Dynamics of HIV-TB co-infection with detection as optimal intervention strategy

Tanvi,; Aggarwal, Rajiv

doi:10.1016/j.ijnonlinmec.2019.103388

Cited by 22 publications

(16 citation statements)

References 23 publications

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“…For a detailed review of HPV models in the literature, see the work of Omame et al [25] and the references therein. Recently, optimal control and cost-effectiveness analysis have been applied to deterministic mathematical models [17,21,31,40]. Although numerous epidemiological evidences to support the co-infection of HPV and Chlamydia trachomatis exist in the literature, no robust optimal control mathematical model has been developed to better understand the dynamics of the co-infection of the two diseases.…”

Section: Introductionmentioning

confidence: 99%

Optimal Control and Cost-Effectiveness Analysis of an HPV–Chlamydia trachomatis Co-infection Model

2021

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In this work, a co-infection model for human papillomavirus (HPV) and Chlamydia trachomatis with cost-effectiveness optimal control analysis is developed and analyzed. The disease-free equilibrium of the co-infection model is shown not to be globally asymptotically stable, when the associated reproduction number is less unity. It is proven that the model undergoes the phenomenon of backward bifurcation when the associated reproduction number is less than unity. It is also shown that HPV re-infection (ε p = 0) induced the phenomenon of backward bifurcation. Numerical simulations of the optimal control model showed that: (i) focusing on HPV intervention strategy alone (HPV prevention and screening), in the absence of Chlamydia trachomatis control, leads to a positive population level impact on the total number of individuals singly infected with Chlamydia trachomatis, (ii) Concentrating on Chlamydia trachomatis intervention controls alone (Chlamydia trachomatis prevention and treatment), in the absence of HPV intervention strategies, a positive population level impact is observed on the total number of individuals singly infected with HPV. Moreover, the strategy that combines and implements HPV and Chlamydia trachomatis prevention controls is the most cost-effective of all the control strategies in combating the co-infections of HPV and Chlamydia trachomatis.

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Section: Introductionmentioning

confidence: 99%

Optimal Control and Cost-Effectiveness Analysis of an HPV–Chlamydia trachomatis Co-infection Model

2021

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“…6,7 Mathematical models have been applied extensively in the study of the dynamics of infectious diseases. [8][9][10][11][12][13][14][15] Particularly, models have recently been studied to understand the transmission dynamics of HPV infection (See Omame et al 16 and the references included therein). For instance, Malik et al 17 investigated an optimal control model for HPV, incorporating optimal vaccination strategies for females in the population.…”

Section: Introductionmentioning

confidence: 99%

A co‐infection model for oncogenic human papillomavirus and tuberculosis with optimal control and Cost‐Effectiveness Analysis

Omame

Okuonghae

2021

Optim Control Appl Methods

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A co-infection model for oncogenic human papillomavirus (HPV) and tuberculosis (TB), with optimal control and cost-effectiveness analysis is studied and analyzed to assess the impact of controls against incident infection and against infection with HPV by TB-infected individuals as well as optimal TB treatment in reducing the burden of the co-infection of the two diseases in a population. The co-infection model exhibits backward bifurcation when the associated reproduction number is less than unity. Furthermore, it is shown that TB and HPV re-infection parameters ( p ≠ 0 and t ≠ 0) as well as TB exogenous re-infection term ( 1 ≠ 0) induced the phenomenon of backward bifurcation in the oncogenic HPV-TB co-infection model. The global asymptotic stability of the disease-free equilibrium of the co-infection model is shown not to exist, when the associated reproduction number is below unity. The necessary conditions for the existence of optimal control and the optimality system for the co-infection model is established using the Pontryagin's Maximum Principle. Numerical simulations of the optimal control model reveal that the intervention strategy which combines and implements control against HPV infection by TB infected individuals as well as TB treatment control for dually infected individuals is the most cost-effective of all the control strategies for the control and management of the burden of oncogenic HPV and TB co-infection.

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“…Tanvi et al [38] a model of HIV-TB co-infection with a non-linear treatment rate for TB was explored and conclude that to reduce the co-infection programs that accelerate TB treatment need to be implemented. Tanvi et al [39] explored a model of HIV/AIDS and TB co-infection with detection and treatment of both diseases, performed an optimal control analysis using the maximum principle of Pontryagin and showed the importance of accelerating the detection of cases of both diseases along with the treatment to reduce co-infection.…”

Section: Introductionmentioning

confidence: 99%

A Mathematical Model for the Study of Effectiveness in Therapy in Tuberculosis Taking into Account Associated Diseases

Moya¹,

Pietrus²,

Oliva³

2021

Contemporary Mathematics

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Tuberculosis (TB) remains a major global health problem. We present a deterministic mathematical model for the study of the effectiveness of therapy in TB to determine the impact of HIV/AIDS and diabetes in the spread of the disease and drug resistance. Our model takes into account the relationships between TB, HIV/AIDS, and diabetes and we also study the behavior of multidrug-resistance (MDR-TB) and extensively drug-resistant (XDR-TB). The main mathematical and epidemiology features of the model are investigated. The basic reproduction number (R0) in the different sub-populations (diabetics, HIV/AIDS, and those who do not suffer from these diseases) was studied. Conditions were obtained on the model parameters to know when the growth of the parameters associated with resistance to TB treatment has a negative impact on the transmission of TB in the population based on the R0 study. It is concluded that MDR-TB and XDR-TB have a negative impact on TB control. Computational simulations show that a greater number of drug-sensitive TB cases with respect to MDR-TB and XDR-TB cases are reported in the infected compartments, and MDR-TB cases surpass XDR-TB cases, except in the diabetes sub-population, which has a growth of XDR-TB cases that surpasses the other compartments of infected of all the sub-populations. It was shown when comparing the sub-populations of diabetes and HIV/AIDS, that although the diabetes sub-population reports a higher number of XDR-TB cases, a lower number of drug-sensitive TB and MDR-TB cases, have a greater number of recovered cases with respect to HIV/AIDS sub-population at the end of the study period. Also, when the XDR-TB cases in the diabetes sub-population exceed the other infected compartments, there is a growth of recovered TB in this subpopulation. The results suggest that it is necessary to increase the attention to the diabetic population, which include improved glucose control, increase the number of specialized medical consultations to achieve permanence in TB treatment and control the entry of individuals to the diabetic compartments by tests of diabetes.

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Dynamics of HIV-TB co-infection with detection as optimal intervention strategy

Cited by 22 publications

References 23 publications

Optimal Control and Cost-Effectiveness Analysis of an HPV–Chlamydia trachomatis Co-infection Model

Optimal Control and Cost-Effectiveness Analysis of an HPV–Chlamydia trachomatis Co-infection Model

A co‐infection model for oncogenic human papillomavirus and tuberculosis with optimal control and Cost‐Effectiveness Analysis

A Mathematical Model for the Study of Effectiveness in Therapy in Tuberculosis Taking into Account Associated Diseases

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