A Data-Validated Host-Parasite Model for Infectious Disease Outbreaks

TL;DR

This paper develops and validates a host-parasite mathematical model for infectious disease outbreaks using experimental data from a guppy-gyrodactylid system, highlighting key factors influencing outbreak dynamics.

Contribution

It introduces a data-validated model for host-parasite dynamics, estimating R0 and analyzing factors affecting outbreak timing and severity.

Findings

Parasite growth rate significantly impacts outbreak peak.

Host immune response rate influences outbreak timing.

Model validation confirms accuracy with experimental data.

Abstract

The use of model experimental systems and mathematical models is important to further understanding of infectious disease dynamics and strategize disease mitigation. Gyrodactylids are helminth ectoparasites of teleost fish which have many dynamical characteristics of microparasites but offer the advantage that they can be quantified and tracked over time, allowing further insight into within-host and epidemic dynamics. In this paper, we design a model to describe host-parasite dynamics of the well-studied guppy-Gyrodactylus turnbulli system, using experimental data to estimate parameters and validate it. We estimate the basic reproduction number (R_0), for this system. Sensitivity analysis reveals that parasite growth rate, and the rate at which the guppy mounts an immune response have the greatest impact on outbreak peak and timing both for initial outbreaks and on longer time scales. These findings highlight guppy population resistance and parasite virulence as key factors in disease control, and future work should focus on incorporating heterogeneity in host resistance into disease models and extrapolating to other host-parasite systems.