TY - JOUR

T1 - Social network analysis reveals the failure of between-farm movement restrictions to reduce Salmonella transmission

AU - Conrady, B

AU - Dervic, E H

AU - Klimek, P

AU - Pedersen, L

AU - Reimert, M Merhi

AU - Rasmussen, P

AU - Apenteng, O O

AU - Nielsen, L R

N1 - The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

PY - 2024/5/22

Y1 - 2024/5/22

N2 - An increasing number of countries are investigating options to stop the spread of the emerging zoonotic infection Salmonella (S.) Dublin, which mainly spreads among bovines and with cattle manure. Detailed surveillance and cattle movement data from an 11-year period in Denmark provided an opportunity to gain new knowledge for mitigation options through a combined social network and simulation modeling approach. The analysis revealed similar network trends for non-infected and infected cattle farms despite stringent cattle movement restrictions imposed on infected farms in the national control program. The strongest predictive factor for farms becoming infected was their cattle movement activities in the previous month, with twice the effect of local transmission. The simulation model indicated an endemic S. Dublin occurrence, with peaks in outbreak probabilities and sizes around observed cattle movement activities. Therefore, pre- and post-movement measures within a 1-mo time-window may help reduce S. Dublin spread.

AB - An increasing number of countries are investigating options to stop the spread of the emerging zoonotic infection Salmonella (S.) Dublin, which mainly spreads among bovines and with cattle manure. Detailed surveillance and cattle movement data from an 11-year period in Denmark provided an opportunity to gain new knowledge for mitigation options through a combined social network and simulation modeling approach. The analysis revealed similar network trends for non-infected and infected cattle farms despite stringent cattle movement restrictions imposed on infected farms in the national control program. The strongest predictive factor for farms becoming infected was their cattle movement activities in the previous month, with twice the effect of local transmission. The simulation model indicated an endemic S. Dublin occurrence, with peaks in outbreak probabilities and sizes around observed cattle movement activities. Therefore, pre- and post-movement measures within a 1-mo time-window may help reduce S. Dublin spread.

KW - Faculty of Social Sciences

KW - Salmonella

KW - social network analysis

KW - animal movement

KW - cattle

KW - Denmark

U2 - 10.3168/jds.2023-24554

DO - 10.3168/jds.2023-24554

M3 - Journal article

C2 - 38788850

JO - Journal of Dairy Science

JF - Journal of Dairy Science

SN - 0022-0302

M1 - 2023-24554

ER -