A multi-group model of Schistosoma japonicum transmission dynamics and control: model calibration and control prediction

Control of schistosomiasis by the selective competitive and predatory intervention of intermediate hosts: A mathematical modeling approach

Schistosomiasis, a freshwater-borne neglected tropical disease, disproportionately affects impoverished communities mainly in the tropical regions. Transmission involves humans and intermediate host (IH) snails. This manuscript introduces a mathematical model to probe schistosomiasis dynamics and the role of non-host snail competitors and predators as biological control agents for IH snails. The numerical analyses include investigations into steady-state conditions and reproduction numbers associated with uncontrolled scenarios, as well as scenarios involving non-host snail competitors and/or predators. Sensitivity analysis reveals that increasing snail mortality rates is a key to reducing the IH snail population and control of the transmission. Results show that specific snail competitors and/or predators with strong competition/predation abilities reduce IH snails and the subsequent infectious cercaria populations, reduce the transmission, and possibly eradicate the disease, while those with weaker abilities allow disease persistence. Hence our findings advocate for the effectiveness of snail competitors with suitable competitive pressures and/or predators with appropriate predatory abilities as nature-based solutions for combating schistosomiasis, all while preserving IH snail biodiversity. However, if these strategies are implemented at insignificant levels, IH snails can dominate, and disease persistence may pose challenges. Thus, experimental screening of potential (native) snail competitors and/or predators is crucial to assess the likely behavior of biological agents and determine the optimal biological control measures for IH snails.

Exploring the interplay between climate change and schistosomiasis transmission dynamics

Schistosomiasis, a neglected tropical disease caused by parasitic worms, poses a major public health challenge in economically disadvantaged regions, especially in Sub-Saharan Africa. Climate factors, such as temperature and rainfall patterns, play a crucial role in the transmission dynamics of the disease. This study presents a deterministic model that aims to evaluate the temporal and seasonal transmission dynamics of schistosomiasis by examining the influence of temperature and rainfall over time. Equilibrium states are examined to ascertain their existence and stability employing the center manifold theory, while the basic reproduction number is calculated using the next-generation technique. To validate the model's applicability, demographic and climatological data from Uganda, Kenya, and Tanzania, which are endemic East African countries situated in the tropical region, are utilized as a case study region. The findings of this study provide evidence that the transmission of schistosomiasis in human populations is significantly influenced by seasonal and monthly variations, with incidence rates varying across countries depending on the frequency of temperature and rainfall. Consequently, the region is marked by both schistosomiasis emergencies and re-emergences. Specifically, it is observed that monthly mean temperatures within the range of 22-27 °C create favorable conditions for the development of schistosomiasis and have a positive impact on the reproduction numbers. On the other hand, monthly maximum temperatures ranging from 27 to 33 °C have an adverse effect on transmission. Furthermore, through sensitivity analysis, it is projected that by the year 2050, factors such as the recruitment rate of snails, the presence of parasite egg-containing stools, and the rate of miracidia shedding per parasite egg will contribute significantly to the occurrence and control of schistosomiasis infections. This study highlights the significant influence of seasonal and monthly variations, driven by temperature and rainfall patterns, on the transmission dynamics of schistosomiasis. These findings underscore the importance of considering climate factors in the control and prevention strategies of schistosomiasis. Additionally, the projected impact of various factors on schistosomiasis infections by 2050 emphasizes the need for proactive measures to mitigate the disease's impact on vulnerable populations. Overall, this research provides valuable insights to anticipate future challenges and devise adaptive measures to address schistosomiasis transmission patterns.

A Mathematical Model of the Transmission Dynamics of Bovine Schistosomiasis with Contaminated Environment

Schistosomiasis, a vector-borne chronically debilitating infectious disease, is a serious public health concern for humans and animals in the affected tropical and sub-tropical regions. We formulate and theoretically analyze a deterministic mathematical model with snail and bovine hosts. The basic reproduction number [Formula: see text] is computed and used to investigate the local stability of the model's steady states. Global stability of the endemic equilibrium is carried out by constructing a suitable Lyapunov function. Sensitivity analysis shows that the basic reproduction number is most sensitive to the model parameters related to the contaminated environment, namely: shedding rate of cercariae by snails, cercariae to miracidia survival probability, snails-miracidia effective contact rate and natural death rate of miracidia and cercariae. Numerical results show that when no intervention measures are implemented, there is an increase of the infected classes, and a rapid decline of the number of susceptible and exposed bovines and snails. Effects of the variation of some of the key sensitive model parameters on the schistosomiasis dynamics as well as on the initial disease transmission threshold parameter [Formula: see text] are graphically depicted.

