Integration of empirical network data and agent-based modelling to examine the risk of equine influenza infection in equine athletes in Ontario, Canada.

Overview

• This study developed and used a detailed simulation model to understand how equine influenza spreads among competition horses in Ontario, Canada.
• The model combined real-world data on horse contacts with an agent-based SEIR disease model to evaluate the risk of outbreaks and the effectiveness of vaccination and biosecurity measures.

Background and Problem

• Horses are commonly transported for competitions, increasing the chance of spreading infectious diseases like equine influenza.
• Existing models often oversimplify how horses move and come into contact with each other, limiting their usefulness for real-world disease control.
• Understanding how horse contact patterns influence disease spread can help improve biosecurity and reduce outbreaks among equine athletes.

Study Objectives

• To integrate empirical data on horse contact networks in Ontario with a stochastic agent-based SEIR (Susceptible, Exposed, Infectious, Recovered) model for equine influenza.
• To simulate different outbreak scenarios under varying levels of horse vaccination and contact rates.
• To assess how different interventions like vaccination coverage and reducing contact rates impact outbreak outcomes.

Methods

• Agent-based SEIR Model:
  • Utilizes a stochastic framework where individual horses are modeled as agents transitioning through disease states: Susceptible, Exposed, Infectious, and Recovered.
  • Captures disease dynamics at the individual horse level rather than population averages.
• Empirical Contact Network:
  • Derived from observed competition and home facility interactions among horses in Ontario.
  • Realistic representation of how frequently and with whom horses come into contact.
• Scenarios Simulated:
  • Eight scenarios combining different levels of vaccination coverage ranging from 42.5% to 95%.
  • Two different contact rates modeled with normal distributions: one with a mean of 2 contacts per horse, another with 5 contacts.
  • Both competitor and non-competitor horse populations considered.
• Simulation Details:
  • Each scenario was run 200 times to incorporate stochastic variability.
  • Key outcomes measured: attack rate (proportion infected), number of infected home facilities, number of infected competitions, and outbreak duration.

Key Findings

• Reducing contact rates between horses was more effective at lowering disease spread and outbreak severity than increasing vaccination coverage in non-competitor horses.
• Lower contact led to significant decreases in:
  • Attack rate
  • Number of infected home facilities
  • Number of infected competitions
• High vaccination coverage alone, especially in non-competition horses, was less impactful if contact rates remained high.
• The model highlights that behavioral interventions focused on limiting horse-to-horse contact can be crucial in controlling equine influenza outbreaks.

Implications for Biosecurity and Disease Control

• Biosecurity strategies should prioritize reducing horse contact at competitions and home facilities to mitigate outbreak risks.
• Vaccination remains important but may not suffice alone, particularly if contact rates are not managed.
• Policy makers and horse industry stakeholders can use such integrated modeling approaches to plan targeted interventions during outbreaks.
• The approach demonstrates the value of combining real-world contact data with detailed disease models to improve outbreak predictions and control recommendations.

Conclusion

• This research provides a comprehensive tool to assess equine influenza outbreak risks in Ontario competition horses by combining empirical contact networks and an agent-based SEIR model.
• It underscores the importance of managing contact-related behaviors in addition to vaccination to reduce disease spread in equine populations.