEE) models were used to investigate categorical ordinal intensity of infection associations with morbidity. Separately, logistic GEE models were used to investigate risk factor associations with infection prevalence.

RESULTS

Both Schistosoma haematobium and S. mansoni were prevalent in the three communities, with the prevalence of S. haematobium ranging from 3.3% (24/679; 95% CI = 1.9-4.7) to 19% (114/632; 95% CI = 15.8-22.2) and S. mansoni ranging from 30% (202/679; 95% CI = 26.5-33.5) to 78.3% (409/536; 95% CI = 74.7-81.9). The total prevalence of STH across all three sites was negligible at 1.3% (24/1847; 95% CI = 0.8-1.9) comprising mainly hookworm (10/1847). Multivariable statistical models indicated males to be 2.3 (95% CI = 1.7-3.3) times more likely to have a high intensity S. mansoni infection and 1.5 (95% CI = 1.1-2) times more likely to have a high intensity of S. haematobium infection compared to females. There was no significant difference in the likelihood of infection with S. mansoni between adults and school age children (SAC), however S. haematobium infections were found to be 2.5 (95% CI = 1.8-3.5) times more likely to occur in school age children than in adults. Multivariable statistical models (adjusted for age and sex) indicated an association between schistosomiasis and a number of self-reported morbidity indicators (notably diarrhoea and blood in stool and urine). Low socio-economic status was also associated with SCH infection (OR: 2; 95% CI = 1.3-3.2).

CONCLUSION

The communities targeted by this study showed a range of Schistosoma prevalence's of infection, from hypo-endemic through to meso-endemic and hyper-endemic. The prevalence of SCH across the different age groups in the study locations highlights the large number of individuals currently being left out of the standard morbidity control method of annual treatment of the SAC.

Parasite associations predict infection risk: incorporating co-infections in predictive models for neglected tropical diseases

BACKGROUND

Schistosomiasis and infection by soil-transmitted helminths are some of the world's most prevalent neglected tropical diseases. Infection by more than one parasite (co-infection) is common and can contribute to clinical morbidity in children. Geostatistical analyses of parasite infection data are key for developing mass drug administration strategies, yet most methods ignore co-infections when estimating risk. Infection status for multiple parasites can act as a useful proxy for data-poor individual-level or environmental risk factors while avoiding regression dilution bias. Conditional random fields (CRF) is a multivariate graphical network method that opens new doors in parasite risk mapping by (i) predicting co-infections with high accuracy; (ii) isolating associations among parasites; and (iii) quantifying how these associations change across landscapes.

METHODS

We built a spatial CRF to estimate infection risks for Ascaris lumbricoides, Trichuris trichiura, hookworms (Ancylostoma duodenale and Necator americanus) and Schistosoma mansoni using data from a national survey of Rwandan schoolchildren. We used an ensemble learning approach to generate spatial predictions by simulating from the CRF's posterior distribution with a multivariate boosted regression tree that captured non-linear relationships between predictors and covariance in infection risks. This CRF ensemble was compared against single parasite gradient boosted machines to assess each model's performance and prediction uncertainty.

RESULTS

Parasite co-infections were common, with 19.57% of children infected with at least two parasites. The CRF ensemble achieved higher predictive power than single-parasite models by improving estimates of co-infection prevalence at the individual level and classifying schools into World Health Organization treatment categories with greater accuracy. The CRF uncovered important environmental and demographic predictors of parasite infection probabilities. Yet even after capturing demographic and environmental risk factors, the presences or absences of other parasites were strong predictors of individual-level infection risk. Spatial predictions delineated high-risk regions in need of anthelminthic treatment interventions, including areas with higher than expected co-infection prevalence.

CONCLUSIONS

Monitoring studies routinely screen for multiple parasites, yet statistical models generally ignore this multivariate data when assessing risk factors and designing treatment guidelines. Multivariate approaches can be instrumental in the global effort to reduce and eventually eliminate neglected helminth infections in developing countries.

Prediction of hookworm prevalence in southern India using environmental parameters derived from Landsat 8 remotely sensed data

Soil-transmitted helminth infections propagate poverty and slow economic growth in low-income countries. As with many other neglected tropical diseases, environmental conditions are important determinants of soil-transmitted helminth transmission. Hence, remotely sensed data are commonly utilised in spatial risk models intended to inform control strategies. In the present study, we build upon the existing modelling approaches by utilising fine spatial resolution Landsat 8 remotely sensed data in combination with topographic variables to predict hookworm prevalence in a hilly tribal area in southern India. Hookworm prevalence data collected from two field surveys were used in a random forest model to investigate the predictive capacity of 15 environmental variables derived from two remotely sensed images acquired during dry and rainy seasons. A variable buffer radius (100-1000 m) was applied to the point-prevalence locations in order to integrate environmental conditions around the village centroids into the modelling approach and understand where transmission is more likely. Elevation and slope were the most important variables in the models, with lower elevation and higher slope correlating with higher transmission risk. A modified normalised difference water index was among other recurring important variables, likely responsible for some seasonal differences in model performance. The 300 m buffer distance produced the best model performance in this setting, with another spike at 700 m, and a marked drop-off in R² values at 1000 m. In addition to assessing a large number of environmental correlates with hookworm transmission, the study contributes to the development of standardised methods of spatial linkage of continuous environmental data with point-based disease prevalence measures for the purpose of spatially explicit risk profiling.

Mapping Schistosoma mansoni endemicity in Rwanda: a critical assessment of geographical disparities arising from circulating cathodic antigen versus Kato-Katz diagnostics

BACKGROUND

Schistosomiasis is a neglected tropical disease caused by Schistosoma parasites. Intervention relies on identifying high-risk regions, yet rapid Schistosoma diagnostics (Kato-Katz stool assays (KK) and circulating cathodic antigen urine assays (CCA)) yield different prevalence estimates. We mapped S. mansoni prevalence and delineated at-risk regions using a survey of schoolchildren in Rwanda, where S. mansoni is an endemic parasite. We asked if different diagnostics resulted in disparities in projected infection risk.

METHODS

Infection data was obtained from a 2014 Rwandan school-based survey that used KK and CCA diagnostics. Across 386 schools screened by CCA (N = 19,217). To allow for uncertainty when interpreting ambiguous CCA trace readings, which accounted for 28.8% of total test results, we generated two presence-absence datasets: CCA trace as positive and CCA trace as negative. Samples (N = 9,175) from 185 schools were also screened by KK. We included land surface temperature (LST) and the Normalized Difference Vegetation and Normalized Difference Water Indices (NDVI, NDWI) as predictors in geostatistical regressions.