The Effect of Climate Change and the Snail-Schistosome Cycle in Transmission and Bio-Control of Schistosomiasis in Sub-Saharan Africa

In the next century, global warming, due to changes in climatic factors, is expected to have an enormous influence on the interactions between pathogens and their hosts. Over the years, the rate at which vector-borne diseases and their transmission dynamics modify and develop has been shown to be highly dependent to a certain extent on changes in temperature and geographical distribution. Schistosomiasis has been recognized as a tropical and neglected vector-borne disease whose rate of infection has been predicted to be elevated worldwide, especially in sub-Saharan Africa; the region currently with the highest proportion of people at risk, due to changes in climate. This review not only suggests the need to develop an efficient and effective model that will predict Schistosoma spp. population dynamics but seeks to evaluate the effectiveness of several current control strategies. The design of a framework model to predict and accommodate the future incidence of schistosomiasis in human population dynamics in sub-Saharan Africa is proposed. The impact of climate change on schistosomiasis transmission as well as the distribution of several freshwater snails responsible for the transmission of Schistosoma parasites in the region is also reviewed. Lastly, this article advocates for modelling several control mechanisms for schistosomiasis in sub-Saharan Africa so as to tackle the re-infection of the disease, even after treating infected people with praziquantel, the first-line treatment drug for schistosomiasis.

A mechanistic hydro-epidemiological model of liver fluke risk

The majority of existing models for predicting disease risk in response to climate change are empirical. These models exploit correlations between historical data, rather than explicitly describing relationships between cause and response variables. Therefore, they are unsuitable for capturing impacts beyond historically observed variability and have limited ability to guide interventions. In this study, we integrate environmental and epidemiological processes into a new mechanistic model, taking the widespread parasitic disease of fasciolosis as an example. The model simulates environmental suitability for disease transmission at a daily time step and 25 m resolution, explicitly linking the parasite life cycle to key weather–water–environment conditions. Using epidemiological data, we show that the model can reproduce observed infection levels in time and space for two case studies in the UK. To overcome data limitations, we propose a calibration approach combining Monte Carlo sampling and expert opinion, which allows constraint of the model in a process-based way, including a quantification of uncertainty. The simulated disease dynamics agree with information from the literature, and comparison with a widely used empirical risk index shows that the new model provides better insight into the time–space patterns of infection, which will be valuable for decision support.

Field Testing Integrated Interventions for Schistosomiasis Elimination in the People's Republic of China: Outcomes of a Multifactorial Cluster-Randomized Controlled Trial

Despite significant progress, China faces the challenge of re-emerging schistosomiasis transmission in currently controlled areas due, in part, to the presence of a range of animal reservoirs, notably water buffalo and cattle, which can harbor Schistosoma japonicum infections. Environmental, ecological and social-demographic changes in China, shown to affect the distribution of oncomelanid snails, can also impact future schistosomiasis transmission. In light of their importance in the S. japonicum, lifecycle, vaccination has been proposed as a means to reduce the excretion of egg from cattle and buffalo, thereby interrupting transmission from these reservoir hosts to snails. A DNA-based vaccine (SjCTPI) our team developed showed encouraging efficacy against S. japonicum in Chinese water buffaloes. Here we report the results of a double-blind cluster randomized trial aimed at determining the impact of a combination of the SjCTPI bovine vaccine (given as a prime-boost regimen), human mass chemotherapy and snail control on the transmission of S. japonicum in 12 selected administrative villages around the Dongting Lake in Hunan province. The trial confirmed human praziquantel treatment is an effective intervention at the population level. Further, mollusciciding had an indirect ~50% efficacy in reducing human infection rates. Serology showed that the SjCTPI vaccine produced an effective antibody response in vaccinated bovines, resulting in a negative correlation with bovine egg counts observed at all post-vaccination time points. Despite these encouraging outcomes, the effect of the vaccine in preventing human infection was inconclusive. This was likely due to activities undertaken by the China National Schistosomiasis Control Program, notably the treatment, sacrifice or removal of bovines from trial villages, over which we had no control; as a result, the trial design was compromised, reducing power and contaminating outcome measures. This highlights the difficulties in undertaking field trials of this nature and magnitude, particularly over a long period, and emphasizes the importance of mathematical modeling in predicting the potential impact of control intervention measures. A transmission blocking vaccine targeting bovines for the prevention of S. japonicum with the required protective efficacy would be invaluable in tandem with other preventive intervention measures if the goal of eliminating schistosomiasis from China is to become a reality.

The human-snail transmission environment shapes long term schistosomiasis control outcomes: Implications for improving the accuracy of predictive modeling

INTRODUCTION

Schistosomiasis is a chronic parasitic trematode disease that affects over 240 million people worldwide. The Schistosoma lifecycle is complex, involving transmission via specific intermediate-host freshwater snails. Predictive mathematical models of Schistosoma transmission have often chosen to simplify or ignore the details of environmental human-snail interaction in their analyses. Schistosome transmission models now aim to provide better precision for policy planning of elimination of transmission. This heightens the importance of including the environmental complexity of vector-pathogen interaction in order to make more accurate projections.

