Multi-strain dynamics of PRRS virus
This study focuses on the transmission dynamics of genetically diverse pathogens, particularly in the context of limited cross-immunity, immune-mediated selection, and host population structure. For genetically diverse pathogens, ecological interactions between different genetic lineages can occur if infection by one lineage confers partial cross-immunity to a related lineage, thus creating the potential for immune-mediated competition amongst co-circulating lineages. Partial cross-immunity is thought to be a factor that helps explain epidemiological patterns such as cyclic fluctuations in the frequency of different viral lineages through time as well as immune-mediated selection and emergence of new genetic variants. In addition, host population structure can generate spatial variation in herd immunity that could influence the invasion success and geographic spread of new variants. Given the rich data available in livestock host-pathogen systems, this project provides new insight into multi-lineage ecological theory. Using a highly diverse virus, porcine reproductive and respiratory syndrome virus (PRRSV), which is hyperendemic in pig populations in the U.S., we investigate how continual viral evolution and variable cross-immunity among genetic variants drives co-circulation of different viral lineages, and in turn shapes disease distributions across host metapopulations. Our overarching goal is to determine how evolutionary dynamics, landscape of variable cross-immunity, and connectivity of the host population determines the distribution, co-circulation, and maintenance of genetic diversity of PRRSV lineages.
This study aims to understand how PRRSv evolves, adapts to overcome host immunity, spreads and persists within farms and across the U.S. swine industry. Using a combination of experimental and field-based approaches, we are investigating how continual viral evolution and variable cross-immunity among genetic variants drive the co-circulation of different viral lineages, and in turn shapes the emergence and success of new variants of PRRSv. Ultimately, this work will shed light on the causes and consequences of PRRSv evolution, and the implications of its expanding genetic diversity for disease transmission and control.
Forecasting the spread of endemic viruses of swine in the United States
Despite our growing understanding of the epidemiology of endemic viral diseases of swine, such as PRRSv and PEDv, a gap remains between the science and the ability of producers to be able to effectively estimate and respond to spatial and temporal variation in risk. This gap exists partly because risk factors are complex and constantly changing, which makes it challenging for a producer to accurately assess risk. In this project, we develop machine learning models that predict whether a sow farm will become infected given a number of dynamic risk factors. Through this platform, two-week-in-advance forecasts on which sow farms are most at risk of PEDV outbreaks are delivered each week to participating production systems (representing ~10% of the U.S. swine industry), allowing time to mitigate risk or minimize the impact. Ultimately, the near real-time forecasts will provide tools fordata-informed actions by producers and practitioners to control outbreaks.
Foot-and-mouth disease virus transmission in endemic settings
Foot-and-mouth disease (FMD) is a high-priority transboundary disease that severely impairs animal health and livestock production in many regions of the world, including much of Asia and Africa. Various completed and ongoing focus on the epidemiology of FMD, including viral characterization, phylogenetics and transmission dynamics, that will ultimately help to prevent and control FMD in endemic countries, and improve FMD-preparedness in USA.