An investigation of transportation practices in an Ontario swine system using descriptive network analysis

Autoři: Dylan John Melmer aff001;  Terri L. O’Sullivan aff001;  Amy L. Greer aff001;  Zvonimir Poljak aff001
Působiště autorů: Department of Population Medicine, University of Guelph, Guelph, ON, Canada aff001
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article


The objectives of this research were to describe the contact structure of transportation vehicles and swine facilities in an Ontario swine production system, and to assess their potential contribution to possible disease transmission over different time periods. A years’ worth of data (2015) was obtained from a large swine production and data management company located in Ontario, Canada. There was a total of 155 different transportation vehicles, and 220 different farms within the study population. Two-mode networks were constructed for 1-,3-, and 7-day time periods over the entire year and were analyzed. Trends in the size of the maximum weak component and outgoing contact chain over discrete time periods were investigated using linear regression. Additionally, the number of different types of facilities with betweenness >0 and in/out degree>0 were analyzed using Poisson regression. Maximum weekly outgoing contact chain (MOCCw) contained between 2.1% and 7.1% of the study population. This suggests a potential maximum of disease spread within this population if the disease was detected within one week. Frequency of node types within MOCCw showed considerable variability; although nursery sites were relatively most frequent. The regression analysis of several node and network level statistics indicated a potential peak time of connectivity during the summer months and warrants further confirmation and investigation. The inclusion of transportation vehicles contributed to the linear increase in the maximum weekly weak component (MWCw) size over time. This finding in combination with constant population dynamics, may have been driven by the differential utilization of trucks over time. Despite known limitations of maximum weak components as an estimator of possible outbreaks, this finding suggests that transportation vehicles should be included, when possible and relevant, in the evaluation of contacts between farms.

Klíčová slova:

Data management – Network analysis – Ontario – Sanitation – Swine – Transportation – Veterinary diseases – Veterinary epidemiology


1. Klovdahl AS. Social networks and the spread of infectious diseases: The AIDS example. Soc Sci Med. 1985;21: 1203–1216. doi: 10.1016/0277-9536(85)90269-2 3006260

2. Luke DA, Harris J k. Network analysis in public health: history, methods, and applications. Annu Rev Public Health. 2007;28: 69–93. doi: 10.1146/annurev.publhealth.28.021406.144132 17222078

3. Smith RP, Cook AJC, Christley RM. Descriptive and social network analysis of pig transport data recorded by quality assured pig farms in the UK. Prev Vet Med. 2013;108: 167–177. doi: 10.1016/j.prevetmed.2012.08.011 22959427

4. Melmer DJ, O’Sullivan TL, Poljak Z. A descriptive analysis of swine movements in Ontario (Canada) as a contributor to disease spread. Prev Vet Med. 2018;159: 211–219. doi: 10.1016/j.prevetmed.2018.09.021 30314784

5. Dubé C, Ribble C, Kelton D, McNab B. A review of network analysis terminology and its application to foot-and-mouth disease modelling and policy development. Transbound Emerg Dis. 2009;56: 73–85. doi: 10.1111/j.1865-1682.2008.01064.x 19267879

6. Perri AM, Poljak Z, Dewey C, Harding JCS, O’Sullivan TL. Network analyses using case-control data to describe and characterize the initial 2014 incursion of porcine epidemic diarrhea (PED) in Canadian swine herds. Prev Vet Med. 2019;162: 18–28. doi: 10.1016/j.prevetmed.2018.11.001 30621895

7. Kinsley AC, Perez AM, Craft ME, Vanderwaal KL. Characterization of swine movements in the United States and implications for disease control. Prev Vet Med. 2019;164: 1–9. doi: 10.1016/j.prevetmed.2019.01.001 30771888

8. Spence KL, O’Sullivan TL, Poljak Z, Greer AL. Descriptive analysis of horse movement networks during the 2015 equestrian season in Ontario, Canada. PLoS One. 2019;14: e0219771. doi: 10.1371/journal.pone.0219771 31295312

9. Porphyre T, Boden LA, Correia-Gomes C, Auty HK, Gunn GJ, Woolhouse MEJ. How commercial and non-commercial swine producers move pigs in Scotland: A detailed descriptive analysis. BMC Vet Res. 2014;10: 1–17. doi: 10.1186/1746-6148-10-1

10. Dee S, Deen J, Otake S, Pijoan C. An experimental model to evaluate the role of transport vehicles as a source of transmission of porcine reproductive and respiratory syndrome virus to susceptible pigs. Can J Vet Res. 2004;68: 128–133. 15188957

11. Bottoms K, Poljak Z, Dewey C, Deardon R, Holtkamp D, Friendship R. Investigation of strategies for the introduction and transportation of replacement gilts on southern Ontario sow farms. BMC Vet Res. 2012;8: 217. doi: 10.1186/1746-6148-8-217 23140357

12. Lowe J, Gauger P, Harmon K, Zhang J, Connor J, Yeske P, et al. Role of transportation in spread of porcine epidemic diarrhea virus infection, United States. Emerg Infect Dis. 2014;20: 872–874. doi: 10.3201/eid2005.131628 24750785

13. Thakur KK, Revie C, Hurnik D, Poljak Z, Sanchez J. Simulation of between-farm transmission of porcine reproductive and respiratory syndrome virus in Ontario, Canada using the North American Animal Disease Spread Model. Prev Vet Med. 2015;118: 413–426. doi: 10.1016/j.prevetmed.2015.01.006 25636969

