On the Dynamics of HIV–Tuberculosis Coinfection Model with Temporal Recovery from Tuberculosis: An Analysis

The current study is an attempt to frame a deterministic compartmental model for HIV-TB coinfection, considering temporary recovery from Tuberculosis (TB) after treatment (the possibility of reinfection with TB even after recovery). The proposed HIV<b>-</b>TB coinfection model is a composite of an susceptible-infected (SI) type HIV/AIDS model and a susceptible-exposed-infected-recovered type TB model. In the beginning, the HIV<b>-</b>TB model is constructed, followed by the qualitative investigation of the model. The equilibrium points of the model are obtained and have been examined in detail. Further, the basic reproduction number for the HIV<b>-</b>TB coinfection model has been computed, and the proposed model has been simulated numerically to investigate the effect of treatment on HIV<b>-</b>TB coinfection. Analysis of the model claims the existence of interior equilibrium when both HIV and TB reproduction numbers are more than unity. The results exhibit that TB treatment will be the most efficient in discarding the HIV<b>-</b>TB coinfection disease whenever the basic reproduction of HIV<b>-</b>TB is less than one. In addition, our results suggest that the reinfection of TB after recovery impacts HIV<b>-</b>TB transmission. It has been found that reinfection makes disease eradication more challenging. As, in the presence of reinfection, the total infected cases are always higher than the infected cases in the absence of reinfection.

Authors

Institutions

Publication Details

Journal
Journal of Computational Biology
Published
2025-04-25
DOI
https://doi.org/10.1089/cmb.2024.0763
Primary Topic
Mathematical and Theoretical Epidemiology and Ecology Models
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

On the Dynamics of HIV–Tuberculosis Coinfection Model with Temporal Recovery from Tuberculosis: An Analysis

Hacı Mehmet Başkonuş, Sunil Singh Negi, Nitin Sharma, Pankaj Singh Rana
Journal of Computational Biology
Mathematical and Theoretical Epidemiology and Ecology Models
article

On the Dynamics of HIV–Tuberculosis Coinfection Model with Temporal Recovery from Tuberculosis: An Analysis

Hacı Mehmet Başkonuş, Sunil Singh Negi, Nitin Sharma, Pankaj Singh Rana
article en

Abstract

The current study is an attempt to frame a deterministic compartmental model for HIV-TB coinfection, considering temporary recovery from Tuberculosis (TB) after treatment (the possibility of reinfection with TB even after recovery). The proposed HIV<b>-</b>TB coinfection model is a composite of an susceptible-infected (SI) type HIV/AIDS model and a susceptible-exposed-infected-recovered type TB model. In the beginning, the HIV<b>-</b>TB model is constructed, followed by the qualitative investigation of the model. The equilibrium points of the model are obtained and have been examined in detail. Further, the basic reproduction number for the HIV<b>-</b>TB coinfection model has been computed, and the proposed model has been simulated numerically to investigate the effect of treatment on HIV<b>-</b>TB coinfection. Analysis of the model claims the existence of interior equilibrium when both HIV and TB reproduction numbers are more than unity. The results exhibit that TB treatment will be the most efficient in discarding the HIV<b>-</b>TB coinfection disease whenever the basic reproduction of HIV<b>-</b>TB is less than one. In addition, our results suggest that the reinfection of TB after recovery impacts HIV<b>-</b>TB transmission. It has been found that reinfection makes disease eradication more challenging. As, in the presence of reinfection, the total infected cases are always higher than the infected cases in the absence of reinfection.

Journal of Computational BiologyVol. 32(5)
Jaypee Institute of Information Technology (IN), Harran University (TR), National Institute of Technology Srinagar (IN)
Openalex Percentile: Top 88%
Mathematical and Theoretical Epidemiology and Ecology Models
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.