New Insights into PRRS Seasonality Across Different US Regions - Andreia Arruda, from the 2017 Allen D. Leman Swine Conference, September 16-19, 2017, St. Paul, Minnesota, USA. More presentations at http://www.swinecast.com/2017-leman-swine-conference-material

1. New insights into PRRS seasonality
across U.S. regions
2017 Allen D. Leman Swine Conference
Andreia G. Arruda DVM MS PhD
Assistant Professor

2. Introduction
• Monitoring programs, PRRS incidence and temporal
clustering
Source: MSHMP

3. Introduction
• 2010-2013
₋ Pre-PED
₋ Aggregate

4. Source: MSHMP
Summer PRRS outbreaks
Contribution: C. Vilalta

5. Introduction
• Time-dependent reproductive number (TD-R) for
PRRS
₋ Transmissibility of a pathogen over time
₋ Test efficacy of interventions, identification of “super-
spread” events

6. Introduction
• TD-R for PRRS

7. Introduction
• TD-R for PRRS

8. Materials and Methods
• Objective
Analyze the temporal patterns of PRRS infections at
the farm level for five major swine-producing states
across the U.S.
Are yearly patterns commonly described for PRRS
conserved across different U.S. states?

9. Materials and Methods
• Source: MSHMP 2009-2016
₋ Complete weekly data
₋ Following AASV PRRS status guidelines (status 1)
• Time-series analysis (R v.3.2.3)
₋ 5 states: MN, IA, NC, NE, IL
₋ Autoregressive integrated moving average (ARIMA)
models; trend and season (one year, 6/4/3 months)
covariates
₋ Generalized linear autoregressive moving average model
with a Poisson structure for low counts

10. Materials and Methods
• E.g.: IA

11. Materials and Methods
• E.g.: IA

12. Materials and Methods
• E.g.: IA

13. Results
• 302 farms; 388 weeks
₋ 13 different systems
• Remarkable difference in PRRS seasonality among
states
₋ Yearly peak
₋ Semestral (6 mo) peak
₋ No seasonality

14. Results
State Seasonality Model type
MN
Annual ARIMA (2,0,1)
IA
Every 6 months ARIMA (1,0,0)
NE
Annual ARIMA (0,1,0)
NC
Annual ARIMA (2,0,1)
IL
None GLARMA (1,2,3)

15. Discussion
• Peaks of PRRS vary according to region
₋ Landscape and environmental factors
₋ Identification of outbreaks
₋ Movement of animals
• “Summer breaks” evident in Iowa
₋ Commingling opportunities
₋ Relaxed attitude towards biosecurity
₋ Amount of activities throughout the year

16. Discussion
• Limitations
₋ Sow herds only
₋ Few states assessed
₋ Limited number of production companies
₋ Misclassification/ underreporting
• Future applications
₋ Predictions by region
₋ Investigation of other states

17. Coming up…

18. More on prevention of PRRSv
outbreaks
• Follow-up study to the “land coverage” PRRS
study

19. Arruda, Geary, Morrison
Our hypothesis:
Swine farms are more likely to have PRRS outbreaks if the
prevailing wind direction from the week preceding the
outbreak is directed to areas with no tree coverage
More on prevention of PRRSv
outbreaks

20. What did we do?
• Selected cases and controls
• Cases: sites that had a PRRS outbreak (2009-2016)
• Controls: sites that did not have a PRRS break during the
same week as the case (2009-2016)
• Matched by system
• Selected at random (n = 208)
• Source population: MSHMP

21. What did we do?
• Selected variables we were interested on:
• Barn orientation (N-S, E-W, mixed)
• Distance to main road (ft); main road a highway
• Presence of farm within 1 & 3 km
• Tree coverage
• Weather data

22. What did we do?
• No pain no gainOrientation: E-W
S = 4; 100%
W = 0; 0%
Entrance E
Tree coverage:
“density” in ft (average, continuous)
“completeness” in terms of existing gaps (score 1-4)
“percentage” in terms of how much coverage (0-100%)

23. Presence farm
within 1km;
N direction
What did we do?
Dist to main road
Main road not hwy
Weather data:
Predominant wind direction -7d/ -14d
% calm wind -7d/ -14d
Average wind speed -7d/ -14d

24. Preliminary results
Variable OR (SE) P-value
Presence of farm within 1km 2.06 (0.63) 0.017
Average wind speed -14d 2.0 (0.82) 0.09
Presence of trees between farms (lots)* 0.27 (0.20) 0.08
PRRSv status week before break* - status 4 0.25 (0.15) 0.023
Tree completeness (1-4) direction of 1km farm 0.53 (0.16) 0.035
Average tree percentage (coverage) 0.60 (0.22) 0.15
Average tree density (ft) wind direction -14d 0.67 (0.20) 0.18
% calm wind -14d 0.97 (0.02) 0.06
* References: no trees, status 2vx
Univariable- conditional logistic regression analysis – P < 0.20
Stay tuned…

25. Take-home messages
• Do not assume a high risk for PRRSv infection
solely in the winter
• Ensure high biosecurity standards throughout
the year
• If you have the option, leave trees around
your farm

26. Acknowledgements
• University of Minnesota
₋ MSHMP
₋ Swine veterinarians and producers that agree to share
data
₋ Collaborators:
• Morrison, R. (in memoriam)
• Vilalta, C.
• Alba, A.
• Puig, P.
• Swine Health Information Center
• National Pork Board

27. Thank you
goncalvesarruda.1@osu.edu