Heterogeneous model of schistosomiasis transmission and long-term control: the combined influence of spatial variation and age-dependent factors on optimal allocation of drug therapy

Prospects for genomic surveillance for selection in schistosome parasites

Schistosomiasis is a neglected tropical disease caused by multiple parasitic Schistosoma species, and which impacts over 200 million people globally, mainly in low- and middle-income countries. Genomic surveillance to detect evidence for natural selection in schistosome populations represents an emerging and promising approach to identify and interpret schistosome responses to ongoing control efforts or other environmental factors. Here we review how genomic variation is used to detect selection, how these approaches have been applied to schistosomes, and how future studies to detect selection may be improved. We discuss the theory of genomic analyses to detect selection, identify experimental designs for such analyses, and review studies that have applied these approaches to schistosomes. We then consider the biological characteristics of schistosomes that are expected to respond to selection, particularly those that may be impacted by control programs. Examples include drug resistance, host specificity, and life history traits, and we review our current understanding of specific genes that underlie them in schistosomes. We also discuss how inherent features of schistosome reproduction and demography pose substantial challenges for effective identification of these traits and their genomic bases. We conclude by discussing how genomic surveillance for selection should be designed to improve understanding of schistosome biology, and how the parasite changes in response to selection.

Modeling schistosomiasis transmission: the importance of snail population structure

Background

Schistosomiasis is a neglected tropical disease endemic in 54 countries. A major Schistosoma species, Schistosoma mansoni, is sustained via a life cycle that includes both human and snail hosts. Mathematical models of S. mansoni transmission, used to elucidate the complexities of the transmission cycle and estimate the impact of intervention efforts, often focus primarily on the human host. However, S. mansoni incurs physiological costs in snails that vary with the age of the snail when first infected. Snail demography and the age of snail infection could thus affect the force of infection experienced by humans, which is frequently used to predict the impact of various control strategies.

Methods

To address how these snail host and parasite interactions influence model predictions, we developed deterministic models of schistosomiasis transmission that include varying complexity in the snail population age structure. Specifically, we examined how model outputs, such as schistosome prevalence in human and snail populations, respond to the inclusion of snail age structure.

Results

Our models suggest that snail population age structure modifies the force of infection experienced by humans and the relationship between snail infection prevalence and corresponding human infection prevalence. There are significant differences in estimated snail infection, cercarial density and mean worm burden between models without snail population dynamics and those with snail populations, and between models with a homogeneous snail population and those with age stratification. The variation between finely age-stratified snail populations and those grouped into only juvenile and adult life stages is, however, minimal.

Conclusions

These results indicate that including snails and snail age structure in a schistosomiasis transmission model alters the relationship between snail and human infection prevalence. This highlights the importance of accounting for a heterogeneous intermediate host population in models of schistosomiasis transmission where the impact of proposed control measures is being considered.

To Reduce the Global Burden of Human Schistosomiasis, Use 'Old Fashioned' Snail Control

Control strategies to reduce human schistosomiasis have evolved from 'snail picking' campaigns, a century ago, to modern wide-scale human treatment campaigns, or preventive chemotherapy. Unfortunately, despite the rise in preventive chemotherapy campaigns, just as many people suffer from schistosomiasis today as they did 50 years ago. Snail control can complement preventive chemotherapy by reducing the risk of transmission from snails to humans. Here, we present ideas for modernizing and scaling up snail control, including spatiotemporal targeting, environmental diagnostics, better molluscicides, new technologies (e.g., gene drive), and 'outside the box' strategies such as natural enemies, traps, and repellants. We conclude that, to achieve the World Health Assembly's stated goal to eliminate schistosomiasis, it is time to give snail control another look.

