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Intestinal nematode infections are among the most common infections of humans in developing countries, but precise estimates of the populations at risk of infection, morbidity and mortality are difficult to derive. Careful evaluation of the global distribution and disease burden of nematodes is essential to determine the cost-effectiveness of control and ensure that control programmes are focused appropriately. In turn, understanding the disease burden depends on a summary measure of health as well as reliable data on risks of infection, morbidity and mortality. This review provides an overview of data sources and methods adopted in the Global Burden of Disease study to estimate the burden of intestinal nematodes, including the empirical and modelling challenges in its estimation. Particular attention is paid to efforts to improve our ability to define at-risk populations, based on a Global Atlas of Helminth Infection, and to better estimate attributable morbidity.

Strong statistical associations between soil transmitted helminths and schistosomes are frequently observed in co-endemic human populations, although the underlying explanations remain poorly understood. This study investigates the contribution of host genetics and domestic environment to hookworm and Schistosoma mansoni infection intensity and evaluates the role of genetic and non-genetic factors in covariation of infection intensity. Detailed genealogical information allowed assignment of 1,303 individuals living in the Brazilian community of Americaninhas, Minas Gerais state, to 25 pedigrees (containing between two and 1,159 members) residing in 303 households. The prevalence of co-infection with both hookworms and schistosomes was high (38.5%), with significant correlation between Necator americanus and S. mansoni faecal egg counts (r = 0.242; P < 0.0001). Bivariate variance component analysis demonstrated a modest but significant species-specific heritability for intensity of N. americanus (h2 = 0.196) and S. mansoni infection (h2 = 0.230). However, after accounting for demographic, socio-economic and household risk factors, no evidence for common genetic control of intensity of hookworm and schistosome infection was observed (genetic correlation ρG = 0.15; P = 0.52). There was some evidence for residual clustering within households (household correlation ρC = 0.45; P = 0.06), but the majority (63%) of the covariance between N. americanus and S. mansoni infection intensity remained specific to the individual and could not be explained by shared genes, shared environment or other shared demographic, socio-economic or environmental risk factors. Our results emphasize the importance of exposure to hookworm and schistosome infection in driving the association between levels of infection with these species in hosts resident in areas of high transmission and suggest that much of this common exposure occurs outside the home.

Multiple parasite infections are widespread in the developing world and understanding their geographical distribution is important for spatial targeting of differing intervention packages. We investigated the spatial epidemiology of mono- and co-infection with helminth parasites in East Africa and developed a geostatistical model to predict infection risk. The data used for the analysis were taken from standardised school surveys of Schistosoma mansoni and hookworm (Ancylostoma duodenale/Necator americanus) carried out between 1999 and 2005 in East Africa. Prevalence of mono- and co-infection was modelled using satellite-derived environmental and demographic variables as potential predictors. A Bayesian multi-nominal geostatistical model was developed for each infection category for producing maps of predicted co-infection risk. We show that heterogeneities in co-infection with S. mansoni and hookworm are influenced primarily by the distribution of S. mansoni, rather than the distribution of hookworm, and that temperature, elevation and distance to large water bodies are reliable predictors of the spatial large-scale distribution of co-infection. On the basis of these results, we developed a validated geostatistical model of the distribution of co-infection at a scale that is relevant for planning regional disease control efforts that simultaneously target multiple parasite species.

Marked heterogeneity exists in the patterns of parasitic infection between individuals, households and communities. Analysis of parasite distributions within populations is complicated by the fact that parasite distributions are highly aggregated and few studies have explicitly incorporated this distribution when investigating small-scale spatial heterogeneities. This study aimed to quantify the small-scale (within- and between-household) heterogeneity of helminth infection in an area of Minas Gerais State, Brazil, with rural and urban sectors. Parasitological data from a cross-sectional survey of 1,249 individuals aged 0-86 years from 242 households were analysed. Within-household clustering of infection was assessed using random effect logistic regression models and between-household spatial heterogeneity was assessed using a Bayesian negative binomial spatial model. The overall prevalence of hookworm (Necator americanus) was 66.9%, the prevalence of Schistosoma mansoni was 44.9% and the prevalence of Ascaris lumbricoides was 48.8%. Statistical analysis indicated significant (within) household and (between household) spatial clustering of hookworm in both rural and urban areas and of S. mansoni in rural areas. There was no evidence of either household or spatial clustering of S. mansoni in urban areas. The spatial correlation of S. mansoni was estimated to reduce by half over a distance of 700 m in the rural area. Rural hookworm had a much smaller half-distance (28 m) and urban hookworm showed an even smaller half-distance (12 m). We suggest that such species-specific differences in patterns of infection by environment are primarily due to variation in exposure and parasite life cycle, although host genetic factors cannot be ruled out.