FINDINGS

Across 8,647 children tested by both methods, prevalence was 35.93% for CCA trace as positive, 7.21% for CCA trace as negative and 1.95% for KK. LST was identified as a risk factor using KK, whereas NDVI was a risk factor for CCA models. Models predicted high endemicity in Northern and Western regions of Rwanda, though the CCA trace as positive model identified additional high-risk areas that were overlooked by the other methods. Estimates of current burden for children at highest risk (boys aged 5-9 years) varied by an order of magnitude, with 671,856 boys projected to be infected by CCA trace as positive and only 60,453 projected by CCA trace as negative results.

CONCLUSIONS

Our findings show that people in Rwanda's Northern, Western and capital regions are at high risk of S. mansoni infection. However, variation in identification of environmental risk factors and delineation of at-risk regions using different diagnostics likely provides confusing messages to disease intervention managers. Further research and statistical analyses, such as latent class analysis, can be used to improve CCA result classification and assess its use in guiding treatment regimes.

The extent, nature, and pathogenic consequences of helminth polyparasitism in humans: A meta-analysis

Background

Individual helminth infections are ubiquitous in the tropics; geographical overlaps in endemicity and epidemiological reports suggest areas endemic for multiple helminthiases are also burdened with high prevalences of intestinal protozoan infections, malaria, tuberculosis (TB), and human immunodeficiency virus (HIV). Despite this, pathogens tend to be studied in isolation, and there remains a need for a better understanding of the community ecology and health consequences of helminth polyparasitism to inform the design of effective parasite control programs.

Methodology

We performed meta-analyses to (i) evaluate the commonality of polyparasitism for helminth-helminth, helminth-intestinal protozoa, helminth-malaria, helminth-TB, and helminth-HIV co-infections, (ii) assess the potential for interspecies interactions among helminth-helminth and helminth-intestinal protozoan infections, and (iii) determine the presence and magnitude of association between specific parasite pairs. Additionally, we conducted a review of reported health consequences of multiply-infected individuals compared to singly- or not multiply-infected individuals.

Principal findings

We found that helminth-helminth and helminth-intestinal protozoan multiple infections were significantly more common than single infections, while individuals with malaria, TB, and HIV were more likely to be singly-infected with these infections than co-infected with at least one helminth. Most observed species density distributions significantly differed from the expected distributions, suggesting the potential presence of interspecies interactions. All significant associations between parasite pairs were positive in direction, irrespective of the combination of pathogens. Polyparasitized individuals largely exhibited lower hemoglobin levels and higher anemia prevalence, while the differences in growth-related variables were mostly statistically insignificant.

Conclusions

Our findings confirm that helminth polyparasitism and co-infection with major diseases is common in the tropics. A multitude of factors acting at various hierarchical levels, such as interspecies interactions at the within-host infra-parasite community level and environmental variables at the higher host community level, could explain the observed positive associations between pathogens; there remains a need to develop new frameworks which can consider these multilevel factors to better understand the processes structuring parasite communities to accomplish their control.

Helminth infections are a highly prevalent global health problem. These parasitic worm infections occur in areas also burdened with intestinal protozoan infections, malaria, tuberculosis, and human immunodeficiency virus. While these pathogens tend to be studied in isolation, there remains a need to better understand the nature, extent, and health consequences of helminth polyparasitism and co-infection with major diseases. Here, we reviewed the literature and performed meta-analyses to evaluate the commonality of helminth polyparasitism and co-infection, the potential for interspecies interactions between parasites, the association between parasite pairs, and the health consequences among multiply-infected individuals. We confirmed that polyparasitism and co-infection with major diseases are common in the global South and found that multiply-infected individuals experienced worse health consequences when compared to singly or not-multiply infected individuals. Our analysis suggested the potential presence of interspecies interactions and we identified the existence of positive associations between parasite pairs. These findings support the call for integrating deworming into malaria, TB, and HIV treatment protocols and suggest there remains a need to improve our understanding of the factors influencing co-transmission to achieve sustainable parasite control.

Host immunity, nutrition and coinfection alter longitudinal infection patterns of schistosomes in a free ranging African buffalo population

Schistosomes are trematode parasites of global importance, causing infections in millions of people, livestock, and wildlife. Most studies on schistosomiasis, involve human subjects; as such, there is a paucity of longitudinal studies investigating parasite dynamics in the absence of intervention. As a consequence, despite decades of research on schistosomiasis, our understanding of its ecology in natural host populations is centered around how environmental exposure and acquired immunity influence acquisition of parasites, while very little is known about the influence of host physiology, coinfection and clearance in the absence of drug treatment. We used a 4-year study in free-ranging African buffalo to investigate natural schistosome dynamics. We asked (i) what are the spatial and temporal patterns of schistosome infections; (ii) how do parasite burdens vary over time within individual hosts; and (iii) what host factors (immunological, physiological, co-infection) and environmental factors (season, location) explain patterns of schistosome acquisition and loss in buffalo? Schistosome infections were common among buffalo. Microgeographic structure explained some variation in parasite burdens among hosts, indicating transmission hotspots. Overall, parasite burdens ratcheted up over time; however, gains in schistosome abundance in the dry season were partially offset by losses in the wet season, with some hosts demonstrating complete clearance of infection. Variation among buffalo in schistosome loss was associated with immunologic and nutritional factors, as well as co-infection by the gastrointestinal helminth Cooperia fuelleborni. Our results demonstrate that schistosome infections are surprisingly dynamic in a free-living mammalian host population, and point to a role for host factors in driving variation in parasite clearance, but not parasite acquisition which is driven by seasonal changes and spatial habitat utilization. Our study illustrates the power of longitudinal studies for discovering mechanisms underlying parasite dynamics in individual animals and populations.

Epidemiology of polyparasitism with Taenia solium, schistosomes and soil-transmitted helminths in the co-endemic village of Malanga, Democratic Republic of Congo

Helminth co-infections are common in sub-Saharan Africa. However, little is known about the distribution and determinants of co-infections with Taenia solium taeniasis/cysticercosis. Building on a previous community-based study on human cysticercosis in Malanga village, we investigated co-infections with Taenia solium, soil-transmitted helminths (STHs) and Schistosoma spp and associated risk factors in a random subsample of 330 participants. Real time PCR assays were used to detect DNA of soil-transmitted helminths (STHs), T. solium and Schistosoma in stool samples and Schistosoma DNA in urine samples. Serum samples were tested for T. solium cysticercosis using the B158/B60 monoclonal antibody-based antigen ELISA. Bivariate analysis and logistic regression were applied to assess associations of single and co-infections with common risk factors (age, sex, area, hygiene) as well as pair wise associations between helminth species. Overall, 240 (72.7%) participants were infected with at least one helminth species; 128 (38.8%) harbored at least two helminth species (16.1% with STHs-Schistosoma, 14.5% with STHs-T. solium taeniasis/cysticercosis and 8.2% with Schistosoma-T. solium taeniasis/cysticercosis co-infections). No significant associations were found between Schistosoma-T. solium taeniasis/cysticercosis co-infection and any of the risk factors studied. Males (OR=2 (95%CI=1.1-5), p=0.03) and open defecation behavior (OR=3.8 (95%CI=1.1-6.5), p=0.04) were associated with higher odds of STHs-T. solium taeniasis/cysticercosis co-infection. Village districts that were found at high risk of T. solium taeniasis/cysticercosis were also at high risk of co-infection with STHs and T. solium taeniasis/cysticercosis (OR=3.2 (95%CI=1.1-7.8), p=0.03). Significant pair-wise associations were found between T. solium cysticerci and Necator americanus (OR=2.2 (95%CI=1.2-3.8), p<0.01) as well as Strongyloides stercoralis (OR=2.7 (95%CI=1.1-6.5), p=0.02). These findings show that co-infections with T. solium are common in this polyparasitic community in DRC. Our results on risk factors of helminth co-infections and specific associations between helminths may contribute to a better integration of control within programmes that target more than one NTD.

