Internal versus external determinants of Schistosoma japonicum transmission in irrigated agricultural villages

Integrating genomic and epidemiologic data to accelerate progress toward schistosomiasis elimination

The global community has adopted ambitious goals to eliminate schistosomiasis as a public health problem, and new tools are needed to achieve them. Mass drug administration programs, for example, have reduced the burden of schistosomiasis, but the identification of hotspots of persistent and reemergent transmission threaten progress toward elimination and underscore the need to couple treatment with interventions that reduce transmission. Recent advances in DNA sequencing technologies make whole-genome sequencing a valuable and increasingly feasible option for population-based studies of complex parasites such as schistosomes. Here, we focus on leveraging genomic data to tailor interventions to distinct social and ecological circumstances. We consider two priority questions that can be addressed by integrating epidemiological, ecological, and genomic information: (1) how often do non-human host species contribute to human schistosome infection? and (2) what is the importance of locally acquired versus imported infections in driving transmission at different stages of elimination? These questions address processes that can undermine control programs, especially those that rely heavily on treatment with praziquantel. Until recently, these questions were difficult to answer with sufficient precision to inform public health decision-making. We review the literature related to these questions and discuss how whole-genome approaches can identify the geographic and taxonomic sources of infection, and how such information can inform context-specific efforts that advance schistosomiasis control efforts and minimize the risk of reemergence.

Human Mobility Associated With Risk of Schistosoma japonicum Infection in Sichuan, China

Urbanization increases human mobility in ways that can alter the transmission of classically rural, vector-borne diseases like schistosomiasis. The impact of human mobility on individual-level Schistosoma risk is poorly characterized. Travel outside endemic areas may protect against infection by reducing exposure opportunities, whereas travel to other endemic regions may increase risk. Using detailed monthly travel- and water-contact surveys from 27 rural communities in Sichuan, China, in 2008, we aimed to describe human mobility and to identify mobility-related predictors of S. japonicum infection. Candidate predictors included timing, frequency, distance, duration, and purpose of recent travel as well as water-contact measures. Random forests machine learning was used to detect key predictors of individual infection status. Logistic regression was used to assess the strength and direction of associations. Key mobility-related predictors include frequent travel and travel during July-both associated with decreased probability of infection and less time engaged in risky water-contact behavior, suggesting travel may remove opportunities for schistosome exposure. The importance of July travel and July water contact suggests a high-risk window for cercarial exposure. The frequency and timing of human movement out of endemic areas should be considered when assessing potential drivers of rural infectious diseases.

River networks as ecological corridors: A coherent ecohydrological perspective

This paper draws together several lines of argument to suggest that an ecohydrological framework, i.e. laboratory, field and theoretical approaches focused on hydrologic controls on biota, has contributed substantially to our understanding of the function of river networks as ecological corridors. Such function proves relevant to: the spatial ecology of species; population dynamics and biological invasions; the spread of waterborne disease. As examples, we describe metacommunity predictions of fish diversity patterns in the Mississippi-Missouri basin, geomorphic controls imposed by the fluvial landscape on elevational gradients of species' richness, the zebra mussel invasion of the same Mississippi-Missouri river system, and the spread of proliferative kidney disease in salmonid fish. We conclude that spatial descriptions of ecological processes in the fluvial landscape, constrained by their specific hydrologic and ecological dynamics and by the ecosystem matrix for interactions, i.e. the directional dispersal embedded in fluvial and host/pathogen mobility networks, have already produced a remarkably broad range of significant results. Notable scientific and practical perspectives are thus open, in the authors' view, to future developments in ecohydrologic research.

