title: Bayesian modelling of hunting data may improve the understanding of host-parasite systems: wild boar diseases and vaccination as an example.
abstract: Wildlife diseases are often studied using hunting data. In such studies, inferences about diseases are often made by comparing raw disease prevalence levels, ignoring complications like stochasticity in recruitment. We carried out a field trial to study the effectiveness of oral vaccination of wild boar (Sus scrofa) against classical swine fever (CSF) in the Vosges mountains (Northeastern France) for 3 years (2008-2010). Since August 2004, hunters had carried out three vaccination sessions per year in spring, summer and autumn. During our study period, we determined whether each wild boar hunted in our study area was immunized or not against CSF. We used a Bayesian approach to model the changes in the proportion of vaccinated animals in the population of young animals (i.e., <12 months old). This approach allowed to disentangle the effects of the birth peaks (leading to a decrease) and of both the vaccination sessions and natural infection (leading to an increase) on this proportion. We thus inferred, at the individual level, the probability that a non-immunized animal became vaccinated after a particular session. There was a high between-year variability in the effectiveness of the vaccination: the observed patterns were similar in 2008 and 2010, but 2009 was characterized by an overall greater effectiveness of the vaccination. Within a particular year, the spring vaccination session was more effective than the autumn session, probably because of the higher food availability in autumn that render the vaccination places less attractive to the animals. The vaccination effectiveness was rather low in summer, except in 2009, probably because of higher age identification error this year. This model also highlighted an immunisation of animals occurring outside vaccination periods, which suggests either the presence of the CSF virus in our study area, or the consumption of the vaccine outside the vaccination sessions. Finally, we observed a high spatial variability of the probability of vaccination. The effectiveness of the vaccination was indeed strongly related to both the distribution of the forests and the distribution of the vaccination places in our study area. This study highlights an optimal vaccination effort of 1.25 places per km(2) to maximize the proportion of immune wild boar in that area.
authors.affiliation: Office national de la chasse et de la faune sauvage, Saint Benoist, BP 20. 78612 Le Perray en Yvelines, France. Electronic address: clement.calenge@oncfs.gouv.fr.
authors.forename: Clément
authors.initials: C
authors.lastname: Calenge
authors.affiliation: Office national de la chasse et de la faune sauvage, Micropolis, F-05000 Gap, France. Electronic address: sophie.rossi@oncfs.gouv.fr.
authors.forename: Sophie
authors.initials: S
authors.lastname: Rossi
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D006691:Classical Swine Fever / Q000276:immunology; D005602:France; D005843:Geography; D006790:Host-Parasite Interactions; D008390:Markov Chains; D008954:Models, Biological; D009010:Monte Carlo Method; D011336:Probability; D034421:Sus scrofa / Q000276:immunology* / Q000469:parasitology*; D013552:Swine; D013553:Swine Diseases / Q000276:immunology* / Q000469:parasitology*; D013997:Time Factors; D014611:Vaccination
keywords: Hierarchical model; Markov chain Monte Carlo; Oral immunisation; Sus Scrofa; Vaccine