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.

Hookworm infection

Hookworms are soil-transmitted nematode parasites that can reside for many years in the small intestine of their human hosts; Necator americanus is the predominant infecting species. Adult worms feed on the blood of a host and can cause iron deficiency anaemia, especially in high-risk populations (children and women of childbearing age). Almost 500 million people in developing tropical countries are infected, and simulation models estimate that hookworm infection is responsible for >4 million disability-adjusted life years lost annually. Humans mount an immune response to hookworms, but it is mostly unsuccessful at removing adult worms from the bowel. Accordingly, the host switches to an immune-tolerant state that enables hookworms to reside in the gut for many years. Although anthelmintic drugs are available and widely used, their efficacy varies and the drugs do not prevent reinfection. Thus, other control strategies aimed at improving water quality, sanitation and hygiene are needed. In addition, efforts are underway to develop a human hookworm vaccine through public-private partnerships. However, hookworms could also be a resource; as hookworms have the capability to regulate the host's inflammation, researchers are experimentally infecting patients to treat some inflammatory diseases as an approach to discover new anti-inflammatory molecules. This area of endeavour might well yield new biotherapeutics for autoimmune and allergic diseases.

High prevalence of Strongyloides stercoralis in school-aged children in a rural highland of north-western Ethiopia: the role of intensive diagnostic work-up

Background

Soil-transmitted helminthiases (hookworms, Ascaris lumbricoides and Trichuris trichiura) are extremely prevalent in school-aged children living in poor sanitary conditions. Recent epidemiological data suggest that Strongyloides stercoralis is highly unreported. However, accurate data are essential for conducting interventions aimed at introducing control and elimination programmes.

Methods

We conducted a cross-sectional survey of 396 randomly selected school-aged children in Amhara region in rural area in north-western Ethiopia, to assess the prevalence of S. stercoralis and other intestinal helminths. We examined stools using three techniques: conventional stool concentration; and two S. stercoralis-specific methods, i.e. the Baermann technique and polymerase chain reaction. The diagnostic accuracy of these three methods was then compared.

Results

There was an overall prevalence of helminths of 77.5%, with distribution differing according to school setting. Soil-transmitted helminths were recorded in 69.2%. Prevalence of S. stercoralis and hookworm infection was 20.7 and 54.5%, respectively, and co-infection was detected in 16.3% of cases. Schistosoma mansoni had a prevalence of 15.7%. Prevalence of S. stercoralis was shown 3.5% by the conventional method, 12.1% by the Baermann method, and 13.4% by PCR, which thus proved to be the most sensitive.

Conclusions

Our results suggest that S. stercoralis could be overlooked and neglected in Ethiopia, if studies of soil-transmitted helminths rely on conventional diagnostic techniques alone. A combination of molecular and stool microscopy techniques yields a significantly higher prevalence. In view of the fact that current control policies for triggering drug administration are based on parasite prevalence levels, a comprehensive diagnostic approach should instead be applied to ensure comprehensive control of helminth infections.

Spatial measurement errors in the field of spatial epidemiology

Background

Spatial epidemiology has been aided by advances in geographic information systems, remote sensing, global positioning systems and the development of new statistical methodologies specifically designed for such data. Given the growing popularity of these studies, we sought to review and analyze the types of spatial measurement errors commonly encountered during spatial epidemiological analysis of spatial data.

Methods

Google Scholar, Medline, and Scopus databases were searched using a broad set of terms for papers indexed by a term indicating location (space or geography or location or position) and measurement error (measurement error or measurement inaccuracy or misclassification or uncertainty): we reviewed all papers appearing before December 20, 2014. These papers and their citations were reviewed to identify the relevance to our review.

Results

We were able to define and classify spatial measurement errors into four groups: (1) pure spatial location measurement errors, including both non-instrumental errors (multiple addresses, geocoding errors, outcome aggregations, and covariate aggregation) and instrumental errors; (2) location-based outcome measurement error (purely outcome measurement errors and missing outcome measurements); (3) location-based covariate measurement errors (address proxies); and (4) Covariate-Outcome spatial misaligned measurement errors. We propose how these four classes of errors can be unified within an integrated theoretical model and possible solutions were discussed.

Conclusion

Spatial measurement errors are ubiquitous threat to the validity of spatial epidemiological studies. We propose a systematic framework for understanding the various mechanisms which generate spatial measurement errors and present practical examples of such errors.

Analysing risk factors of co-occurrence of schistosomiasis haematobium and hookworm using bivariate regression models: Case study of Chikwawa, Malawi

Schistosomiasis and soil-transmitted helminth (STH) infections constitute a major public health problem in many parts of sub-Saharan Africa. In areas where prevalence of geo-helminths and schistosomes is high, co-infection with multiple parasite species is common, resulting in disproportionately elevated burden compared with single infections. Determining risk factors of co-infection intensity is important for better design of targeted interventions. In this paper, we examined risk factors of hookworm and S. haematobium co-infection intensity, in Chikwawa district, southern Malawi in 2005, using bivariate count models. Results show that hookworm and S. haematobium infections were much localised with small proportion of individuals harbouring more parasites especially among school-aged children. The risk of co-intensity with both hookworm and S. haematobium was high for all ages, although this diminished with increasing age, increased with fishing (hookworm: coefficient. = 12.29; 95% CI = 11.50-13.09; S. haematobium: 0.040; 95% CI = 0.0037, 3.832). Both infections were abundant in those with primary education (hookworm: coef. = 0.072; 95% CI = 0.056, 0.401 and S. haematobium: coef. = 0.286; 95% CI = 0.034, 0.538). However, much lower risk was observed for those who were farmers (hookworm: coef. = - 0.349, 95% CI = - 0.547,-0.150; S. haematobium: coef. - 0.239, 95% CI = - 0.406, - 0.072). In conclusion, our findings suggest that efforts to control helminths infection should be co-integrated and health promotion campaigns should be aimed at school-going children and adults who are in constant contact with water.

