Untangling the stranglehold through mathematical modelling of Streptococcus equi subspecies equi transmission.

The researchers in this article used mathematical modeling to study the transmission dynamics of Streptococcus equi subspecies equi, a bacterium responsible for strangles, a major equine disease globally. They aimed to identify future research areas, expand the understanding of the disease’s epidemiology, and quantify the level of control effort required to combat its spread.

Research Methodology

• The team created a compartmental deterministic model to estimate the transmission parameters of Strangles. This model was built using data and information currently available in scientific literature, aiming to enhance the understanding of transmission parameters and identify areas that require future research.
• The parameters analyzed included duration of carriership, relative infectiousness of carriers, proportion of infections leading to carriership, and the duration of immunity after natural infection. These indicators are necessary in understanding the transmission dynamics of Streptococcus equi subspecies equi and in strategizing its control.
• They compared available incidence and (sero-) prevalence data with the model outputs to refine any uncertain parameter figures to improve their model.

Findings

• The study found that the relative infectiousness of the carriers and the duration of carriership are essential knowledge gaps that future research needs to address.
• Combining deterministic compartmental simulations with seroprevalence data suggested that the relative infectiousness of carriers compared to acutely ill horses lies between 0.05 and 0.5, and the duration of protective immunity after infection is likely 4-6 years.
• The article also infers that the presence of carriers alone can maintain the endemicity of Strangles in a population, and so control strategies must not neglect carriers.
• They suggested that weekly screening for strangles symptoms could be sufficient to keep the basic reproduction number (R) under 1, provided horses are screened for carriership post-infection.
• In extreme scenarios, vaccinations alone may not be sufficient to prevent major outbreaks.

Simulations

• A stochastic agent-based model was also created to simulate a remount depot and validated using historic recurrence data of strangles within individuals. This model was used to evaluate whether the recurrence data could be explained without the assumption that one in four horses fails to mount a lasting immune response.
• The results showed that the observed data could occur without needing to rely on the aforementioned assumption. This is another important finding, as it challenges the conventional understanding of horse immunity in the context of Strangles disease.