Controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in Australia.

Disease modelling is one approach for providing new insights into wildlife disease epidemiology. This paper describes a spatio-temporal, stochastic, susceptible- exposed-infected-recovered process model that simulates the potential spread of classical swine fever through a documented, large and free living wild pig population following a simulated incursion. The study area (300 000 km2) was in northern Australia. Published data on wild pig ecology from Australia, and international Classical Swine Fever data was used to parameterise the model. Sensitivity analyses revealed that herd density (best estimate 1-3 pigs km-2), daily herd movement distances (best estimate approximately 1 km), probability of infection transmission between herds (best estimate 0.75) and disease related herd mortality (best estimate 42%) were highly influential on epidemic size but that extraordinary movements of pigs and the yearly home range size of a pig herd were not. CSF generally established (98% of simulations) following a single point introduction. CSF spread at approximately 9 km2 per day with low incidence rates (< 2 herds per day) in an epidemic wave along contiguous habitat for several years, before dying out (when the epidemic arrived at the end of a contiguous sub-population or at a low density wild pig area). The low incidence rate indicates that surveillance for wildlife disease epidemics caused by short lived infections will be most efficient when surveillance is based on detection and investigation of clinical events, although this may not always be practical. Epidemics could be contained and eradicated with culling (aerial shooting) or vaccination when these were adequately implemented. It was apparent that the spatial structure, ecology and behaviour of wild populations must be accounted for during disease management in wildlife. An important finding was that it may only be necessary to cull or vaccinate relatively small proportions of a population to successfully contain and eradicate some wildlife disease epidemics.

Salmonella infection in a remote, isolated wild pig population.

Although wild pig populations are known to sometimes be infected by Salmonella, the situation in Australia has received little attention and few population-based, planned studies have been conducted. Understanding the distribution of Salmonella infections within wild pig populations allows the potential hazard posed to co-grazing livestock to be assessed. We sampled a remote and isolated wild pig population in northwestern Australia. Faecal and mesenteric lymph node samples were collected from 651 wild pigs at 93 locations and cultured for Salmonella. The population sampled was typical of wild pig populations in tropical areas of Australia, and sampling occurred approximately halfway through the population's breeding season (38% of the 229 adult females were pregnant and 35% were lactating). Overall, the prevalence of Salmonella infection based on culture of 546 freshly collected faecal samples was 36.3% (95% CI 32.1-40.7%), and based on culture of mesenteric lymph nodes was 11.9% (95% CI, 9.4-15.0%). A total of 39 serovars (139 isolates) were identified--29 in faecal samples and 24 in lymph node samples--however neither Salmonella enterica serovar Typhimurium nor Salmonella Cholerasuis were isolated. There was a significant (p<0.0001) disagreement between faecal and lymph node samples with respect to Salmonella isolation, with isolation more likely from faecal samples. Prevalence differed between age classes, with piglets being less likely to be faecal-positive but more likely to be lymph node positive than adults. The distribution of faecal-positive pigs was spatially structured, with spatial clusters being identified. Study results suggest that this population of wild pigs is highly endemic for Salmonella, and that Salmonella is transmitted from older to younger pigs, perhaps associated with landscape features such as water features. This might have implications for infection of co-grazing livestock within this environment.

Integrating survey and molecular approaches to better understand wildlife disease ecology.

Infectious wildlife diseases have enormous global impacts, leading to human pandemics, global biodiversity declines and socio-economic hardship. Understanding how infection persists and is transmitted in wildlife is critical for managing diseases, but our understanding is limited. Our study aim was to better understand how infectious disease persists in wildlife populations by integrating genetics, ecology and epidemiology approaches. Specifically, we aimed to determine whether environmental or host factors were stronger drivers of Salmonella persistence or transmission within a remote and isolated wild pig (Sus scrofa) population. We determined the Salmonella infection status of wild pigs. Salmonella isolates were genotyped and a range of data was collected on putative risk factors for Salmonella transmission. We a priori identified several plausible biological hypotheses for Salmonella prevalence (cross sectional study design) versus transmission (molecular case series study design) and fit the data to these models. There were 543 wild pig Salmonella observations, sampled at 93 unique locations. Salmonella prevalence was 41% (95% confidence interval [CI]: 37-45%). The median Salmonella DICE coefficient (or Salmonella genetic similarity) was 52% (interquartile range [IQR]: 42-62%). Using the traditional cross sectional prevalence study design, the only supported model was based on the hypothesis that abundance of available ecological resources determines Salmonella prevalence in wild pigs. In the molecular study design, spatial proximity and herd membership as well as some individual risk factors (sex, condition score and relative density) determined transmission between pigs. Traditional cross sectional surveys and molecular epidemiological approaches are complementary and together can enhance understanding of disease ecology: abundance of ecological resources critical for wildlife influences Salmonella prevalence, whereas Salmonella transmission is driven by local spatial, social, density and individual factors, rather than resources. This enhanced understanding has implications for the control of diseases in wildlife populations. Attempts to manage wildlife disease using simplistic density approaches do not acknowledge the complexity of disease ecology.