Proceedings of the National Academy of Sciences · 2023 · 48 citations · 51 references
Public HealthBiostatisticsInfectious DiseasesBayesian BiostatisticsBayesian Data AnalysisEpidemiologyLatent Tuberculosis InfectionPulmonary TuberculosisTuberculosis CareTuberculosis DiagnosisTuberculosis EpidemiologyTuberculosis PreventionDisease DurationMycobacterium Tuberculosis InfectionMycobacterium Tuberculosis PathogenesisPulmonary Tuberculosis EpidemiologySymptomatic Disease PrevalenceTuberculosis Cohort AnalysisTuberculosis Incidence EstimationTuberculosis Mortality
Traditional understanding of the risk of progression from Mycobacterium tuberculosis ( Mtb ) infection to tuberculosis (TB) overlooks diverse presentations across a spectrum of disease. We developed a deterministic model of Mtb infection and minimal (pathological damage but not infectious), subclinical (infectious but no reported symptoms), and clinical (infectious and symptomatic) TB, informed by a rigorous evaluation of data from a systematic review of TB natural history. Using a Bayesian approach, we calibrated the model to data from historical cohorts that followed tuberculin-negative individuals to tuberculin conversion and TB, as well as data from cohorts that followed progression and regression between disease states, disease state prevalence ratios, disease duration, and mortality. We estimated incidence, pathways, and 10-y outcomes following Mtb infection for a simulated cohort. Then, 92.0% (95% uncertainty interval, UI, 91.4 to 92.5) of individuals self-cleared within 10 y of infection, while 7.9% (95% UI 7.4 to 8.5) progressed to TB. Of those, 68.6% (95% UI 65.4 to 72.0) developed infectious disease, and 33.2% (95% UI 29.9 to 36.4) progressed to clinical disease. While 98% of progression to minimal disease occurred within 2 y of infection, only 71% and 44% of subclinical and clinical disease, respectively, occurred within this period. Multiple progression pathways from infection were necessary to calibrate the model and 49.5% (95% UI 45.6 to 53.7) of those who developed infectious disease undulated between disease states. We identified heterogeneous pathways across disease states after Mtb infection, highlighting the need for clearly defined disease thresholds to inform more effective prevention and treatment efforts to end TB.
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