Socioeconomic Inequalities in Neglected Tropical Diseases: A Systematic Review

BACKGROUND

Neglected tropical diseases (NTDs) are generally assumed to be concentrated in poor populations, but evidence on this remains scattered. We describe within-country socioeconomic inequalities in nine NTDs listed in the London Declaration for intensified control and/or elimination: lymphatic filariasis (LF), onchocerciasis, schistosomiasis, soil-transmitted helminthiasis (STH), trachoma, Chagas' disease, human African trypanosomiasis (HAT), leprosy, and visceral leishmaniasis (VL).

METHODOLOGY

We conducted a systematic literature review, including publications between 2004-2013 found in Embase, Medline (OvidSP), Cochrane Central, Web of Science, Popline, Lilacs, and Scielo. We included publications in international peer-reviewed journals on studies concerning the top 20 countries in terms of the burden of the NTD under study.

PRINCIPAL FINDINGS

We identified 5,516 publications, of which 93 met the inclusion criteria. Of these, 59 papers reported substantial and statistically significant socioeconomic inequalities in NTD distribution, with higher odds of infection or disease among poor and less-educated people compared with better-off groups. The findings were mixed in 23 studies, and 11 studies showed no substantial or statistically significant inequality. Most information was available for STH, VL, schistosomiasis, and, to a lesser extent, for trachoma. For the other NTDs, evidence on their socioeconomic distribution was scarce. The magnitude of inequality varied, but often, the odds of infection or disease were twice as high among socioeconomically disadvantaged groups compared with better-off strata. Inequalities often took the form of a gradient, with higher odds of infection or disease each step down the socioeconomic hierarchy. Notwithstanding these inequalities, the prevalence of some NTDs was sometimes also high among better-off groups in some highly endemic areas.

CONCLUSIONS

While recent evidence on socioeconomic inequalities is scarce for most individual NTDs, for some, there is considerable evidence of substantially higher odds of infection or disease among socioeconomically disadvantaged groups. NTD control activities as proposed in the London Declaration, when set up in a way that they reach the most in need, will benefit the poorest populations in poor countries.

Application of GIS technology in public health: successes and challenges

The uptake and acceptance of Geographic Information Systems (GIS) technology has increased since the early 1990s and public health applications are rapidly expanding. In this paper, we summarize the common uses of GIS technology in the public health sector, emphasizing applications related to mapping and understanding of parasitic diseases. We also present some of the success stories, and discuss the challenges that still prevent a full scope application of GIS technology in the public health context. Geographical analysis has allowed researchers to interlink health, population and environmental data, thus enabling them to evaluate and quantify relationships between health-related variables and environmental risk factors at different geographical scales. The ability to access, share and utilize satellite and remote-sensing data has made possible even wider understanding of disease processes and of their links to the environment, an important consideration in the study of parasitic diseases. For example, disease prevention and control strategies resulting from investigations conducted in a GIS environment have been applied in many areas, particularly in Africa. However, there remain several challenges to a more widespread use of GIS technology, such as: limited access to GIS infrastructure, inadequate technical and analytical skills, and uneven data availability. Opportunities exist for international collaboration to address these limitations through knowledge sharing and governance.

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.

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.

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.

Enterobiasis and strongyloidiasis and associated co-infections and morbidity markers in infants, preschool- and school-aged children from rural coastal Tanzania: a cross-sectional study

Background

There is a paucity of data pertaining to the epidemiology and public health impact of Enterobius vermicularis and Strongyloides stercoralis infections. We aimed to determine the extent of enterobiasis, strongyloidiasis, and other helminth infections and their association with asymptomatic Plasmodium parasitaemia, anaemia, nutritional status, and blood cell counts in infants, preschool-aged (PSAC), and school-aged children (SAC) from rural coastal Tanzania.

Methods

A total of 1,033 children were included in a cross-sectional study implemented in the Bagamoyo district in 2011/2012. Faecal samples were examined for intestinal helminth infections using a broad set of quality controlled methods. Finger-prick blood samples were subjected to filariasis and Plasmodium parasitaemia testing and full blood cell count examination. Weight, length/height, and/or mid-upper arm circumference were measured and the nutritional status determined in accordance with age.

Results

E. vermicularis infections were found in 4.2% of infants, 16.7%, of PSAC, and 26.3% of SAC. S. stercoralis infections were detected in 5.8%, 7.5%, and 7.1% of infants, PSAC, and SAC, respectively. Multivariable regression analyses revealed higher odds of enterobiasis in children of all age-groups with a reported anthelminthic treatment history over the past six months (odds ratio (OR): 2.15; 95% confidence interval (CI): 1.22 - 3.79) and in SAC with a higher temperature (OR: 2.21; CI: 1.13 - 4.33). Strongyloidiasis was associated with eosinophilia (OR: 2.04; CI: 1.20-3.48) and with Trichuris trichiura infections (OR: 4.13; CI: 1.04-16.52) in children of all age-groups, and with asymptomatic Plasmodium parasitaemia (OR: 13.03; CI: 1.34 - 127.23) in infants. None of the investigated helminthiases impacted significantly on the nutritional status and anaemia, but moderate asymptomatic Plasmodium parasitaemia was a strong predictor for anaemia in children aged older than two years (OR: 2.69; 95% CI: 1.23 – 5.86).

Conclusions

E. vermicularis and S. stercoralis infections were moderately prevalent in children from rural coastal Tanzania. Our data can contribute to inform yet missing global burden of disease and prevalence estimates for strongyloidiasis and enterobiasis. The association between S stercoralis and asymptomatic Plasmodium parasitaemia found here warrants further comprehensive investigations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-014-0644-7) contains supplementary material, which is available to authorized users.

Impact of Schistosoma mansoni on malaria transmission in Sub-Saharan Africa

Background

Sub-Saharan Africa harbors the majority of the global burden of malaria and schistosomiasis infections. The co-endemicity of these two tropical diseases has prompted investigation into the mechanisms of coinfection, particularly the competing immunological responses associated with each disease. Epidemiological studies have shown that infection with Schistosoma mansoni is associated with a greater malaria incidence among school-age children.

Methodology

We developed a co-epidemic model of malaria and S. mansoni transmission dynamics which takes into account key epidemiological interaction between the two diseases in terms of elevated malaria incidence among individuals with S. mansoni high egg output. The model was parameterized for S. mansoni high-risk endemic communities, using epidemiological and clinical data of the interaction between S. mansoni and malaria among children in sub-Saharan Africa. We evaluated the potential impact of the S. mansoni–malaria interaction and mass treatment of schistosomiasis on malaria prevalence in co-endemic communities.

Principal Findings

Our results suggest that in the absence of mass drug administration of praziquantel, the interaction between S. mansoni and malaria may reduce the effectiveness of malaria treatment for curtailing malaria transmission, in S. mansoni high-risk endemic communities. However, when malaria treatment is used in combination with praziquantel, mass praziquantel administration may increase the effectiveness of malaria control intervention strategy for reducing malaria prevalence in malaria- S. mansoni co-endemic communities.

