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Abstract
Tuberculosis (TB) is characterized by a subclinical phase (symptoms absent or not considered abnormal); prediagnostic phase (symptoms noticed but diagnosis not pursued); and clinical phase (care actively sought). Diagnostic capacity during these phases is limited.To estimate the population-level impact of TB case-finding strategies in the presence of subclinical and prediagnostic disease.We created a mathematical epidemic model of TB, calibrated to global incidence. We then introduced three prototypical diagnostic interventions: increased sensitivity of diagnosis in the clinical phase by 20% ("passive"); early diagnosis during the prediagnostic phase at a rate of 10% per year ("enhanced"); and population-based diagnosis of 5% of undiagnosed prevalent cases per year ("active").If the subclinical phase was ignored, as in most models, the passive strategy was projected to reduce TB incidence by 18% (90% uncertainty range [UR], 11-32%) by year 10, compared with 23% (90% UR, 14-35%) for the enhanced strategy and 18% (90% UR, 11-28%) for the active strategy. After incorporating a subclinical phase into the model, consistent with population-based prevalence surveys, the active strategy still reduced 10-year TB incidence by 16% (90% UR, 11-28%), but the passive and enhanced strategies' impact was attenuated to 11% (90% UR, 8-25%) and 6% (90% UR, 4-13%), respectively. The degree of attenuation depended strongly on the transmission rate during the subclinical phase.Subclinical disease may limit the impact of current diagnostic strategies for TB. Active detection of undiagnosed prevalent cases may achieve greater population-level TB control than increasing passive case detection.
View details for DOI 10.1164/rccm.201207-1217OC
View details for Web of Science ID 000315977200014
View details for PubMedID 23262515