A review of geospatial and ecological factors affecting disease spread in wild pigs: Considerations for models of foot-and-mouth disease spread

Modelling African swine fever introduction in diverse Australian feral pig populations

African swine fever (ASF) is a viral disease that affects domestic and feral pigs. While not currently present in Australia, ASF outbreaks have been reported nearby in Indonesia, Timor-Leste, and Papua New Guinea. Feral pigs are found in all Australian states and territories and are distributed in a variety of habitats. To investigate the impacts of an ASF introduction event in Australia, we used a stochastic network-based metapopulation feral pig model to simulate ASF outbreaks in different regions of Australia. Outbreak intensity and persistence in feral pig populations was governed by local pig recruitment rates, population size, carcass decay period, and, if applicable, metapopulation topology. In Northern Australia, the carcass decay period was too short for prolonged persistence, while endemic transmission could possibly occur in cooler southern areas. Populations in Macquarie Marshes in New South Wales and in Namadgi National Park in the Australian Capital Territory had the highest rates of persistence. The regions had different modes of transmission that led to long-term persistence. Endemic Macquarie Marshes simulations were characterised by rapid transmission caused by high population density that required a fragmented metapopulation to act as a bottleneck to slow transmission. Endemic simulations in Namadgi, with low density and relatively slow transmission, relied on large, well-connected populations coupled with long carcass decay times. Despite the potential for endemic transmission, both settings required potentially unlikely population sizes and dynamics for prolonged disease survival.

Novel estimation of African swine fever transmission parameters within smallholder villages in Lao P.D.R

African Swine Fever (ASF) disease transmission parameters are crucial for making response and control decisions when faced with an outbreak, yet they are poorly quantified for smallholder and village contexts within Southeast Asia. Whilst disease-specific factors - such as latent and infectious periods - should remain reasonably consistent, host, environmental and management factors are likely to affect the rate of disease spread. These differences are investigated using Approximate Bayesian Computation with Sequential Monte-Carlo methods to provide disease parameter estimates in four naïve pig populations in villages of Lao People's Democratic Republic. The villages represent smallholder pig farmers of the Northern province of Oudomxay and the Southern province of Savannakhet, and the model utilised field mortality data to validate the transmission parameter estimates over the course of multiple model generations. The basic reproductive number between-pigs was estimated to range from 3.08 to 7.80, whilst the latent and infectious periods were consistent with those published in the literature for similar genotypes in the region (4.72 to 6.19 days and 2.63 to 5.50 days, respectively). These findings demonstrate that smallholder village pigs interact similarly to commercial pigs, however the spread of disease may occur slightly slower than in commercial study groups. Furthermore, the findings demonstrated that despite diversity across the study groups, the disease behaved in a consistent manner. This data can be used in disease control programs or for future modelling of ASF in smallholder contexts.

Mathematical modeling at the livestock-wildlife interface: scoping review of drivers of disease transmission between species

Modeling of infectious diseases at the livestock-wildlife interface is a unique subset of mathematical modeling with many innate challenges. To ascertain the characteristics of the models used in these scenarios, a scoping review of the scientific literature was conducted. Fifty-six studies qualified for inclusion. Only 14 diseases at this interface have benefited from the utility of mathematical modeling, despite a far greater number of shared diseases. The most represented species combinations were cattle and badgers (for bovine tuberculosis, 14), and pigs and wild boar [for African (8) and classical (3) swine fever, and foot-and-mouth and disease (1)]. Assessing control strategies was the overwhelming primary research objective (27), with most studies examining control strategies applied to wildlife hosts and the effect on domestic hosts (10) or both wild and domestic hosts (5). In spatially-explicit models, while livestock species can often be represented through explicit and identifiable location data (such as farm, herd, or pasture locations), wildlife locations are often inferred using habitat suitability as a proxy. Though there are innate assumptions that may not be fully accurate when using habitat suitability to represent wildlife presence, especially for wildlife the parsimony principle plays a large role in modeling diseases at this interface, where parameters are difficult to document or require a high level of data for inference. Explaining observed transmission dynamics was another common model objective, though the relative contribution of involved species to epizootic propagation was only ascertained in a few models. More direct evidence of disease spill-over, as can be obtained through genomic approaches based on pathogen sequences, could be a useful complement to further inform such modeling. As computational and programmatic capabilities advance, the resolution of the models and data used in these models will likely be able to increase as well, with a potential goal being the linking of modern complex ecological models with the depth of dynamics responsible for pathogen transmission. Controlling diseases at this interface is a critical step toward improving both livestock and wildlife health, and mechanistic models are becoming increasingly used to explore the strategies needed to confront these diseases.

