A Cumulative Training Approach to Schistosomiasis Vector Density Prediction

Part 1: Medical Artificial Intelligence Modeling (MAIM)International audienceThe purpose of this paper is to propose a framework of building classification models to deal with the problem in predicting Schistosomiasis vector density. We aim to resolve this problem using remotely sensed satellite image extraction of environment feature values, in conjunction with data mining and machine learning approaches. In this paper we assert that there exists an intrinsic link between the density and distribution of the Schistosomiasis disease vector and the rate of infection of the disease in any given community; it is this link that the paper is focused to investigate. Using machine learning techniques, we want to accumulate the most significant amount of data possible to help with training the machine to classify snail density (SD) levels. We propose to use a novel cumulative training approach (CTA) as a way of increasing the accuracy when building our classification and prediction model

Incremental Transductive Learning Approaches to Schistosomiasis Vector Classification

The key issues pertaining to collection of epidemic disease data for our analysis purposes are that it is a labour intensive, time consuming and expensive process resulting in availability of sparse sample data which we use to develop prediction models. To address this sparse data issue, we present novel Incremental Transductive methods to circumvent the data collection process by applying previously acquired data to provide consistent, confidence-based labelling alternatives to field survey research. We investigated various reasoning approaches for semisupervised machine learning including Bayesian models for labelling data. The results show that using the proposed methods, we can label instances of data with a class of vector density at a high level of confidence. By applying the Liberal and Strict Training Approaches, we provide a labelling and classification alternative to standalone algorithms. The methods in this paper are components in the process of reducing the proliferation of the Schistosomiasis disease and its effects.Comment: 8 pages, 5 figures, Dragon 4 Symposiu

A Research Agenda for Helminth Diseases of Humans: Modelling for Control and Elimination

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

PLoS Negl Trop Dis

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

Potential impact of climate change and water resources development on the epidemiology of schistosomiasis in China

