Identifying Environmental Factors for Soil Transmitted and Food Borne Helminth Diseases in Border Regions of Northern Thailand
Identifying Environmental Factors for Soil Transmitted and Food Borne Helminth Diseases in Border Regions of Northern Thailand
批准号:
2608636
负责人:
金额:
$0.0万
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2021
资助国家:
英国
项目状态:
已结题
起止时间:
2021 至 --
中文摘要
人类的寄生虫感染(蠕虫硫酶)通过破坏健康和农业生产力,极大地影响了泰国等低收入和中等收入国家。特别是在整个东南亚,城市地区的扩张和公共卫生项目不太发达国家的人口流动增加了疾病的传播。该项目将调查环境对蠕虫病传播的影响。许多新出现的蠕虫硫酶通过增加人与动物之间的接触、强化和整合食品生产系统以及扩大迁徙与环境联系在一起[1]。因此,许多蠕虫疾病的有效控制和治疗将受益于将临床、兽医和农业组成部分更好地整合到环境驱动的研究战略中。泰国被归类为“中等偏上收入”国家。然而,由于蠕虫疾病的性质,流行地点受到柬埔寨、老挝和缅甸等边境国家的严重影响,这些国家都被归类为“最不发达”国家。我们的研究团队最近利用高度敏感的分子诊断技术,在泰国三个边境地区确定了人类感染率的基线。在过去,低估了泰国等社区的蠕虫感染和我们之前在菲律宾的工作[2],为政府政策的制定提供了不完整的信息。拟议的项目将使用已经建立的人类流行数据[3]来关注泰国北部流行地区的特定地点和寄生虫物种,以便确定疾病传播的环境因素。一类寄生虫,土壤传播蠕虫(STH),需要严重的环境污染才能有效地传播疾病。全球约有15亿或四分之一的人口感染STH,包括蛔虫、鞭虫和钩虫等主要物种。在土壤或未清洗的蔬菜中发现的寄生虫卵是主要的感染源。同样,食源性疾病,包括致癌的奥比索氏菌,是通过食用未煮熟的鱼感染的,并与水源以及蜗牛和鱼类宿主之间的相互作用有关。这名学生将在泰国花费相当长的时间,收集土壤、蔬菜和水生样本,以便使用传统显微镜和最近发展起来的分子分析进行诊断。将使用空间模型(地理信息系统地理信息系统)对疾病的环境焦点进行分层,以显示食物和地理在蠕虫疾病传播中的重要性。地球观测数据将用于建立气候和其他相关环境因素的地理信息系统层,并使干预战略能够针对未来可能的变化进行评估。确定疾病传播的环境因素将导致建立预测性模型,以便更好地了解政府控制政策。
英文摘要
Parasitic worm infections (helminthiases) of humans greatly impact low to medium income countries such as Thailand, by undermining health and agricultural productivity. Particularly across Southeast Asia, the expansion of urban areas and the movement of people from countries with less developed public health programs, have increased disease transmission. This project will investigate environmental influences on helminth disease transmission. Many emerging helminthiases are linked to the environment through increased contact between humans and animals, the intensification and integration of food production systems, and the expansion of migration [1]. Therefore, effective control and treatment of many helminth diseases would benefit from better integration of clinical, veterinary and agricultural components embedded in an environmentally-driven research strategy.Thailand is classified as an 'Upper Middle Income' Country. However due the nature of helminth diseases endemic sites are significantly impacted by border countries including Cambodia, Laos and Myanmar, all of which are classified as 'Least Developed' Countries. Our research team has recently established baseline human infection rates in three Thailand border regions, using highly sensitive molecular diagnostics. In the past the under-estimation of helminth infections in communities such as Thailand and our previous work in the Philippines [2], provides incomplete information for the development of government policy.The proposed project will use already established human prevalence data [3] to focus on specific locations and parasite species in endemic regions of Northern Thailand, so that environmental components of disease transmission can be identified. One class of parasites, soil transmitted helminths (STH), requires significant environmental contamination for effective disease transmission. Approximately 1.5 billion or 1/4 of the world's population are infected by STH, including the main species of Ascaris, Trichuris and hookworm. Parasite eggs found in the soil or unwashed vegetables are the primary source of infection. Similarly, food borne diseases, including the cancer-causing Opisthorchis, are contracted by consuming uncooked fish, and are linked to water sources, and the interaction between snail and fish hosts. The student will spend considerable time in Thailand, collecting soil, vegetable and aquatic samples for diagnostics using traditional microscopy and more recently developed molecular analysis. Environmental foci of disease will be stratified using spatial modelling (GIS geographical information system) to demonstrating the importance of food and geography, in helminth disease transmission. Earth observation data will be used to build GIS layers of climatic and other relevant environmental factors, and enable intervention strategies to be assessed against likely future changes. Identification of environmental components of disease transmission will lead to predictive models for better informed government control policies.
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