Inferences about the transmission of Schmallenberg virus within and between farms



Gubbins, Simon, Turner, Joanne ORCID: 0000-0002-0258-2353, Baylis, Matthew ORCID: 0000-0003-0335-187X, van der Stede, Yves, van Schaik, Gerdien, Abrahantes, Jose Cortinas and Wilson, Anthony J
(2014) Inferences about the transmission of Schmallenberg virus within and between farms. PREVENTIVE VETERINARY MEDICINE, 116 (4). pp. 380-390.

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Abstract

In the summer of 2011 Schmallenberg virus (SBV), a Culicoides-borne orthobunyavirus, emerged in Germany and The Netherlands and subsequently spread across much of Europe. To draw inferences about the transmission of SBV we have developed two models to describe its spread within and between farms. The within-farm model was fitted to seroprevalence data for cattle and sheep farms in Belgium and The Netherlands, with parameters estimated using approximate Bayesian computation. Despite the short duration of viraemia in cattle and sheep (mean of 3-4 days) the within-farm seroprevalence can reach high levels (mean within-herd seroprevalence >80%), largely because the probability of transmission from host to vector is high (14%) and SBV is able to replicate quickly (0.03 per day-degree) and at relatively low temperatures (threshold for replication: 12.3°C). Parameter estimates from the within-farm model were then used in a separate between-farm model to simulate the regional spread of SBV. This showed that the rapid spread of SBV at a regional level is primarily a consequence of the high probability of transmission from host to vector and the temperature requirements for virus replication. Our results, obtained for a region of the UK in a typical year with regard to animal movements, indicate that there is no need to invoke additional transmission mechanisms to explain the observed patterns of rapid spread of SBV in Europe. Moreover, the imposition of movement restrictions, even a total movement ban, has little effect on the spread of SBV at this scale.

Item Type: Article
Additional Information: ## TULIP Type: Articles/Papers (Journal) ##
Uncontrolled Keywords: Epidemiology, SBV, Modelling, Vector-borne disease, Approximate Bayesian computation
Depositing User: Symplectic Admin
Date Deposited: 10 Dec 2014 08:55
Last Modified: 15 Dec 2022 11:52
DOI: 10.1016/j.prevetmed.2014.04.011
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/2003379