Spatial modelling was applied to self-reported schistosomiasis data from over 2.5 million school students from 12,399 schools in all regions of mainland Tanzania. The aims were to derive statistically robust prevalence estimates in small geographical units (wards), to identify spatial clusters of high and low prevalence and to quantify uncertainty surrounding prevalence estimates. The objective was to permit informed decision-making for targeting of resources by the Tanzanian national schistosomiasis control programme. Bayesian logistic regression models were constructed to investigate the risk of schistosomiasis in each ward, based on the prevalence of self-reported schistosomiasis and blood in urine. Models contained covariates representing climatic and demographic effects and random effects for spatial clustering. Degree of urbanisation, median elevation of the ward and median normalised difference vegetation index (NDVI) were significantly and negatively associated with schistosomiasis prevalence. Most regions contained wards that had >95% certainty of schistosomiasis prevalence being >10%, the selected threshold for bi-annual mass chemotherapy of school-age children. Wards with >95% certainty of schistosomiasis prevalence being >30%, the selected threshold for annual mass chemotherapy of school-age children, were clustered in north-western, south-western and south-eastern regions. Large sample sizes in most wards meant raw prevalence estimates were robust. However, when uncertainties were investigated, intervention status was equivocal in 6.7–13.0% of wards depending on the criterion used. The resulting maps are being used to plan the distribution of praziquantel to participating districts; they will be applied to prioritising control in those wards where prevalence was unequivocally above thresholds for intervention and might direct decision-makers to obtain more information in wards where intervention status was uncertain.

Highlights • A Bayesian latent class meta-analysis of diagnostic tests for soil-transmitted helminths was performed. • Overall sensitivity of evaluated diagnostic tests was low. • Test performance was strongly influenced by intensity of infection. • FLOTAC method sensitivity was highest overall and in both intensity groups. • The performance of the Kato-Katz method in high intensity settings was acceptable., Reliable, sensitive and practical diagnostic tests are an essential tool in disease control programmes for mapping, impact evaluation and surveillance. To provide a robust global assessment of the relative performance of available diagnostic tools for the detection of soil-transmitted helminths, we conducted a meta-analysis comparing the sensitivities and the quantitative performance of the most commonly used copro-microscopic diagnostic methods for soil-transmitted helminths, namely Kato-Katz, direct microscopy, formol-ether concentration, McMaster, FLOTAC and Mini-FLOTAC. In the absence of a perfect reference standard, we employed a Bayesian latent class analysis to estimate the true, unobserved sensitivity of compared diagnostic tests for each of the soil-transmitted helminth species Ascaris lumbricoides, Trichuris trichiura and the hookworms. To investigate the influence of varying transmission settings we subsequently stratified the analysis by intensity of infection. Overall, sensitivity estimates varied between the different methods, ranging from 42.8% for direct microscopy to 92.7% for FLOTAC. The widely used double slide Kato-Katz method had a sensitivity of 74–95% for the three soil-transmitted helminth species at high infection intensity, however sensitivity dropped to 53–80% in low intensity settings, being lowest for hookworm and A. lumbricoides. The highest sensitivity, overall and in both intensity groups, was observed for the FLOTAC method, whereas the sensitivity of the Mini-FLOTAC method was comparable with the Kato-Katz method. FLOTAC average egg count estimates were significantly lower compared with Kato-Katz, while the compared McMaster counts varied. In conclusion, we demonstrate that the Kato-Katz and Mini-FLOTAC methods had comparable sensitivities. We further show that test sensitivity of the Kato-Katz method is reduced in low transmission settings.