The spatial spread of schistosomiasis: A multidimensional network model applied to Saint-Louis region, Senegal

Schistosomiasis is a parasitic, water-related disease that is prevalent in tropical and subtropical areas of the world, causing severe and chronic consequences especially among children. Here we study the spatial spread of this disease within a network of connected villages in the endemic region of the Lower Basin of the Senegal River, in Senegal. The analysis is performed by means of a spatially explicit metapopulation model that couples local-scale eco-epidemiological dynamics with spatial mechanisms related to human mobility (estimated from anonymized mobile phone records), snail dispersal and hydrological transport of schistosome larvae along the main water bodies of the region. Results show that the model produces epidemiological patterns consistent with field observations, and point out the key role of spatial connectivity on the spread of the disease. These findings underline the importance of considering different transport pathways in order to elaborate disease control strategies that can be effective within a network of connected populations.

The Interdependence between Schistosome Transmission and Protective Immunity

Mass drug administration (MDA) for control of schistosomiasis is likely to affect transmission dynamics through a combination of passive vaccination and reduction of local transmission intensity. This is indicated in phenomenological models of immunity and the impact of MDA, yet immunity parameters in these models are not validated by empirical data that reflects protective immunity to reinfection. There is significant empirical evidence supporting the role of IgE in acquired protective immunity. This is proposed to be a form of delayed concomitant immunity, driven at least in part by protective IgE responses to the tegument allergen-like (TAL) family of proteins. Specific questions have arisen from modeling studies regarding the strength and duration of the protective immune response. At present, field studies have not been specifically designed to address these questions. There is therefore a need for field studies that are explicitly designed to capture epidemiological effects of acquired immunity to elucidate these immunological interactions. In doing so, it is important to address the discourse between theoretical modelers and immuno-epidemiologists and develop mechanistic models that empirically define immunity parameters. This is of increasing significance in a climate of potential changing transmission dynamics following long-term implementation of MDA.

Heterogeneity in schistosomiasis transmission dynamics

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Transmission dynamics of schistosomiasis presents multiple heterogeneity sources.

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A comprehensive framework for heterogeneous disease transmission is proposed.

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Heterogeneous multigroup communities can be more prone to parasite transmission.

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Presence of multiple water sources can hinder parasite transmission.

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Spatial and temporal heterogeneities can have nontrivial implications for endemicity.

Simple models of disease propagation often disregard the effects of transmission heterogeneity on the ecological and epidemiological dynamics associated with host-parasite interactions. However, for some diseases like schistosomiasis, a widespread parasitic infection caused by Schistosoma worms, accounting for heterogeneity is crucial to both characterize long-term dynamics and evaluate opportunities for disease control. Elaborating on the classic Macdonald model for macroparasite transmission, we analyze families of models including explicit descriptions of heterogeneity related to differential transmission risk within a community, water contact patterns, the distribution of the snail host population, human mobility, and the seasonal fluctuations of the environment. Through simple numerical examples, we show that heterogeneous multigroup communities may be more prone to schistosomiasis than homogeneous ones, that the availability of multiple water sources can hinder parasite transmission, and that both spatial and temporal heterogeneities may have nontrivial implications for disease endemicity. Finally, we discuss the implications of heterogeneity for disease control. Although focused on schistosomiasis, results from this study may apply as well to other parasitic infections with complex transmission cycles, such as cysticercosis, dracunculiasis and fasciolosis.

Modeling Key Drivers of Cholera Transmission Dynamics Provides New Perspectives for Parasitology

Hydroclimatological and anthropogenic factors are key drivers of waterborne disease transmission. Information on human settlements and host mobility on waterways along which pathogens and hosts disperse, and relevant hydroclimatological processes, can be acquired remotely and included in spatially explicit mathematical models of disease transmission. In the case of epidemic cholera, such models allowed the description of complex disease patterns and provided insight into the course of ongoing epidemics. The inclusion of spatial information in models of disease transmission can aid in emergency management and the assessment of alternative interventions. Here, we review the study of drivers of transmission via spatially explicit approaches and argue that, because many parasitic waterborne diseases share the same drivers as cholera, similar principles may apply.

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

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

What is required in terms of mass drug administration to interrupt the transmission of schistosome parasites in regions of endemic infection?

