Malaria across borders: Measuring imported infections and contributions to local transmission in Uganda and Zimbabwe

跨境疟疾：衡量输入性感染及其对乌干达和津巴布韦当地传播的影响

• 批准号: 10620337
• 负责人: Isabel Rodríguez-Barraquer
• 金额: $ 77.06万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-16 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10620337
• 关键词: Adult; Africa South of the Sahara; Area; Behavioral; Cessation of life; Classification; Clinical Management; Collection; Data; Diagnosis; Epidemiology; Failure; Funding; Genomics; Geographic Locations; Geography; Health care facility; Household; Impact evaluation; Individual; Infection; Infrastructure; International; Interruption; Intervention; Longitudinal Studies; Malaria; Measures; Mozambique; Outcome; Parasites; Pattern; Plasmodium falciparum; Recording of previous events; Reporting; Research; Residual state; Resources; Risk Factors; Role; Sampling; Site; Statistical Models; Surveillance Methods; Surveys; Testing; Travel; Uganda; United States National Institutes of Health; Zimbabwe; analytical method; design; epidemiologic data; genomic data; improved; international center; malaria infection; malaria transmission; predictive modeling; risk mitigation; transmission process; vector control

PROJECT SUMMARY/ABSTRACT Malaria cases and deaths primarily caused by Plasmodium falciparum have declined significantly in sub- Saharan Africa as a result of the broad deployment of vector control and effective clinical management. In low to moderate-transmission settings slated for elimination, imported cases become an increasingly important epidemiological consideration. In these settings, imported cases may a) represent a high but poorly defined proportion of the overall malaria burden, b) result in secondary transmission that can impede local elimination efforts, and c) may require additional or alternative interventions than standard control measures. Imported cases, when currently evaluated at all, are operationally defined as infections acquired outside of a defined geographic area and identified based on travel history. However, lack of capture of asymptomatic infections together with variable quality of travel history collection limit the utility of this standard approach to identifying imported infections and quantifying their role in transmission. Further, there are no routinely collected data that would allow evaluation of the impact of imported cases on local transmission. In this proposal, we will collect detailed travel histories, perform active surveillance for asymptomatic infections, and generate parasite genomic data to more accurately define the role of imported infections in two representative border regions of sub-Saharan Africa (Tororo District, Uganda and Mutasa District, Zimbabwe) that leverage substantial surveillance infrastructure from the NIH-funded International Centers of Excellence for Malaria Research (ICEMR) network and will employ active (via a longitudinal study) and passive (via health facility surveillance) designs to capture asymptomatic and symptomatic infections. We propose the following Specific Aims.1) To quantify and characterize imported malaria infections. We will use a probabilistic approach to classify infections as imported or local via detailed travel and other behavioral survey data and determine the travel patterns and risk factors associated with importation. 2) To determine the impact of importation on local transmission and identify appropriate targeted interventions. We will use parasite genomics and epidemiological data to define local transmission and the impact of imported infections, taking advantage of dense sampling of symptomatic and asymptomatic infections in focused geographies. We will use a robust set of statistical modeling approaches, including Bayesian estimation of transmission networks incorporating all genomic and epidemiologic data. We will use these data to model the predicted impact of various combinations of targeted interventions. The expected outcome of the proposed research is evidence on appropriate surveillance methods for imported malaria infections and on the contribution of these infections to sustaining transmission. By identifying ways to better target interventions, these results will impact national and international malaria control efforts as they strive for elimination and require evidence on how to mitigate the risk of imported malaria infections.

项目总结/摘要 主要由恶性疟原虫引起的疟疾病例和死亡人数在2000年以下显著下降， 由于广泛部署病媒控制和有效的临床管理，撒哈拉非洲的艾滋病毒/艾滋病感染率已下降。在低 到预定消除的中等传播环境，输入性病例变得越来越重要， 流行病学考虑。在这些设置中，导入的病例可能a）代表高但定义不明确的 占疟疾总负担的比例，B）导致二次传播，可能阻碍当地消灭疟疾 努力，以及c）可能需要标准控制措施以外的额外或替代干预措施。进口 在目前进行评估时，病例在操作上被定义为在定义的范围之外获得的感染。 地理区域，并根据旅行历史进行识别。然而，缺乏无症状感染者的捕获 以及旅行历史收集的可变质量限制了这种标准方法的实用性， 输入性感染并量化其在传播中的作用。此外，没有常规收集的数据， 可以评估输入性病例对本地传播的影响。在本提案中，我们将收集 详细的旅行史，对无症状感染者进行积极监测，并产生寄生虫 基因组数据，以更准确地确定输入性感染的作用，在两个有代表性的边境地区， 撒哈拉以南非洲（乌干达托罗罗区和津巴布韦穆塔萨区）， 来自NIH资助的国际疟疾研究卓越中心的监测基础设施 （ICEMR）网络，并将采用主动（通过纵向研究）和被动（通过卫生设施监测） 旨在捕获无症状和有症状的感染者。我们提出以下具体目标：1） 对输入性疟疾感染进行量化和定性。我们将使用概率方法对感染进行分类 通过详细的旅行和其他行为调查数据，确定旅行模式， 与进口有关的风险因素。2)确定输入对本地传播的影响， 确定适当的有针对性的干预措施。我们将使用寄生虫基因组学和流行病学数据来定义 本地传播和输入性感染的影响， 和无症状感染者。我们将使用一套强大的统计模型 方法，包括贝叶斯估计的传输网络纳入所有基因组和 流行病学数据。我们将使用这些数据来模拟各种目标组合的预测影响， 干预措施。拟议研究的预期结果是适当监测的证据 关于输入性疟疾感染的方法以及这些感染对持续传播的作用的报告。 通过确定更好地针对干预措施的方法，这些结果将影响国家和国际疟疾 在努力消除疟疾的过程中，需要采取控制措施，并需要关于如何减轻输入性疟疾风险的证据 感染.