Conclusions/Significance

Schistosomiasis treatment and control programmes in regions where S. mansoni and malaria are highly prevalent may have indirect benefits on reducing malaria transmission as a result of disease interactions. In particular, mass praziquantel administration may not only have the direct benefit of reducing schistosomiasis infection, it may also reduce malaria transmission and disease burden.

Malaria and Schistosoma mansoni are co-endemic in many regions of sub-Saharan Africa. Evidence from clinical and epidemiological studies support the hypothesis that concurrent infection with S. mansoni is associated with greater malaria incidence among school-age children. We use mathematical modeling to evaluate the epidemiological impact of S. mansoni infection on malaria transmission in sub-Saharan Africa. Using epidemiological data on the increased risk of malaria incidence in S. mansoni endemic communities from Senegal, we developed a co-epidemic model of malaria and S. mansoni transmission dynamics to address key epidemiological interactions between the two diseases. Parameterizing our model for S. mansoni high-risk endemic communities, we show that the interaction between S. mansoni and malaria may reduce the effectiveness of malaria treatment for curtailing malaria transmission. Moreover, we show that in addition to reducing schistosomiasis health burden, mass praziquantel administration will generate indirect benefit in terms of reducing malaria transmission and disease burden in S. mansoni–malaria co-endemic communities. Our findings indicate the possible benefit of scaling up schistosomiasis control efforts in sub-Saharan Africa, and especially in areas were S. mansoni and malaria are highly prevalent.

Cross-sectional study of the burden of vector-borne and soil-transmitted polyparasitism in rural communities of Coast Province, Kenya

Background

In coastal Kenya, infection of human populations by a variety of parasites often results in co-infection or poly-parasitism. These parasitic infections, separately and in conjunction, are a major cause of chronic clinical and sub-clinical human disease and exert a long-term toll on economic welfare of affected populations. Risk factors for these infections are often shared and overlap in space, resulting in interrelated patterns of transmission that need to be considered at different spatial scales. Integration of novel quantitative tools and qualitative approaches is needed to analyze transmission dynamics and design effective interventions.

Methodology

Our study was focused on detecting spatial and demographic patterns of single- and co-infection in six villages in coastal Kenya. Individual and household level data were acquired using cross-sectional, socio-economic, and entomological surveys. Generalized additive models (GAMs and GAMMs) were applied to determine risk factors for infection and co-infections. Spatial analysis techniques were used to detect local clusters of single and multiple infections.

Principal findings

Of the 5,713 tested individuals, more than 50% were infected with at least one parasite and nearly 20% showed co-infections. Infections with Schistosoma haematobium (26.0%) and hookworm (21.4%) were most common, as was co-infection by both (6.3%). Single and co-infections shared similar environmental and socio-demographic risk factors. The prevalence of single and multiple infections was heterogeneous among and within communities. Clusters of single and co-infections were detected in each village, often spatially overlapped, and were associated with lower SES and household crowding.

Conclusion

Parasitic infections and co-infections are widespread in coastal Kenya, and their distributions are heterogeneous across landscapes, but inter-related. We highlighted how shared risk factors are associated with high prevalence of single infections and can result in spatial clustering of co-infections. Spatial heterogeneity and synergistic risk factors for polyparasitism need to be considered when designing surveillance and intervention strategies.

In Coast Province, Kenya, infections with Schistosoma haematobium, Plasmodium spp., filarial nematodes, and geohelminths are common, resulting in high levels of both single infections and polyparasitism. The long-term effect of these infections, separately or in combination, has a major impact on human health and on the economic welfare of affected populations. The transmission dynamics of these parasitic infections can be linked to shared risk factors that often overlap in space. We studied human and environmental factors driving transmission and the resulting spatial pattern of infections in six communities, using cross-sectional, socio-economic and entomological surveys. Single and co-infections were widespread in the communities, and were associated with environmental, demographic and socio-economic risk factors, including distance of community from the coast, sanitation and human age and crowding. The spatial patterns of single and co-infections were heterogeneous among and within communities, with overlapping clusters of single and multiple infections in areas where houses with lower socio-economic status and more crowding were located. The heterogeneities among and within communities can provide important insights when designing surveillance and intervention strategies when planning appropriate surveillance and control strategies targeting polyparasitism.

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.

Predictive risk mapping of schistosomiasis in Brazil using Bayesian geostatistical models

Schistosomiasis is one of the most common parasitic diseases in tropical and subtropical areas, including Brazil. A national control programme was initiated in Brazil in the mid-1970s and proved successful in terms of morbidity control, as the number of cases with hepato-splenic involvement was reduced significantly. To consolidate control and move towards elimination, there is a need for reliable maps on the spatial distribution of schistosomiasis, so that interventions can target communities at highest risk. The purpose of this study was to map the distribution of Schistosoma mansoni in Brazil. We utilized readily available prevalence data from the national schistosomiasis control programme for the years 2005-2009, derived remotely sensed climatic and environmental data and obtained socioeconomic data from various sources. Data were collated into a geographical information system and Bayesian geostatistical models were developed. Model-based maps identified important risk factors related to the transmission of S. mansoni and confirmed that environmental variables are closely associated with indices of poverty. Our smoothed predictive risk map, including uncertainty, highlights priority areas for intervention, namely the northern parts of North and Southeast regions and the eastern part of Northeast region. Our predictive risk map provides a useful tool for to strengthen existing surveillance-response mechanisms.

Spatial analysis of schistosomiasis human cases in the horticultural community of Zona da Mata of Pernambuco state, Brazil

The objective of this study was to describe the spatial distribution of schistosomiasis in horticultural community of Natuba, district of Vitória de Santo Antão, Pernambuco state. It was conducted a parasitological survey, examined the fecal material of 310 community residents. The cases positive for Schistosoma mansoni were geocoded and included in the computerized template of the community, generating maps of spatial distribution with kernel estimators. The results showed a high prevalence of schistosomiasis, with 28.4% of the parasites. Other parasites were found in 25.8% of the population. The use of GIS tools to map and understand the possible distribution of cases of schistosomiasis in the space occupied by the community highlighting and listing locations of lower elevation (able to flooding), with a higher frequency of human cases. Studies like this provide information to the local health services, may intervene and bring about change for individuals living in areas with low housing conditions to minimize their exposure to risk of contracting schistosomiasis.

Analysis of Schistosomiasis haematobium infection prevalence and intensity in Chikhwawa, Malawi: an application of a two part model

Background

Urinary Schistosomiasis infection, a common cause of morbidity especially among children in less developed countries, is measured by the number of eggs per urine. Typically a large proportion of individuals are non-egg excretors, leading to a large number of zeros. Control strategies require better understanding of its epidemiology, hence appropriate methods to model infection prevalence and intensity are crucial, particularly if such methods add value to targeted implementation of interventions.

