A mathematical model for the prediction of the impact of HIV infection on tuberculosis.

ABSTRACT

A mathematical model is introduced to study the accelerating impact of HIV infection on the incidence rates of tuberculosis (TB) disease. A sexually active population (15-49 years) is followed cross-sectionally over a period of time. Beginning with the year in which HIV infection was probably first present in the population, the model calculates the growing yearly incidence rates of new TB disease in HIV-positive and in HIV-negative individuals. Model equations, derived by an actuarial method, are developed recursively. Input information required for the calculations includes the age distribution of the study population, pre-HIV annual TB infection rates, annual HIV infection and mortality rates, and estimates of annual TB disease breakdown rates in the absence and in the presence of HIV infection. With correct input data, the model provides a useful blueprint for health agencies in designing effective programmes for curbing the future course of these dual epidemics in the population.