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Spatial relative risk of PRRS summer outbreaks and factors associated with PRRS incidence during summer

Juan M. Sanhueza1*, Mark A. Stevenson2, Carles Vilalta Sans1, Mariana Kikuti1 and Cesar Corzo1
  • 1 University of Minnesota Twin Cities, United States
  • 2 The University of Melbourne, Australia

Background Porcine reproductive and respiratory syndrome (PRRS) was described for the first time in the United States (US) during the late 1980’s. The syndrome is characterized by lethargy, fever, late term abortions, increased pre-weaning mortality, and respiratory signs (Christianson & Joo, 1994). After the initial reports, the disease spread quickly in the US (Bautista et al., 1993). Nowadays, the disease is endemic in US pig herds and causes extensive economic loss that has been estimated at USD 664 million (Holtkamp et al., 2013). PRRS incidence in the US is monitored through the Morrison’s swine health monitoring project (MSHMP), a voluntary participation industry-driven program that receives, stores and reports weekly incidence of PRRS in about 50% of sow population of US (Perez et al., 2019). Over the years, PRRS has showed a marked seasonal pattern of high incidence during fall and winter, and low incidence during spring and summer (Tousignant et al., 2015). Although most PRRS outbreaks occur during the fall and winter, an unquantified percentage of outbreaks still occur during the summer. Additionally, anecdotal reports suggested that these so called “summer outbreaks” were increasing in frequency in recent years. In this study we described the incidence of PRRS summer outbreaks over calendar time and identify geographical areas where there is a high and low incidence of PRRS summer outbreaks. Methods MSHMP PRRS incidence data from July 2009 to December 2018 were used for analyses. A summer outbreak was defined as a PRRS outbreak reported between June 21st and September 21st in any given year. Yearly incidence rate summer outbreaks was estimated by dividing the number of PRRS outbreaks reported during summer by the total number of weeks a farm was at risk during summer in each year. The Mann-Kendall test was used to evaluate the incidence trend over the years. Additionally, the association between the incidence rate during summer and recorded putative risk factors such as year, herd size, farm filtration status (year-round filtration, partially filtered, and not filtered), and region was assessed using a Poisson model. Time at risk in weeks was used as an offset in the model. The spatial relative risk of PRRS summer outbreaks was estimated using an adaptive kernel smoothing approach (Davies & Hazelton, 2010). Pilot bandwidths of summer outbreaks and non-summer outbreaks were estimated separately using a bootstrap method (Davies et al., 2018). The density of cases (summer outbreaks) was compared to the density of controls (i.e. no summer outbreaks). The ratio of these two densities was used to identify geographical areas of high and low incidence of PRRS summer outbreaks. Edge effects were corrected to reduce the introduction of bias near the boundaries of the region studied (Kelsall & Diggle, 1995). Tolerance contour lines were calculated using Monte Carlo test (Kelsall & Diggle, 1995). Spatial relative risk was estimated using the sparr package (Davies et al., 2011) in R (R Core Team, 2018). Results Since 2009, 182 out of 1329 PRRS outbreaks (13.7% of total outbreaks) were recorded during summer. The incidence rate of PRRS outbreaks during summer averaged 3.3 (95% CI 2.9 – 3.7) cases per 100 farm-summers between 2009 and 2017. No significant increasing or decreasing trend was detected over the years (p=0.47). Spatial relative risk of summer outbreaks was higher in an area of the Midwest located in South-west Minnesota and North-west Iowa. The estimated spatial risk of PRRS summer outbreaks in this area ranged between 1.4 and 2.4 times the spatial risk of PRRS outbreaks during non-summer months. Final Poisson model results showed a regional effect of PRRS summer outbreaks in which farms located in the Midwest had 3.2 times higher incidence rate than in the North-East (p = 0.02) and 1.8 times higher than in the South-East (p=0.12). A borderline significant association (RR 1.3, p=0.07) was observed between farms with more than 2,500 sows in their inventory than farms with ≤2500 sows. Additionally, a borderline association was observed between partially filtered farms (RR 1.98, p=0.12) and non-filtered farms. No significant incidence rate difference was observed between year-round filtered farms and non-filtered farms. Finally, incidence rate of PRRS during summer did not vary significantly across the years (p=0.5). Conclusion Our results showed that PRRS outbreaks continue to occur during the summer at a low level of 3 cases per 100 farm-summers. However, no evidence of increasing or decreasing trend was observed across the years. Summer outbreaks tended to cluster spatially in a limited area of the Midwest. Several factors may play a role on this increased spatial risk. For example, this is a highly dense area where pigs often commingle from different sources. This may elevate the infection pressure of sow farms located in that area. Additionally, a borderline significant increased incidence rate of summer outbreaks was observed for partially filtered farms compared with non-filtered farms. Partially filtered farms are filtered farms that decide to stop filtration, often during summer months, to increase ventilation and manage the temperature inside the farm during summer. These findings warrant further investigation and encourage swine producers to maintain bio-security measures throughout the year, particularly for those farms located in areas with a higher risk of PRRS summer outbreaks.

