The geography of H5N1 avian influenza in the United States: Human-environment ecosystem drivers of transmission and viral evolution
Goals: This study aims to understand the genetic evolution of avian influenza, particularly a highly pathogenic H5N1 virus lineage over time and identify the ecological factors that drive human infections and viral change. Central to the study is a systematic analysis and characterization of the spatiotemporal distributions of viral genotypes and their genetic divergence from precursor avian influenza viruses. It leverages advanced geospatial modeling, machine learning, and geospatial artificial intelligence (GeoAI) techniques to identify key viral traits, such as transmission potential and virulence, and to elucidate geographic ecosystem factors that influence the spread and evolution of the virus. The study generates a publicly available database that integrates information on avian influenza viruses with associated human-animal-environment ecosystem variables.
Funding: National Science Foundation BCS 2519776 (PI)
Comparative Evolution and Ecology of Swine Influenza Viruses in China and the United States
Goals: This project investigates the evolution and ecology of swine influenza A viruses. It also investigates the unique, common, and synergistic ecological drivers of viral evolution of swine influenza viruses through geospatial modeling and machine learning and develops an influenza risk assessment tool. Influenza A viruses (IAVs) are responsible for substantial human morbidity and mortality and continue to present a substantial public health challenge. In addition to humans, IAVs can infect birds, pigs, horses, dogs, sea mammals, and a number of other animal species. It has been proposed that pigs are intermediate host “mixing vessels” that generate pandemic IAV strains through genetic reassortment among avian, swine, and/or human IAVs. The genesis and emergence of these highly transmissible pandemic viruses is complicated and protracted, requiring multiple reassortment events and mutations across years as seen with the 2009 pandemic H1N1 IAV. All pandemic viruses have also been transmitted back to pigs across continents. They rapidly became panzootic in pigs and have enriched the IAV genetic pool in pigs, enhanced IAV evolution at the human-swine interface, and facilitated emergence of novel enzootic and pandemic IAVs. Since 2009, novel swine IAVs (SIVs) arising from reassortment between the emerging 2009 pandemic H1N1 virus and enzootic SIVs have frequently been detected in swine populations worldwide, most noticeably in China and the US. A number of these novel SIVs (e.g. avian-like H1N1 in China and H3N2v in the US) have caused sporadic spillovers to humans and raised dynamic levels of concerns that another influenza pandemic may occur, causing economic challenges for the industry. Although evolutionary events (i.e., reassortment and mutations) have been readily documented, it is not yet clear which are typical, which are atypical, which evolutionary events for these IAVs increase threats to human and animal health, and which ecological and evolutionary principals are driving such events.
Funding: National Science Foundation DEB-2109745 (CoPI)
Predicting the spread of antimalarial drug resistance using deep learning surrogates
Goals: Malaria remains one of the major global public health challenges and emerging resistance to antimalarials in Africa threaten to increase morbidity and mortality. Currently, a major challenge for disease ecology is understanding and predicting how resistance to interventions emerges and spreads, which is information that national control programs could use to tailor interventions. Here we use deep learning surrogates (DLS) to overcome current limitations in modeling approaches to develop surrogates to predict temporal and spatial emergence and spread of antimalarial resistance.
Funding: National Institutes of Health (NIAID) R01AI190302 (CoI)
Impacts of Environment, Host Genetics and Antigen Diversity on Malaria Vaccine Efficacy
Goals: The major goals of this project are to study the interactions between the leading malaria vaccine (RTS,S) and environmental factors, host genetics, parasite antigen diversity, and other malaria control measures. This multi-site study in Africa is the first major attempt at understanding the impact of spatial ecology on malaria vaccine efficacy and the first generation of molecular data into an ecological vaccine trial analysis.
Funding: National Institutes of Health (NIAID) R01AI137410 (PI)
Importation and transmission of malaria in Zanzibar: a case study for elimination
Goals: The major goal of this project is to conduct a combined genomics and epidemiologic assessment of the factors preventing malaria elimination in Zanzibar, including importation and local transmission. The Zanzibar archipelago is a case study for regions that are close to achieving malaria elimination but have stalled due to their proximity to nearby areas with high transmission. This project will quantify and map malaria importation and residual local transmission on the islands and highlight how human movement drives persistent transmission. The tools developed will help malaria control programs in pre-elimination settings design interventions to traverse “the last mile” to becoming malaria-free.
Funding: National Institutes of Health (NIAID) R01AI155730 (CoI)