Continental-scale, data-driven predictive assessment of eliminating the vector-borne disease, lymphatic filariasis, in sub-Saharan Africa by 2020

BACKGROUND

There are growing demands for predicting the prospects of achieving the global elimination of neglected tropical diseases as a result of the institution of large-scale nation-wide intervention programs by the WHO-set target year of 2020. Such predictions will be uncertain due to the impacts that spatial heterogeneity and scaling effects will have on parasite transmission processes, which will introduce significant aggregation errors into any attempt aiming to predict the outcomes of interventions at the broader spatial levels relevant to policy making. We describe a modeling platform that addresses this problem of upscaling from local settings to facilitate predictions at regional levels by the discovery and use of locality-specific transmission models, and we illustrate the utility of using this approach to evaluate the prospects for eliminating the vector-borne disease, lymphatic filariasis (LF), in sub-Saharan Africa by the WHO target year of 2020 using currently applied or newly proposed intervention strategies. METHODS AND RESULTS: We show how a computational platform that couples site-specific data discovery with model fitting and calibration can allow both learning of local LF transmission models and simulations of the impact of interventions that take a fuller account of the fine-scale heterogeneous transmission of this parasitic disease within endemic countries. We highlight how such a spatially hierarchical modeling tool that incorporates actual data regarding the roll-out of national drug treatment programs and spatial variability in infection patterns into the modeling process can produce more realistic predictions of timelines to LF elimination at coarse spatial scales, ranging from district to country to continental levels. Our results show that when locally applicable extinction thresholds are used, only three countries are likely to meet the goal of LF elimination by 2020 using currently applied mass drug treatments, and that switching to more intensive drug regimens, increasing the frequency of treatments, or switching to new triple drug regimens will be required if LF elimination is to be accelerated in Africa. The proportion of countries that would meet the goal of eliminating LF by 2020 may, however, reach up to 24/36 if the WHO 1% microfilaremia prevalence threshold is used and sequential mass drug deliveries are applied in countries.

CONCLUSIONS

We have developed and applied a data-driven spatially hierarchical computational platform that uses the discovery of locally applicable transmission models in order to predict the prospects for eliminating the macroparasitic disease, LF, at the coarser country level in sub-Saharan Africa. We show that fine-scale spatial heterogeneity in local parasite transmission and extinction dynamics, as well as the exact nature of intervention roll-outs in countries, will impact the timelines to achieving national LF elimination on this continent.

Low Transmission to Elimination: Rural Development as a Key Determinant of the End-Game Dynamics of Schistosoma japonicum in China

Rural development has been a critical component of China’s economic miracle since the start of economic reform in the early 1980s, both benefiting from and contributing to the nation’s rapid economic growth. This development has yielded substantial improvements of public health relevance, including contributing to major reductions in schistosomiasis prevalence. The history of schistosomiasis elimination in Japan suggests that development played a dominant causal role in that nation. We argue that it is highly probable that a similar story is playing out in at least some large regions of China. In particular, we summarize evidence from Sichuan Province which supports the case that economic development has led to improvements in rural irrigation and water supply which, together with changes in crop selection and agricultural mechanization, have all contributed to sustainable reductions in the prevalence of Schistosoma japonicum. The two major factors that have experienced major reductions are the area of snail habitat and the degree of human exposure, both through a variety of mechanisms which differ by region and economic circumstance. However, hotspots of transmission remain. Overall, however, economic development in traditionally endemic areas has provided the resources to carry out projects that have had major beneficial impacts on disease transmission that are likely to be sustainable.

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.

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.

Exposure versus Susceptibility as Alternative Bases for New Approaches to Surveillance for Schistosoma japonicum in Low Transmission Environments

Currently, schistosomiasis in China provides an excellent example of many of the challenges of moving from low transmission to the elimination of transmission for infectious diseases generally. In response to the surveillance dimension of these challenges, we here explore two strategic approaches to inform priorities for the development of improved methods addressed specifically to schistosomiasis in the low transmission environment. We utilize an individually-based model and the exposure data used earlier to explore surveillance strategies, one focused on exposure assessment and the second on our estimates of variability in individual susceptibility in the practical context of the current situation in China and the theoretical context of the behavior of transmission dynamics near the zero state. Our findings suggest that individual susceptibility is the major single determinant of infection intensity in both the low and medium risk environments. We conclude that there is considerable motivation to search for a biomarker of susceptibility to infection in humans, but that there would also be value in a method for monitoring surface waters for the free-swimming forms of the parasite in endemic or formerly endemic environments as an early warning of infection risk.

