Advancing lymphatic filariasis elimination with parasite genomic epidemiology - Project summary Lymphatic filariasis (LF) is a mosquito-borne infection caused by filarial nematodes, leading to acute fever attacks and long-term disability due to hydrocele, lymphedema, and elephantiasis. The Global Program to Eliminate Lymphatic Filariasis (GPELF) is the largest public health intervention initiative based on mass drug administration (MDA), aiming to interrupt the parasite lifecycle by treating the at-risk population with drugs that clear transmissible first stage larvae (microfilariae, mf) in the human host. Despite years of MDA, LF transmission persists or has resurged in some countries that were deemed to have reached elimination targets, threatening the World Health Organization’s elimination goals. To mitigate this risk, understanding the various causes of infection resurgence is essential, and closing this knowledge gap is our focus. Current measures of infection, which rely on counting mf in blood (since adult filariae are not directly accessible) or detection of circulating filarial antigen, cannot differentiate between recrudescence and reinfection, or determine the origin of transmission. We recently demonstrated that a comprehensive full-genome analysis of individual mf from Wuchereria bancrofti infected individuals enables (a) estimation of the number of reproductively active females, (b) genetically tracking these maternal lineages through treatment, and (c) differentiation between recrudescence and reinfection. This prior advancement facilitates determination of parasite population genetics among hosts and geographies. In this proposal, we will test our overarching hypothesis that by reconstructing sibling relationships in longitudinal mf samples and performing genomic characterization in geospatial mf samples it is possible to monitor the number of reproductively active adult females, differentiate new and established maternal families, and understand the population dynamics in elimination contexts. Analyzing longitudinal samples provides insights into temporal changes in the parasite population (Aim 1), while analyzing geospatial samples identifies transmission sources (Aim 2). Together, these analyses will elucidate the causes of persistent or resurgent infections and enable the generation of evidence- based empirical parameter estimates for transmission modeling (Aim 3) to determine the likelihood and pace of resurgence, supporting identification of the optimal surveillance strategies. Collectively, the results of our research will link newly generated population genetic information to transmission dynamics modelling to predict the risk that parasite migration and/or resurgence (or poor treatment response) will impede W. bancrofti elimination.
