mework for Optimising Control at the Local Level: Coordinated strategies for Neglected Tropical Diseases and Malaria (FOCAL-NTD)

优化地方一级控制的mework：被忽视的热带病和疟疾的协调策略（FOCAL-NTD）

• 批准号: MR/M014975/2
• 负责人: Michelle Stanton
• 金额: $ 12.98万
• 依托单位: Lancaster University
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FM014975%2F2
• 关键词: mework; Optimising; Control; Local; Level

Disease control programmes require knowledge of the geographical distribution of the target disease in order to establish where control interventions are most needed. In instances where the disease risk is approximately constant across a geographical area (i.e. spatially homogeneous), programmes are able to evenly distribute interventions amongst the population. However, disease risk can often be very variable (i.e. spatially heterogeneous), particularly in the case of parasitic diseases in which the relationship between the parasite and the human host is dependent on the surrounding environment. In these instances a 'blanket' intervention approach isn't sufficient to eliminate a disease from an area, as resources are wasted in areas where there is no disease risk, and are not adequately focused to completely remove disease 'hotspots'. The aim of this project is to develop a framework that enables disease control efforts to be targeted more effectively. In addition to considering individual diseases, the framework will encourage coordination between control programmes in areas where multiple diseases are co-endemic, thus accelerating these programmes simultaneously towards their control/elimination goals. This project will focus on three neglected tropical diseases (NTDs) and coinfections with malaria in order to demonstrate the flexibility of the framework being developed. These NTDs are Human African Trypanosomiasis (HAT, transmitted by tsetse flies) schistosomiasis (transmitted in freshwater by an intermediate host snail) and lymphatic filariasis (LF, transmitted by mosquitoes). Local level risk maps for each of these diseases will be produced using data provided by project collaborators from endemic countries, including Malawi and Uganda. These maps will combine disease/vector/intermediate host information with information on the risk factors of the diseases in question. Geographically referenced risk factors could include those that influence the presence and/or density of the disease's vector/intermediate host, or influence how likely a person is to come into contact with the vector/intermediate host. Using the example of schistosomiasis, this may include factors such as the distance of the village to the nearest freshwater source, factors influencing the intermediate host/parasite ability to survive and breed (e.g. altitude, temperature, vegetation) and information on control activities have been implemented in the area. Traditional methods of collecting local level disease risk data use survey teams to collect information, with surveys often being expensive, time-consuming and logistically difficult to undertake in rural areas of developing countries. In addition to developing risk maps based on previously collected information, alternative methods for obtaining local level disease-related data will be explored. Two approaches will be considered. Firstly, more efficient spatial sampling methods for determining which sites should be surveyed will be developed. These methods will be 'flexible' in the sense that the selection of sites to sample will be done iteratively, and will be selected strategically in order to reduce the uncertainty in the estimated geographical distribution of disease risk in the study area. The second approach focuses on using community members to collect disease-related information, as opposed to a dedicated survey team. Community members are becoming increasingly involved in disease control activities in developing countries, and this has been shown to improve intervention coverage and acceptability. This project will explore ways in which community members can more directly contribute to disease control activities through the development of mobile phone-based surveillance and reporting tools. Community members in Malawi and Uganda will be trained to report information such as preventive therapy coverage (for schistosomiasis and LF) and vector control (malaria and HAT) respectively.

疾病控制方案需要了解目标疾病的地理分布情况，以便确定哪些地方最需要控制干预措施。在疾病风险在一个地理区域内大致恒定（即空间上均匀）的情况下，方案能够在人口中平均分配干预措施。然而，疾病风险往往变化很大（即空间异质性），特别是在寄生虫病的情况下，寄生虫和人类宿主之间的关系取决于周围环境。在这些情况下，“全面”干预方法不足以从一个地区消除疾病，因为资源浪费在没有疾病风险的地区，并且没有充分集中于完全消除疾病“热点”。该项目的目的是制定一个框架，使疾病控制工作能够更有效地针对目标。除了考虑个别疾病外，该框架还将鼓励在多种疾病共同流行的地区协调控制方案，从而加快这些方案同时实现控制/消除目标。该项目将侧重于三种被忽视的热带疾病和疟疾合并感染，以展示正在制定的框架的灵活性。这些NTD是人类非洲锥虫病（HAT，由采采蝇传播）、血吸虫病（由中间宿主蜗牛在淡水中传播）和淋巴丝虫病（LF，由蚊子传播）。将利用包括马拉维和乌干达在内的流行国家的项目合作者提供的数据，绘制每种疾病的地方一级风险图。这些地图将把疾病/病媒/中间宿主的信息与有关疾病的风险因素的信息联合收割机结合起来。地理参照风险因素可包括影响疾病病媒/中间宿主的存在和/或密度，或影响一个人接触病媒/中间宿主的可能性的因素。以血吸虫病为例，这可能包括诸如村庄与最近淡水源的距离、影响中间宿主/寄生虫生存和繁殖能力的因素（例如海拔、温度、植被）以及有关该地区已开展防治活动的信息。收集地方一级疾病风险数据的传统方法是利用调查小组来收集信息，而在发展中国家的农村地区开展调查往往费用昂贵、耗时，而且在后勤方面存在困难。除了根据以前收集的信息绘制风险图外，还将探讨获取地方一级疾病相关数据的替代方法。将考虑两种办法。首先，将制定更有效的空间抽样方法，以确定哪些地点应进行调查。这些方法将是“灵活的”，在这个意义上，选择的网站进行采样将反复进行，并将选择战略，以减少不确定性的估计地理分布的疾病风险在研究领域。第二种方法侧重于利用社区成员收集与疾病有关的信息，而不是专门的调查小组。社区成员越来越多地参与发展中国家的疾病控制活动，这已证明提高了干预措施的覆盖面和可接受性。该项目将探讨社区成员如何通过开发基于移动的电话的监测和报告工具，更直接地为疾病控制活动作出贡献。马拉维和乌干达的社区成员将接受培训，分别报告预防性治疗覆盖率（血吸虫病和LF）和病媒控制（疟疾和HAT）等信息。

项目成果

The development of high resolution maps of tsetse abundance to guide interventions against human African trypanosomiasis in northern Uganda.

• DOI: 10.1186/s13071-018-2922-5
• 发表时间: 2018-06-08
• 期刊: Parasites & vectors
• 影响因子: 3.2
• 作者: Stanton MC;Esterhuizen J;Tirados I;Betts H;Torr SJ
• 通讯作者: Torr SJ

Geostatistical models using remotely-sensed data predict savanna tsetse decline across the interface between protected and unprotected areas in Serengeti, Tanzania.

• DOI: 10.1111/1365-2664.13091
• 发表时间: 2018-07
• 期刊: The Journal of applied ecology
• 作者: Lord JS;Torr SJ;Auty HK;Brock PM;Byamungu M;Hargrove JW;Morrison LJ;Mramba F;Vale GA;Stanton MC
• 通讯作者: Stanton MC

The application of drones for mosquito larval habitat identification in rural environments: a practical approach for malaria control?

无人机在农村环境中识别蚊子幼虫栖息地的应用：控制疟疾的实用方法？

• DOI: 10.1101/2020.08.05.237933
• 发表时间: 2020
• 作者: Stanton M