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Foot and mouth disease (FMD) is an important livestock disease in Thailand, with outbreaks occurring every year. However, the effects of FMD control measures in Thailand have received little research attention. Epidemiological models have been widely used to evaluate FMD outbreak control, but such a model has never been developed for Thailand. We constructed a stochastic between-farm transmission model to evaluate FMD control measures. The epidemiological unit of the model was the farm, which could be in different states: susceptible, latent, undetected infectious, detected infectious and recovered. The between-farm transmission was calculated by the sum of distance-dependent transmission and trade network transmission using parameters derived from FMD outbreaks in 2016–2017. We used this model to simulate the outbreaks with and without the implementation of the following control measures: culling all animals on infected farms, ring vaccination, animal movement restrictions and isolation of infected farms. The control measures were evaluated by estimating the number of secondarily infected farms and the outbreak duration for each scenario. The model was simulated in two study areas located in the Lamphaya Klang subdistrict (high farm density) and the Bo Phloi district (low farm density). The effects of control measures differed between the two study areas. When farm density was high, rigid control measures were required to prevent a major outbreak. Among all options, culling the animals on infected farms resulted in the lowest number of infected farms and the shortest outbreak duration. In contrast, for an area with a low farm density, less stringent control measures were sufficient to control the usually minor outbreaks. The results indicate that different areas require a different approach to control an outbreak of FMD. [ABSTRACT FROM AUTHOR]

Information on the epidemiological and economic consequences of control measures is fundamental to design effective foot and mouth disease (FMD) control measures. One approach to obtaining this information is through bioeconomic modelling. In this study, a bioeconomic model was used to evaluate FMD control in two different study areas in Thailand: a high farm density area predominantly consisting of dairy farms and a low farm density area with mixed farm types. The bioeconomic model consists of an epidemiological part and an economic part. For the epidemiological part, a stochastic between-farm transmission model was constructed with transmission parameters estimated from FMD outbreaks in Thailand. The outputs from the epidemiological model, i.e. the number of infected farms, the number of affected farms and the outbreak duration, are used as inputs for economic model to calculate the economic consequences. We applied the simulation model with four FMD control measures: culling the animals of infected farms, ring vaccination, animal movement restrictions and isolation of infected farms. Furthermore, we included effect of farmers' compliance to asses its effect on control measures. The simulated FMD outbreaks in the low farm density area were small, thus control measures did not greatly affect the size of outbreaks and, therefore, did not have a positive economic return. In contrast, in the high farm density area, FMD outbreaks were large without control measures. All measures reduced the size of the outbreaks but resulted in different total costs. In terms of outbreak control, culling infectious farms was the best option, but its total cost was higher than ring vaccination or isolation of infected farms. In terms of cost-effectiveness, ring vaccination was the best measure. If farmers' compliance were low, all control measures would be ineffective, resulting in high total cost of the outbreak. The cost distribution between compliant and non-compliant farms showed that non-compliant farms paid more than compliant farms, except for the ring vaccination scenario. The results emphasize the economic significance to customize control measures specific to the area's conditions and highlight the importance of farmers' compliance when designing control measures., Competing Interests: Declaration of Competing Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)