On a stochastic epidemic SIR model with non homogenous population: a toy model for HIV

In this paper we generalise a simple discrete time stochastic SIR type model defined by Tuckwell and Williams. The SIR model by Tuckwell and Williams assumes a homogeneous population, a fixed infectious period, and a strict transition from susceptible to infected to recovered. In contrast, our model introduces two groups, $A$ and $B$, where group $B$ has a higher risk of infection due to increased contact rates. Additionally, the duration in the infected class follows a probability distribution rather than being fixed. Finally, individuals in group $B$ can transition directly to the recovered class R, allowing us to analyze the impact of this preventive measure on disease spread. Finally, we apply this model to the spread of HIV, analyzing how risk behaviors, rapid testing, and PrEP-like therapies influence the epidemic dynamics.

Publication Details

Journal
ArXiv.org
Published
2025-04-18
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

On a stochastic epidemic SIR model with non homogenous population: a toy model for HIV

ArXiv.org
COVID-19 epidemiological studies
article

On a stochastic epidemic SIR model with non homogenous population: a toy model for HIV

article en

Abstract

In this paper we generalise a simple discrete time stochastic SIR type model defined by Tuckwell and Williams. The SIR model by Tuckwell and Williams assumes a homogeneous population, a fixed infectious period, and a strict transition from susceptible to infected to recovered. In contrast, our model introduces two groups, $A$ and $B$, where group $B$ has a higher risk of infection due to increased contact rates. Additionally, the duration in the infected class follows a probability distribution rather than being fixed. Finally, individuals in group $B$ can transition directly to the recovered class R, allowing us to analyze the impact of this preventive measure on disease spread. Finally, we apply this model to the spread of HIV, analyzing how risk behaviors, rapid testing, and PrEP-like therapies influence the epidemic dynamics.

ArXiv.org
Good health and well-being
Openalex Percentile: Top 48%
COVID-19 epidemiological studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

On a stochastic epidemic SIR model with non homogenous population: a toy model for HIV · ArXiv.org (2025) | TGRS Research Map | TGRS