BACKGROUND

Schistosomiasis is endemic in 54 countries, but has one of the lowest coverages by mass drug administration of all helminth diseases. However, with increasing drug availability through donation, the World Health Organisation has set a goal of increasing coverage to 75 % of at-risk children in endemic countries and elimination in some regions. In this paper, we assess the impact on schistosomiasis of the WHO goals in terms of control and elimination.

METHODS

We use an age-structured deterministic model of schistosome transmission in a human community and the effect of mass drug administration. The model is fitted to baseline data from a longitudinal re-infection study in Kenya and validated against the subsequent re-infection data. We examine the impact on host worm burden of the current treatment trend, extrapolated to meet the WHO goals, and its sensitivity to uncertainty in important parameters. We assess the feasibility of achieving elimination.

RESULTS

Model results show that the current treatment trend, extrapolated to the WHO goals, is able to greatly reduce host worm burdens. If coverage is continued at the same level beyond 2020, elimination is possible for low to moderate transmission settings, where transmission intensity is defined by the basic reproduction number, R0. Low levels of adult coverage have a significant impact on worm burden in all settings. Model validation against the re-infection survey demonstrates that the age-structured model is able to match post-treatment data well in terms of egg output, but that some details of re-infection among school children and young adults are not currently well represented.

CONCLUSIONS

Our work suggests that the current WHO treatment goals should be successful in bringing about a major reduction in schistosome infection in treated communities. If continued over a 15 year period, they are likely to result in elimination, at least in areas with lower transmission.

Modelling control of Schistosoma haematobium infection: predictions of the long-term impact of mass drug administration in Africa

Background

Effective control of schistosomiasis remains a challenging problem for endemic areas of the world. Given knowledge of the biology of transmission and past experience with mass drug administration (MDA) programs, it is important to critically evaluate the likelihood that MDA programs will achieve substantial reductions in Schistosoma prevalence. In implementing the World Health Organization Roadmap for Neglected Tropical Diseases it would useful for policymaking to model projections of the status of Schistosoma control in MDA-treated areas in the next 5–10 years.

Methods

Calibrated mathematical models were used to project the effects of different frequency and coverage of MDA for schistosomiasis haematobia control in present-day endemic communities, taking into account uncertainties of parasite biology and input data. The modeling approach in this analysis was the Stratified Worm Burden model developed in our earlier works, calibrated using data from longitudinal S. haematobium control trials in Kenya.

Results

Model-based simulations of MDA control in typical low-risk and higher-risk communities indicated that infection prevalence can be substantially reduced within 10 years only when there is a high degree of community participation (>70 %) with at least annual MDA. Significant risk for re-emergence of infection remains if MDA is suspended.

Conclusions

In a stable (stationary) ecosystem, Schistosoma reproduction and transmission are sufficiently robust that the process of human infection continues, even under pressure from aggressive MDA. MDA alone is unlikely to interrupt transmission, and once mass treatment is suspended, the prevalence of human infection is likely to rebound to pre-control levels over a period of 25–30 years. MDA success in achieving very low levels of infection prevalence is highly dependent on treatment coverage and frequency within the local human population, and requires that both adults and children be included in drug delivery coverage. Ultimately, supplemental snail control and significant improvements in sanitation will be required to achieve full control of schistosomiasis by elimination of ongoing Schistosoma transmission.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-015-1144-3) contains supplementary material, which is available to authorized users.

Modelling the effects of mass drug administration on the molecular epidemiology of schistosomes

As national governments scale up mass drug administration (MDA) programs aimed to combat neglected tropical diseases (NTDs), novel selection pressures on these parasites increase. To understand how parasite populations are affected by MDA and how to maximize the success of control programmes, it is imperative for epidemiological, molecular and mathematical modelling approaches to be combined. Modelling of parasite population genetic and genomic structure, particularly of the NTDs, has been limited through the availability of only a few molecular markers to date. The landscape of infectious disease research is being dramatically reshaped by next-generation sequencing technologies and our understanding of how repeated selective pressures are shaping parasite populations is radically altering. Genomics can provide high-resolution data on parasite population structure, and identify how loci may contribute to key phenotypes such as virulence and/or drug resistance. We discuss the incorporation of genetic and genomic data, focussing on the recently sequenced Schistosoma spp., into novel mathematical transmission models to inform our understanding of the impact of MDA and other control methods. We summarize what is known to date, the models that exist and how population genetics has given us an understanding of the effects of MDA on the parasites. We consider how genetic and genomic data have the potential to shape future research, highlighting key areas where data are lacking, and how future molecular epidemiology knowledge can aid understanding of transmission dynamics and the effects of MDA, ultimately informing public health policy makers of the best interventions for NTDs.

