Harnessing publicly available geospatial data to guide vector-borne disease interventions in sub-Saharan Africa

利用公开的地理空间数据指导撒哈拉以南非洲地区媒介传播疾病的干预措施

• 批准号: 2665178
• 金额: --
• 依托单位: Liverpool School of Tropical Medicine
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2665178
• 关键词: Harnessing; publicly; available; geospatial; data

Climate and environmental factors are key drivers to the spatial and temporal distributions of vector-borne diseases affecting sub-Saharan Africa. For example, malaria hotspots are frequently located in rural areas which contain habitat favoured by the Anopheles mosquito vector. It is therefore possible to leverage the relationship between climate, environment and disease transmission risk to identify areas with the greatest need for control interventions and subsequently target resources more effectively.We now live in a world where vast amount of information on climate and environment is being continuously collected by remote sensing methods e.g. satellites at ever higher spatial and temporal resolutions and increasingly being made publicly available. National control programmes are also improving their data collection and reporting systems. For example, many countries now routinely collect health information e.g. number of confirmed malaria cases using digital health management information systems. While large-scale static maps of continent-level risk are increasingly commonplace, using methods such as geostatistical modelling or species distribution modelling to estimate disease burden and highlight areas of high transmission risk, the vast amount of public health information contained in these data sources has yet to be fully harnessed with respect to guiding national control programme activities. The aim of this project is to develop methods by which spatially and temporally tailored outputs of disease risk can be generated and utilised to optimise vector-borne disease control activities. The project will focus on malaria and NTD transmission in sub-Saharan Africa, and will make use of freely available resources such as Google Earth Engine and R Shiny to access data, analyse and present resulting outputs.

气候和环境因素是影响撒哈拉以南非洲的媒介传播疾病的空间和时间分布的关键驱动因素。例如，疟疾热点地区通常位于农村地区，那里是按蚊媒介的栖息地。因此，可以利用气候、环境和疾病传播风险之间的关系来确定最需要控制干预的区域，并随后更有效地瞄准资源。我们现在生活在一个通过遥感方法（例如遥感方法）不断收集大量气候和环境信息的世界。卫星的空间和时间分辨率越来越高，并且越来越多地向公众开放。国家控制计划也在改进其数据收集和报告系统。例如，许多国家现在定期收集健康信息，例如使用数字健康管理信息系统确诊的疟疾病例数量。虽然大陆级风险的大规模静态地图越来越普遍，使用地统计模型或物种分布模型等方法来估计疾病负担并突出高传播风险区域，但这些数据源中包含的大量公共卫生信息尚未充分利用来指导国家控制计划活动。该项目的目的是开发方法，通过这些方法可以生成并利用空间和时间定制的疾病风险输出来优化媒介传播疾病控制活动。该项目将重点关注撒哈拉以南非洲地区的疟疾和被忽视的热带病传播，并将利用 Google Earth Engine 和 R Shiny 等免费资源来访问数据、分析和呈现结果。