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An Embedded Multiscale Modelling to Guide Control and Elimination of Paratuberculosis in Ruminants.

Rendani Netshikweta¹, Winston Garira¹

¹Modelling Health and Environmental Linkages Research Group (MHELRG), Department of Mathematics and Applied Mathematics, University of Venda, Private Bag X5050, Thohoyandou 0950, South Africa.

Computational and Mathematical Methods in Medicine

|December 6, 2021

Summary

This study introduces a multiscale model for paratuberculosis in ruminants, revealing superinfection impacts early disease stages while bacterial replication drives long-term dynamics. The model aids in evaluating intervention strategies.

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Area of Science:

Infectious disease dynamics
Mathematical modeling
Veterinary epidemiology

Background:

Multiscale modeling is crucial for understanding complex infectious disease systems.
Paratuberculosis (paratuberculosis) poses significant challenges in ruminant populations.
Integrating within-host and between-host dynamics is essential for accurate disease modeling.

Purpose of the Study:

To develop an embedded multiscale model for paratuberculosis in ruminants.
To investigate the reciprocal influence of within-host and between-host scales on disease dynamics.
To evaluate the effectiveness of paratuberculosis interventions using the developed model.

Main Methods:

Development of an embedded multiscale model integrating within-host and between-host scales.
Numerical analysis of the multiscale model to study disease dynamics.
Simulation of paratuberculosis progression under different intervention scenarios.

Main Results:

Superinfection primarily influences paratuberculosis dynamics at the initial infection phase.
Mycobacterium avium subspecies paratuberculosis (MAP) bacterial replication continuously drives disease dynamics throughout infection.
The model provides a framework for comparing the efficacy of various health interventions.

Conclusions:

The embedded multiscale model effectively captures the complexity of paratuberculosis transmission and progression.
Understanding the distinct roles of superinfection and bacterial replication is key to disease management.
This modeling approach can inform targeted intervention strategies for paratuberculosis control in ruminants.