Surveillance programs for environmentally-mediated infectious diseases in the developing world present challenges to public health authorities in acquiring adequate resources for their widespread use as well as in the availability of practical and reliable methods. These challenges are exacerbated in cases where transmission is suppressed to low but persistent levels, as is currently the case for the parasitic disease schistosomiasis in China. In this paper we use epidemiologically-based computer modeling to explore the potential utility of new approaches based on human susceptibility on one hand and exposure-related methods on the other. Our intent is to motivate the development of new methods based on one or both of these strategic approaches and aimed at the low transmission environment. We conclude that there is considerable motivation to search for a biomarker of susceptibility to infection in humans and also to develop a method for monitoring surface waters for the free-swimming forms of the parasite in endemic or formerly endemic environments as an early warning of infection risk.

Bayesian calibration of simulation models for supporting management of the elimination of the macroparasitic disease, Lymphatic Filariasis

Background

Mathematical models of parasite transmission can help integrate a large body of information into a consistent framework, which can then be used for gaining mechanistic insights and making predictions. However, uncertainty, spatial variability and complexity, can hamper the use of such models for decision making in parasite management programs.

Methods

We have adapted a Bayesian melding framework for calibrating simulation models to address the need for robust modelling tools that can effectively support management of lymphatic filariasis (LF) elimination in diverse endemic settings. We applied this methodology to LF infection and vector biting data from sites across the major LF endemic regions in order to quantify model parameters, and generate reliable predictions of infection dynamics along with credible intervals for modelled output variables. We used the locally calibrated models to estimate breakpoint values for various indicators of parasite transmission, and simulate timelines to parasite extinction as a function of local variations in infection dynamics and breakpoints, and effects of various currently applied and proposed LF intervention strategies.

Results

We demonstrate that as a result of parameter constraining by local data, breakpoint values for all the major indicators of LF transmission varied significantly between the sites investigated. Intervention simulations using the fitted models showed that as a result of heterogeneity in local transmission and extinction dynamics, timelines to parasite elimination in response to the current Mass Drug Administration (MDA) and various proposed MDA with vector control strategies also varied significantly between the study sites. Including vector control, however, markedly reduced the duration of interventions required to achieve elimination as well as decreased the risk of recrudescence following stopping of MDA.

Conclusions

We have demonstrated how a Bayesian data-model assimilation framework can enhance the use of transmission models for supporting reliable decision making in the management of LF elimination. Extending this framework for delivering predictions in settings either lacking or with only sparse data to inform the modelling process, however, will require development of procedures to estimate and use spatio-temporal variations in model parameters and inputs directly, and forms the next stage of the work reported here.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-015-1132-7) contains supplementary material, which is available to authorized users.

Exploring the contribution of host susceptibility to epidemiological patterns of Schistosoma japonicum infection using an individual-based model

We recently reported the analysis of epidemiological data suggesting variability in individual susceptibility to infection by Schistosoma japonicum among rural villagers who reside in Sichuan Province of southwestern China. By supplementing the data used in the earlier analysis from other studies we have reported from this region, we presented improved estimates of cercarial exposure, which in turn, result in stronger evidence of susceptibility. This analysis was conducted using an individual-based mathematical model (IBM) whose use was motivated by the nature and extent of field data from the low-transmission environments exemplified by one of our datasets and typical of the current situation in most endemic areas of China. In addition to individual susceptibility and water contact, the model includes stochastic aspects of cercarial exposure as well as of diagnostic procedures, the latter being particularly relevant to the low-transmission environment. The simulation studies show that, to produce key aspects of the epidemiological findings, the distribution of susceptibility ranges over several orders of magnitude and is highly right skewed. We found no compelling evidence that the distribution of susceptibility differed between the two populations that underlie both the epidemiological and simulation results.

