Estimation models for the morbidity of the horses infected with equine influenza virus.

The research is about creating estimation models to understand the severity or prevalence (morbidity) of equine influenza virus in horses. These models were developed using data from a 1992 outbreak and applied to evaluate a new vaccination program started in 1998 by the Japan Racing Association.

Overview of the Research

• The research aimed to develop estimation models to predict the morbidity of horses infected with the equine influenza virus. The researchers used linear regression, logistic regression, and probit transformation models to make these estimations.

Data Collection

• The researchers used data from an outbreak at the Sha Tin Racing Track in Hong Kong in 1992 to develop their estimation models. They then applied these models to estimate morbidity rates at training centers belonging to the Japan Racing Association (JRA) in October 1997 and in October 1998.
• In 1998, the JRA began a new vaccination program in which every horse must be vaccinated twice a year. The vaccine used included two US lineage virus strains, which did not include any EU lineage virus strains.

Simulation Models and Results

• The researchers compared the geometric mean (GM) values of hemagglutination inhibition (HI) titers for two virus strains in 1997 and 1998. Both of these GM values rose significantly indicating an increase in the level of antibodies in the horse’s blood which in turn suggests increased immunity.
• Their calculations showed that morbidity rates for one of the strains (LP93) diminished significantly across all estimation models. However, for the second strain (SF89), the estimated morbidity rates diminished only slightly.

Conclusion of the Study

• The researchers concluded that their simulation models could estimate the effect of the vaccine on each of the equine virus strains through the morbidity rates of infected horses, demonstrating their potential usefulness in vaccine evaluation.