Dynamical Models of Tuberculosis and Their Applications

TLDR

Tuberculosis resurgence since the 1980s spurred research into its transmission dynamics, with early 1960s models using simulations and recent models applying modern dynamical systems analysis. This article reviews work on TB dynamics and control. The review surveys TB control strategies, vaccination policies, HIV co‑infection, drug resistance, immune responses, demographics, transport, contact patterns, and presents model formulations ranging from ODEs and PDEs to Markov chains and simulations.

Abstract

The reemergence of tuberculosis (TB) from the 1980s to the early 1990s instigated extensive researches on the mechanisms behind the transmission dynamics of TB epidemics. This article provides a detailed review of the work on the dynamics and control of TB. The earliest mathematical models describing the TB dynamics appeared in the 1960s and focused on the prediction and control strategies using simulation approaches. Most recently developed models not only pay attention to simulations but also take care of dynamical analysis using modern knowledge of dynamical systems. Questions addressed by these models mainly concentrate on TB control strategies, optimal vaccination policies, approaches toward the elimination of TB in the U.S.A., TB co-infection with HIV/AIDS, drug-resistant TB, responses of the immune system, impacts of demography, the role of public transportation systems, and the impact of contact patterns. Model formulations involve a variety of mathematical areas, such as ODEs (Ordinary Differential Equations) (both autonomous and non-autonomous systems), PDEs (Partial Differential Equations), system of difference equations, system of integro-differential equations, Markov chain model, and simulation models.