The temporal patterns of disease severity and prevalence in schistosomiasis

Schistosomiasis is one of the most widespread public health problems in the world. In this work, we introduce an eco-epidemiological model for its transmission and dynamics with the purpose of explaining both intra- and inter-annual fluctuations of disease severity and prevalence. The model takes the form of a system of nonlinear differential equations that incorporate biological complexity associated with schistosome's life cycle, including a prepatent period in snails (i.e., the time between initial infection and onset of infectiousness). Nonlinear analysis is used to explore the parametric conditions that produce different temporal patterns (stationary, endemic, periodic, and chaotic). For the time-invariant model, we identify a transcritical and a Hopf bifurcation in the space of the human and snail infection parameters. The first corresponds to the occurrence of an endemic equilibrium, while the latter marks the transition to interannual periodic oscillations. We then investigate a more realistic time-varying model in which fertility of the intermediate host population is assumed to seasonally vary. We show that seasonality can give rise to a cascade of period-doubling bifurcations leading to chaos for larger, though realistic, values of the amplitude of the seasonal variation of fertility.

Population biology of Schistosoma mating, aggregation, and transmission breakpoints: more reliable model analysis for the end-game in communities at risk

Mathematical modeling is widely used for predictive analysis of control options for infectious agents. Challenging problems arise for modeling host-parasite systems having complex life-cycles and transmission environments. Macroparasites, like Schistosoma, inhabit highly fragmented habitats that shape their reproductive success and distribution. Overdispersion and mating success are important factors to consider in modeling control options for such systems. Simpler models based on mean worm burden (MWB) formulations do not take these into account and overestimate transmission. Proposed MWB revisions have employed prescribed distributions and mating factor corrections to derive modified MWB models that have qualitatively different equilibria, including ‘breakpoints’ below which the parasite goes to extinction, suggesting the possibility of elimination via long-term mass-treatment control. Despite common use, no one has attempted to validate the scope and hypotheses underlying such MWB approaches. We conducted a systematic analysis of both the classical MWB and more recent “stratified worm burden” (SWB) modeling that accounts for mating and reproductive hurdles (Allee effect). Our analysis reveals some similarities, including breakpoints, between MWB and SWB, but also significant differences between the two types of model. We show the classic MWB has inherent inconsistencies, and propose SWB as a reliable alternative for projection of long-term control outcomes.

Predicted impact of mass drug administration on the development of protective immunity against Schistosoma haematobium

Previous studies suggest that protective immunity against Schistosoma haematobium is primarily stimulated by antigens from dying worms. Praziquantel treatment kills adult worms, boosting antigen exposure and protective antibody levels. Current schistosomiasis control efforts use repeated mass drug administration (MDA) of praziquantel to reduce morbidity, and may also reduce transmission. The long-term impact of MDA upon protective immunity, and subsequent effects on infection dynamics, are not known. A stochastic individual-based model describing levels of S. haematobium worm burden, egg output and protective parasite-specific antibody, which has previously been fitted to cross-sectional and short-term post-treatment egg count and antibody patterns, was used to predict dynamics of measured egg output and antibody during and after a 5-year MDA campaign. Different treatment schedules based on current World Health Organisation recommendations as well as different assumptions about reductions in transmission were investigated. We found that antibody levels were initially boosted by MDA, but declined below pre-intervention levels during or after MDA if protective immunity was short-lived. Following cessation of MDA, our models predicted that measured egg counts could sometimes overshoot pre-intervention levels, even if MDA had had no effect on transmission. With no reduction in transmission, this overshoot occurred if protective immunity was short-lived. This implies that disease burden may temporarily increase following discontinuation of treatment, even in the absence of any reduction in the overall transmission rate. If MDA was additionally assumed to reduce transmission, a larger overshoot was seen across a wide range of parameter combinations, including those with longer-lived protective immunity. MDA may reduce population levels of immunity to urogenital schistosomiasis in the long-term (3-10 years), particularly if transmission is reduced. If MDA is stopped while S. haematobium is still being transmitted, large rebounds (up to a doubling) in egg counts could occur.