METHODOLOGY AND PRINCIPAL FINDINGS

We propose a nonlinear snail force of infection (FOI) that takes into account an intermediate larval stage (miracidium) and snail biology. We focused, in particular, on the effects of snail force of infection (FOI) on the impact of mass drug administration (MDA) in human communities. The proposed (modified) model was compared to a conventional model in terms of their predictions. A longitudinal dataset generated in Kenya field studies was used for model calibration and validation. For each sample community, we calibrated modified and conventional model systems, then used them to model outcomes for a range of MDA regimens. In most cases, the modified model predicted more vigorous post-MDA rebound, with faster relapse to baseline levels of infection. The effect was pronounced in higher risk communities. When compared to observed data, only the modified system was able to successfully predict persistent rebound of Schistosoma infection.

CONCLUSION AND SIGNIFICANCE

The observed impact of varying location-specific snail inputs sheds light on the diverse MDA response patterns noted in operational research on schistosomiasis control, such as the recent SCORE project. Efficiency of human-to-snail transmission is likely to be much higher than predicted by standard models, which, in practice, will make local elimination by implementation of MDA alone highly unlikely, even over a multi-decade period.

Opportunities and challenges for modelling epidemiological and evolutionary dynamics in a multihost, multiparasite system: Zoonotic hybrid schistosomiasis in West Africa

Multihost multiparasite systems are evolutionarily and ecologically dynamic, which presents substantial trans-disciplinary challenges for elucidating their epidemiology and designing appropriate control. Evidence for hybridizations and introgressions between parasite species is gathering, in part in line with improvements in molecular diagnostics and genome sequencing. One major system where this is becoming apparent is within the Genus Schistosoma, where schistosomiasis represents a disease of considerable medical and veterinary importance, the greatest burden of which occurs in sub-Saharan Africa. Interspecific hybridizations and introgressions bring an increased level of complexity over and above that already inherent within multihost, multiparasite systems, also representing an additional source of genetic variation that can drive evolution. This has the potential for profound implications for the control of parasitic diseases, including, but not exclusive to, widening host range, increased transmission potential and altered responses to drug therapy. Here, we present the challenging case example of haematobium group Schistosoma spp. hybrids in West Africa, a system involving multiple interacting parasites and multiple definitive hosts, in a region where zoonotic reservoirs of schistosomiasis were not previously considered to be of importance. We consider how existing mathematical model frameworks for schistosome transmission could be expanded and adapted to zoonotic hybrid systems, exploring how such model frameworks can utilize molecular and epidemiological data, as well as the complexities and challenges this presents. We also highlight the opportunities and value such mathematical models could bring to this and a range of similar multihost, multi and cross-hybridizing parasites systems in our changing world.

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.

Multi-host model and threshold of intermediate host Oncomelania snail density for eliminating schistosomiasis transmission in China

Schistosomiasis remains a serious public health issue in many tropical countries, with more than 700 million people at risk of infection. In China, a national integrated control strategy, aiming at blocking its transmission, has been carried out throughout endemic areas since 2005. A longitudinal study was conducted to determine the effects of different intervention measures on the transmission dynamics of S. japonicum in three study areas and the data were analyzed using a multi-host model. The multi-host model was also used to estimate the threshold of Oncomelania snail density for interrupting schistosomiasis transmission based on the longitudinal data as well as data from the national surveillance system for schistosomiasis. The data showed a continuous decline in the risk of human infection and the multi-host model fit the data well. The 25th, 50th and 75th percentiles, and the mean of estimated thresholds of Oncomelania snail density below which the schistosomiasis transmission cannot be sustained were 0.006, 0.009, 0.028 and 0.020 snails/0.11 m², respectively. The study results could help develop specific strategies of schistosomiasis control and elimination tailored to the local situation for each endemic area.

A controlled, before-and-after trial of an urban sanitation intervention to reduce enteric infections in children: research protocol for the Maputo Sanitation (MapSan) study, Mozambique

INTRODUCTION

Access to safe sanitation in low-income, informal settlements of Sub-Saharan Africa has not significantly improved since 1990. The combination of a high faecal-related disease burden and inadequate infrastructure suggests that investment in expanding sanitation access in densely populated urban slums can yield important public health gains. No rigorous, controlled intervention studies have evaluated the health effects of decentralised (non-sewerage) sanitation in an informal urban setting, despite the role that such technologies will likely play in scaling up access.

METHODS AND ANALYSIS

We have designed a controlled, before-and-after (CBA) trial to estimate the health impacts of an urban sanitation intervention in informal neighbourhoods of Maputo, Mozambique, including an assessment of whether exposures and health outcomes vary by localised population density. The intervention consists of private pour-flush latrines (to septic tank) shared by multiple households in compounds or household clusters. We will measure objective health outcomes in approximately 760 children (380 children with household access to interventions, 380 matched controls using existing shared private latrines in poor sanitary conditions), at 2 time points: immediately before the intervention and at follow-up after 12 months. The primary outcome is combined prevalence of selected enteric infections among children under 5 years of age. Secondary outcome measures include soil-transmitted helminth (STH) reinfection in children following baseline deworming and prevalence of reported diarrhoeal disease. We will use exposure assessment, faecal source tracking, and microbial transmission modelling to examine whether and how routes of exposure for diarrhoeagenic pathogens and STHs change following introduction of effective sanitation.

