| Neglected Tropical Diseases (NTDs), defined by World Health Organization,constitute a wide array of chronic disabling diseases that widely distribute indeveloping countries, especially in poor and remote areas. In recent years, manystudies focus on developing innovative strategies for prevention and control of NTDsby considering multiple factors, such as social and biological factors.The project entitled “Innovative Strategies for Sustainable Control of NTDsthrough Socio-Ecosystem-Based Interventions” was initiated by Regional Networkfor Asian Schistosomiasis and Other Helminth Diseases (RNAS+) and fund byInternational Development Research Centre in year2011, with its main objective toestablish a uniform procedure for developing innovative strategies for the sustainablecontrol of NTDs through social-ecosystem-based interventions. This study was a tinybranch of the project and took schistosomiasis in mountainous areas in PeopleRepublic of China (P.R. China) as an example to explore the distribution and riskfactors at different scales. A substantial number of studies of schistosomiasis in lakeand marshland regions had been done. Few researches were reported in mountainousregions. In this study, we collected environmental data (remote sensing data anddigital maps), data of parasitic diseases (prevalence in human and snail) and socialeconomic data (knowledge, attitudes and practice,[KAP] relating to schistosomiasis)to explore the distribution and risk factors of schistososmiasis at different scales. Theentire study is divided into four sections:ChapterⅠ Classification of ecological zones in large-scale regional levelObjective: This part attempts to develop classification method in order toclassify ecological zones at large scale based on multidimensional environmentalfactors. Methods: All IDRC project countries members, i.e. Vietnam, Laos,Thailand, Cambodia, the Philippines and Yunnan, Guangdong and Guangxi provincesof P.R. China were chosen as study area. Land surface temperature (LST) andvegetation index (NDVI) data were extracted from MODIS satellite images from2002.07to2011.07. Multivariate cluster analysis was applied to classify study areasinto different ecological zones. Results: Five ecological zones were detected: A zonedistributed in middle region of Gugangxi Province, north of Vietnam, middle west of Thailand and northwest of Philippines; B zone distributed in Laos, southwest ofCambodia, southwest of Thailand and west of Philippines; C zone distributed in eastof Yunnan Province, middle south of Guangdong Province, middle east of Thailandand southwest of Cambodia; D zone distributed in north of Guangdong and GuangxiProvince, north of Vietnam, northwest of Thailand and west of Philippines; E zonedistributed in west of Yunnan Province, middle of Guangxi Province, northeast ofCambodia, northwest of Thailand and middle west of Philippines. Each zone hasdifferent degree of risk for schistosomiasis. Conclusion: The eco-zone classificationmethod is feasible and it sheds lights in setting up monitoring sites and inter-countrycooperation of neglected tropical diseases (NTDs) control, including schistosomiasis.Chapter Ⅱ Spatial and temporal analysis of Oncomelania hupensis inmountainous endemic regionObjective: To study the spatial characteristics and temporal trends ofOncomelania hupensis in Eryuan County from2005to2012. Methods: The datasetof snail survey from2005-2012(percent of frames with living snail, mean density ofliving snail, mean density of infected snail and infection rate of snail) were collected.The spatial analysis dataset was constituted by matching the survey data with thevector map of Eryuan County. The spatial and local autocorrelation analysis, kerneldensity analysis and "hot spots" analysis were applied to analyze the spatialcharacteristics and temporal trends of snails. Results: Living snail in Eryuan Countymainly distribute in Yonglian, Qieye, Tuanjie and Jiangdeng regions. The area as wellas density values of snail are decreasing gradually from year2007. The infected snaildistributed mainly in Yonglian village from2005to2007. The spatial clustering ofglobal autocorrelation (Moran’s I) was increasing from2007to2012and all Moran’sI values showed statistically significant. The local spatial autocorrelation analysisindicated that the number of villages of High-High type of correlation modelincreased from2in2005to7in2012, which mainly clustered in plateau canyon areas.Further "hot spot" analysis found that living snails gathered in Xinzhuang, Liantie,Yongsheng and Yongle nearby areas. Conclusion: The snail distribution in Eryuanhas global and local spatial autocorrelation. The number of villages of High-Hightype of correlation increased. These findings provide the basis for targetcontrol ofOncomelania hupensis in the future. Chapter Ⅲ Identification of environmental risk factors of snail habitats andprediction in mountainous regionObjective: To explore the risk environmental factors of snail habitats and predictpotential endemic areas in mountainous regions in an efficient and cost-effectivemanner. Methods: Remote sensing data of Land Surface Temperature (LST) andNormalized Difference Vegetation Index (NDVI) as well as Digital Elevation Model(DEM) were downloaded from the Internet. They were applied with snail surveydatasets to develop ecological niche model to predict the potential habitats of O.hupensis in study area. Results: Among all communities with snail infested,96.4%are located in the range of1200meters near river system;79%distribute in the rangeof-0.15℃-4.85℃of night temperature in January;75%are located in the range of0.38-0.7of NDVI;71.4%are located in the range of1950-2491m of elevation;75%are located in the range of1°-20°slope. Above mentioned suitable range ofenvironmental factors are ranked and applied to establish ecological niche model. Itwas proved that the newly built ecological niche model has85%sensitivity and75%specificity. Conclusion: Based on the LST, NDVI, DEM and hydrologicalcharacteristics derived from DEM, ecological niche model can be established topredict potential snail habitats.Chapter Ⅳ Study of social factors of schistosomiasis in individual levelObjective: The study sought to know the social factors of schistosomiasis inindividual level in two subtypes of a mountainous region in Eryuan County, YunnanProvince. This study’s aim is to provide evidence for establishing more specific andeffective control measures for disease interruption in two subtypes of a mountainousregion. Methods: A uniform set of quantitative questionnaires combined within-depth interviews (IDIs) were conducted to investigate knowledge, attitude andpractice of schistosomiasis of residents. All participants were examined forschistosomiasis using both a serological test (indirect hemagglutination assay [IHA])and a stool examination (Kato-Katz). A Chi-square test and binary logistic regressionmodels (forward logistic regression with P-value <0.05as inclusion criteria andP-value>0.1as exclusion criteria) were applied to analyze the relationship betweenthe variables. Results: The infection rate was once the higher in Yongle, but is nowthe highest in Xinzhuang, where there are more risk factors for schistosomiasis, suchas frequently grazing cattle, digging vegetables or cutting grass in the field, as well asraising cattle by free grazing. In both communities, among the respondents aged15years or below, more than one third didn’t know the name, endemic areas, and animalreservoirs of schistosomiasis. Conclusion: In short, Eryuan County’s overallawareness of the cause and preventive measures of schistosomiasis was found to be high. But due to various dominating risk factors, different control strategies should bedesigned keeping in mind the two different subtypes of endemic areas forschistosomiasis in mountainous regions, namely plateau basins and plateau canyons. |
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