Rare Events of Host Switching for Diseases using a SIR Model with Mutations

TL;DR

This study models the rare event of disease host switching from animals to humans using an SIR network model with mutations, employing advanced numerical techniques to estimate extremely small probabilities and outbreak severity.

Contribution

It introduces a novel application of the $1/t$ Wang-Landau algorithm to accurately estimate tiny probabilities of host switching and disease severity in a complex network model.

Findings

Calculated probabilities as small as 10^{-120} for host switching.

Obtained the full distribution of disease severity in humans.

Identified correlations between outbreak size and disease characteristics.

Abstract

We numerically study disease dynamics that lead to the disease switching from one host species to another, resulting in diseases gaining the ability to infect, e.g., humans. Unlike previous studies that focused on branching processes starting with the first infected humans, we begin by considering a disease pathogen that initially cannot infect humans. We model the entire process, starting from an infection in the animal population, including mutations that eventually enable the disease to cause an epidemic outbreak in the human population. We use an SIR model on a network consisting of 132 dog and 1320 human nodes, with a single parameter representing the gene of the pathogen. We use numerical large-deviation techniques, specifically the $1/t$ Wang-Landau algorithm, to calculate the potentially very small probability of the host switching event. With this approach we are able to resolve probabilities as small as $10^{-120}$. Additionally the $1/t$ Wang-Landau algorithm allows us to obtain the complete probability density function $P(C)$ of the cumulative fraction $C$ of infected humans, which is an indicator for the severity of the disease in the human population. We also calculate correlations of $C$ with selected quantities $q$ that characterize the outbreak. Due to the application of the rare-event algorithm, this is possible for the entire range of $C$ values.