ETHICS

Study protocols have been reviewed and approved by human subjects review boards at the London School of Hygiene and Tropical Medicine, the Georgia Institute of Technology, the University of North Carolina at Chapel Hill, and the Ministry of Health, Republic of Mozambique.

TRIAL REGISTRATION NUMBER

NCT02362932.

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 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.

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.

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.

Developmental models for estimating ecological responses to environmental variability: structural, parametric, and experimental issues

Developmental models that account for the metabolic effect of temperature variability on poikilotherms, such as degree-day models, have been widely used to study organism emergence, range and development, particularly in agricultural and vector-borne disease contexts. Though simple and easy to use, structural and parametric issues can influence the outputs of such models, often substantially. Because the underlying assumptions and limitations of these models have rarely been considered, this paper reviews the structural, parametric, and experimental issues that arise when using degree-day models, including the implications of particular structural or parametric choices, as well as assumptions that underlie commonly used models. Linear and non-linear developmental functions are compared, as are common methods used to incorporate temperature thresholds and calculate daily degree-days. Substantial differences in predicted emergence time arose when using linear versus non-linear developmental functions to model the emergence time in a model organism. The optimal method for calculating degree-days depends upon where key temperature threshold parameters fall relative to the daily minimum and maximum temperatures, as well as the shape of the daily temperature curve. No method is shown to be universally superior, though one commonly used method, the daily average method, consistently provides accurate results. The sensitivity of model projections to these methodological issues highlights the need to make structural and parametric selections based on a careful consideration of the specific biological response of the organism under study, and the specific temperature conditions of the geographic regions of interest. When degree-day model limitations are considered and model assumptions met, the models can be a powerful tool for studying temperature-dependent development.

Road to the elimination of schistosomiasis from Asia: the journey is far from over

Schistosomiasis is a neglected tropical disease with a very long endemic history in Asia. Great strides have been made to control the disease in China and the Philippines but the road to elimination is far from over, given the zoonotic nature of the schistosome parasites in both countries.

Spatially explicit modeling of schistosomiasis risk in eastern China based on a synthesis of epidemiological, environmental and intermediate host genetic data

Schistosomiasis japonica is a major parasitic disease threatening millions of people in China. Though overall prevalence was greatly reduced during the second half of the past century, continued persistence in some areas and cases of re-emergence in others remain major concerns. As many regions in China are approaching disease elimination, obtaining quantitative data on Schistosoma japonicum parasites is increasingly difficult. This study examines the distribution of schistosomiasis in eastern China, taking advantage of the fact that the single intermediate host serves as a major transmission bottleneck. Epidemiological, population-genetic and high-resolution ecological data are combined to construct a predictive model capable of estimating the probability that schistosomiasis occurs in a target area (“spatially explicit schistosomiasis risk”). Results show that intermediate host genetic parameters are correlated with the distribution of endemic disease areas, and that five explanatory variables—altitude, minimum temperature, annual precipitation, genetic distance, and haplotype diversity—discriminate between endemic and non-endemic zones. Model predictions are correlated with human infection rates observed at the county level. Visualization of the model indicates that the highest risks of disease occur in the Dongting and Poyang lake regions, as expected, as well as in some floodplain areas of the Yangtze River. High risk areas are interconnected, suggesting the complex hydrological interplay of Dongting and Poyang lakes with the Yangtze River may be important for maintaining schistosomiasis in eastern China. Results demonstrate the value of genetic parameters for risk modeling, and particularly for reducing model prediction error. The findings have important consequences both for understanding the determinants of the current distribution of S. japonicum infections, and for designing future schistosomiasis surveillance and control strategies. The results also highlight how genetic information on taxa that constitute bottlenecks to disease transmission can be of value for risk modeling.

Schistosomiasis is considered the second most devastating parasitic disease after malaria. In China, it is transmitted to humans, cattle and other vertebrate hosts by a single intermediate snail host. It has long been suggested that the close co-evolutionary relationship between parasite and intermediate host makes the snail a major transmission bottleneck in the disease life cycle. Here, we use a novel approach to model the disease distribution in eastern China based on a combination of epidemiological, ecological, and genetic information. We found four major high risk areas for schistosomiasis occurrence in the large lakes and flood plain regions of the Yangtze River. These regions are interconnected, suggesting that the disease may be maintained in eastern China in part through the annual flooding of the Yangtze River, which drives snail transport and admixture of genotypes. The novel approach undertaken yielded improved prediction of schistosomiasis disease distribution in eastern China. Thus, it may also be of value for the predictive modeling of other host- or vector-borne diseases.