Acknowledgements

We are grateful to all participants of the Morrison’s Swine Health Monitoring Project (MSHMP) and the Swine Health Information Center (SHIC).

References

Bautista, E. M., R. B. Morrison, S. M. Goyal, J. E. Collins and J. F. Annelli, 1993: Seroprevalence of PRRS virus in the United States. JSHAP, 1, 4-8. Christianson, W. T. and H. S. Joo, 1994: Porcine reproductive and respiratory syndrome: A review. JSHAP, 2, 10-28. Davies, T. M. and M. L. Hazelton, 2010: Adaptive kernel estimation of spatial relative risk. Statistics in medicine, 29, 2423-2437. Davies, T. M., M. L. Hazelton and J. C. Marshall, 2011: sparr: Analyzing Spatial Relative Risk Using Fixed and Adaptive Kernel Density Estimation in R. 2011, 39, 14. Davies, T. M., J. C. Marshall and M. L. Hazelton, 2018: Tutorial on kernel estimation of continuous spatial and spatiotemporal relative risk. Statistics in Medicine, 37, 1191-1221. Holtkamp, D. J., J. B. Kliebenstein and E. J. Neumann, 2013: Assessment of the economic impact of porcine reproductive and respiratory syndrome virus on United States pork producers. JSHAP, 21, 72-84. Kelsall, J. E. and P. J. Diggle, 1995: Non-parametric estimation of spatial variation in relative risk. Statistics in medicine, 14, 2335-2342. Perez, A. M., D. C. Linhares, A. G. Arruda, K. VanderWaal, G. Machado, C. Vilalta, J. Sanhueza, J. Torrison, M. Torremorell and C. Corzo, 2019: Individual or common good? Voluntary data sharing to inform disease surveillance systems in food animals. Frontiers in Veterinary Science. Accepted, ahead of publication. doi: 10.3389/fvets.2019.00194. R Core Team, 2018: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Vienna, Austria. Tousignant, S. J., A. M. Perez, J. F. Lowe, P. E. Yeske and R. B. Morrison, 2015: Temporal and spatial dynamics of porcine reproductive and respiratory syndrome virus infection in the United States. Am J Vet Res, 76, 70-76.

Keywords: PRRs, summer outbreaks, spatial risk, Incidence rate, Risk factors

Conference: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data, Davis, United States, 8 Oct - 10 Oct, 2019.

Presentation Type: Regular oral presentation

Topic: Spatio-temporal surveillance and modeling approaches

Citation: Sanhueza JM, Stevenson MA, Vilalta Sans C, Kikuti M and Corzo C (2019). Spatial relative risk of PRRS summer outbreaks and factors associated with PRRS incidence during summer. Front. Vet. Sci. Conference Abstract: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data. doi: 10.3389/conf.fvets.2019.05.00090

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Received: 10 Jun 2019; Published Online: 27 Sep 2019.

* Correspondence: Mx. Juan M Sanhueza, University of Minnesota Twin Cities, St. Paul, United States, jsanhueza@uct.cl