The Allee effect and elimination of neglected tropical diseases: a mathematical modelling study

Elimination and control programmes for neglected tropical diseases (NTDs) are underway around the world, yet they are generally informed by epidemiological modelling only to a rudimentary degree. Chief among the modelling-derived predictors of disease emergence or controllability is the basic reproduction number R0. The ecological systems of several of the NTDs include density-dependent processes--which alter the rate of e.g. parasite establishment or fecundity--that complicate the calculation of R0. Here we show how the forms of the density-dependent functions for a model of the NTD lymphatic filariasis affect the effective reproduction number Reff. We construct infection transmission models containing various density-dependent functions and show how they alter the shape of the Reff profile, affecting two important epidemiological outcome variables that relate to elimination and control programmes: the parasite transmission breakpoint (or extinction threshold) and the reproduction fitness, as measured by Reff. The current drive to control, eliminate or eradicate several parasitic infections would be substantially aided by the existence of ecological Allee effects. For these control programmes, the findings of this paper are encouraging, since a single positive density dependency (DD) can introduce a reasonable chance of achieving elimination; however, there are diminishing returns to additional positive DDs.

Associations between schistosomiasis and the use of human waste as an agricultural fertilizer in China

Background

Human waste is used as an agricultural fertilizer in China and elsewhere. Because the eggs of many helminth species can survive in environmental media, reuse of untreated or partially treated human waste, commonly called night soil, may promote transmission of human helminthiases.

Methodology/Principal Findings

We conducted an open cohort study in 36 villages to evaluate the association between night soil use and schistosomiasis in a region of China where schistosomiasis has reemerged and persisted despite control activities. We tested 2,005 residents for Schistosoma japonicum infection in 2007 and 1,365 residents in 2010 and interviewed heads of household about agricultural practices each study year. We used an intervention attributable ratio framework to estimate the association between night soil use and S. japonicum infection. Night soil use was reported by half of households (56% in 2007 and 46% in 2010). Village night soil use was strongly associated with human S. japonicum infection in 2007. We estimate cessation of night soil use would lead to a 49% reduction in infection prevalence in 2007 (95% CI: 12%, 71%). However, no association between night soil and schistosomiasis was observed in 2010. These inconsistent findings may be due to unmeasured confounding or temporal shifts in the importance of different sources of S. japonicum eggs on the margins of disease elimination.

Conclusions/Significance

The use of untreated or partially treated human waste as an agricultural fertilizer may be a barrier to permanent reductions in human helminthiases. This practice warrants further attention by the public health community.

Many people use human waste as an agricultural fertilizer, often called “night soil.” If the waste is not properly treated, the use of night soil may promote the spread of infectious diseases. We suspected that night soil use may facilitate the spread of the water-borne disease, schistosomiasis, as some schistosomiasis eggs can survive in the environment for weeks. We conducted a study in 36 villages in rural China in order to see if the amount of night soil used in a village was associated with schistosomiasis. The study was conducted in an area where schistosomiasis reemerged and persisted despite an aggressive disease control program. We found half of households reported using night soil—it was used on all major crops and by people across the socio-economic spectrum. We also found that night soil use was strongly associated with schistosomiasis infection in 2007, but not in 2010. Our findings show the use of human waste as an agricultural fertilizer is common in our study region and may increase schistosomiasis infections. The extent to which night soil is used and risks of this practice should be evaluated as part of disease control programs targeting schistosomiasis and other human helminthiases.

Schistosomiasis japonica: modelling as a tool to explore transmission patterns

Modelling is an important tool for the exploration of Schistosoma japonicum transmission patterns. It provides a general theoretical framework for decision-makers and lends itself specifically to assessing the progress of the national control programme by following the outcome of surveys. The challenge of keeping up with the many changes of social, ecological and environmental factors involved in control activities is greatly facilitated by modelling that can also indicate which activities are critical and which are less important. This review examines the application of modelling tools in the epidemiological study of schistosomiasis japonica during the last 20 years and explores the application of enhanced models for surveillance and response. Updated and timely information for decision-makers in the national elimination programme is provided but, in spite of the new modelling techniques introduced, many questions remain. Issues on application of modelling are discussed with the view to improve the current situation with respect to schistosomiasis japonica.

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.

