Rationale: 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. Objectives: To estimate the population-level impact of TB casefinding strategies in the presence of subclinical and prediagnostic disease. Methods: 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"). Measurements and Main Results: 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. Conclusions: 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.Keywords: tuberculosis; diagnostic techniques and procedures; models; theoretical; epidemiology Improved diagnosis is a cornerstone of current efforts to control tuberculosis (TB) (1). For the last 15 years, the World Health Organization (WHO) and Stop TB Partnership have focused on improving TB case detection and treatment success, in part because key mathematical models predicted that meeting these targets would result in improved disease control (2). Although the directly observed therapy, short-course strategy has been scaled up globally and has saved more than 1 million lives (3), 1.4 million people still die every year from TB (4). Most of these deaths reflect diagnosis that is either delayed, missed, or never attempted. Strategies for improving TB diagnosis generally take one of three forms: (1) improvement of the "passive" diagnostic system (e.g., deploying new diagnostic tools, such as Xpert MTB/RIF [5,6] for diagnosis of people who present with TB symptoms); (2) "enhanced" diagnosis that aims to reduce delays in diagnosis for patients with recognizable symptoms, such as community awareness campaigns (7) and improved access to TB diagnostic services (8); and (3) "active" strategies that do not rely on patient presentation (e.g., household surveys [9], contact in...