Modelling the spread of foot-and-mouth disease in Australia

Preparedness for an incursion of an exotic animal disease is of key importance to government, industry, producers and the Australian community. An important aspect of Australia's preparedness for a possible incursion of foot-and-mouth disease is investigation into the likely effectiveness and cost-efficiency of eradication strategies when applied to different regional outbreak scenarios. Disease modelling is a tool that can be used to study diseases such as foot-and-mouth disease to better understand potential disease spread and control under different conditions. The Australian Government Department of Agriculture, Fisheries and Forestry has been involved with epidemiologic simulation modelling for more than 10 years, and has developed a sophisticated spatial model for foot-and-mouth disease (AusSpread) that operates within a geographic information system framework. The model accommodates real farm boundary or point-location data, as well as synthesised data based on agricultural census and land use information. The model also allows for interactions between herds or flocks of different animal species and production type, and considers the role that such interactions are likely to play in the epidemiology of a regional outbreak of foot-and-mouth disease. The user can choose mitigations and eradication strategies from those that are currently described in Australia's veterinary emergency plan. The model also allows the user to evaluate the impact of constraints on the availability of resources for mitigations or eradication measures. Outputs include a range of maps and tabulated outbreak statistics describing the geographic extent of the outbreak and its duration, the numbers of affected, slaughtered, and, as relevant, vaccinated herds or flocks, and the cost of control and eradication. Cost-related outputs are based on budgets of the value of stock and the cost of mitigations, each of which can be varied by the user. These outputs are a valuable resource to assist with policy development and disease management.     

The role of spatial mixing in the spread of foot-and-mouth disease

A model of epidemic dispersal (based on the assumption that susceptible cattle were homogeneously mixed over space, or non-spatial model) was compared to a partially spatially explicit and discrete model (the spatial model), which was composed of differential equations and used geo-coded data (Euclidean distances between county centroids). While the spatial model accounted for intra- and inter-county epidemic spread, the non-spatial model did not assess regional differences. A geo-coded dataset that resembled conditions favouring homogeneous mixing assumptions (based on the 2001 Uruguayan foot-and-mouth disease epidemic), was used for testing. Significant differences between models were observed in the average transmission rate between farms, both before and after a control policy (animal movement ban) was imposed. They also differed in terms of daily number of infected farms: the non-spatial model revealed a single epidemic peak (at, approximately, 25 epidemic days); while the spatial model revealed two epidemic peaks (at, approximately, 12 and 28 days, respectively). While the spatial model fitted well with the observed cumulative number of infected farms, the non-spatial model did not (P<0.01). In addition, the spatial model: (a) indicated an early intra-county reproductive number R of approximately 87 (falling to <1 within 25 days), and an inter-county R<1; (b) predicted that, if animal movement restrictions had begun 3 days before/after the estimated initiation of such policy, cases would have decreased/increased by 23 or 26%, respectively. Spatial factors (such as inter-farm distance and coverage of vaccination campaigns, absent in non-spatial models) may explain why partially explicit spatial models describe epidemic spread more accurately than non-spatial models even at early epidemic phases. Integration of geo-coded data into mathematical models is recommended.     

