A nested multiscale model to study paratuberculosis in ruminants - Netshikweta, Rendani; Garira, Winston (Frontiers in Applied Mathematics and Statistics, 2022)
In this study, we present a nested multiscale model that integrates the within-host scale and the between-host scale disease dynamics for Paratuberculosis in ruminants such as cattle, goats and sheep, with the aim of ascertaining the influence of initial infective inoculum dose on its dynamics. Ruminant paratuberculosis is often characterized as an environmentally-transmitted disease and it is caused by bacteria called Mycobacterium avium subspecies paratuberculosis that can survive in the physical environment for a considerable period of time. In the context of nested multiscale models developed at host level of organization of a disease system, a key feature is that the within-host scale and the between-host scale disease dynamics influence each other in a reciprocal way, with the between-host scale influencing the within-host scale through initial infective inoculum dose which susceptible ruminants may consume from the environment. The numerical results of the nested multiscale model presented in this study demonstrate that once the minimum infectious dose is consumed, then the infection at the within-host scale is sustained more by pathogen replication than by super-infection. From these results we conclude that super-infection might have an insignificant effect on the dynamics of PTB in ruminants. However, at this stage we cannot precisely conclude if super-infection does not effect on the dynamics of the disease. This would be investigated further elsewhere using an embedded multiscale model, which more appropriate in gives us conclusive results. We further demonstrate the need to use nested multiscale models over single-scale modelling approach by estimating a key parameter for pathogen replication that cannot be estimated using single-scale models.