Compartmental Spatial Multi-Patch Deterministic and Stochastic Models for Dengue

TL;DR

This paper develops and compares deterministic and stochastic compartmental models for dengue spread across multiple spatial patches, incorporating human mobility via residence-time matrices to better understand disease dynamics.

Contribution

It introduces a novel multi-patch modeling framework for dengue that integrates stochastic and deterministic approaches with human mobility data.

Findings

Stochastic and deterministic models show similar disease spread patterns.

Numerical solutions highlight the impact of human mobility on dengue transmission.

The models provide insights into spatial disease dynamics and control strategies.

Abstract

Dengue is a vector-borne viral disease increasing dramatically over the past years due to improvement in human mobility. The movement of host individuals between and within the patches are captured via a residence-time matrix. A system of ordinary differential equations (ODEs) modeling the spatial spread of disease among the multiple patches is used to create a system of stochastic differential equations (SDEs). Numerical solutions of the system of SDEs are compared with the deterministic solutions obtained via ODEs.