14. Dee S, Deen J, Burns D, Douthit G, Pijoan C. An evaluation of disinfectants for the sanitation of porcine reproductive and respiratory syndrome virus-contaminated transport vehicles at cold temperatures. Can J Vet Res. 2005;69: 64–70. 15745225

15. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.; 2015. Available:

16. Højsgaard S, Halekoh U. doBy: Groupwise Statistics, LSmeans, Linear Contrasts, Utilities. R package version 4.5–15.; 2016. Available:

17. Grolemund G, Wickham H. Dates and Times Made Easy with lubridate. J Stat Softw. 2011;3: 1–25. Available:

18. Csardi G, Nepusz T. The igraph software package for complex network research. InterJournal. 2006;Complex Sy: 1695. Available:

19. Noemark M, Widgren S. EpiContactTrace: an R-package for contact tracing during livestock disease outbreaks and for risk-based surveillance. BMC Vet Res. 2014;10: 71. doi: 10.1186/1746-6148-10-71 24636731

20. Poumian M. Disinfection of trucks and trailers. Rev Sci Tech. 1995;14: 165–176. 7548965

21. Arruda AG., Friendship R, Carpenter J, Hand K, Poljak Z. Network, cluster and risk factor analyses for porcine reproductive and respiratory syndrome using data from swine sites participating in a disease control program. Prev Vet Med. 2016;128: 41–50. doi: 10.1016/j.prevetmed.2016.03.010 27237389

22. Anonymous. OSHAB Transport Biosecurity Gap Analysis. 2012. pp. 1–25. Available:

23. Dubé C, Ribble C, Kelton D, McNab B. Comparing network analysis measures to determine potential epidemic size of highly contagious exotic diseases in fragmented monthly networks of dairy cattle movements in Ontario, Canada. Transbound Emerg Dis. 2008;55: 382–392. doi: 10.1111/j.1865-1682.2008.01053.x 18840200

24. Guinat C, Relun A, Wall B, Morris A, Dixon L, Pfeiffer DU. Exploring pig trade patterns to inform the design of risk-based disease surveillance and control strategies. Sci Rep. 2016;6: 28429. doi: 10.1038/srep28429 27357836

25. Kao RR, Green DM, Johnson J, Kiss IZ. Disease dynamics over very different time-scales: foot-and-mouth disease and scrapie on the network of livestock movements in the UK. J R Soc Interface. 2007;4: 907–16. doi: 10.1098/rsif.2007.1129 17698478

26. Ajayi T, Dara R, Misener M, Pasma T, Moser L, Poljak Z. Herd-level prevalence and incidence of porcine epidemic diarrhoea virus (PEDV) and porcine deltacoronavirus (PDCoV) in swine herds in Ontario, Canada. Transbound Emerg Dis. 2018; 1197–1207. doi: 10.1111/tbed.12858 29607611

27. Thakur K, Revie CW, Hurnik D, Poljak Z, Sanchez J. Analysis of Swine Movement in Four Canadian Regions: Network Structure and Implications for Disease Spread. Transbound Emerg Dis. 2016;63: e14–e26. doi: 10.1111/tbed.12225 24739480

28. Dorjee S, Revie CW, Poljak Z, McNab WB, Sanchez J. Network analysis of swine shipments in Ontario, Canada, to support disease spread modelling and risk-based disease management. Prev Vet Med. 2013;112: 118–127. doi: 10.1016/j.prevetmed.2013.06.008 23896577

29. Lee K, Polson D, Lowe E, Main R, Holtkamp D, Martínez-López B. Unraveling the contact patterns and network structure of pig shipments in the United States and its association with porcine reproductive and respiratory syndrome virus (PRRSV) outbreaks. Prev Vet Med. 2017;138: 113–123. doi: 10.1016/j.prevetmed.2017.02.001 28237226

30. Rautureau S, Dufour B, Durand B. Structural vulnerability of the French swine industry trade network to the spread of infectious diseases. Anim J. 2012;6: 1152–62. doi: 10.1017/S1751731111002631 23031477

31. Valdes-Donoso P, VanderWaal K, Jarvis LS, Wayne SR, Perez AM. Using machine learning to predict swine movements within a regional program to improve control of infectious diseases in the US. Front Vet Sci. 2017;4: 1–1. doi: 10.3389/fvets.2017.00001

32. Arruda AG, Poljak Z, Friendship R, Carpenter J, Hand K. Descriptive analysis and spatial epidemiology of porcine reproductive and respiratory syndrome (PRRS) for swine sites participating in area regional control and elimination programs from 3 regions of Ontario. Can J Vet Res. 2015;79: 268–278. 26424906

33. Elbers ARW, Stegeman A, Moser H, Ekker HM, Smak J. JA, Pluimers FH. The classical swine fever epidemic 1997–1998 in The Netherlands: descriptive epidemiology. Prev Vet Med. 1999;42: 157–84. doi: 10.1016/s0167-5877(99)00074-4 10619154

34. Dee S, Deen J, Burns D, Douthit G, Pijoan C. An assessment of sanitation protocols for commercial transport vehicles. Proceedings of the 18th IPVS Congress, Hamburg. 2004.

Článek vyšel v časopise


2020 Číslo 1
Nejčtenější tento týden