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.
Q fever in dairy cattle herds occurs mainly after inhalation of contaminated aerosols generated from excreta by shedder animals. Propagation of Coxiella burnetii, the cause of the disease between ruminant herds could result from transmission between neighbouring herds and/or the introduction of infected shedder animals in healthy herds. The objective of this study were (i) to describe the spatial distribution C. burnetii-infected dairy cattle herds in two different regions: the Finistère District in France (2,829 herds) and the island of Gotland in Sweden (119 herds) and (ii) to quantify and compare the relative contributions of C. burnetii transmission related to neighbourhood and to animal movements on the risk for a herd to be infected. An enzyme--linked immunosorbent assay was used for testing bulk tank milk in May 2012 and June 2011, respectively. Only one geographical cluster of positive herds was identified in north-western Finistère. Logistic regression was used to assess the association of risk for a herd to test positively with local cattle density (the total number of cattle located in a 5 km radius circle) and the in-degree (ID) parameter, a measure of the number of herds from which each herd had received animals directly within the last 2 years. The risk for a herd to test positively was higher for herds with a higher local cattle density [odds ratio (OR) = 2.3, 95% confidence interval (CI) = 1.6-3.2, for herds with a local density between 100 and 120 compared to herds with a local density 60]. The risk was also higher for herds with higher IDs (OR = 2.3, 95% CI = 1.6-3.2, for herds with ID 3 compared to herds that did not introduce animals). The proportion of cases attributable to infections in the neighbourhood in high-density areas was twice the proportion attributable to animal movements, suggesting that wind plays a main role in the transmission.