Search

The definition of the spatial relatedness between infectious and susceptible animal groups is a fundamental component of spatio-temporal modelling of disease outbreaks. A common neighbourhood definition for disease spread in wild and feral animal populations is the distance between the centroids of neighbouring group home ranges. This distance can be used to define neighbourhood interactions, and also to describe the probability of successful disease transmission. Key limitations of this approach are (1) that a susceptible neighbour of an infectious group with an overlapping home range - but whose centroid lies outside the home range of an infectious group - will not be considered for disease transmission, and (2) the degree of overlap between the home ranges is not taken into account for those groups with centroids inside the infectious home range. We assessed the impact of both distance-based and range overlap methods of disease transmission on model-predicted disease spread. Range overlap was calculated using home ranges modelled as circles. We used the Sirca geographic automata model, with the population data from a nine-county study area in Texas that we have previously described. For each method we applied 100 model repetitions, each of 100 time steps, to 30 index locations. The results show that the rate of disease spread for the range-overlap method is clearly less than the distance-based method, with median outbreaks modelled using the latter being 1.4-1.45 times larger. However, the two methods show similar overall trends in the area infected, and the range-overlap median (48 and 120 for cattle and pigs, respectively) falls within the 5th-95th percentile range of the distance-based method (0-96 and 0-252 for cattle and pigs, respectively). These differences can be attributed to the calculation of the interaction probabilities in the two methods, with overlap weights generally resulting in lower interaction probabilities. The definition of spatial neighbourhood has important implications for models used in decision-support systems for disease preparedness and response. This research presents a first step towards more realistic representations that could be used in spatio-temporal models of disease outbreaks., (Copyright © 2011 Elsevier B.V. All rights reserved.)

The United States has been free of FMD since the 1920s. Faced with an incursion of FMD virus that might involve wildlife species, it is crucial that appropriate mitigation strategies be applied rapidly to control the disease. Disease spread models can be used to evaluate the design of optimal strategies. Using a previously developed susceptible-infected-recovered geographic automata model (Sirca) to simulate the spread of FMD through white-tailed deer populations in south Texas, we conducted a series of experiments to determine how pre-emptive mitigation strategies applied to white-tailed deer populations might impact the predicted magnitude and distribution of outbreaks following FMD virus incursion. Based on previously derived deer distributions in the two ecoregions found within the study area, simulated outbreaks were evaluated by comparing the median number of deer predicted to be infected and the median area predicted affected for a baseline scenario and 3 mitigation strategies: targeted cull, random cull and targeted depopulation buffer. Substantial differences were observed in the predicted magnitude of outbreaks both by mitigation strategy and by ecoregion: depending on the ecoregion, the creation of a targeted depopulation buffer could reduce the number of deer predicted infected by up to 52%, and the area affected by up to 31%. Results suggest that the outcome of an FMD incursion that involves wildlife species, such as white-tailed deer in south Texas, might depend on both where the incursion occurs and the type of pre-emptive mitigation strategy applied., (Copyright 2010 Elsevier B.V. All rights reserved.)

We investigated how the size and distribution of wild deer and feral pigs - species that might act as potential foot-and-mouth disease (FMD) virus maintenance hosts - might affect the persistence and spread of FMD. We used a susceptible-latent-infected-recovered geographic-automata model and spatially referenced data from southern Texas, USA. Within this study area, 100 locations were randomly selected and FMD virus spread was simulated (50 simulations each) at each location. As expected, the predicted sizes (km(2)) of the wild deer outbreaks were highly correlated (r(SP)>0.95) with the number of deer at incursion locations, the total number of deer within 2 km of incursion locations, and the minimum and maximum deer herd size within 2 km of incursion locations. However, the predicted sizes of the feral pig outbreaks were only moderately correlated (r(SP) 0.63-0.67) with the total, maximum and variance of the number of feral pigs within 2 km of incursion locations. Lack of continuity within the feral pig herd distribution across the landscape makes predicting disease spread more difficult than for deer, a more homogenously distributed species. When assessing the potential of wild and feral animal species at a locality to act as maintenance hosts of FMD virus, estimates of the population size and distribution might serve as a useful indicator of potential outbreaks in some circumstances.

We describe an approach to modelling the spatio-temporal spread of foot and mouth disease through feral animal and unfenced livestock populations. We used a susceptible-infected-recovered model, implemented in a cellular automata framework, to assess the spread of FMD across two regions of Queensland, Australia. Following a sensitivity analysis on the infectious states, scenario analyses were conducted using feral pigs only as the susceptible population, and then with the addition of livestock, and initiated in the wet season and in the dry season. The results indicate that, depending on the season the outbreak is initiated, and without the implementation of control measures, an outbreak of Foot and Mouth Disease around Winton could continue unchecked, while an outbreak around Cape York may die out naturally. The approach explicitly incorporates the spatial relationships between the populations through which the disease spreads and provides a framework by which the spread of disease outbreaks can be explored through varying the model parameters. It highlights the emergence and importance of spatio-temporal patterns, something that previous modelling of FMD in feral animal and unfenced livestock populations has lacked.