Do wild suids from Ndumo Game Reserve, South Africa, play a role in the maintenance and transmission of African swine fever to domestic pigs?

Warthogs (Phacochoerus africanus) and bushpigs (Potamochoerus larvatus) are considered as the wild reservoirs of ASF. They are both present in Ndumo Game Reserve (NGR), located in the Northern South African Province of KwaZulu on the border with Mozambique. In that area, the occurrence of tick-warthog sylvatic cycle of ASF has been suspected for years. To assess if wild suids represent a risk of ASF virus spillover to domestic pigs, wild suid abundance and incursions outside NGR boundaries were estimated using transect counts, fence patrols and camera traps. Also, the presence of Ornithodoros ticks was explored in 35 warthog burrows within NGR. In addition, blood samples were taken from 67 domestic pig farms located outside NGR to be tested for ASF antibodies. Information on interactions between domestic and wild suids and ASF occurrence was gathered using interviews with pig farmers (n = 254) in the study area. In conclusion, the bushpigs and warthog's population estimates in NGR are 5 and 3-5 individuals/km² , respectively. Both species move out of the reserve regularly (15.4 warthogs/day and 6.35 bushpigs/day), with movements significantly increasing in the dry season. Some farmers observed warthogs and bushpigs as far as 8 and 19 km from NGR, respectively, but no reports of direct wild-domestic suids interactions or ASF outbreaks. Also, no soft ticks were detected in all warthog burrows and all the pig blood samples were negative for ASF antibodies. The absence of ticks in warthog burrows, the absence of antibodies in pigs sampled, the absence of reported outbreaks, and no familiarity with ASF in the study area, suggest that a sylvatic cycle of ASF is, at present, unlikely in NGR. This conclusion must be confirmed by a larger survey of warthog burrows and monitoring potential antibodies in warthogs from NGR.

Effects of social structure and management on risk of disease establishment in wild pigs

Contact heterogeneity among hosts determines invasion and spreading dynamics of infectious disease, thus its characterization is essential for identifying effective disease control strategies. Yet, little is known about the factors shaping contact networks in many wildlife species and how wildlife management actions might affect contact networks. Wild pigs in North America are an invasive, socially structured species that pose a health concern for domestic swine given their ability to transmit numerous devastating diseases such as African swine fever (ASF). Using proximity loggers and GPS data from 48 wild pigs in Florida and South Carolina, USA, we employed a probabilistic framework to estimate weighted contact networks. We determined the effects of sex, social group and spatial distribution (monthly home-range overlap and distance) on wild pig contact. We also estimated the impacts of management-induced perturbations on contact and inferred their effects on ASF establishment in wild pigs with simulation. Social group membership was the primary factor influencing contacts. Between-group contacts depended primarily on space use characteristics, with fewer contacts among groups separated by >2 km and no contacts among groups >4 km apart within a month. Modelling ASF dynamics on the contact network demonstrated that indirect contacts resulting from baiting (a typical method of attracting wild pigs or game species to a site to enhance recreational hunting) increased the risk of disease establishment by ~33% relative to direct contact. Low-intensity population reduction (<5.9% of the population) had no detectable impact on contact structure but reduced predicted ASF establishment risk relative to no population reduction. We demonstrate an approach for understanding the relative role of spatial, social and individual-level characteristics in shaping contact networks and predicting their effects on disease establishment risk, thus providing insight for optimizing disease control in spatially and socially structured wildlife species.

