Mapping malaria incidence using health facility surveillance data in Uganda

项目总结 在撒哈拉以南非洲，疟疾是发病率和死亡率的主要原因，估计有2亿人。 2017年病例和死亡人数为40.5万人。有效监测疟疾病例是追踪疾病的关键 负担，允许有针对性的干预措施，并评估控制努力的效果。当前的方法是 疟疾监测是通过卫生管理信息系统进行的，该系统依赖于 准确诊断和报告病例。不幸的是，这两种行为都没有始终如一地经常执行 影响这些数据的质量。此外，即使存在高质量的HMI数据， 对疟疾发病率的准确分母进行量化是不明确的，因为集水区 各地的卫生设施没有明确界定。在没有衡量疟疾发病率的情况下，随着时间的推移， 传播地区无法准确衡量疟疾发病率，因此无法有效地 以高危人群为目标，跟踪实现目标的进展。 这项提案的目标是利用高质量的卫生设施监测数据来产生高 乌干达疟疾发病率随时间变化的分辨率、准确的风险图，乌干达是世界第五大疟疾国家 全球疟疾负担。自2006年以来，已在34个哨点收集了高质量的个人级别患者数据 乌干达各地的卫生设施，作为乌干达疟疾监测项目的一部分，拥有近100%的实验室 对所有疑似患有疟疾的人进行检测，并提供有关患者地理居住地的信息。这个 研究将确定卫生设施周围的集水区，以产生发病率的人口分母 这些哨点周围的比率(目标1)，并确定环境、人口统计和干预预测因素 随着时间的推移，34个地点周围的疟疾发病率(目标2)。这些信息将被用来建立一个统计 在乌干达所有60,791个村庄预测发病率并生成疟疾风险月度地图的模型 (目标3)。拟议的工作将提供关于乌干达疟疾负担的宝贵见解，使 对近期控制措施的长期评估，包括大量经杀虫剂处理的蚊子的分布 蚊帐和室内滞留喷洒杀虫剂。从这项研究中获得的知识将直接推动 NIAID的使命是减少疟疾发病率和死亡率，最终目标是根除疟疾。这个 拟议的培训，在一个优秀的指导团队的指导下，将加强申请者的流行病学和 她未来职业生涯所需的统计方法、研究能力和内容专业知识 独立的学术研究员。特别是，申请者将获得必要的地理空间分析技能， 传染病流行病学方法，以及传播研究结果，以提高科学知识 和公共卫生实践。

PROJECT SUMMARY In sub-Saharan Africa, malaria is a major cause of morbidity and mortality with an estimated 200 million cases and 405,000 deaths in 2017. Effective surveillance of malaria cases is essential for tracking disease burden, allowing for targeted interventions, and evaluating the effect of control efforts. The current method for conducting malaria surveillance is through the health management information system (HMIS), which relies on accurate diagnosis and reporting of cases. Unfortunately, neither are performed consistently, often compromising the quality of these data. Furthermore, even in the presence of high quality HMIS data, quantifying an accurate denominator for malaria incidence rates is ambiguous because catchment areas around health facilities are not well defined. Without measures of malaria incidence over time, high transmission regions cannot accurately measure malaria morbidity and therefore are unable to effectively target high risk groups and track progress toward goals. The goal of this proposal is to leverage quality health facility surveillance data to generate high resolution, accurate risk maps of malaria incidence over time in Uganda, the country with the fifth largest malaria burden globally. Since 2006, high quality individual-level patient data has been collected in 34 sentinel health facilities across Uganda as part of the Uganda Malaria Surveillance Project, with nearly 100% laboratory testing of all individuals suspected of having malaria and information on patient geographic residence. The study will define catchment areas around health facilities to generate a population denominator for incidence rates around these sentinel sites (Aim 1) and identify environmental, demographic, and intervention predictors of malaria incidence around the 34 sites over time (Aim 2). This information will be used to build a statistical model to predict incidence and generate monthly maps of malaria risk in all 60,791 villages across Uganda (Aim 3). The proposed work will provide valuable insights on the burden of malaria in Uganda, allowing for long-term evaluation of recent control interventions including mass distributions of insecticide-treated mosquito nets and indoor residual spraying of insecticides. Knowledge gained from this research will directly advance the NIAID’s mission of reducing malaria morbidity and mortality with the ultimate goal of eradication. The proposed training, guided by an excellent mentorship team, will enhance the applicant’s epidemiologic and statistical methods, research competency, and content expertise needed for her career as a future independent academic researcher. In particular, the applicant will gain necessary skills in geospatial analyses, infectious disease epidemiologic methods, and communication of findings to improve both scientific knowledge and public health practice.