Schistosomiasis japonica, caused by the blood fluke Schistosoma japonicum, has been endemic in China since ancient times. An estimated 11 million people were infected in the mid-1950s. Recognizing the huge public health significance and the economic impact of the disease, the central government of China implemented a large-scale control programme, which has been sustained and constantly adapted over the past half century. Today, the endemic areas are mainly confined to the lake and marshland regions along the Yangtze River in five provinces, namely Jiangsu, Anhui, Jiangxi, Hunan and Hubei. It is estimated that currently about 800,000 people are infected and that 40 million people are at risk of infection. Historically, the northern geographical limit where schistosomiasis transmission occurred was around the 33°15’ N latitude (e.g. in Baoying county, Jiangsu province), governed by low temperature thresholds. Based on various climate models, the Intergovernmental Panel of Climate Change (IPCC) recently concluded that the Earth has warmed by approximately 0.6°C over the past 100 years. This unusual warming has been particularly pronounced during the last three decades. There is growing consensus that the global trend of climate warming will continue in the 21st century. It has been suggested that climate change could impact on the distribution of the intermediate host snail of S. japonicum, i.e. Oncomelania hupensis. The frequency and transmission dynamics of schistosomiasis can also be affected by waterresource development and management. Among others, the South-to-North Water Transfer (SNWT) project” is currently under construction in China, which intends to divert water from South (the snail-infested Yangtze River) to North (Beijing and Tianjing) via the lakes of Gaoyou, Hongze and others. The implementation and operation of this project could further amplify the negative effects of climate change and facilitate the northward spread of O. hupensis. The main objective of this PhD thesis was to explore the potential impact of climate change and the SNWT project on the future distribution of schistosomiasis japonica, particularly in eastern China. The techniques used were geographic information system (GIS) and remote sensing (RS), coupled with Bayesian spatial statistics, which have become key tools for disease mapping and prediction. First, we reviewed the application of GIS/RS techniques for the epidemiology and control of schistosomiasis in China. The applications included mapping prevalence and intensity data of S. japonicum at a large scale, and identifying and predicting suitable habitats for O. hupensis at a small scale. Other prominent applications were the prediction of infection risk due to ecological transformations, particularly those induced by floods and water-resource development projects, and the potential impact of climate change. We discussed the limitations of the previous work, and outlined potential new applications of GIS/RS techniques, namely quantitative GIS, WebGIS and the utilization of emerging satellite-derived data, as they hold promise to further enhance infection risk mapping and disease prediction. We also stressed current research needs to overcome some of the remaining challenges of GIS/RS applications for schistosomiasis, so that further and sustained progress can be made towards the ultimate goal to eliminate the disease from China. Second, recognizing the advantages of combining GIS/RS techniques with advanced spatial statistical approaches, we developed Bayesian spatio-temporal models to analyze the relationship between key climatic factors and the risk of schistosomiasis infection. We used parasitological data collected annually from 1990 to 1998 by means of cross-sectional surveys carried out in 47 counties of Jiangsu province. Climatic factors, namely land surface temperature (LST) and normalized difference vegetation index (NDVI), were obtained from satellite sensors. Our analysis suggested a negative association between NDVI and the risk of S. japonicum infection, whereas an increase in LST contributed to a significant increase in S. japonicum infection prevalence. Third, in order to better understand the changes in the frequency and transmission dynamics of schistosomiasis in a warmer future China, a series of laboratory experiments were conducted to assess the effect of temperature on the parasite-intermediate host snail interaction. We found a positive linear relationship between the development of. S. japonicum larvae harboured in O. hupensis and temperature. In snails kept at 15.3°C, S. japonicum larvae tend to halt their development, while peak development occurs at 30°C. The temperature at which half of the snails were in hibernation is 6.4°C. A statistically significant positive association was observed between temperature and oxygen intake of O. hupensis at temperatures below 13.0°C. We also detected a logistic relationship between snails’ oxygen intake and their hibernation rate. Our results underscored the important role temperature plays both for the activity of O. hupensis and the development of S. japonicum larvae harboured in the intermediate host snail. Fourth, to substantiate the claim that global warming might alter the frequency and transmission dynamics of S. japonicum in China, we conducted a time-series analysis from 1972-2002, using temperature data from 39 counties of Jiangsu province. Using annual growing degree days (AGDDs) with a temperature threshold of 15.3°C, we forecasted changes in S. japonicum transmission. The final model included a temporal and a spatial component. The temporal trend consisted of second order polynomials in time plus a seasonality component, while the spatial trend was formed by second order polynomials of the coordinates plus the thin plate smoothing splines. The AGDDs of S. japonicum in 2003 and 2006 and their difference were calculated. The temperatures at the 39 locations showed an increasing temporal trend and seasonality with periodicities of 12, 6 and 3 months. The predicted AGDDs increased gradually from north to south in both 2003 and 2006. The increase in AGDD was particularly pronounced in the southern part of the study area. Our results suggest that alterations in the transmission intensity of S. japonicum in south Jiangsu will be more pronounced than in the northern part of the province. Fifth, we further assessed the potential impact of climate change on the distribution of O.hupensis via a spatially-explicit analytical approach. We employed two 30-year composite datasets comprising average monthly temperatures collected at 623 meteorological stations throughout China, spanning the periods 1961-1990 and 1971-2000. Temperature changes were assessed spatially between the 1960s and the 1990s for January, as this is the critical month for survival of O. hupensis. Our results show that the mean January temperatures increased at 590 stations (94.7%), and that China’s average January temperature in the 1990s was 0.96°C higher than 30 years earlier. The historical 0-1°C January isotherm, which has been considered the approximate northern limit of S. japonicum transmission, has shifted from 33°15’ N to 33°41’ N, expanding the potential transmission area by 41,335 km2. This translates to an estimated additional 21 million people at risk of schistosomiasis. Two lakes that form part of the SNWT project are located in this new potential transmission area, namely Hongze and Baima. Finally, we applied GIS/RS techniques to predict potentially new snail habitats around the lakes of Hongze and Baima, as well as Gaoyou lake, which is considered as a habitat where O. hupensis could re-emerge. A model based on flooding areas, NDVI and a wetness index extracted from Landsat images was developed to predict the snail habitats at a small scale. A total of 163.6 km2 of potential O. hupensis habitats were predicted around the three study lakes. In conclusion, our work suggests that global warming and a major water-resource development project could impact on the distribution of S. japonicum and its intermediate host snail in China and demonstrates that the combination of GIS, RS and Bayesian spatial statistical methods is a powerful approach in estimating their extent. The predictions can serve as a basis for health policy makers and disease control managers, and can be of use in the establishment and running of schistosomiasis surveillance systems. It is further suggested that an efficient early warning system should be set up in potential new endemic areas to monitor subtle changes in snail habitats due to climate change and major ecological transformations, and to assure the early detection of emerging and re-emerging schistosomiasis

A Research Agenda for Helminth Diseases of Humans: Towards Control and Elimination

Human helminthiases are of considerable public health importance in sub-Saharan Africa, Asia, and Latin America. The acknowledgement of the disease burden due to helminth infections, the availability of donated or affordable drugs that are mostly safe and moderately efficacious, and the implementation of viable mass drug administration (MDA) interventions have prompted the establishment of various large-scale control and elimination programmes. These programmes have benefited from improved epidemiological mapping of the infections, better understanding of the scope and limitations of currently available diagnostics and of the relationship between infection and morbidity, feasibility of community-directed or school-based interventions, and advances in the design of monitoring and evaluation (M&E) protocols. Considerable success has been achieved in reducing morbidity or suppressing transmission in a number of settings, whilst challenges remain in many others. Some of the obstacles include the lack of diagnostic tools appropriate to the changing requirements of ongoing interventions and elimination settings; the reliance on a handful of drugs about which not enough is known regarding modes of action, modes of resistance, and optimal dosage singly or in combination; the difficulties in sustaining adequate coverage and compliance in prolonged and/or integrated programmes; an incomplete understanding of the social, behavioural, and environmental determinants of infection; and last, but not least, very little investment in research and development (R&D). The Disease Reference Group on Helminth Infections (DRG4), established in 2009 by the Special Programme for Research and Training in Tropical Diseases (TDR), was given the mandate to undertake a comprehensive review of recent advances in helminthiases research, identify research gaps, and rank priorities for an R&D agenda for the control and elimination of these infections. This review presents the processes undertaken to identify and rank ten top research priorities; discusses the implications of realising these priorities in terms of their potential for improving global health and achieving the Millennium Development Goals (MDGs); outlines salient research funding needs; and introduces the series of reviews that follow in this PLoS Neglected Tropical Diseases collection, “A Research Agenda for Helminth Diseases of Humans.

