title: A novel method to identify herds with an increased probability of disease introduction due to animal trade.
abstract: In the design of surveillance, there is often a desire to target high risk herds. Such risk-based approaches result in better allocation of resources and improve the performance of surveillance activities. For many contagious animal diseases, movement of live animals is a main route of transmission, and because of this, herds that purchase many live animals or have a large contact network due to trade can be seen as a high risk stratum of the population. This paper presents a new method to assess herd disease risk in animal movement networks. It is an improvement to current network measures that takes direction, temporal order, and also movement size and probability of disease into account. In the study, the method was used to calculate a probability of disease ratio (PDR) of herds in simulated datasets, and of real herds based on animal movement data from dairy herds included in a bulk milk survey for Coxiella burnetii. Known differences in probability of disease are easily incorporated in the calculations and the PDR was calculated while accounting for regional differences in probability of disease, and also by applying equal probability of disease throughout the population. Each herd's increased probability of disease due to purchase of animals was compared to both the average herd and herds within the same risk stratum. The results show that the PDR is able to capture the different circumstances related to disease prevalence and animal trade contact patterns. Comparison of results based on inclusion or exclusion of differences in risk also highlights how ignoring such differences can influence the ability to correctly identify high risk herds. The method shows a potential to be useful for risk-based surveillance, in the classification of herds in control programmes or to represent influential contacts in risk factor studies.
authors.affiliation: Department of Disease Control and Epidemiology, National Veterinary Institute (SVA), SE-751 89 Uppsala, Sweden; Department of Animal Environment and Health, Swedish University of Agricultural Sciences (SLU), Box 234, SE-532 23 Skara, Sweden. Electronic address: jenny.frossling@sva.se.
authors.forename: Jenny
authors.initials: J
authors.lastname: Frössling
authors.affiliation: INRA, UMR1300 Biology, Epidemiology and Risk Analysis (BioEpAR), La Chantrerie, CS 40706, 44307 Nantes, France; LUNAM Université, Oniris, UMR BioEpAR, CS 40706, 44307 Nantes, France.
authors.forename: Simon
authors.initials: S
authors.lastname: Nusinovici
authors.affiliation: Department of Disease Control and Epidemiology, National Veterinary Institute (SVA), SE-751 89 Uppsala, Sweden.
authors.forename: Maria
authors.initials: M
authors.lastname: Nöremark
authors.affiliation: Department of Disease Control and Epidemiology, National Veterinary Institute (SVA), SE-751 89 Uppsala, Sweden.
authors.forename: Stefan
authors.initials: S
authors.lastname: Widgren
authors.affiliation: Department of Disease Control and Epidemiology, National Veterinary Institute (SVA), SE-751 89 Uppsala, Sweden.
authors.forename: Ann
authors.initials: A
authors.lastname: Lindberg
mesh_terms: D063147:Animal Distribution; D000818:Animals; D002417:Cattle; D002418:Cattle Diseases / Q000453:epidemiology / Q000382:microbiology* / Q000635:transmission; D003198:Computer Simulation; D016997:Coxiella burnetii / Q000254:growth & development*; D062665:Epidemiological Monitoring / Q000662:veterinary*; D005260:Female; D008892:Milk / Q000382:microbiology; D015995:Prevalence; D011778:Q Fever / Q000453:epidemiology / Q000382:microbiology / Q000635:transmission / Q000662:veterinary*; D018570:Risk Assessment / Q000379:methods; D013548:Sweden / Q000453:epidemiology
keywords: Animal movement; Cattle; Contact network; Coxiella burnetii; Probability of disease ratio