Methods

We consider data that were collected in a cluster randomized study in 2004 in Chikhwawa district, Malawi, where eighteen (18) villages were selected and randomised to intervention and control arms. We developed a two-part model, with one part for analysis of infection prevalence and the other to model infection intensity. In both parts of the model we adjusted for age, sex, education level, treatment arm, occupation, and poly-parasitism. We also assessed for spatial correlation in the model residual using variogram analysis and mapped the spatial variation in risk. The model was fitted using maximum likelihood estimation.

Results and discussion

The study had a total of 1642 participants with mean age of 32.4 (Standard deviation: 22.8), of which 55.4 % were female. Schistosomiasis prevalence was 14.2 %, with a large proportion of individuals (85.8 %) being non-egg excretors, hence zero-inflated data. Our findings showed that S. haematobium was highly localized even after adjusting for risk factors. Prevalence of infection was low in males as compared to females across all the age ranges. S. haematobium infection increased with presence of co-infection with other parasite infection. Infection intensity was highly associated with age; with highest intensity in school-aged children (6 to 15 years). Fishing and working in gardens along the Shire River were potential risk factors for S. haematobium infection intensity. Intervention reduced both infection intensity and prevalence in the intervention arm as compared to control arm. Farmers had high infection intensity as compared to non farmers, despite the fact that being a farmer did not show any significant association with probability of infection.

These results evidently indicate that infection prevalence and intensity are associated with risk factors differently, suggesting a non-singular epidemiological setting. The dominance of agricultural, socio-economic and demographic factors in determining S. haematobium infection and intensity suggest that disease transmission and control strategies should continue centring on improving socio-economic status, environmental modifications to control S. haematobium intermediate host snails and mass drug administration, which may be more promising approaches to disease control in high intensity and prevalence settings.

Schistosomiasis is one of the great causes of morbidity among school aged children in the tropical region and Sub Saharan Africa in particular. It's mainly transmitted through contact with water infested with intermediate host snail Cercariae. Currently, over 200 million people are estimated to be infected in SSA alone. Here, we used robust and contemporary statistical methods in a two part application to analyse risk factors for S. haematobium infection intensity and prevalence. We found that S. haematobium was more common in younger children as compared to older children, thus making the infection and prevalence age dependent. We also found that mass chemotherapy reduced both infection prevalence and intensity. We found that dominance of agricultural, socio-economic and demographic factors in determining S. haematobium infection risk in the villages carries important implications for disease surveillance and control strategies. Therefore disease transmission and control strategies centered on improving strategies involving socio-economic status, environmental modifications to control S. haematobium intermediate host snails and mass drug administration may be more promising approaches to disease control in high intensity and prevalence settings.

Serum CCL11 (eotaxin-1) and CCL17 (TARC) are serological indicators of multiple helminth infections and are driven by Schistosoma mansoni infection in humans

OBJECTIVES

To evaluate systemic serum cytokine and chemokine markers for inflammation and Th1/Th2 responses in relation to multiple helminth infections, parasite burden and/or nutritional status of individuals.

METHODS

In a longitudinal study, stool samples from 210 individuals from an area highly endemic for Ascaris lumbricoides, Necator americanus and Schistosoma mansoni were examined before and 12 months after clearance of parasites by chemotherapy. On both occasions, the presence of mono- or multiple infections and intensities of infection were compared with nutritional parameters and with serum cytokines or chemokines as markers for inflammatory, regulatory or Th1- or Th2-type immune responses.

RESULTS

Before treatment, we were not able to associate any altered nutritional parameters with increased inflammatory responses, and highest intensities of infection were found in eutrophic participants with multiple infections. In contrast, major changes in serum Th2-type chemokine levels were measured in individuals infected with intestinal helminths and/or S. mansoni, and resulted in significantly higher CCL11 and CCL17 concentrations, both before treatment and after reinfection.

CONCLUSIONS

The driving force for these elevated type 2 serum chemokine concentrations was an S. mansoni infection and faecal egg counts significantly correlated with serum IL-10 concentrations.

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.

Determining treatment needs at different spatial scales using geostatistical model-based risk estimates of schistosomiasis

Background

After many years of neglect, schistosomiasis control is going to scale. The strategy of choice is preventive chemotherapy, that is the repeated large-scale administration of praziquantel (a safe and highly efficacious drug) to at-risk populations. The frequency of praziquantel administration is based on endemicity, which usually is defined by prevalence data summarized at an arbitrarily chosen administrative level.

Methodology

For an ensemble of 29 West and East African countries, we determined the annualized praziquantel treatment needs for the school-aged population, adhering to World Health Organization guidelines. Different administrative levels of prevalence aggregation were considered; country, province, district, and pixel level. Previously published results on spatially explicit schistosomiasis risk in the selected countries were employed to classify each area into distinct endemicity classes that govern the frequency of praziquantel administration.

Principal Findings

Estimates of infection prevalence adjusted for the school-aged population in 2010 revealed that most countries are classified as moderately endemic for schistosomiasis (prevalence 10–50%), while four countries (i.e., Ghana, Liberia, Mozambique, and Sierra Leone) are highly endemic (>50%). Overall, 72.7 million annualized praziquantel treatments (50% confidence interval (CI): 68.8–100.7 million) are required for the school-aged population if country-level schistosomiasis prevalence estimates are considered, and 81.5 million treatments (50% CI: 67.3–107.5 million) if estimation is based on a more refined spatial scale at the provincial level.

Conclusions/Significance

Praziquantel treatment needs may be over- or underestimated depending on the level of spatial aggregation. The distribution of schistosomiasis in Ethiopia, Liberia, Mauritania, Uganda, and Zambia is rather uniform, and hence country-level risk estimates are sufficient to calculate treatment needs. On the other hand, countries like Burkina Faso, Mali, Mozambique, Sudan, and Tanzania show large spatial heterogeneity in schistosomiasis risk, which should be taken into account for calculating treatment requirements.

More than 200 million people are affected by the snailborne disease schistosomiasis. The main strategy to control schistosomiasis is to regularly treat school-aged children with the drug praziquantel. The frequency of praziquantel treatment depends on the average prevalence of schistosomiasis, which can be defined as low (prevalence <10%), moderate (10–50%), or high (>50%). However, it remains unclear at which geographical scale these prevalence levels should be considered to avoid unnecessary treatments but still comply with local needs. We investigated the effect of the geographical scale for an ensemble of 29 West and East African countries using previously published model-based schistosomiasis risk estimates obtained at high spatial resolution. These estimates allow spatial risk aggregation at different geographical scales (i.e., country, region, district, or pixel level). More than 70 million praziquantel treatments are required every year for school-aged children if countrylevel estimates are used. On a more refined geographical scale (i.e., province), annualized praziquantel treatments increase by 12%. Depending on the averaged schistosomiasis prevalence and the spatial risk variation across a country, the difference in the estimated amount of praziquantel between country-level aggregation and other geographical scales might be very important, as for example in Burkina Faso, Ghana, and Mali.

