Are cull sow movements impacting disease transmission? - Dr. Jim Lowe and Dr. Ben Blair, University of Illinois, from the 2017 North American PRRS/National Swine Improvement Federation Joint Meeting, December 1‐3, 2017, Chicago, Illinois, USA. More presentations at http://www.swinecast.com/2017-north-american-prrs-nsif-joint-meeting

1. Understanding Cull Sow
Movements in North America:
Implications on Disease
Transmission
Benjamin Blair and James Lowe
Integrated Food Animal Management Systems
Department of Veterinary Clinical Medicine
College of Veterinary Medicine, University of Illinois

2. Funding and Acknowledgements
• Funding: Swine Health Information Center Project #16-275
• Harvest plant owners and staff
• SHIC cull animal movement committee

3. Are trucks important?
• Environmental samples were collected from 518 livestock trailers prior to and
after unloading pigs into the lairage at six harvest plants located central US.
• Samples were collected over a 2-3 day period at each facility with all samples
collected between 14 June and 20 June 2013.
• Samples were collected by
• Rubbing a “Swiffer” which was moistened with 20 ml of Phosphate Buffered Saline over
approximately a 900 cm2 area located 15 cm from the back of the trailer on the floor.
• The “Swiffer” was then placed in a sterile bag and the liquid was removed with manual
pressure.
• The liquid was placed in a sterile tube which was maintained at 4C for transportation to the
laboratory.
• Dedicated latex gloves were worn for each sample collection
• Samples were processed at the Iowa State Veterinary Diagnostic Laboratory
(Ames, IA USA) using their PEDV PCR test.
Lowe et al, EID 2014

4. One positive trailer in means 1.7 positive
trailers at exit
Plant
Contaminated
at entry
Contaminated
at Plant
Contamination
Ratio
A 2.25% 8.05% 3.58
B 7.00% 4.30% 0.61
C 10.84% 10.81% 1.00
D 2.00% 0.00% 0.00
E 14.56% 3.08% 0.62
G 3.00% 1.03% 0.34
All 5.98% 4.31% 0.72
Lowe et al, EID 2014

5. Conditions at the time of unloading influence
contamination rates
More virus increases riskMore contact increases risk

6. If contact at the plant is a risk for disease spread
between farms….
Then we need to understand how trucks
connect farms together into a network to
understand the role of animal marketing
channels in disease spread.

7. Finishing
Site 2
Finishing
Site 1
Harvest Plant
Truck
Wash
Trailer 1
A simple model of marketing movements:
Market Animals
or

8. Truck
Wash
Harvest
Plant 1
Sow Farm
2
Sow Farm
1
Collection
Point 2
Collection
Point 1
A simple model of marketing movements:
Cull Sows
Harvest
Plant 2
Trailer 1 Trailer 2 Trailer 3 Trailer 4 Trailer 5 Trailer 6

9. Truck
Wash
Harvest
Plant 1
Sow Farm
2
Sow Farm
1
Collection
Point 2
Collection
Point 1
Could measuring two relationships give us insight into
how the system functions?
Harvest
Plant 2
Trailer 1 Trailer 2 Trailer 3 Trailer 4 Trailer 5 Trailer 6

10. What we did to try and answer that question?
• Cull sow data from 1 harvest plant over 1 week
• Captured all PREMID and the last know source prior to arrival at the
plant for sows harvested.
• Identified geo-locations for each PREMID and shipping location.
• Calculated the distances between the Farm, the last known shipping
location and the plant.
• Investigated the relationships between the distances and where sows
where shipped from.

11. What did we find….
There is good data available and sows
come from all over the place!
•We captured 2263 sows’ data, which was 90.4% of
all sows harvested
•297 source farms from 21 states and Canada
•16 shipping locations from 7 states and Canada

12. A small but significant number of sows (14%) originated from
collection points greater than 150 miles from the sow farm and
2.5% of all sows traveled 5 times as far from the farm to the final
collection point as from the final collection point to the farm.

13. Key Findings
1. Capturing detailed information about cull swine shipment locations and
farms of origin at the time of harvest was both feasible and practical.
2. Collecting market movement data between the farm of origin and the
last shipping location to the plant proved to be impossible.
3. 86% of animals originated from a terminal collection point that was in
close proximity to the source farm.
4. 14% of culls traveled more than 240 kilometers from the source farm to
the terminal collection point.
5. 2.5% of all culls traveled 5 times as far to the terminal collection point
from the source farm than they did from terminal collection point to
terminal market.
6. We hypothesize that these culls moved between collection points prior
to arrival at the harvest plant.

14. A “big data problem”
•We have a “big data problem”… that we can’t
get a hold of any big data…
•So…. We have to collect some data… the
challenge is what data?
•Can we build a model to help us understand
what factors might be the most important?

15. Searching for Understanding
• We wanted to understand if in any of the data we collect or that is present through the USDA could be
used to understand what drives the manner in which sows move.
• A linear regression model was built look for correlations between the percentage of far off sows and
things such as market composition, regional price spreads, light-heavy spreads, etc.
• Regional prices spreads were strongly correlated with the number of far sows entering this terminal
market

16. Next Steps: Stochastic Model of Cull
Marketing
• Phase 1 (On going): A Stochatic model
of cull sow movements in the US
• Level: State based model
• Available Data: Movement data from a
single plant, sow populations of each
state and FSIS inspected cull plants
• Outcome: Understand how random
variations in our linear model (distance to
plant, changes in slaughter numbers at
individual plants, plant location, market
prices) effect the distribution of sow
movements.
• Phase 2: Apply phase 1 model to build
epidemic model for novel disease
introduction.

17. Next Steps: Automating PREMID capture
• We have identified a technology that will allow us to use images of
tags and digitize them though imaging processing software.
• Current beta tests of the software on images of tags that were removed from
sows suggested the technology could be viable and further evaluation of its
application in the plant is warranted.
• In conjunction to the text recognition software, we are currently beta
testing low cost hardware that could be installed into plants allowing
us to in real time capture and process images of tags.

18. Original Image Convert to B-W Image Segment Image
Text Recognition

19. Integrated Food Animal Management Systems
Department of Veterinary Clinical Medicine
University of Illinois
jlowe@Illinois.edu
Thank You