Field transmission intensity of Schistosoma japonicum measured by basic reproduction ratio from modified Barbour's model

BACKGROUND

Schistosomiasis japonica, caused by infection with Schistosoma japonicum, is still recognized as a major public health problem in the Peoples' Republic of China. Mathematical modelling of schistosomiasis transmission has been undertaken in order to assess and project the effects of various control strategies for elimination of the disease. Seasonal fluctuations in transmission may have the potential to impact on the population dynamics of schistosomiasis, yet no model of S. japonicum has considered such effects. In this paper, we characterize the transmission dynamics of S. japonicum using a modified version of Barbour's model to account for seasonal variation (SV), and investigate the effectiveness of the control strategy adopted in Liaonan village of Xingzi county, Jiangxi Province.

METHODS

We use mathematical tools for stability analysis of periodic systems and derive expressions for the basic reproduction ratio of S. japonicum in humans; we parameterise such expressions with surveillance data to investigate the conditions for persistence or elimination of the disease in the study village. We perform numerical simulations and parametric sensitivity analysis to understand local transmission conditions and compare values of the basic reproductive ratio with and without seasonal fluctuations.

RESULTS

The explicit formula of the basic reproduction ratio for the SV-modified Barbour's model is derived. Results show that the value of the basic reproduction ratio, R0, of Liaonan village, Xingzi county is located between 1.064 and 1.066 (very close to 1), for schistosomiasis transmission during 2006 to 2010, after intensification of control efforts.

CONCLUSIONS

Our modified version of the Barbour model to account for seasonal fluctuations in transmission has the potential to provide better estimations of infection risk than previous models. Ignoring seasonality tends to underestimate R0 values albeit only marginally. In the absence of simultaneous R0 estimations for villages not under control interventions (such villages do not currently exist in China), it is difficult to assess whether control strategies have had a substantial impact on levels of transmission, as the parasite population would still be able to maintain itself at an endemic level, highlighting the difficulties faced by elimination efforts.

Cautioning the use of degree-day models for climate change projections in the presence of parametric uncertainty

Developmental models, such as degree-day models, are commonly used to predict the impact of future climate change on the intensity, distribution, and timing of the transmission of infectious diseases, particularly those caused by pathogens carried by vectors or intermediate hosts. Resulting projections can be useful in policy discussions concerning regional or national responses to future distributions of important infectious diseases. Although the simplicity of degree-day models is appealing, little work has been done to analyze their ability to make reliable projections of the distribution of important pathogens, vectors, or intermediate hosts in the presence of the often considerable parametric uncertainty common to such models. Here, a population model of Oncomelania hupensis, the intermediate host of Schistosoma japonicum, was used to investigate the sensitivity of host range predictions in Sichuan Province, China, to uncertainty in two key degree-day model parameters: delta(min) (minimum temperature threshold for development) and K (total degree-days required for completion of snail development). The intent was to examine the consequences of parametric uncertainty in a plausible biological model, rather than to generate the definitive model. Results indicate that model output, the seasonality of population dynamics, and range predictions, particularly along the edge of the range, are highly sensitive to changes in model parameters, even at levels of parametric uncertainty common to such applications. Caution should be used when interpreting the results of degree-day models used to generate predictions of disease distribution and risk under scenarios of future climate change, and predictions should be considered most reliable when the temperature ranges used in projections resemble those used to estimate model parameters. Given the potential for substantial changes in degree-day model output with modest changes in parameter values, caution is warranted when results will be used to inform policy and management decisions.

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

Currently schistosomiasis transmission has been suppressed to low levels in many historically endemic areas of China by widespread use of praziquantel in human and bovine populations and application of niclosamide for snail control. However, re-emergent transmission has signalled the need for sustainable interventions beyond these repeated chemical interventions. To take advantage of ongoing investment in rural infrastructure, an index of schistosomiasis transmission potential is needed to identify villages where environmental modifications would be particularly effective. Based on a retrospective analysis of data from 10 villages in Sichuan Province, an index linked to the basic reproductive number is shown to have promise in meeting this need. However, a lack of methods for estimating the spatial components of the proposed metric and for estimating the import of cercariae and miracidia from neighbouring villages leads to significant uncertainty in its estimation. These findings suggest a priority effort to develop methods for measuring the free-swimming forms of the parasite in surface waters. This need is underscored by the high cost and limited sensitivity of current methods for diagnosing human infection and mounting evidence of the inadequacy of snail surveys to identify environments supporting low levels of transmission.

A STUDY OF SCHISTOSOME TRANSMISSION DYNAMICS AND ITS CONTROL

This article concentrates on the study of delay effect on a model of schistosomiasis transmission with control measures such as predation or harvesting and chemotherapy. In the presence of predation or harvesting and chemotherapy, system admits multiple endemic equilibria. Mathematical analysis shows that they are opposite in nature regarding stability. One may observe switching phenomena for the unstable equilibrium by incorporating delay. The disease may be highly endemic if there is no control measure, which is obvious from the model analysis. Results obtained in this paper are also verified through numerical simulations.

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.