Long-term impact of the World Bank Loan Project for schistosomiasis control: a comparison of the spatial distribution of schistosomiasis risk in China

BACKGROUND

The World Bank Loan Project (WBLP) for controlling schistosomiasis in China was implemented during 1992-2001. Its short-term impact has been assessed from non-spatial perspective, but its long-term impact remains unclear and a spatial evaluation has not previously been conducted. Here we compared the spatial distribution of schistosomiasis risk using national datasets in the lake and marshland regions from 1999-2001 and 2007-2008 to evaluate the long-term impact of WBLP strategy on China's schistosomiasis burden.

METHODOLOGY/PRINCIPAL FINDINGS

A hierarchical Poisson regression model was developed in a Bayesian framework with spatially correlated and uncorrelated heterogeneities at the county-level, modeled using a conditional autoregressive prior structure and a spatially unstructured Gaussian distribution, respectively. There were two important findings from this study. The WBLP strategy was found to have a good short-term impact on schistosomiasis control, but its long-term impact was not ideal. It has successfully reduced the morbidity of schistosomiasis to a low level, but can not contribute further to China's schistosomiasis control because of the current low endemic level. A second finding is that the WBLP strategy could not effectively compress the spatial distribution of schistosomiasis risk. To achieve further reductions in schistosomiasis-affected areas, and for sustainable control, focusing on the intermediate host snail should become the next step to interrupt schistosomiasis transmission within the two most affected regions surrounding the Dongting and Poyang Lakes. Furthermore, in the lower reaches of the Yangtze River, the WBLP's morbidity control strategy may need to continue for some time until snails in the upriver provinces have been well controlled.

CONCLUSION

It is difficult to further reduce morbidity due to schistosomiasis using a chemotherapy-based control strategy in the lake and marshland regions of China because of the current low endemic levels of infection. The future control strategy for schistosomiasis should instead focus on a snail-based integrated control strategy to maintain the program achievements and sustainably reduce the burden of schistosomiasis in China.

First malaria infections in a cohort of infants in Benin: biological, environmental and genetic determinants. Description of the study site, population methods and preliminary results

OBJECTIVES

Malaria infection of the placenta during pregnancy was found to be associated with infant susceptibility to malaria. Other factors such as the intensity of malaria transmission and the nutritional status of the child might also play a role, which has not been adequately taken into account in previous studies. The aim of this study was to assess precisely the parts played by environmental, nutritional and biological determinants in first malaria infections, with a special interest in the role of placental infection. The objective of this paper is not to present final results but to outline the rationale of the study, to describe the methods used and to report baseline data.

DESIGN

A cohort of infants followed with a parasitological (symptomatic and asymptomatic parasitaemia) and nutritional follow-up from birth to 18 months. Ecological, entomological and behavioural data were collected along the duration of the study.

SETTING

A rural area in Benin with two seasonal peaks in malaria transmission.

PARTICIPANTS

656 infants of women willing to participate in the study, giving birth in one of the three maternity clinics and living in one of the nine villages of the study area.

PRIMARY OUTCOME MEASURES

The time and frequency of first malaria parasitaemias in infants, according to Plasmodium falciparum infection of the placenta.

RESULTS

11% of mothers had a malaria-infected placenta at delivery. Mosquito catches made every 6 weeks in the area showed an average annual P falciparum entomological inoculation rate of 15.5, with important time and space variations depending on villages. Similarly, the distribution of rainfalls, maximal during the two rainy seasons, was heterogeneous over the area.

CONCLUSIONS

Considering the multidisciplinary approach of all factors potentially influencing the malaria status of newborn babies, this study should bring evidence on the implication of placental malaria in the occurrence of first malaria infections in infants.

Plasmodium-helminth coinfection and its sources of heterogeneity across East Africa

Background. Plasmodium–helminth coinfection can have a number of consequences for infected hosts, yet our knowledge of the epidemiology of coinfection across multiple settings is limited. This study investigates the distribution and heterogeneity of coinfection with Plasmodium falciparum and 3 major helminth species across East Africa.

Methods. Cross-sectional parasite surveys were conducted among 28 050 children in 299 schools across a range of environmental settings in Kenya, Uganda, and Ethiopia. Data on individual, household, and environmental risk factors were collected and a spatially explicit Bayesian modeling framework was used to investigate heterogeneities of species infection and coinfection and their risk factors as well as school- and individual-level associations between species.

Results. Broad-scale geographical patterns of Plasmodium–helminth coinfection are strongly influenced by the least common infection and by species-specific environmental factors. At the individual level, there is an enduring positive association between P. falciparum and hookworm but no association between P. falciparum and Schistosoma species. However, the relative importance of such within-individual associations is less than the role of spatial factors in influencing coinfection risks.

Conclusions. Patterns of coinfection seem to be influenced more by the distribution of the least common species and its environmental risk factors, rather than any enduring within-individual associations.

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.

From innovation to application: social-ecological context, diagnostics, drugs and integrated control of schistosomiasis

Compared to malaria, tuberculosis and HIV/AIDS, schistosomiasis remains a truly neglected tropical disease. Schistosomiasis, perhaps more than any other disease, is entrenched in prevailing social-ecological systems, since transmission is governed by human behaviour (e.g. open defecation and patterns of unprotected surface water contacts) and ecological features (e.g. living in close proximity to suitable freshwater bodies in which intermediate host snails proliferate). Moreover, schistosomiasis is intimately linked with poverty and the disease has spread to previously non-endemic areas as a result of demographic, ecological and engineering transformations. Importantly though, thanks to increased advocacy there is growing awareness, financial and technical support to control and eventually eliminate schistosomiasis as a public health problem at local, regional and global scales. The purpose of this review is to highlight recent progress made in innovation, validation and application of new tools and strategies for research and integrated control of schistosomiasis. First, we explain that schistosomiasis is deeply embedded in social-ecological systems and explore linkages with poverty. We then summarize and challenge global statistics, risk maps and burden estimates of human schistosomiasis. Discovery and development research pertaining to novel diagnostics and drugs forms the centrepiece of our review. We discuss unresolved issues and emerging opportunities for integrated and sustainable control of schistosomiasis and conclude with a series of research needs.

