Simulation studies of African horse sickness in Spain.

This research utilized a mathematical model to understand the factors impacting the spread of African horse sickness in Spain, and to evaluate the effectiveness of various vaccination strategies. These findings may inform the development of improved control strategies for this disease.

Methodology

• The authors of the research developed a mathematical model to simulate epidemics of African horse sickness. The model took into account two host species – horses and donkeys – and one vector species, the biting midge known as Culicoides imicola.
• The model analyzed the likelihood of an epidemic following the introduction of the virus into a new region.
• A stratified random sampling method, known as Latin hypercube sampling, was used to perform a sensitivity analysis on the likelihood of an epidemic occurring.
• Different vaccination strategies were then evaluated systematically in the model. Their effectiveness was examined considering a variety of parameters.

Findings

• When an epidemic occurred, most potential hosts got infected. However, the peak prevalence in the vector species, C. imicola, was low and never exceeded 3%.
• The likelihood of an outbreak depended on a few main factors including the size of the vector population, the rate of recovery in horses from the disease and the time of year the virus was introduced.
• Vaccination effectiveness was influenced by factors including the time gap between virus introduction and protection, the percentage of host animals vaccinated, and whether or not donkeys were included in the vaccination programs.

Implications

• The findings indicate that the factors affecting epidemic likelihood and vaccination effectiveness should be priorities for empirical research. Such information can be valuable for managing and preventing future outbreaks.
• The factors that most significantly influence the success of different vaccination strategies should be considered when designing control strategies. This applies especially to areas that are at risk of virus introduction.