A research agenda for helminth diseases of humans: modelling for control and elimination

Mathematical modelling of helminth infections has the potential to inform policy and guide research for the control and elimination of human helminthiases. However, this potential, unlike in other parasitic and infectious diseases, has yet to be realised. To place contemporary efforts in a historical context, a summary of the development of mathematical models for helminthiases is presented. These efforts are discussed according to the role that models can play in furthering our understanding of parasite population biology and transmission dynamics, and the effect on such dynamics of control interventions, as well as in enabling estimation of directly unobservable parameters, exploration of transmission breakpoints, and investigation of evolutionary outcomes of control. The Disease Reference Group on Helminth Infections (DRG4), established in 2009 by the Special Programme for Research and Training in Tropical Diseases (TDR), was given the mandate to review helminthiases research and identify research priorities and gaps. A research and development agenda for helminthiasis modelling is proposed based on identified gaps that need to be addressed for models to become useful decision tools that can support research and control operations effectively. This agenda includes the use of models to estimate the impact of large-scale interventions on infection incidence; the design of sampling protocols for the monitoring and evaluation of integrated control programmes; the modelling of co-infections; the investigation of the dynamical relationship between infection and morbidity indicators; the improvement of analytical methods for the quantification of anthelmintic efficacy and resistance; the determination of programme endpoints; the linking of dynamical helminth models with helminth geostatistical mapping; and the investigation of the impact of climate change on human helminthiases. It is concluded that modelling should be embedded in helminth research, and in the planning, evaluation, and surveillance of interventions from the outset. Modellers should be essential members of interdisciplinary teams, propitiating a continuous dialogue with end users and stakeholders to reflect public health needs in the terrain, discuss the scope and limitations of models, and update biological assumptions and model outputs regularly. It is highlighted that to reach these goals, a collaborative framework must be developed for the collation, annotation, and sharing of databases from large-scale anthelmintic control programmes, and that helminth modellers should join efforts to tackle key questions in helminth epidemiology and control through the sharing of such databases, and by using diverse, yet complementary, modelling approaches.

Modeling the effect of chronic schistosomiasis on childhood development and the potential for catch-up growth with different drug treatment strategies promoted for control of endemic schistosomiasis

In areas endemic for schistosomiasis having limited healthcare, targeted drug treatment of school-age children is recommended for control of Schistosoma-associated morbidity. However, optimal timing, number, and frequency of treatments are not established. Because longitudinal studies of long-term impact of treatment are few, for current policy considerations we performed quantitative simulation (based on calibrated modeling of Schistosoma-associated disease formation) to project the impact of different school-age treatment regimens. Using published efficacy data from targeted programs, combined with age-specific risk for growth retardation and reinfection, we examined the likely impact of different strategies for morbidity prevention. Results suggest the need for early, repeated treatment through primary school years to optimally prevent the disabling sequelae of stunting and undernutrition. Dynamics of infection/reinfection during childhood and adolescence, combined with early treatment effects against reversible infection-associated morbidities, create a need for aggressive retreatment of preadolescents to achieve optimal suppression of morbidity where drug-based control is used.

A new approach to modelling schistosomiasis transmission based on stratified worm burden

BACKGROUND/OBJECTIVE

Multiple factors affect schistosomiasis transmission in distributed meta-population systems including age, behaviour, and environment. The traditional approach to modelling macroparasite transmission often exploits the 'mean worm burden' (MWB) formulation for human hosts. However, typical worm distribution in humans is overdispersed, and classic models either ignore this characteristic or make ad hoc assumptions about its pattern (e.g., by assuming a negative binomial distribution). Such oversimplifications can give wrong predictions for the impact of control interventions.