Model approaches for estimating the influence of time-varying socio-environmental factors on macroparasite transmission in two endemic regions

The environmental determinants of vector- and host-borne diseases include time-varying components that modify key transmission parameters, resulting in transient couplings between environmental phenomena and transmission processes. While some time-varying drivers are periodic in nature, some are aperiodic, such as those that involve episodic events or complex patterns of human behavior. Understanding these couplings can allow for prediction of periods of peak infection risk, and ultimately presents opportunities for optimizing intervention selection and timing. Schistosome macroparasites of humans exhibit multiple free-living stages as well as intermediate hosts, and are thus model organisms for illustrating the influence of environmental forcing on transmission. Time-varying environmental factors, termed gating functions, for schistosomes include larval response to temperature and rainfall, seasonal water contact patterns and snail population dynamics driven by weather variables. The biological bases for these modifiers are reviewed, and their values are estimated and incorporated into a transmission model that simulates a multi-year period in two schistosomiasis endemic regions. Modeling results combined with a scale dependent correlation analysis indicate the end effect of these site-specific gating functions is to strongly govern worm burden in these communities, in a manner particularly sensitive to the hydrological differences between sites. Two classes of gating functions were identified, those that act in concert to modify human infection (and determine worm acquisition late in the season), and those that act on snail infection (and determine early season worm acquisition). The importance of these factors for control programs and surveillance is discussed.

Modelling environmentally-mediated infectious diseases of humans: transmission dynamics of schistosomiasis in China

Macroparasites of humans are sensitive to a variety of environmental variables, including temperature, rainfall and hydrology, yet current comprehension of these relationships is limited. Given the incomplete mechanistic understanding of environment-disease interactions, mathematical models that describe them have seldom included the effects of time-varying environmental processes on transmission dynamics and where they have been included, simple generic, periodic functions are usually used. Few examples exist where seasonal forcing functions describe the actual processes underlying the environmental drivers of disease dynamics. Transmission of human schistosomes, which involves multiple environmental stages, offers a model for applying our understanding of the environmental determinants of the viability, longevity, infectivity and mobility of these stages to controlling disease in diverse environments. Here, a mathematical model of schistosomiasis transmission is presented which incorporates the effects of environmental variables on transmission. Model dynamics are explored and several key extensions to the model are proposed.

Transmission of Schistosoma japonicum in marshland and hilly regions of China: parasite population genetic and sibship structure

The transmission dynamics of Schistosoma japonicum remain poorly understood, as over forty species of mammals are suspected of serving as reservoir hosts. However, knowledge of the population genetic structure and of the full-sibship structuring of parasites at two larval stages will be useful in defining and tracking the transmission pattern between intermediate and definitive hosts. S. japonicum larvae were therefore collected in three marshland and three hilly villages in Anhui Province of China across three time points: April and September-October 2006, and April 2007, and then genotyped with six microsatellite markers. Results from the population genetic and sibling relationship analyses of the parasites across two larval stages demonstrated that, within the marshland, parasites from cattle showed higher genetic diversity than from other species; whereas within the hilly region, parasites from dogs and humans displayed higher genetic diversity than those from rodents. Both the extent of gene flow and the estimated proportion of full-sib relationships of parasites between two larval stages indicated that the cercariae identified within intermediate hosts in the marshlands mostly came from cattle, whereas in the hilly areas, they were varied between villages, coming primarily from rodents, dogs or humans. Such results suggest a different transmission process within the hilly region from within the marshlands. Moreover, this is the first time that the sibling relationship analysis was applied to the transmission dynamics for S. japonicum.

Schistosoma japonicum involves two obligatory host stages, with asexual reproduction within a molluscan host and sexual reproduction within a mammalian host. Having over 40 species of mammals suspected of being potential reservoirs complicates the transmission patterns. Understanding the complex transmission patterns is further hampered by the ethical and logistical difficulty in sampling adult worms from mammalian hosts. However, the two free-swimming larval stages, cercariae (released from a mollusc and then infective to a mammal) and miracidia (hatched from eggs passed in a mammal's faeces, and then infective to a mollusc), are available, and elucidating the genetic composition of parasites at theses two stages could provide information of infection processes. Here we sampled cercariae during April 2006, miracidia during September-October 2006, and cercariae during April 2007 in three marshland and three hilly villages in Anhui Province of China, and, using microsatellite markers, analyzed the population genetic structure and, for the first time, the familial relationships of parasites at different stages. We found contrasting population structures of parasites, and host species-associated diversities and transmission patterns of parasites between and within two regions. Moreover, we demonstrate that the successful application of sibship analyses to infection process provides an alternative approach to the dissection of transmission dynamics.

