Quantification of tuberculosis exposure in a high-burdened setting: a modelling study

Abstract

Recent studies using sensitive aerosol sampling and detection methodologies, have enumerated aerosolized Mycobacterium tuberculosis (Mtb) across a spectrum of tuberculosis states in a high-burdened setting. To estimate the Mtb exposure rate we used a Bayesian inference approach to fit a reversible catalytic model to age-specific, respiratory bioaerosol Mtb prevalence data. Longitudinal monitoring of symptomatic sputum-negative, untreated clinic attendees informed a prior for the Mtb bioaerosol clearance rate. Based on an observed bioaerosol Mtb population prevalence of 62.6% and a clearance half-life of 83 days, the estimated exposure rate was 5.1/year. This result was extremely sensitive to bioaerosol Mtb population prevalence but including a simulated rate of exposure of zero until the age of 10-years did not influence the overall estimate for rate of exposure. A catalytic model without reversion was a poorer fit to the prevalence data than the primary reverse catalytic model. Mtb bioaerosol sampling findings imply an extremely high rate of Mtb exposure within TB endemic communities with rapid cycling between bioaerosol carriage and clearance. Even assuming a much lower bioaerosol Mtb population prevalence, the estimated exposure rate is an order of magnitude greater than published annual rates of Mtb infection.