Waterborne epidemics via a new coupled SIR--Pathogen--Navier-Stokes system: Mathematical modeling, nonlinear analysis and numerical simulation

TL;DR

This paper introduces a novel coupled SIR-Pathogen-Navier-Stokes model that integrates epidemiological dynamics with fluid mechanics to better understand waterborne disease spread, supported by mathematical proofs and numerical simulations.

Contribution

It develops a new mathematical framework coupling SIR dynamics with fluid flow, including pathogen transport and viscosity effects, with proven existence and uniqueness of solutions.

Findings

Model captures waterborne pathogen dispersal influenced by water currents.

Numerical simulations demonstrate the impact of hydrodynamics on epidemic spread.

The framework provides insights into environmental contamination and epidemic decline.

Abstract

Water-borne diseases are still a major public health concern, as there are circumstances under which water could act as a carrier of the pathogen, extending their modeling beyond direct contact between hosts. In the present work, we introduce a new mathematical framework, coupling epidemiological dynamics with fluid motion, in order to understand the spatial spread of such an infection. Our model couples the classical Susceptible-Infected-Recovered (SIR) model with the Navier-Stokes equations describing the motion of fluids, which enhances the existing literature by simultaneously taking into account two aspects: the pathogen being transported by the water currents and the dependence of the effective viscosity of the fluid on the pathogen concentration. We apply the Faedo-Galerkin method and compactness arguments to prove the existence of a global, biologically feasible solution to the coupled SIR--Pathogen--Navier-Stokes (SIRPNS) system. Additionally, we investigate the uniqueness of such solutions in the two-dimensional case. Finally, by constructing a numerical scheme based on the semi-implicit scheme in time and the finite element method in space, we run several numerical simulations to show how infection dispersal, environmental contamination, and hydrodynamic feedback together govern the spatial dynamics, persistence, and eventual decline of waterborne epidemics.