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Identifying and optimizing prevention and control strategies against the spread of viral pathogens within U.S. feral swine populations
Dr. Lindsey Holmstrom October 20, 2013
Project HSHQDC-10-C-00116
Overview
Review of current knowledge of U.S. feral swine CA Wild Pig Project GPS data Field data collection Data analyses
Conceptual model
Future directions
Sargent (2008) 2
Widespread distribution, populations continue to increase Recent migrations/purposeful introductions in northern states Eurasian boar importation from Canada Population estimates range from 4 to 5 million Economic costs: ~ $1.5 billion/year FAD spread?
SCWDS http://128.192.20.53/nfsms
U.S. Feral Swine Population
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Factors influencing disease spread in feral swine
1. Population distribution and density
2. Social and spatial structure
3. Population dynamics
4. Movements
5. Habitat connectivity
6. Inter-species contact
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Factors influencing disease spread in feral swine
1. Population distribution/density Distributions continue to increase in the US
Natural dispersal from existent populations Release or escape of domestic swine that then become feral Escape from hunting preserves or confinement operations European wild boar importation Purposeful translocation and release by humans for sport hunting
Feral swine are extremely adaptable
Reliable and adequate food and water supply and vegetation cover Densities higher in resource-rich areas Human environment change has made habitat more favorable for feral swine
Difficult (impossible) to eradicate
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Factors influencing disease spread in feral swine
2. Social and spatial structure Form social groups called sounders Consist of two or more sows and their young Majority younger pigs
Adult boars are usually solitary Territorial Interaction during breeding, at common water/food sources
Usually nocturnal, seldom move during the day
Photo courtesy of Fred Parker, 2011 6
Factors influencing disease spread in feral swine
3. Population dynamics Highest reproductive capacity of all large, free-ranging mammals 1-2 litters of 4–8 piglets per year Populations can double in 4 months 70% of population would need to be killed to keep current status quo
Populations are resource driven
In good years, populations rapidly recover to large numbers after high
mortality
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Factors influencing disease spread in feral swine
4. Movements Sedentary within their home range
Home range typically 3-5 square miles, up to 20 square miles Sex, age, habitat, food availability, and temperature
Movement is not random across the landscape
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Factors influencing disease spread in feral swine
5. Habitat connectivity Connectivity of populations across fragmented landscapes
Interaction between social groups
Population structure
Overlapping home ranges – where?
Landscape barriers
Photo courtesy of Drs. H. Morgan Scott and Susan Cooper 9
Factors influencing disease spread in feral swine
6. Inter-species contact Feral swine are sympatric with outdoor domestic livestock and other
wildlife species Predation on calves, lambs, goat kids, exotic game
Photos courtesy of Henry Coletto 10
Exotic Transboundary Diseases
Foot and mouth disease (FMD) African buffaloes maintenance hosts 22,214 deer killed in CA outbreak, 1925 Unexpected for feral swine to be reservoirs but could play an important role in disease spread Bulgaria 2011 outbreaks and role of wild boar
African swine fever (ASF) Infects domestic/wild suids, Up to 100% morbidity and mortality Acute and chronic disease forms Virus usually disappears from wild boar when disease is controlled in domestic swine Milder viral strains are emerging
Photo courtesy of California Dept. of Fish and Game
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Exotic Transboundary Diseases
Classical swine fever (CSF) CSF endemic in some wild boar populations Germany: 1990-98, ~59% of outbreaks due to direct/ indirect contact with infected wild boars
Economic costs due to control measures ~US $1.5 billion
Italy – Illegal to hunt UK 2000: ham sandwich? CSF outbreaks in wild boar, 1990 – 2001
Source: Artois et al. 2002
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Interplay of ecological and epidemiological factors affecting disease spread in feral swine
Source: Kramer-Schadt et al. 2007 13
The Problem GAO (2009): “If wildlife became infected [with an exotic transboundary
disease]…response would be greatly complicated and could require more veterinarians and different expertise.”
US response plans
Assess the risk wildlife present and strategies to prevent domestic/wildlife interaction – how?
What we do not know: Fade-out or become endemic? Time to detection? Potential domestic/wild pig interaction? Control and mitigation strategies?