Exploring the impact of infection-induced immunity on the transmission of Schistosoma japonicum in hilly and mountainous environments in China

Schistosomiasis has long been a threat to villagers in hilly and mountainous areas of southwestern China where the intermediate snail host is abundant. In recent years our group has focused on the development and parameterization of a community-level mathematical model of S. japonicum transmission that accounts for the role of environmental determinants of transmission intensity in Sichuan Province. To date the model has not incorporated acquired immunity. A review of previous epidemiologic data from our study area in Sichuan suggested modeling of acquired immunity as a function of history of infection. To explore the potential impacts on the dynamics of transmission, a mathematical representation of acquired immunity was incorporated, and parameterized based on this epidemiological evidence. It is shown through simulation that the effect of immunity is to reduce the rate of worm development and thereby lower the endemic level significantly. The effect was more striking at increasing levels of a village'tm)s basic reproductive number. Further, residual immunity modestly alters the threshold of external parasite input necessary to trigger re-emergence of transmission and its subsequent rate of development. Despite limitations in our quantitative knowledge of the immunity function, these findings, along with the uncertainties in transmission dynamics at low infection levels, underscore the need for improved diagnostic methods for disease control, especially in potentially re-emergent settings.

Sequential modelling of the effects of mass drug treatments on anopheline-mediated lymphatic filariasis infection in Papua New Guinea

BACKGROUND

Lymphatic filariasis (LF) has been targeted by the WHO for global eradication leading to the implementation of large scale intervention programs based on annual mass drug administrations (MDA) worldwide. Recent work has indicated that locality-specific bio-ecological complexities affecting parasite transmission may complicate the prediction of LF extinction endpoints, casting uncertainty on the achievement of this initiative. One source of difficulty is the limited quantity and quality of data used to parameterize models of parasite transmission, implying the important need to update initially-derived parameter values. Sequential analysis of longitudinal data following annual MDAs will also be important to gaining new understanding of the persistence dynamics of LF. Here, we apply a Bayesian statistical-dynamical modelling framework that enables assimilation of information in human infection data recorded from communities in Papua New Guinea that underwent annual MDAs, into our previously developed model of parasite transmission, in order to examine these questions in LF ecology and control.

RESULTS

Biological parameters underlying transmission obtained by fitting the model to longitudinal data remained stable throughout the study period. This enabled us to reliably reconstruct the observed baseline data in each community. Endpoint estimates also showed little variation. However, the updating procedure showed a shift towards higher and less variable values for worm kill but not for any other drug-related parameters. An intriguing finding is that the stability in key biological parameters could be disrupted by a significant reduction in the vector biting rate prevailing in a locality.

CONCLUSIONS

Temporal invariance of biological parameters in the face of intervention perturbations indicates a robust adaptation of LF transmission to local ecological conditions. The results imply that understanding the mechanisms that underlie locally adapted transmission dynamics will be integral to identifying points of system fragility, and thus countermeasures to reliably facilitate LF extinction both locally and globally.

The challenge of effective surveillance in moving from low transmission to elimination of schistosomiasis in China

Until recently, intensified efforts in China to suppress the transmission of Schistosoma japonicum relied principally on routine praziquantel treatment, extensive use of molluscicides and health education programs. These efforts, now supplemented by a broader range of control measures, have been quite successful in reducing the prevalence and intensity of human infection to very low levels. However, re-emergent transmission has occurred in formerly endemic areas of several provinces, signalling the need for more locally effective, integrated control strategies. We argue that these low but persistent levels of transmission also require important changes in both the tactics and strategy of disease surveillance to move forward towards elimination. Here we present recent data exemplifying the low transmission environment which suggests that we are reaching limits of detection of current diagnostic techniques used for human infection surveillance in these communities. However, both epidemiological data and theoretical results indicate that (i) transmission in the human population can persist at very low infection intensities even in the presence of routine control activities; (ii) the parasite can be reintroduced into parasite-free environments by very modest external inputs; and (iii) transmission at these low infection intensities exhibits very slow inter-year dynamics. These observations motivate the need for new, sensitive tools to identify low-level infections in mammalian or snail hosts, or the presence of S. japonicum in environmental media. Environmental monitoring offers an alternative, and perhaps more efficient, approach to large-scale surveillance of human infections in low transmission regions.