METHODS

We propose a new modelling approach to macro-parasite transmission by stratifying human populations according to worm burden, and replacing MWB dynamics with that of 'population strata'. We developed proper calibration procedures for such multi-component systems, based on typical epidemiological and demographic field data, and implemented them using Wolfram Mathematica.

RESULTS

Model programming and calibration proved to be straightforward. Our calibrated system provided good agreement with the individual level field data from the Msambweni region of eastern Kenya.

CONCLUSION

The Stratified Worm Burden (SWB) approach offers many advantages, in that it accounts naturally for overdispersion and accommodates other important factors and measures of human infection and demographics. Future work will apply this model and methodology to evaluate innovative control intervention strategies, including expanded drug treatment programmes proposed by the World Health Organization and its partners.

Parasites and poverty: the case of schistosomiasis

Simultaneous and sequential transmission of multiple parasites, and their resultant overlapping chronic infections, are facts of life in many underdeveloped rural areas. These represent significant but often poorly measured health and economic burdens for affected populations. For example, the chronic inflammatory process associated with long-term schistosomiasis contributes to anaemia and undernutrition, which, in turn, can lead to growth stunting, poor school performance, poor work productivity, and continued poverty. To date, most national and international programs aimed at parasite control have not considered the varied economic and ecological factors underlying multi-parasite transmission, but some are beginning to provide a coordinated approach to control. In addition, interest is emerging in new studies for the re-evaluation and recalibration of the health burden of helminthic parasite infection. Their results should highlight the strong potential of integrated parasite control in efforts for poverty reduction.

Two-year impact of single praziquantel treatment on infection in the national control programme on schistosomiasis in Burkina Faso

OBJECTIVE

To evaluate the impact on schistosomiasis of biennial treatment with praziquantel (PZQ) among school-age children in Burkina Faso, the first country that achieved full national coverage with treatment of more than 90% of the school-age population.

METHODS

A cohort of 1727 schoolchildren (6-14 years old) was monitored at yearly intervals through a longitudinal survey. Additional groups of schoolchildren were monitored in cross-sectional surveys. Parasitological examinations for Schistosoma haematobium and Schistosoma mansoni were performed, and prevalence and intensity of infection before and after treatment were analysed.

FINDINGS

Data from the longitudinal cohort show that a single round of PZQ treatment significantly reduced prevalence of S. haematobium infection by 87% (from 59.6% to 7.7%) and intensity of infection by 92.8% (from 94.2 to 6.8 eggs/10 ml of urine) 2 years post-treatment. The impact on infection was also confirmed by a cross-sectional survey 2 years post-treatment. Importantly, the proportion of school-age children with heavy S. haematobium infection decreased from around 25% before treatment to around 2-3% 2 years post-treatment. Cross-sectional comparison of S. haematobium infection in 7-year-old children in their first year at school, who received treatment through community-based drug delivery, also showed significant reduction in both prevalence (65.9%) and intensity of S. haematobium infection (78.4%) 2 years after single treatment. A significant reduction in S. mansoni infection was also achieved.

CONCLUSION

Significant and sustained reduction in S. haematobium infection was achieved by biennial treatment in school-age children in Burkina Faso. This may provide a cost-effective treatment strategy for similar national schistosomiasis control programmes in sub-Saharan Africa.

Connectivity sustains disease transmission in environments with low potential for endemicity: modelling schistosomiasis with hydrologic and social connectivities

Social interaction and physical interconnections between populations can influence the spread of parasites. The role that these pathways play in sustaining the transmission of parasitic diseases is unclear, although increasingly realistic metapopulation models are being used to study how diseases persist in connected environments. We use a mathematical model of schistosomiasis transmission for a distributed set of heterogeneous villages to show that the transport of parasites via social (host movement) and environmental (parasite larvae movement) pathways has consequences for parasite control, spread and persistence. We find that transmission can be sustained regionally throughout a group of connected villages even when individual village conditions appear not to support endemicity. Optimum transmission is determined by an interplay between different transport pathways, and not necessarily by those that are the most dispersive (e.g. disperse social contacts may not be optimal for transmission). We show that the traditional targeting of villages with high infection, without regard to village interconnections, may not lead to optimum control. These findings have major implications for effective disease control, which needs to go beyond considering local variations in disease intensity, to also consider the degree to which populations are interconnected.

