A stochastic modeling study of quarantine strategies against foot-and-mouth disease risks through cattle trades across the Thailand-Myanmar border

Prev Vet Med. 2024 Sep:230:106282. doi: 10.1016/j.prevetmed.2024.106282. Epub 2024 Jul 10.

Abstract

Foot-and-mouth disease (FMD) is an important endemic disease in livestock in Southeast Asia. Transboundary movement of animals may result in the transnational disease spread. A major cattle market is located at the Thailand-Myanmar border, where most cattle imported from Myanmar are traded. In this study, we built a stochastic susceptible-exposed-infectious-recovered (SEIR) model to investigate the effectiveness of a private animal quarantine service center in preventing FMDV from entering the major cattle market. We computed with different parameters and found that, with 50 % vaccine effectiveness, the risk of releasing infected cattle to the market per batch was generally low during the quarantine period of 21 and 28 days, with the risk ranging from 0.071 to 0.078 and 0.032 to 0.036, respectively. Despite the best scenario, the zero-risk state is difficult to attain. The sensitivity analysis highlights that the percentage of immune animals before entering the quarantine centers and the vaccine effectiveness are important factors. In conclusion, the 21-day quarantine period mitigates the risk of FMDV introduction into the cattle market. This control measure should be rigorously maintained to sustainably prevent FMDV outbreaks through transboundary animal movements, especially among countries in FMD-endemic regions.

Keywords: Cattle trade; Foot-and-mouth disease; Quarantine; Risk; Transboundary.

MeSH terms

  • Animals
  • Cattle
  • Cattle Diseases* / epidemiology
  • Cattle Diseases* / prevention & control
  • Cattle Diseases* / virology
  • Commerce
  • Foot-and-Mouth Disease Virus / immunology
  • Foot-and-Mouth Disease* / epidemiology
  • Foot-and-Mouth Disease* / prevention & control
  • Myanmar / epidemiology
  • Quarantine* / veterinary
  • Stochastic Processes*
  • Thailand / epidemiology