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

撒哈拉以南非洲高传播地区的疟疾控制和消除对全球健康构成了重大挑战。这些地区各个年龄段的大部分人口都携带恶性疟原虫，但没有临床表现，为传播提供了巨大的感染库。这种无症状储存库是由寄生虫的巨大抗原多样性维持的。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。这项研究从多基因和高度重组家族 var 的角度探讨了流行病学和恶性疟原虫多样性之间的双向相互作用，该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，以便对恶性疟原虫的多样化传播宿主及其消除能力产生新的认识。第一个目标是在采取两项控制干预措施（即室内滞留喷洒和季节性疟疾化学预防）后，对加纳邦戈区的该水库进行纵向深层采样。在按年龄分层的连续横截面数据的基础上，本研究将评估与传统的疟指标和中性分子标记相比，var 系统在控制干预条件下监测该水库的信息量。第二个目标是基于随机代理模型开发应变理论，该模型跟踪每个宿主的感染历史和寄生虫的进化变化。随着时间的推移，病原体种群结构以及 var 系统对干预的反应进行了研究，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种中等复杂性的传播模型，该模型可以适合常规流行病学数据，但仍然包含寄生虫多样性对流行病学的主要影响。特别是，将研究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界面的计算模型，以及适用于恶性疟原虫其他多基因家族以及免疫逃逸依赖于高度重组基因家族的其他病原体的群体遗传结构的网络分析。

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.