Long-term outcomes of school-based treatment for control of urinary schistosomiasis: a review of experience in Coast Province, Kenya

Urinary schistosomiasis remains a significant burden for Africa and the Middle East. The success of population-based control programs will depend on their impact, over many years, on Schistosoma haematobium reinfection and associated disease. In a multi-year (1984-1992) control program in Kenya, we examined risk for S. haematobium reinfection and late disease during and after annual school-based treatment. In this setting, long-term risk of new infection was independently associated with location, age, hematuria, and incomplete treatment, but not with sex or frequency of water contact. Thus, very local environmental features and age-related factors played an important role in S. haematobium transmission, such that population-based control programs should optimally tailor their efforts to local conditions on a village-by-village basis. In 2001-2002, the late benefits of earlier participation in school-based antischistosomal therapy were estimated in a cohort of formerly-treated adult residents compared to never-treated adults from the same villages. Among age-matched subjects, current infection prevalence was lower among those who had received remote therapy. In addition, prevalence of bladder abnormality was lower in the treated group, who were free of severe bladder disease. Treatment of affected adults resulted in rapid resolution of infection and any detectable bladder abnormalities. We conclude that continued treatment into adulthood, as well as efforts at long-term prevention of infection (transmission control) are necessary to achieve optimal morbidity control in affected communities.

Parasitological impact of 2-year preventive chemotherapy on schistosomiasis and soil-transmitted helminthiasis in Uganda

BACKGROUND

Schistosomiasis and soil-transmitted helminthiasis (STH) are among the neglected tropical diseases in Africa. A national control program for these diseases was initiated in Uganda during March 2003. Annual treatment with praziquantel and albendazole was given to schoolchildren in endemic areas and to adults in selected communities where local prevalence of Schistosoma mansoni in schoolchildren was high.

METHODS

The impact of the treatment program was monitored through cohorts of schoolchildren and adults. Their infection status with S. mansoni and STH was determined by parasitological examinations at baseline and at annual follow-ups. The prevalence and intensity of S. mansoni and STH before and after treatment were analyzed.

RESULTS

Two rounds of treatment significantly reduced the prevalence of S. mansoni infection in schoolchildren across three regions in the country from 33.4-49.3% to 9.7-29.6%, and intensity of infection from 105.7-386.8 eggs per gram of faeces (epg) to 11.6-84.1 epg. The prevalence of hookworm infection was reduced from 41.2-57.9% to 5.5-16.1%, and intensity of infection from 186.9-416.8 epg to 3.7-36.9 epg. The proportion of children with heavy S. mansoni infection was significantly reduced from 15% (95% CI 13.4-16.8%) to 2.3% (95% CI 1.6-3.0%). In adults, significant reduction in the prevalence and intensity of S. mansoni and hookworm infections was also observed. More importantly, the prevalence and intensity of both S. mansoni and hookworm infections in the cohorts of newly-recruited 6-year-olds who had never previously received treatment decreased significantly over 2 years: 34.9% (95% CI 31.9-37.8%) to 22.6% (95% CI 19.9-25.2%) and 171.1 epg (95% CI 141.5-200.7) to 72.0 epg (95% CI 50.9-93.1) for S. mansoni; and 48.4% (95% CI 45.4-51.5) to 15.9% (95% CI 13.6-18.2) and 232.7 epg (95% CI 188.4-276.9) to 51.4 epg (95% CI 33.4-69.5) for hookworms, suggesting a general decline in environmental transmission levels.

CONCLUSION

Annual anthelminthic treatment delivered to schoolchildren and to adults at high risk in Uganda can significantly reduce the prevalence and intensity of infection for schistosomiasis and STH, and potentially also significantly reduce levels of environmental transmission of infection.