Risk factors for helminth infections in a rural and a peri-urban setting of the Dongting Lake area, People's Republic of China

Schistosomiasis japonica and soil-transmitted helminthiasis are endemic parasitic diseases in the People's Republic of China (PR China). As very few studies have reported on the distribution and interaction of multiple species helminth infections, we carried out a comparative study of households in a rural village and a peri-urban setting in the Dongting Lake area of Hunan province in November and December 2006 to determine the extent of single and multiple species infections, the underlying risk factors for infection, and the relationships with clinical manifestations and self-reported morbidity. In each household, stool samples were collected and subjected to the Kato-Katz method for identifying Schistosoma japonicum, Ascaris lumbricoides, hookworm and Trichuris trichiura infections. Clinical examinations were performed and questionnaire surveys conducted at both household and individual subject levels. Complete parasitological, clinical and questionnaire data were obtained for 1,298 inhabitants of the two settings. The overall prevalences of single infections of S. japonicum, A. lumbricoides, hookworm and T. trichiura were 6.5%, 5.5%, 3.0% and 0.8%, respectively; the majority of the infections were of light intensity. We found significant negative associations between wealth and infections with S. japonicum and A. lumbricoides. Clinical manifestations of splenomegaly, hepatomegaly and anaemia were prevalent (9.0%, 3.7% and 10.9%, respectively), the latter two being significantly (P<0.05) associated with schistosomiasis. Self-reported symptoms were more common among females but there was considerable under-reporting in both sexes when relying only on spontaneous recall. Our findings may guide the design and targeting of a more equitable, comprehensive and integrated parasitic disease control programme in Hunan province and in other areas of PR China.

Efficacy of integrated school based de-worming and prompt malaria treatment on helminths -Plasmodium falciparum co-infections: A 33 months follow up study

Background

The geographical congruency in distribution of helminths and Plasmodium falciparum makes polyparasitism a common phenomenon in Sub Saharan Africa. The devastating effects of helminths-Plasmodium co-infections on primary school health have raised global interest for integrated control. However little is known on the feasibility, timing and efficacy of integrated helminths-Plasmodium control strategies. A study was conducted in Zimbabwe to evaluate the efficacy of repeated combined school based antihelminthic and prompt malaria treatment.

Methods

A cohort of primary schoolchildren (5-17 years) received combined Praziquantel, albendazole treatment at baseline, and again during 6, 12 and 33 months follow up surveys and sustained prompt malaria treatment. Sustained prompt malaria treatment was carried out throughout the study period. Children's infection status with helminths, Plasmodium and helminths-Plasmodium co-infections was determined by parasitological examinations at baseline and at each treatment point. The prevalence of S. haematobium, S. mansoni, STH, malaria, helminths-Plasmodium co-infections and helminths infection intensities before and after treatment were analysed.

Results

Longitudinal data showed that two rounds of combined Praziquantel and albendazole treatment for schistosomiasis and STHs at 6 monthly intervals and sustained prompt malaria treatment significantly reduced the overall prevalence of S. haematobium, S. mansoni, hookworms and P. falciparum infection in primary schoolchildren by 73.5%, 70.8%, 67.3% and 58.8% respectively (p < 0.001, p < 0.001, p < 0.001, p < 0.001 respectively). More importantly, the prevalence of STH + schistosomes, P. f + schistosomes, and P. f + STHs + schistosomes co-infections were reduced by 68.0%, 84.2%, and 90.7%, respectively. The absence of anti-helminthic treatment between the 12 mth and 33 mth follow-up surveys resulted in the sharp increase in STHs + schistosomes co-infection from 3.3% at 12 months follow up survey to 10.7%, slightly more than the baseline level (10.3%) while other co-infection combinations remained significantly low. The overall prevalence of heavy S. haematobium, S. mansoni and hookworms infection intensities were significantly reduced from: 17.9-22.4% to 2.6-5.1%, 1.6-3.3% to 0.0% and 0.0-0.7% to 0.0% respectively.

Conclusion

Biannual Integrated school based antihelminthic and sustained prompt malaria treatment has a potential to reduce the burden of helminths-plasmodium co-infections in primary school children. In areas of stable malaria transmission, active case finding is recommended to track and treat asymptomatic malaria cases as these may sustain transmission in the community.

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.

Bayesian geostatistics in health cartography: the perspective of malaria

Maps of parasite prevalences and other aspects of infectious diseases that vary in space are widely used in parasitology. However, spatial parasitological datasets rarely, if ever, have sufficient coverage to allow exact determination of such maps. Bayesian geostatistics (BG) is a method for finding a large sample of maps that can explain a dataset, in which maps that do a better job of explaining the data are more likely to be represented. This sample represents the knowledge that the analyst has gained from the data about the unknown true map. BG provides a conceptually simple way to convert these samples to predictions of features of the unknown map, for example regional averages. These predictions account for each map in the sample, yielding an appropriate level of predictive precision.

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.

Helminth and intestinal protozoa infections, multiparasitism and risk factors in Champasack province, Lao People's Democratic Republic

BACKGROUND

Detailed investigations of multiparasitism are scarce in the Mekong River basin. We assessed helminth (trematode, nematode, and cestode), and intestinal protozoa infections, and multiparasitism in random population samples from three different eco-epidemiological settings in Champasack province, southern Lao People's Democratic Republic (Lao PDR), and determined underlying risk factors.

METHODOLOGY

Two stool samples were collected from 669 individuals aged ≥ 6 months over consecutive days and examined for helminth infections using the Kato-Katz method. Additionally, one stool sample per person was subjected to a formalin-ethyl acetate concentration technique for diagnosis of helminth and intestinal protozoa infections. Questionnaires were administered to obtain individual and household-level data pertaining to behavior, demography and socioeconomic status. Risk factors for hepato-biliary and intestinal parasitic infections and multiparasitism were determined using multiple logistic regressions analyses.

PRINCIPAL FINDINGS

MULTIPLE SPECIES INTESTINAL PARASITE INFECTIONS WERE COMMON: 86.6% of the study participants harbored at least two and up to seven different parasites concurrently. Regarding nematode infections, hookworm was the most prevalent species (76.8%), followed by Ascaris lumbricoides (31.7%) and Trichuris trichiura (25.0%). Regarding trematodes, Opisthorchis viverrini and Schistosoma mekongi infections were found in 64.3% and 24.2% of the participants, respectively. Infections with intestinal protozoa were rare.

CONCLUSIONS/SIGNIFICANCE

There is a pressing need to intensify and sustain helminth control interventions in the southern part of Lao PDR. Given the high prevalence with nematode and trematode infections and the extent of multiparasitism, preventive chemotherapy is warranted. This intervention should be coupled with health education and improved access to clean water and adequate sanitation to consolidate morbidity control and enhance sustainability.

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.

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.

Developing vaccines to combat hookworm infection and intestinal schistosomiasis

Hookworm infection and schistosomiasis rank among the most important health problems in developing countries. Both cause anaemia and malnutrition, and schistosomiasis also results in substantial intestinal, liver and genitourinary pathology. In sub-Saharan Africa and Brazil, co-infections with the hookworm, Necator americanus, and the intestinal schistosome, Schistosoma mansoni, are common. The development of vaccines for these infections could substantially reduce the global disability associated with these helminthiases. New genomic, proteomic, immunological and X-ray crystallographic data have led to the discovery of several promising candidate vaccine antigens. Here, we describe recent progress in this field and the rationale for vaccine development.