Dispersal and Land Cover Contribute to Pseudorabies Virus Exposure in Invasive Wild Pigs

We investigated the landscape epidemiology of a globally distributed mammal, the wild pig (Sus scrofa), in Florida (U.S.), where it is considered an invasive species and reservoir to pathogens that impact the health of people, domestic animals, and wildlife. Specifically, we tested the hypothesis that two commonly cited factors in disease transmission, connectivity among populations and abundant resources, would increase the likelihood of exposure to both pseudorabies virus (PrV) and Brucella spp. (bacterial agent of brucellosis) in wild pigs across the Kissimmee Valley of Florida. Using DNA from 348 wild pigs and sera from 320 individuals at 24 sites, we employed population genetic techniques to infer individual dispersal, and an Akaike information criterion framework to compare candidate logistic regression models that incorporated both dispersal and land cover composition. Our findings suggested that recent dispersal conferred higher odds of exposure to PrV, but not Brucella spp., among wild pigs throughout the Kissimmee Valley region. Odds of exposure also increased in association with agriculture and open canopy pine, prairie, and scrub habitats, likely because of highly localized resources within those land cover types. Because the effect of open canopy on PrV exposure reversed when agricultural cover was available, we suggest that small-scale resource distribution may be more important than overall resource abundance. Our results underscore the importance of studying and managing disease dynamics through multiple processes and spatial scales, particularly for non-native pathogens that threaten wildlife conservation, economy, and public health.

How many feral pigs in Australia? An update

The abundance of feral pigs in Australia has been estimated previously and been a topic of some debate. This study aims to update a previous estimate of abundance (13.5 million, 95% CI: 3.5 million to 23.5 million) of feral pigs in Australia. Abundance estimates for the 1970s, 1980s, 1990s, 2000s and 2010s were collated from published literature. Mean abundances in the middle decades were estimated using the ratio method. The average abundance of feral pigs varied from 4.4 million (95% CI: 2.4 million to 6.3 million) in the 1980s, to 3.0 million (95% CI: 2.3 million to 3.7 million) in the 1990s, to 3.2 million (95% CI: 2.4 million to 4.0 million) in the 2000s. Mean density across all 142 studies was 1.03 pigs km–2. The average abundance of feral pigs in Australia during the 1980s to 2000s was much lower and more precise than estimated previously, so scientists and managers should update their use of abundance estimates. Density estimates are above, and below, estimates of threshold host densities for infectious exotic disease establishment.

Challenges and Opportunities Developing Mathematical Models of Shared Pathogens of Domestic and Wild Animals

Diseases that affect both wild and domestic animals can be particularly difficult to prevent, predict, mitigate, and control. Such multi-host diseases can have devastating economic impacts on domestic animal producers and can present significant challenges to wildlife populations, particularly for populations of conservation concern. Few mathematical models exist that capture the complexities of these multi-host pathogens, yet the development of such models would allow us to estimate and compare the potential effectiveness of management actions for mitigating or suppressing disease in wildlife and/or livestock host populations. We conducted a workshop in March 2014 to identify the challenges associated with developing models of pathogen transmission across the wildlife-livestock interface. The development of mathematical models of pathogen transmission at this interface is hampered by the difficulties associated with describing the host-pathogen systems, including: (1) the identity of wildlife hosts, their distributions, and movement patterns; (2) the pathogen transmission pathways between wildlife and domestic animals; (3) the effects of the disease and concomitant mitigation efforts on wild and domestic animal populations; and (4) barriers to communication between sectors. To promote the development of mathematical models of transmission at this interface, we recommend further integration of modern quantitative techniques and improvement of communication among wildlife biologists, mathematical modelers, veterinary medicine professionals, producers, and other stakeholders concerned with the consequences of pathogen transmission at this important, yet poorly understood, interface.