Environmental effects on parasitic disease transmission exemplified by schistosomiasis in western China

Environmental effects on the transmission of many parasitic diseases are well recognized, but the role of specific factors like climate and agricultural practices in modulating transmission is seldom characterized quantitatively. Based on studies of Schistosoma japonicum transmission in irrigated agricultural environments in western China, a mathematical model was used to quantify environmental impacts on transmission intensity. The model was calibrated by using field data from intervention studies in three villages and simulated to predict the effects of alternative control options. Both the results of these interventions and earlier epidemiological findings confirm the central role of environmental factors, particularly those relating to snail habitat and agricultural and sanitation practices. Moreover, the findings indicate the inadequacy of current niclosamide-praziquantel strategies alone to achieve sustainable interruption of transmission in some endemic areas. More generally, the analysis suggests a village-specific index of transmission potential and how this potential is modulated by time-varying factors, including climatological variables, seasonal water-contact patterns, and irrigation practices. These time-variable factors, a village's internal potential, and its connectedness to its neighbors provide a framework for evaluating the likelihood of sustained schistosomiasis transmission and suggest an approach to quantifying the role of environmental factors for other parasitic diseases.

Spatial epidemiology of human schistosomiasis in Africa: risk models, transmission dynamics and control

This paper reviews recent studies on the spatial epidemiology of human schistosomiasis in Africa. The integrated use of geographical information systems, remote sensing and geostatistics has provided new insights into the ecology and epidemiology of schistosomiasis at a variety of spatial scales. Because large-scale patterns of transmission are influenced by climatic conditions, an increasing number of studies have used remotely sensed environmental data to predict spatial distributions, most recently using Bayesian methods of inference. Such data-driven approaches allow for a more rational implementation of intervention strategies across the continent. It is suggested that improved incorporation of transmission dynamics into spatial models and assessment of uncertainties inherent in data and modelling approaches represent important future research directions.

Transmission control for schistosomiasis - why it matters now

Current population-based schistosomiasis treatment programs are a first step to reducing the global burden of Schistosoma-related disease; however, they might not dramatically reduce parasite transmission in highly endemic areas. Consequently, the benefits of these programs remain in doubt because recurring low-level reinfection is likely to be associated with subtle but persistent morbidities such as anemia, undernutrition and diminished performance status. The real health benefits of transmission control need to be reconsidered and attention given to more aggressive and, ultimately, more affordable parasite elimination strategies. The next generation of schistosomiasis control can be optimized using new monitoring tools and effective transmission containment.

Ectoparasites and age-dependent survival in a desert rodent

Host age is one of the key factors in host-parasite relationships as it possibly affects infestation levels, parasite-induced mortality of a host, and parasite distribution among host individuals. We tested two alternative hypotheses about infestation pattern and survival under parasitism in relation to host age. The first hypothesis assumes that parasites are recruited faster than they die and, thus, suggests that adult hosts will show higher infestation levels than juveniles because the former have more time to accumulate parasites. The second hypothesis assumes that parasites die faster than they are recruited and, thus, suggests that adults will show lower infestation levels because of acquired immune response and/or the mortality of heavily infested juveniles and, thus, selection for less infested adults. As the negative effects of parasites on host are often intensity-dependent, we expected that the age-related differences in infestation may be translated to lower or higher survival under parasitism of adults, in the cases of the first and the second hypotheses, respectively. We manipulated ectoparasite numbers using insecticide and assessed the infestation pattern in adult and juvenile gerbils (Gerbillus andersoni) in the Negev Desert. We found only a partial support for age-dependent parasitism. No age-related differences in infestation and distribution among host individuals were found after adjusting the ectoparasite numbers to the host's surface area. However, age-related differences in survival under parasitism were revealed. The survival probability of parasitized juveniles decreased in about 48% compared to unparasitized hosts while the survival probability of adults was not affected by ectoparasites. Our results suggest that the effect of host age on host-parasite dynamics may not explicitly be determined by age-dependent differences in ectoparasite recruitment or mortality processes but may also be affected by other host-related and parasite-related traits.