Schistosomiasis in the People's Republic of China: the era of the Three Gorges Dam

The potential impact of the Three Gorges Dam (TGD) on schistosomiasis transmission in China has invoked considerable global concern. The TGD will result in changes in the water level and silt deposition downstream, favoring the reproduction of Oncomelania snails. Combined with blockages of the Yangtze River's tributaries, these changes will increase the schistosomiasis transmission season within the marshlands along the middle and lower reaches of the Yangtze River. The changing schistosome transmission dynamics necessitate a comprehensive strategy to control schistosomiasis. This review discusses aspects of the epidemiology and transmission of Schistosoma japonicum in China and considers the pathology, clinical outcomes, diagnosis, treatment, immunobiology, and genetics of schistosomiasis japonica together with an overview of current progress in vaccine development, all of which will have an impact on future control efforts. The use of synchronous praziquantel (PZQ) chemotherapy for humans and domestic animals is only temporarily effective, as schistosome reinfection occurs rapidly. Drug delivery requires a substantial infrastructure to regularly cover all parts of an area of endemicity. This makes chemotherapy expensive and, as compliance is often low, a less than satisfactory control option. There is increasing disquiet about the possibility that PZQ-resistant schistosomes will develop. Consequently, as mathematical modeling predicts, vaccine strategies represent an essential component in the future control of schistosomiasis in China. With the inclusion of focal mollusciciding, improvements in sanitation, and health education into the control scenario, China's target of reducing the level of schistosome infection to less than 1% by 2015 may be achievable.

Parameter estimation and site-specific calibration of disease transmission models

The use of mathematical models for developing management options for controlling infectious diseases at alocal scale requires that the structure and parameters of the model reflect the realities of transmission at that scale. Data available to inform local models are generally sparse and come from diverse sources and in diverse formats. These characteristics of the data and the complex structure of transmission models, result in many different parameter sets which mimic the local behavior of the system to within the resolution of field data, even for a model of fixed structure. A Bayesian approach is described, at both a practical and a theoretical level, which involves the assignment of prior parameter distributions and the definition of a semi-quantitative goodness of fit criteria which are essentially priors on the observable outputs. Monte Carlo simulations are used to generate samples from the posterior parameter space. This space is generally much more constrained than the prior space, but with a highly complex multivariate structure induced by the mathematical model. In applying the approach to a model of schistosomiasis transmission in a village in southwestern China, calibration of the model was found to be sensitive to the effective reproductive number, R(eff). This finding has implications both for computation time for the Monte Carlo analysis and for the specification of field data to efficiently calibrate the model for transmission control.

Contrasting reservoirs for Schistosoma japonicum between marshland and hilly regions in Anhui, China--a two-year longitudinal parasitological survey

Schistosoma japonicum remains highly endemic in many counties in China and has recently re-emerged, to a large extent, in previously controlled areas. To test the hypothesis that small rodents and less agriculturally important domestic animals such as dogs and cats may play an important role in the transmission and potential re-emergence of this disease, an annual investigation of S. japonicum among humans, domestic animals and rodents, combined with detailed surveys of the snail intermediate host, was performed across 3 marshland villages and 3 hilly villages in Anhui province of China over 2 consecutive years. The highest infection prevalence and intensity observed across all mammals was in rodents in the hilly region; while in the marshland, bovines were suspected as the main reservoirs. However, relatively high infection prevalence levels were also found in dogs and cats in both regions. Such results may have implications for the current human- and bovine-oriented control policy for this medically and veterinarily important disease, particularly within the hilly regions of mainland China.

Leveraging rural energy investment for parasitic disease control: schistosome ova inactivation and energy co-benefits of anaerobic digesters in rural China

Background

Cooking and heating remain the most energy intensive activities among the world's poor, and thus improved access to clean energies for these tasks has been highlighted as a key requirement of attaining the major objectives of the UN Millennium Development Goals. A move towards clean energy technologies such as biogas systems (which produce methane from human and animal waste) has the potential to provide immediate benefits for the control of neglected tropical diseases. Here, an assessment of the parasitic disease and energy benefits of biogas systems in Sichuan Province, China, is presented, highlighting how the public health sector can leverage the proliferation of rural energy projects for infectious disease control.

Methodology/Findings

First, the effectiveness of biogas systems at inactivating and removing ova of the human parasite Schistosoma japonicum is experimentally evaluated. Second, the impact of biogas infrastructure on energy use and environmental quality as reported by surveyed village populations is assessed, as is the community acceptance of the technology. No viable eggs were recovered in the effluent collected weekly from biogas systems for two months following seeding with infected stool. Less than 1% of ova were recovered viable from a series of nylon bags seeded with ova, a 2-log removal attributable to biochemical inactivation. More than 90% of Ascaris lumbricoides ova (used as a proxy for S. japonicum ova) counted at the influent of two biogas systems were removed in the systems when adjusted for system residence time, an approximate 1-log removal attributable to sedimentation. Combined, these inactivation/removal processes underscore the promise of biogas infrastructure for reducing parasite contamination resulting from nightsoil use. When interviewed an average of 4 years after construction, villagers attributed large changes in fuel usage to the installation of biogas systems. Household coal usage decreased by 68%, wood by 74%, and crop waste by 6%. With reported energy savings valued at roughly 600 CNY per year, 2–3 years were required to recoup the capital costs of biogas systems. In villages without subsidies, no new biogas systems were implemented.

