TY - JOUR
T1 - Characterization of swine movements in the United States and implications for disease control
AU - Kinsley, A. C.
AU - Perez, A. M.
AU - Craft, M. E.
AU - Vanderwaal, K. L.
PY - 2019/3/1
Y1 - 2019/3/1
N2 - Understanding between-farm movement patterns is an essential component in developing effective surveillance and control programs in livestock populations. Quantitative knowledge on movement patterns is particularly important for the commercial swine industry, in which large numbers of pigs are frequently moved between farms. Here, we described the annual movement patterns between swine farms in three production systems of the United States and identified farms that may be targeted to increase the efficacy of infectious disease control strategies. Research results revealed a high amount of variability in movement patterns across production systems, indicating that quantities captured from one production system and applied to another may lead to invalid estimations of disease spread. Furthermore, we showed that targeting farms based on their mean infection potential, a metric that captured the temporal sequence of movements, substantially reduced the potential for transmission of an infectious pathogen in the contact network and performed consistently well across production systems. Specifically, we found that by targeting farms based on their mean infection potential, we could reduce the potential spread of an infectious pathogen by 80% when removing approximately 25% of farms in each of the production systems. Whereas other metrics, such as degree, required 26–35% of farms to be removed in two of the production systems to reach the same outcome; this outcome was not achievable in one of the production systems. Our results demonstrate the importance of fine-scale temporal movement data and the need for in-depth understanding of the contact structure in developing more efficient disease surveillance and response strategies in swine production systems.
AB - Understanding between-farm movement patterns is an essential component in developing effective surveillance and control programs in livestock populations. Quantitative knowledge on movement patterns is particularly important for the commercial swine industry, in which large numbers of pigs are frequently moved between farms. Here, we described the annual movement patterns between swine farms in three production systems of the United States and identified farms that may be targeted to increase the efficacy of infectious disease control strategies. Research results revealed a high amount of variability in movement patterns across production systems, indicating that quantities captured from one production system and applied to another may lead to invalid estimations of disease spread. Furthermore, we showed that targeting farms based on their mean infection potential, a metric that captured the temporal sequence of movements, substantially reduced the potential for transmission of an infectious pathogen in the contact network and performed consistently well across production systems. Specifically, we found that by targeting farms based on their mean infection potential, we could reduce the potential spread of an infectious pathogen by 80% when removing approximately 25% of farms in each of the production systems. Whereas other metrics, such as degree, required 26–35% of farms to be removed in two of the production systems to reach the same outcome; this outcome was not achievable in one of the production systems. Our results demonstrate the importance of fine-scale temporal movement data and the need for in-depth understanding of the contact structure in developing more efficient disease surveillance and response strategies in swine production systems.
KW - Contact network
KW - Infectious disease contact
KW - Movement
KW - Social network analysis
KW - Swine
UR - http://www.scopus.com/inward/record.url?scp=85060176958&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85060176958&partnerID=8YFLogxK
U2 - 10.1016/j.prevetmed.2019.01.001
DO - 10.1016/j.prevetmed.2019.01.001
M3 - Article
C2 - 30771888
AN - SCOPUS:85060176958
VL - 164
SP - 1
EP - 9
JO - Preventive Veterinary Medicine
JF - Preventive Veterinary Medicine
SN - 0167-5877
ER -