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Updated: May 14, 2026
04:23
A Murine Model of Dengue Virus-induced Acute Viral Encephalitis-like Disease
Published on: April 28, 2019
Stochastic dynamics of dengue epidemics
David R de Souza1, Tânia Tomé, Suani T R Pinho
1Instituto de Física, Universidade de São Paulo, Caixa Postal 66318, 05314-970 São Paulo, Brazil.
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|February 16, 2013
Summary
This study models vector-borne disease spread using interconnected human (SIR) and mosquito (SIS) dynamics. Certain infection rates prevent disease transmission, regardless of mosquito death rates.
Area of Science:
- Epidemiology
- Mathematical Biology
- Disease Modeling
Background:
- Vector-transmitted diseases like dengue pose significant public health challenges.
- Understanding disease dynamics requires modeling interactions between human and vector populations.
- Stochastic models offer insights into disease thresholds and transmission dynamics.
Purpose of the Study:
- To develop a stochastic Markovian dynamics model for vector-borne diseases.
- To analyze the interconnected SIR (human) and SIS (mosquito) population dynamics.
- To determine the disease threshold and reproductive ratio.
Main Methods:
- Stochastic Markovian dynamics approach.
- Development of a truncation scheme for evolution equations.
- Numerical simulations to validate theoretical findings.
Main Results:
- The model establishes interconnected SIR and SIS dynamics for disease transmission.
- A truncation scheme was developed to derive the disease threshold and reproductive ratio.
- Numerical simulations confirmed the theoretical threshold.
- Identified specific infection rate values that preclude disease spread.
Conclusions:
- Disease transmission is impossible under certain infection rate conditions, irrespective of mosquito mortality.
- The model provides a framework for understanding disease control strategies.
- Highlights the critical role of infection rates in disease prevention.
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