Modeling Emerging Disease in the U.S. Swine Herd

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1 Modeling Emerging Disease in the U.S. Swine Herd Shweta Bansal Assistant Professor of Biology, Georgetown University Faculty Fellow, National Institutes of Health

2 U.S. Agricultural Disease Preparedness New, emerging, and evolving pathogens are a challenge to animal health and production. Although improved management and better diagnostic and prophylactic tools are now available, emerging diseases and changes in animal management will always create new opportunities for old diseases. Successfully overcoming these challenges requires a U.S. agricultural research enterprise that harnesses the newest advances from across the physical and life sciences, builds on a broader public investment in science and technology, and then applies these discoveries to the specific challenges of agriculture.

3 U.S. Livestock Diseases Current outbreak: PEDV Potential threat: FMD Zoonotic impact: Influenza Mole, Nature (2013)

4 U.S. Swine Industry The U.S. swine industry is highly connected and intensely aggregated U.S. swine production density (USDA Agricultural Census) U.S. Swine Movement Shields & Mathews, USDA (2002)

5 Linking Disease to Livestock Movement Increased livestock movement Increased prevalence of btb High animal throughputs High risk of infection Gilbert et al, Nature (2005) Shirley & Rushton, Epidemiology and Infection (2005)

6 Role of Disease Modeling During Epidemic Assess means of spread Predict future spread Design control DETERMINE TRANSMISSION PATHWAYS Endemic Stage Disease Management CONTAIN SPREAD Prior to Emergence Surveillance Preparedness RISK ANALYSIS

7 PEDV Transmission Pathways

8 PEDV Spread in U.S. Data: USDA/AASV; O Dea et al (2014)

9 Open Questions About PEDV Is swine movement responsible for propagating the infection? What other factors increase risk of infection? What was the source of the infection in the U.S.? Important for surveillance, control and preparedness

10 Role of Swine Movement in PEDV Is swine movement responsible for propagating the infection? Evidence of spread by trailers found (Lowe et al, 2014) Many states have responded by limiting imports from PEDV-free premises However, mode of transmission remains open to speculation

11 Role of Movement in PEDV Spread O Dea, Snelson, Bansal (2015, In Review)

12 What is the impact of movement direction? Evidence for trailer-based transmission

13 Source of Infection What was the source of the infection in the U.S.? First cases detected in OH and IN but entry unknown

14 Source of PEDV in US Do arrival times of PEDV in different states provide information on origin? Arrival times of PEDV April 2013 Dec 2013

15 Estimation of Likely Disease Source Input: probability of disease spread between areas, genetic data, time of disease detection, model of detection error Output: approximate likelihood of each state as source Source: IN Distribution of arrival times from IN OH Source: KS

16 Controlling an Outbreak

17 Movement Restrictions to Control PEDV Self-imposed restrictions Optimized restrictions

18 Regionalization as a Tool for Livestock Disease Control Complex network community structure analysis

19 Large-Scale U.S. Regionalization Densitydependent transmission Frequencydependent transmission

20 Feasibility of Regionalization Optimized for feasibility and efficiency 1) Spatial cohesiveness 2) Spatial contiguity

21 Assessing Risk of Emergence

22 Quantifying Risks for Swine Disease Emergence + Swine density Live swine movement + + Importation of swine Shipment of pork + animal feed

23 Quantifying Risks for Swine Disease Emergence Network-based model of risk for swine disease emergence Identification of hotspots for introduction and spread

24 Summary Network modeling swine industry connectivity PEDV: identification of disease transmission pathways and sources Crucial for identifying biosecurity gaps and preventing future introductions Design of control strategies for containing spread Optimal strategies adapted for feasibility and business continuity Risk analysis for swine disease emergence Improved biosurveillance and preparedness Increased access to global trading partners

25 Acknowledgements Group Eamon O Dea Ian Carroll Madeline Campbell Collaborators: Harry Snelson (AASV) Ryan Miller (USDA APHIS) Jason Lombard (USDA APHIS) Katie Portacci (USDA APHIS) Colleen Webb (CSU/RAPIDD) Michael Buhnerkempe (UCLA/RAPIDD) James Wood (Cambridge) John Korslund (USDA APHIS) Laura Pomeroy (OSU) Bryan Grenfell (Princeton) Support: Department of Homeland Security Foreign Animal Disease Modeling Program RAPIDD Program of the Science & Technology Directorate of the DHS and the Fogarty International Center, National Institutes of Health. Images from Wikimedia Commons. Michigan Farm Bureau, USDA, BBC News

26 Modeling Emerging Disease in the U.S. Swine Herd Shweta Bansal Web:

From Network Structure to Consequences & Control

From Network Structure to Consequences & Control Shweta Bansal Isaac Newton Institute, Cambridge University Infectious Disease Dynamics Programme August 2013 Number of papers Network Epidemiology Network