Temporal strain structure and response to interventions in a high endemicity region of Plasmodium falciparum

恶性疟原虫高流行区的时间应变结构和对干预措施的反应

• 批准号: 10207415
• 负责人: Karen Patricia Day
• 金额: $ 60.4万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-19 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10207415
• 关键词: Address; Africa South of the Sahara; Age; Antigenic Diversity; Antigens; Area; Blood; Chemoprevention; Clinical; Complex; Computer Models; Data; Data Analyses; Epidemiology; Evolution; Family; Gene Family; Ghana; Immune; Infection; Intervention; Laboratories; Malaria; Modeling; Molecular; Monitor; Multigene Family; Parasites; Pathway Analysis; Plasmodium falciparum; Population; Recombinants; Recording of previous events; Research; Residual state; Sampling; Structure; System; Time; Work; base; effectiveness evaluation; epidemiologic data; global health; indexing; molecular marker; pathogen; population genetic structure; resilience; response; theories; tool; transmission process

Malaria control and elimination in areas of high transmission in sub-Saharan Africa present a significant challenge to global health. A large fraction of the population across all ages in these areas harbor Plasmodium falciparum without clinical manifestations, providing a vast reservoir of infection for transmission. This asymptomatic reservoir is sustained by the enormous antigenic diversity of the parasite. Thus, the challenge for hyperendemic regions requires that the malaria field comes to terms with such diversity, studying it as a complex adaptive system. This study addresses the two-way interaction between epidemiology and P. falciparum diversity from the perspective of the multigene and highly recombinant family known as var, which encodes for the major antigen of the blood stage of infection. This project combines theory with field and laboratory work lo generate new understanding of the diverse transmission reservoir of P. falciparum and its resilience to elimination. The first aim is the longitudinal deep sampling of this reservoir in the Bongo District, Ghana following two control interventions (i.e. indoor residual spraying and seasonal malaria chemoprevention). On the basis of age-stratified serial cross-sectional data, this study will assess how informative the var system is to monitor this reservoir under conditions of the control interventions, compared to traditional malariometric indices and neutral molecular markers. The second aim develops strain theory based on a stochastic agent-based model that tracks the history of infection of each host and the evolutionary change of the parasite. Pathogen population structure over time and responses of the var system to intervention are investigated in ways that inform both molecular data analyses and control efforts. The third aim develops a transmission model of intermediate complexity that can be fitted to routine epidemiological data but still incorporates the major effects of parasite diversity on epidemiology. In particular, the existence of a threshold in transmission intensity that impacts parasite antigenic diversity will be investigated. Contributions include computational models at the interface of epidemiology and evolution, and network analyses of population genetic structure applicable to other multigene families of P. falciparum, as well as to other pathogens whose immune escape relies on highly-recombinant gene families.

在撒哈拉以南非洲的疟疾高传播区控制和消除疟疾对全球卫生构成重大挑战。在这些地区，所有年龄段的人口中有很大一部分人携带没有临床表现的恶性疟原虫，为传播提供了巨大的感染库。这种无症状的宿主是由寄生虫巨大的抗原性多样性维持的。因此，高流行地区面临的挑战要求疟疾领域接受这种多样性，将其作为一个复杂的适应系统进行研究。本研究从多基因和高度重组的VAR家族的角度探讨流行病学和恶性疟原虫多样性之间的双向相互作用。VAR家族编码感染血液阶段的主要抗原。该项目将理论与现场和实验室工作相结合，以期对恶性疟原虫不同传播宿主及其消灭能力有新的认识。第一个目标是在两种控制措施(即室内残留喷洒和季节性疟疾化学预防)之后，对加纳邦戈区的这一水库进行纵向深度抽样。基于年龄分层的连续横断面数据，本研究将评估VAR系统在控制干预条件下与传统的变异性指数和中性分子标记相比在监测该储层方面的信息量有多大。第二个目标是发展基于随机代理模型的菌株理论，该模型跟踪每个宿主的感染历史和寄生虫的进化变化。病原体种群结构随时间的变化和VAR系统对干预的反应被调查，为分子数据分析和控制工作提供信息。第三个目标是开发一个中等复杂性的传播模型，该模型可适用于常规流行病学数据，但仍包含寄生虫多样性对流行病学的主要影响。特别是，将调查影响寄生虫抗原多样性的传播强度阈值的存在。贡献包括流行病学和进化交界处的计算模型，以及适用于其他恶性疟原虫多基因家族以及其免疫逃逸依赖于高度重组基因家族的其他病原体的种群遗传结构的网络分析。