Modelling seasonal habitat suitability for wide-ranging species: Invasive wild pigs in northern Australia

Invasive wildlife often causes serious damage to the economy and agriculture as well as environmental, human and animal health. Habitat models can fill knowledge gaps about species distributions and assist planning to mitigate impacts. Yet, model accuracy and utility may be compromised by small study areas and limited integration of species ecology or temporal variability. Here we modelled seasonal habitat suitability for wild pigs, a widespread and harmful invader, in northern Australia. We developed a resource-based, spatially-explicit and regional-scale approach using Bayesian networks and spatial pattern suitability analysis. We integrated important ecological factors such as variability in environmental conditions, breeding requirements and home range movements. The habitat model was parameterized during a structured, iterative expert elicitation process and applied to a wet season and a dry season scenario. Model performance and uncertainty was evaluated against independent distributional data sets. Validation results showed that an expert-averaged model accurately predicted empirical wild pig presences in northern Australia for both seasonal scenarios. Model uncertainty was largely associated with different expert assumptions about wild pigs' resource-seeking home range movements. Habitat suitability varied considerably between seasons, retracting to resource-abundant rainforest, wetland and agricultural refuge areas during the dry season and expanding widely into surrounding grassland floodplains, savanna woodlands and coastal shrubs during the wet season. Overall, our model suggested that suitable wild pig habitat is less widely available in northern Australia than previously thought. Mapped results may be used to quantify impacts, assess risks, justify management investments and target control activities. Our methods are applicable to other wide-ranging species, especially in data-poor situations.

Disease-emergence dynamics and control in a socially-structured wildlife species

Once a pathogen is introduced in a population, key factors governing rate of spread include contact structure, supply of susceptible individuals and pathogen life-history. We examined the interplay of these factors on emergence dynamics and efficacy of disease prevention and response. We contrasted transmission dynamics of livestock viruses with different life-histories in hypothetical populations of feral swine with different contact structures (homogenous, metapopulation, spatial and network). Persistence probability was near 0 for the FMDV-like case under a wide range of parameter values and contact structures, while persistence was probable for the CSFV-like case. There were no sets of conditions where the FMDV-like pathogen persisted in every stochastic simulation. Even when population growth rates were up to 300% annually, the FMDV-like pathogen persisted in <25% of simulations regardless of transmission probabilities and contact structure. For networks and spatial contact structure, persistence probability of the FMDV-like pathogen was always <10%. Because of its low persistence probability, even very early response to the FMDV-like pathogen in feral swine was unwarranted while response to the CSFV-like pathogen was generally effective. When pre-emergence culling of feral swine caused population declines, it was effective at decreasing outbreak size of both diseases by ≥80%.

Modelling foot-and-mouth disease transmission in a wild pig-domestic cattle ecosystem

OBJECTIVE

To use simulation modelling to predict the potential spread and to explore control options for a foot-and-mouth disease (FMD) incursion in a mixed wild pig-domestic cattle ecosystem in northern Australia.

DESIGN

Based on aerial surveys, expert opinion and published data, the wild pig and grazing cattle distributions were simulated. A susceptible-infected-resistant disease-spread model was coded and parameterised according to published literature and expert opinion.

METHODS

A baseline scenario was simulated in which infection was introduced via wild pigs, with transmission from pigs to cattle and no disease control. Assumptions regarding disease transmission were investigated via sensitivity analyses. Predicted size and length of outbreaks were compared for different control strategies based on movement standstill, surveillance and depopulation.

RESULTS

In most of the simulations, FMD outbreaks were predicted to be ongoing after 6 months, with more cattle herds infected than wild pig herds (median 907 vs. 22, respectively). Assuming only pig-to-pig transmission, the infection routinely died out. In contrast, assuming cattle-to-cattle, cattle-to-pig or pig-to-cattle transmission resulted in FMD establishing and spreading in more than 75% of simulations. A control strategy targeting wild pigs only was not predicted to be successful. Control based on cattle only was successful in eradicating the disease. However, control targeting both pigs and cattle resulted in smaller outbreaks.