Schistosomiasis control in China : strategy of control and rapid assessment of schistosomiasis risk by remote sensing (RS)and geographic information system (GIS)

Human schistosomiasis remains one of the most prevalent parasitic infections in the tropics and subtropics. The disease currently is endemic in 76 countries and territories and continues to be a major public health concern, especially in the developing world. It is estimated that 650 million people are at risk of infection. Among the 200 million people actually infected, 120 million are symptomatic and 20 million suffer severe disease. Although morbidity control – in line with recommendations put forth by the World Health Organization – has been carried out in China for more than 20 years, it is estimated that 90 million people still live in areas where they are at risk of infection, and 820,000 people are infected with the parasite, i.e. Schistosoma japonicum. The estimated area of intermediate host snail habitats comprise 3,436 km2, concentrated in the 5 lake regions along the Yangtze River that include the provinces of Anhui, Jiangsu, Jiangxi, Hubei and Hunan. The marshlands of the Poyang Lake region represent some of the strongholds for the transmission of S. japonicum. In these settings, for example, the percentages of acute cases and intermediate host snail habitats represent 79.5% and 96.4%, respectively. With the World Bank Loan Project (WBLP) to control schistosomiasis in China, the overall prevalence of S. japonicum was significantly reduced, but in highly endemic areas the re-infection rates are high. In the first part of the present thesis, I summarize the 50-year history of China’s experience and expertise in schistosomiasis control. Particular emphasis is placed on morbidity control and achievements made by the WBLP carried out between 1992 and 2001. Reviewing this body of literature reveals that morbidity control of schistosomiasis in China has been successful, and hence this strategy will continue to form the backbone of protecting people’s health. However, total expenditures have been considerable, and with the termination of the WBLP there is concern that schistosomiasis might re-emerge. In the second part of this thesis, I describe the successful development of a novel compound model to identify the habitats of Oncomelania hupensis, the intermediate host snail of S. japonicum, and hence the identification of high-risk areas of disease transmission. There are three findings that warrant particular notion. First, visual land use classification on multi-temporal Landsat images was performed for preliminary prediction of O. hupensis habitats. Second, extraction of the normalized difference vegetation index and the tasseled cap transformation greenness index were used for improved snail habitat prediction. Third, buffer zones with distances of 600 and 1,200 m were made around the predicted snail habitats to differentiate between high (>15%), moderate (3-15%) and low risk of S. japonicum infection prevalence (< 3%). Preliminary validation of the compound model against ground-based snail surveys in the Poyang Lake region revealed that the model had an excellent predictive ability. The model therefore holds promise for rapid and inexpensive identification of high-risk areas, and can guide subsequent control interventions, such as whether mass or selective chemotherapy should be employed. The model can also be used for diseases surveillance in general and the monitoring of ecological transformations on the transmission dynamics of S. japonicum, for example in the Three Gorges Dam area

Mapping and modeling of neglected tropical diseases in Brazil and Bolivia

Accurately defining disease distributions and calculating disease risk is an important step in the control and prevention of diseases. This study used geographical information systems and remote sensing technologies within the MaxEnt ecological niche modeling program to create predictive risk maps for leprosy and Schistosomiasis in Brazil and Chagas disease in both Brazil and Bolivia. New disease cases were compiled for leprosy, Schistosomiasis, and Chagas disease from the Brazilian ministry of Health for 2001 to 2009 and the data was stratified to a 10,000 population for each municipality. Bolivian Chagas prevalence rates were calculated from 2007 to 2009 survey data. Environmental data was compiled from MODIS satellite imagery, and WorldClim data for both countries. Socioeconomic data was compiled from the Brazilian IBGE and the Bolivian INE. Leprosy results showed that areas of lower moisture and specific temperature ranges were related to areas of high leprosy case detection especially in the central western, north eastern and northern regions of the country. The states of Bahia and Minas Gerais continue to show the highest levels of new Schistosomiasis cases and also were predicted to have some of the highest risks for the disease in our study. This study confirmed the importance of sanitation and educational level in relation to Schistosomiasis, which has been previously established in other studies. Chagas disease models identified altitude as being important, as well as lower levels of precipitation, and higher ranges of temperature which correspond to the biological requirements of the insect vectors. Information for housing materials was only found for Bolivia, but demonstrated the importance of improved housing materials. Adobe wall materials were found to be highly related to the disease while areas with hardwood floors demonstrated a direct negative correlation. These studies demonstrated that MaxEnt can be successfully adapted to disease prevalence and incidence studies and provides governmental agencies with an easily understandable method to define disease risk area for use in resource planning, targeting, and implementation. This study emphasizes the need for more refined socioeconomic data to create better socioeconomic and smaller regional study areas to better elucidate region specific disease characteristics