Conclusions

Sustainable strategies that integrate rural energy needs and sanitation offer tremendous promise for long-term control of parasitic diseases, while simultaneously reducing energy costs and improving quality of life. Government policies can enhance the financial viability of such strategies by introducing fiscal incentives for joint sanitation/sustainable energy projects, along with their associated public outreach and education programs.

Modeling the dynamics and control of transmission of Schistosoma japonicum and S. mekongi in Southeast Asia

A mathematical model for transmission of schistosomes is useful to predict effects of various control measures on suppression of these parasites. This review focuses on epidemiological and environmental factors in Schistosoma japonicum and Schistosoma mekongi infections and recent advances in mathematical models of Schistosoma transmission.

The evaluation of control measures against Schistosoma mekongi in Cambodia by a mathematical model

We constructed a mathematical model for the transmission of Schistosoma mekongi in Cambodia. The simulation of the model will be instrumental in planning schistosomiasis control measures. The model includes two definitive hosts, humans and dogs, as animal reservoirs. Dogs are recognized to play an important role in schistosomiasis transmission in Cambodia. For the purpose of dealing with age-specific prevalence and intensity of infection, the human population was classified into eight age categories in the model. To describe the seasonal fluctuation of the intermediate host population of S. mekongi, the "Post-Spate Survival" hypothesis was adopted for the population dynamics of Neotricula aperta present in the Mekong River. We carried out simulations to evaluate the effect of universal treatment (UT) and targeted mass treatment (TT) with praziquantel on the reduction in prevalence of S. mekongi. The simulations indicated that biyearly UT for 8 years or yearly TT for 5 years after three courses of yearly UT could reduce the prevalence to below 5% when a UT or TT coverage of 85% of inhabitants was achieved. The simulation suggested that the suppression of S. mekongi in Cambodia would be possible by UT or TT with a high coverage rate.

Coupling hydrologic and infectious disease models to explain regional differences in schistosomiasis transmission in southwestern China

Rainfall-runoff models have become essential tools for conceptualizing and predicting the response of hydrologic processes to changing environments, but they have rarely been applied to challenges facing health scientists. Yet with their efficient parameterization and modest data requirements, they hold great promise for epidemiological application. A modeling analysis incorporating simple hydrologic constraints on transmission of the human parasite Schistosoma japonicum in southwestern China was conducted by coupling a lumped parameter rainfall-runoff model (IHACRES) with a delay-differential equation schistosomiasis transmission model modified to account for channel flows and on-field egg inactivation. Model predictions of prevalence and infection timing agree with observations in the region, which indicate that hydrological differences between sites can lead to pronounced differences in transmission. Channel flows are shown to be important in determining infection intensity and timing in modeled village populations. In the periodic absence of flow, overall transmission intensity is reduced among all modeled risk groups. However, the influence of hydrologic variability was greater on the cercarial stage of the parasite than the miracidial stage, due to the parasite ova's ability to survive dormant on fields between rain events. The predictive power gained from including hydrological data in epidemiological models can improve risk assessments for environmentally mediated diseases, under both long-term climate change scenarios and near-term weather fluctuations.

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.

The role of 'passive chemotherapy' plus health education for schistosomiasis control in China during maintenance and consolidation phase

In order to explore the possibility of further optimising schistosomiasis control during the maintenance and consolidation phase in China, two highly endemic villages were selected to compare the strategy of 'passive chemotherapy' plus health education to that of mass chemotherapy singly. Emphasis was placed on treatment coverage with praziquantel among individuals infected with Schistosoma japonicum and costs incurred for treating an infected person. The results show that the former strategy was almost as good as the latter producing treatment coverage rates among egg-positives of 96.2-97.1% during 2 years, while corresponding rates of 100% were achieved in the village where mass chemotherapy was employed. Importantly, the cost of the former strategy was only about half that of mass chemotherapy, i.e. 49.0% in the first year and 54.6% in the following. Moreover, 'passive chemotherapy' together with health education can conveniently be integrated into the primary health care system making it an attractive strategy for schistosomiasis control during the maintenance and consolidation phase.

Modeling the dynamics and control of Schistosoma japonicum transmission on Bohol island, the Philippines

We have investigated a mathematical model for the transmission of Schistosoma japonicum in the infested region of northeastern Bohol island in the Philippines. The development of transmission models is important for planning control strategies. Since S. japonicum has a complicated mode of transmission, the rates of transmission among its hosts cannot be measured directly by field observation. Instead, they have been estimated through model analysis. The model takes into account the seasonal variations and includes a function of control measures. In 1981, a project to eliminate schistosomiasis started on Bohol island. The prevalence decreased dramatically and has kept low level less than 1%. The simulations based on the model predicted that there is little probability of resurgence of an epidemic in the northeastern endemic villages of Bohol island due to the fact that the project has attained a high coverage of selective mass treatment based on stool examination accompanied by a successful snail control operation.