CONCLUSIONS

If FMD is controlled in cattle in the modelled ecosystem, it is likely to be self-limiting in wild pigs. However, to eradicate disease as quickly as possible, both wild pigs and cattle should be targeted for control.

Assessing the potential spread and maintenance of foot-and-mouth disease virus infection in wild ungulates: general principles and application to a specific scenario in Thrace

Foot-and-mouth disease (FMD), due to infection with serotype O virus, occurred in wild boar and within eleven outbreaks in domestic livestock in the south-east of Bulgaria, Thrace region, in 2011. Hence, the issue of the potential for the spread and maintenance of FMD virus (FMDV) infection in a population of wild ungulates became important. This assessment focused on the spread and maintenance of FMDV infection within a hypothetical wild boar and deer population in an environment, which is characterized by a climate transitional between Mediterranean and continental and variable wildlife population densities. The assessment was based on three aspects: (i) a systematic review of the literature focusing on experimental infection studies to identify the parameters describing the duration of FMDV infection in deer and wild boar, as well as observational studies assessing the occurrence of FMDV infection in wild deer and wild boar populations, (ii) prevalence survey data of wild boar and deer in Bulgaria and Turkey and (iii) an epidemiological model, simulating the host-to-host spread of FMDV infections. It is concluded, based on all three aspects, that the wildlife population in Thrace, and so wildlife populations in similar ecological settings, are probably not able to maintain FMD in the long term in the absence of FMDV infection in the domestic host population. However, limited spread of FMDV infection in time and space in the wildlife populations can occur. If there is a continued cross-over of FMDV between domestic and wildlife populations or a higher population density, virus circulation may be prolonged.

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.

Potential impact of introduction of foot-and-mouth disease from wild pigs into commercial livestock premises in California

OBJECTIVE

To estimate potential spread of foot-and-mouth disease (FMD) if introduced from wild pigs in California and to evaluate efficacies of various control strategies.

SAMPLE POPULATION

Data for California livestock and from hunter surveys on wild pigs in California.

PROCEDURES

A spatial, stochastic simulation model was used to simulate FMD epidemics that might occur if a dairy or beef herd were infected from contact with a wild pig. Index herd location and type were examined, in addition to different statewide movement ban (SWMB) durations, to determine their effect on extent of the epidemic.

RESULTS

Duration, number of infected premises, size of simulated outbreak, number of culled animals, and spatial distribution of infected herds resulting from the simulated outbreaks varied considerably among geographic regions, depending on index case type and location. Outbreaks beginning in the southern region of California were consistently longest, whereas those beginning in the northern region were shortest. The largest outbreaks resulted from index cases located in the southern and valley regions, whereas outbreaks were smallest when originating in the Sonoma or northern regions. For all regions, when the index herd was a dairy herd, size and duration of the outbreak were consistently reduced with implementation of an SWMB >or= 3 days.

CONCLUSIONS AND CLINICAL RELEVANCE

Introduction of FMDV from wild pigs into a dairy or beef herd could result in a large and rapidly spreading outbreak, potentially affecting large numbers of herds. Size and duration of the outbreak might be reduced with an SWMB; however, the impact is highly dependent on the index herd type and location.

Spatial epidemiology in zoonotic parasitic diseases: insights gained at the 1st International Symposium on Geospatial Health in Lijiang, China, 2007

The 1st International Symposium on Geospatial Health was convened in Lijiang, Yunnan province, People's Republic of China from 8 to 9 September, 2007. The objective was to review progress made with the application of spatial techniques on zoonotic parasitic diseases, particularly in Southeast Asia. The symposium featured 71 presentations covering soil-transmitted and water-borne helminth infections, as well as arthropod-borne diseases such as leishmaniasis, malaria and lymphatic filariasis. The work made public at this occasion is briefly summarized here to highlight the advances made and to put forth research priorities in this area. Approaches such as geographical information systems (GIS), global positioning systems (GPS) and remote sensing (RS), including spatial statistics, web-based GIS and map visualization of field investigations, figured prominently in the presentation.