Lack of data on factors affecting disease spread in feral swine populations
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CA Wild Pig Project: The Approach
Collect empirical data on California wild pigs Global positioning systems (GPS) Geographic information systems (GIS)
Data collection and analyses based on factors important to disease spread: Habitat, movements, contacts, population
connectivity
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Wild Pigs in California Estimated population varies from 200,000-1 million
Non-native, invasive species
Year-round hunting, no bag limit
Hybrid: feral swine/Eurasian boar
California Dept. of Fish & Game
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CA wild pig project 3 study areas representing different ecoregions
North Coast Redwoods, oak
Central Coast Oak, grasslands
San Joaquin Valley Oak, grasslands, riparian
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The Data Sampling sounders and boars Locations monitored Collar stays on pigs for 10 wks GPS locations every 15 min (7pm-7am); every 1 hr (7am-7pm)
Blood samples – USDA:APHIS WS ASF, FMD, CSF, influenza, PRV, brucellosis, trichinella, tularemia, Hepatitis E, E. coli, toxoplasmosis
Genetic samples Hair, tissues, blood
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Data collection: March 2010 – October 2012
GPS collars placed on 59 pigs at 8 different study sites Finished GPS collar retrieval (Dec 2012)
San Diego County trapping
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Wildlife data collection process Feral swine dataset we are collecting will be the largest in
the US Modeling, FAD policy, surveillance purposes Continued interest in analyses/findings
Process of collecting good/useful feral swine data
Time Dependent on weather, season/ food availability, human disturbance (e.g. hunting, logging), “pig knowledge”, trap placement
Relevance for FAD response plans
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GPS Data Analyses
1. Movement patterns How do pigs move through different habitat
types?
2. Factors associated with habitat selection Where do pigs spend their time?
3. Habitat connectivity What is the spatial extent of contact between
(sub)populations?
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GPS data analyses Analyses focus on parameters used in current wildlife disease models
Movement parameters Day/night, daily, weekly, monthly movements; hog type Environmental and seasonal assessments
Probability of contact between social groups (herds
of wild pigs) 22
1. Movement Patterns
Current feral swine disease model parameters: Random movement of wild pigs within circular home ranges; 1km
daily movement distance1-3 Mobility models sensitive to daily herd movement distances1-2
Study site Hog type (number)
Distance traveled during the day
Distance traveled in preferred habitat
Distance traveled per day (CI)
North Coast Boar (9)
Sounder (13)
52% less
47% less
8.76 km (7.652, 9.998)
5.84 (5.11, 6.85)
Central Coast Boar (11)
Sounder (11)
58% less
45% less
7.77 km (6.45, 8.26)
4.53 (3.87, 5.28)
San Joaquin Valley
Boar (6)
Sounder (10)
55% less
44% less
6.87 km (5.44, 8.34)
5.45 km (3.71, 6.57)
1. Cowled et al. 2012 2. Kramer-Schadt et al. 2009 3. Milne et al. 2008
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2. Factors affecting habitat selection
Knowledge of general and local distribution needed (i.e. where are pigs?) Currently this is done using expert opinion, hunting
or anecdotal information due to resource constraints
Relationships between habitat selection and landscape pattern affect distribution Habitat selection as a proxy for distribution Where do pigs spend their time?
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Study design: longitudinal, spatial Spatial extent:
100% Minimum Convex Polygon Resolution (pixel): 500x500 meters Unit of analysis: landscape unit Outcome:
time spent in landscape unit Explanatory variables:
Habitat (% cover, distance to water, cover/food, NDVI, etc.) Temperature, precipitation Road density Month (season), time of day, study site
Offset: area of useable land
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2. Factors affecting habitat selection
Identify the habitat connectivity/contact of feral swine populations and assess disease spread control options
Can landscape features be exploited to
disconnect feral swine populations across the landscape?
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Data analyses
Current feral swine disease model parameters: Contact usually occurs (e.g. 0.75 probability1) at locations where home ranges overlap1-4 Models sensitive to probability of disease transmission1-2,4
Study site Contact type Percent home range
overlap Percent of locations within overlapping home range
North Coast
Boar to Boar
Boar to Sounder
Sounder to Sounder
4.593%
10.887%
14.438%
1.047%
4.673%
23.453%
Central Coast
Boar to Boar
Boar to Sounder
Sounder to Sounder
6.345%
14.342%
21.434%
3.234%
7.790%
24.627%
San Joaquin Valley
Boar to Boar
Boar to Sounder
Sounder to Sounder
5.25%
11.551%
21.690%
4.554%
8.501%
20.255%
1. Cowled et al. 2012 2. Laffan et al. 2011 3. Kramer-Schadt et al. 2009 4. Milne et al. 2008
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Conceptual Model
Base conceptual model for viral pathogens in feral swine populations
Increase complexity based on type of pathogen
FMD, CSF, PRV
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Implications for foreign animal diseases
Understanding potential FAD spread requires knowledge of wild pig distribution Habitat selection
Understanding movements and potential contact Spatial extent/velocity of disease spread
Identifying areas of increased disease spread Where to look? 39
Future Directions
Wildlife disease model
Livestock/wildlife interface
Disease Control Strategies
Wildlife database
Continued data analysis Comparisons with Texas feral swine dataset New Mexico GPS data collection Landscape genetics analyses
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Acknowledgements
Supported by the Foreign Animal Disease Modeling Program of the U. S. Department of Homeland Security Science & Technology Directorate
Drs. Pam Hullinger, Tim Carpenter, Este Geraghty (UC Davis), Morgan Scott (Kansas State Univ.)
Collaborators USDA/APHIS Wildlife Services – Shannon Chandler CA Dept. of Fish & Game – Ben Gonzales, Marc Kenyon Dick Seever, Rural Pig Management, CA Private land owners, CA
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