Modeling TB and HIV co-infections

Lih Ing W Roeger, Zhilan Feng, Carlos Castillo-Chavez

Research output: Contribution to journalArticlepeer-review

92 Scopus citations

Abstract

Tuberculosis (TB) is the leading cause of death among individuals infected with the human immunodeficiency virus (HIV). The study of the joint dynamics of HIV and TB present formidable mathematical challenges due to the fact that the models of transmission are quite distinct. Furthermore, although there is overlap in the populations at risk of HIV and TB infections, the magnitude of the proportion of individuals at risk for both diseases is not known. Here, we consider a highly simplified deterministic model that incorporates the joint dynamics of TB and HIV, a model that is quite hard to analyze. We compute independent reproductive numbers for TB (R1) and HIV (R2) and the overall reproductive number for the system, R = max.{R 1,R2\. The focus is naturally (given the highly simplified nature of the framework) on the qualitative analysis of this model. We find that if R < 1 then the disease-free equilibrium is locally asymptotically stable. The TB-only equilibrium ET is locally asymptotically stable if R1 > 1 and R2 < 1. However, the symmetric condition, R1 < 1 and R2 > 1, does not necessarily guarantee the stability of the HIV-only equilibrium Eu, and it is possible that TB can coexist with HIV when R2 > 1. In other words, in the case when R1 < 1 and R2 > 1 (or when R1 > 1 and R1 > 1), we are able to find a stable HIV/TB coexistence equilibrium. Moreover, we show that the prevalence level of TB increases with R2 > 1 under certain conditions. Through simulations, we find that i) the increased progression rate from latent to active TB in co-infected individuals may play a significant role in the rising prevalence of TB; and ii) the increased progression rates from HIV to AIDS have not only increased the prevalence level of HIV while decreasing TB prevalence, but also generated damped oscillations in the system.

Original languageEnglish (US)
Pages (from-to)815-837
Number of pages23
JournalMathematical Biosciences and Engineering
Volume6
Issue number4
DOIs
StatePublished - Oct 2009

Keywords

  • Co-infection
  • Disease reproduction number
  • HIV
  • TB
  • Tuberculosis

ASJC Scopus subject areas

  • Modeling and Simulation
  • General Agricultural and Biological Sciences
  • Computational Mathematics
  • Applied Mathematics

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