Abstract
This paper seeks to examine the sensitivity of tuberculosis transmission (TB) dynamics to the rate at which infectious individuals with active TB begin a TB treatment course, and therefore cease to be infectious to others. We model this by varying both the rate at which individuals are diagnosed and begin treatment, and the demographic conditions in which the epidemic occurs. An agestructured deterministic ordinary differential equation model is used to study the sensitivity of TB transmission dynamics to the implementation of a more effective diagnostic such as Xpert MTB/ RIF in a high HIV prevalence setting. Sensitivity analysis of the effectiveness of the diagnostic (λ) shows the interim disease dynamics in three demographic scenarios defined by differences in HIV prevalence and age structure at a constant transmission rate. In the near future, we expect the diagnostic to have the most effect in areas of high HIV prevalence. In the long term, we expect the diagnostic to have the most significant impact at high transmission rates regardless of HIV prevalence and age structure.
Highlights
To eliminate tuberculosis (TB), a reduction in incidence is imperative
We studied the sensitivity of TB infection dynamics to the rate at which infectious individuals with active TB are placed on a TB treatment course, and cease to be infectious to others, by varying both 1) the rate at which individuals are diagnosed and begin TB treatment, and 2) the demographic conditions in which the epidemic occurs, to reflect the diverse demographic scenarios in Sub-Saharan Africa and to explore influence of demography
We explore the effects of changing the rate at which these individuals move from the infected and infectious, to the infected and noninfectious compartment on TB infection dynamics, an effect that may be accomplished though improved diagnostics
Summary
To eliminate tuberculosis (TB), a reduction in incidence is imperative. One of the strategies to reduce the incidence of TB is to effectively treat all patients with TB with early case detection and higher cure rates, which will interrupt transmission [1].Time to treatment could be decreased through the use of a more accurate diagnostic, by reducing time to diagnosis, or other interventions access to care once diagnosed.There is opportunity for improvement in commonly used TB diagnostics, both in accuracy and speed of diagnosis. The model is designed to explore the potential effects of improved time to treatment though more accurate and timely diagnosis. All children and HIV+ adults can be susceptible to TB, latently infected with TB, or actively infected but not infectious to others. We explore the effects of changing the rate at which these individuals move from the infected and infectious, to the infected and noninfectious compartment on TB infection dynamics, an effect that may be accomplished though improved diagnostics. TB infection is governed by the rate of interaction between those susceptible to TB and those infected with active, infectious TB, and the infection parameter, β. Individuals recover from active TB at rates γ (HIV−), α (HIV+), and τ (children). HIV infection and aging dynamics are modeled separately, with individuals moving between TB, HIV and age states independently.
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