Strategies for Reducing Incidence of Tuberculosis Disease in a Low-Burden Setting

Pulmonary tuberculosis (TB) is a communicable disease that has an airborne route of transmission. It is a disease of poverty that exists in every country of the world. Within high-income, low TB burden settings, the disease increasingly affects vulnerable and underserved population groups who are hard to reach. In tandem, as TB becomes rarer, expertise in diagnosing and managing the disease declines. These two facts threaten TB elimination efforts because the delayed diagnosis of pulmonary TB can lead to transmission. Transmission can cause primary disease, or a latent TB infection (LTBI) that without appropriate precautions can reactivate at a later date, thereby causing future transmission. As such, within high-income countries already adept at identifying contacts and offering prophylaxis, it is making timelier diagnoses of pulmonary TB to interrupt transmission that is crucial. This work focuses on strategies aimed at improving current programming efforts in a high-income setting. The studies presented herein: 1) characterize the most infectious cases, with implications for raising clinical suspicion among all providers, 2) show that it is possible to ‘predict’ pulmonary TB among a cohort of people referred for TB services on the basis of readily available information from a targeted medical history, and, 3) identify a significant point of contact with the healthcare setting for undiagnosed pulmonary TB patients (the emergency department). This latter study suggests that, once validated, prediction algorithms for pulmonary TB may provide diagnostic tools that would have great application in settings where TB is frequently overlooked.