Performing Department
Population Health & Reproduction
Non Technical Summary
The growing niche of pastured pork farms reflects consumer demand for local, sustainable, high-quality, "humanely" raised meat. One of the obvious challenges of raising pigs outdoors is the increased likelihood of domestic swine interfacing with wildlife, including feral pigs, and a corresponding increasing risk of disease transmission between the two populations. Feral pigs are an invasive species in the U.S. and their expanding population creates negative impacts on agriculture crops, ecosystems and native wildlife. Feral pigs also serve as a reservoir for many zoonotic diseases and pathogens that can infect livestock and humans (e.g., Shiga toxin-producing Escherichia coli (STEC), Pseudorabies, Brucella suis, and Hepatitis E virus (HEV)). Despite multiple control efforts, California has one of the highest and widest distributions of feral pigs.. The two parallel trends of an expanding feral pig population and a growing interest in pasture-raised pork creates a possible disease transmission link between existing pathogens harbored in feral pigs and humans. No studies have surveyed HEV prevalence in pasture-raised pig systems or feral swine populations in CA. The overall research objective is to fill a critical information gap regarding the epidemiology of HEV in pasture-raised and feral pigs in California. The results of this project will provide valuable information to researchers, stakeholders and consumers regarding the overall food safety risks associated with this type of pasture-raised pig system. In addition, we will create a multi-disciplinary outreach program to address the public health and food safety concerns in these systems.
Animal Health Component
100%
Research Effort Categories
Basic
(N/A)
Applied
100%
Developmental
0%
Goals / Objectives
The overall research objective is to fill a critical information gap regarding the epidemiology of Hepatitis E virus (HEV) in pasture-raised and feral pigs in California. The specific objectives are: 1) To estimate HEV prevalence in pasture-raised pigs and feral pigs; 2) To identifyrisk factors associated with the interface of pasture-raised pigs and feral pigs; and 3) To develop UC CE-VME outreach capabilities.
Project Methods
A cross-sectional study will be conducted with pasture-raised pig farms located in three regions of Northern California and Central Coast. These areas were selected due to the proximity to the University, recent growth of pasture-raised pig farms in these counties near Bay Area markets, proximity or contact with feral pigs, and participation in an on-going projects. The inclusion criteria include: 1) farm incorporates a pasture-raised pig? system; 2) small to medium-sized farm; 3) farm interfaces with feral pigs; and 4) willingness to participate. A cross-sectional study will be conducted on 15 pasture-raised pig farms (114 individual domestic pigs and 36 individual feral pigs). Within each region, five farms will be identified and a stratified proportional sampling will be conducted (6, 12, or 19 individual samples per farm, depending on the total animals: 25, 50 or 350 pigs). Two approaches will be conducted in order to collect feral pig samples in the surrounding areas of the enrolled farms. 1) fecal samples obtained by hunters or landowner depredation and 2) samples collected by USDA APHIS WS during their statewide comprehensive feral swine surveillance effort will be shared with this project. A sampling kit will be sent to farmers, hunters and landowners. All samples will be processed for viral RNA detection using real-time reverse transcriptase PCR for HEV in the DiCaprio laboratory using standard methods. A questionnaire will include the following topics: 1) demographics, 2) management practices, 3) animal health and disease prevention, 4) biosecurity, and 5) environmental factors. The prevalence (overall and as stratified prevalence by sampling period, farm type and county) will be estimated using Bayesian methods. The association between potential risk factors and HEV prevalence will be calculated using generalized linear mixed models.