A point pattern model of the spread of foot-and-mouth disease

The spatial spread of foot-and-mouth disease (FMD) is influenced by several sources of spatial heterogeneity: heterogeneity of the exposure to the virus, heterogeneity of the animal density and heterogeneity of the networks formed by the contacts between farms. A discrete space model assuming that farms can be reduced to points is proposed to handle these different factors. The farm-to-farm process of transmission of the infection is studied using point-pattern methodology. Farm management, commercial exchanges, possible airborne transmission, etc. cannot be explicitly taken into account because of lack of data. These latter factors are introduced via surrogate variables such as herd size and distance between farms. The model is built on the calculation of an infectious potential for each farm.This method has been applied to the study of the 1967-1968 FMD epidemic in UK and allowed us to evaluate the spatial variation of the probability of infection during this epidemic. Maximum likelihood estimation has been conducted conditional on the absence of data concerning the farms which were not infected during the epidemic. Model parameters have then been tested using an approximated conditional-likelihood ratio test. In this case study, results and validation are limited by the lack of data, but this model can easily be extended to include other information such as the effect of wind direction and velocity on airborne spread of the virus or the complex interactions between the locations of farms and the herd size. It can also be applied to other diseases where point approximation is convenient. In the context of an increase of animal density in some areas, the model explicitly incorporates the density and known epidemiological characteristics (e.g. incubation period) in the calculation of the probability of FMD infection. Control measures such as vaccination or slaughter can be simply introduced, respectively, as a reduction of the susceptible population or as a reduction of the source of infection.     

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

Around the world, wild boar or feral pigs are infected by a range of infectious organisms with important, productivity, public health or economic consequences. Consequently, the potential role of wild pigs in outbreaks of important exotic diseases, like foot-and-mouth disease (FMD), has been a significant consideration in many countries. Disease modelling is one means to study the epidemiology of disease and has been used to assess the potential role of wild pigs in FMD incursions. Many of these models have been strategic in nature. They have contributed to a broad understanding of disease control in wild pigs (e.g. the concept of threshold densities and the need to cull pigs below this density for disease fadeout to occur), but have not incorporated many of the key drivers affecting disease behaviour. Some of these drivers include important ecological, behavioural and geospatial relationships, such as interaction between different host species and the distribution, density and connectivity of pig populations. New approaches to modelling disease spread such as spatial simulation models use spatial data and explicitly incorporate geospatial relationships. These approaches can provide useful quantitative models that can be used to explore mitigation strategies under specific disease outbreak conditions. However, to date, most studies have been limited by inadequate data, and computational issues or have not explored mitigation strategies. To inform management strategies for emergency epidemics such as FMD in wild pigs, there is scope to further develop and use models to explore a range of incursion scenarios and investigate the efficacy of different mitigation strategies.     

Epidemiological basis useful for the control of foot-and-mouth disease

Although known for many years, foot-and-mouth disease is still able to represent a real threat to many farming economies in the world. The recent 2001 Western European epizootics linked to O PanAsia virus strain can illustrate the fact that many questions are still unanswered in the field of foot-and-mouth epidemiology. It also demonstrates that the increase in international trade, including livestock, animal products and animal food, means an increase in the probability of transmitting, through the same way, some animal diseases, foot-and-mouth included. In our economies, a rapid identification of the virus and a fast elimination of infected, contaminated and even some contact animals are still the key factors to react in front of such a disease.

Résumé

Bien que connue depuis des années, la fièvre aphteuse représente toujours une menace réelle pour beaucoup d'économies agricoles de la planète. L'épisode récent de 2001 en Europe Occidentale, lié au virus O PanAsia, illustre le fait que de nombreuses questions sont toujours sans réponse au niveau de l'épidémiologie de la maladie. Cet épisode démontre aussi que le développement du commerce international des animaux et des produits animaux se traduit par une augmentation de la probabilité de transmettre, de la même façon, diverses maladies animales dont la fièvre aphteuse. Dans nos économies, une identification rapide du virus, suivie d'une élimination précoce des animaux malades, contaminés, voire contact, restent les clefs d'une maîtrise de la fièvre aphteuse.     

Poverty impacts of foot-and-mouth disease and the poverty reduction implications of its control

Foot-and-mouth disease (FMD) remains one of the most important livestock diseases of the world, given its highly infectious nature, its broad economic impacts on animal wellbeing and productivity, and its implications for successful access to domestic and export markets for livestock and products. The impacts of the disease vary markedly between developed and developing countries, and also within many developing countries. These differences in impact shape some markedly heterogeneous incentives for FMD control and eradication, which become of particular importance when setting priorities for poverty reduction in developing countries. Some consider that the benefits from FMD control accrue only to the better off in such societies and, as such, may not be a priority for investments targeted at poverty reduction. But is that view justified? Others see the control of FMD as a major development opportunity in a globalised environment. In this paper, Brian Perry and Karl Rich summarise the differential impacts of FMD and its control, and link these findings with the growing understanding of how the control of this globally important disease may contribute to the processes of pro-poor growth in certain countries of the developing world.     

Risk factors for local spread of foot-and-mouth disease, 2010 epidemic in Japan

To provide a basis for effective foot-and-mouth disease (FMD) prevention measures, factors associated with local spread were investigated in this study using data of the 2010 FMD epidemic in Japan. Thirty-eight local clusters within a 500-m radius from source farms were selected. In the clusters with pig source farms, more neighboring farms were infected in a short time compared with the clusters with cattle source farms. The influence of distance and wind upon local spread did not show a significant difference between infected and noninfected neighboring farms. Large-size pig farms posed a greater risk of inducing local spread; the odds ratio with reference to small-size cattle farms was 16.73. Middle-size and large-size cattle farms had a greater risk of infection; odds ratios with reference to small-size cattle farms were 15.65 and 25.52, respectively. The present results are useful for understanding features of local spread and prioritizing farms for control measures.     

Identification of geographic factors associated with early spread of foot-and-mouth disease

OBJECTIVE: To explore whether early analysis of spatial data may result in identification of variables associated with epidemic spread of foot and mouth disease. SAMPLE POPULATION: 37 farms with infected cattle (ie, case farms) reported within the first 6 days of the 2001 Uruguayan foot-and-mouth disease epidemic. PROCEDURE: A georeferenced database was created and retrospective analysis was performed on case farm location in relation to farm density, cattle density, farm type (ie, beef vs dairy cattle production), road density, case farm distance to the nearest road, farm size, farm ownership, and day of infection. Mean or median results of 1 to 3 day versus 4 to 6 day spatial data were compared. Spatial-temporal associations were investigated by correlation analysis. RESULTS: Comparison of mean or median values between the first 3 days and days 4 to 6 of the epidemic and results of correlation analysis indicated a significant increase in road density, cattle density, and dairy cattle production and a significant decrease in farm size and case farm distance to the nearest road that developed over time. A route that linked most case farms by the shortest possible distance and also considered significantly associated variables was created. It included 86.1% of all case farms reported by 60 days into the epidemic. CONCLUSIONS AND CLINICAL RELEVANCE: Epidemic direction can be assessed on the basis of road density and other spatial variables as early as 6 days into an epidemic. Epidemic control areas may be more effectively identified if local and regional georeferenced data are considered.     

Effectiveness of movement-prevention regulations to reduce the spread of foot-and-mouth disease in The Netherlands

After the foot-and-mouth disease (FMD) outbreak in 2001 the Dutch government implemented movement-prevention regulations to reduce the number of contacts between farms and consequently the risk of spread of highly contagious animal infections in the future. We studied the efficacy of these regulations by comparing registered cattle-movement data from 2000 to those from 2002. We also used the spatial and stochastic simulation model InterFMD to evaluate the consequences of the observed alterations in cattle-contact structure on the spread and control of a FMD epidemic.

There was a significant decrease in the number of cattle movements “for live use”, no difference in the number of group movements “for live use” and a distinct change in the overall contact structure. The most important structure changes were a decrease in the number of group movements from dairy farms to cattle-collection centres (−44%), and an increase in the number of group movements from dairy farms to beef farms (111%).

Our simulations demonstrated that the implemented regulations result in a concentration of the FMD-affected area and therefore in a reduction in size of the epidemics. Based on the intended Dutch strategy to control future FMD outbreaks, the decrease in extreme epidemics (95th percentiles) went from 31 infected farms in an epidemic-length of 65 days to 8 infected farms in an epidemic-length of 53 days in sparsely populated areas. In densely populated areas this decrease went from 135 infected farms to 103, while the duration reduced from 88 days to 81.