Current respiratory isolation guidelines, issued by the Centers for Disease Control and Prevention, for the control of nosocomial transmission of tuberculosis (TB) are based on early identification and isolation of patients considered at risk for the disease. However, because of under- recognition of patients with TB and over-diagnosis of patients at risk for the disease, these guidelines have not been fully effective. The over-diagnosis not only results in large numbers of patients unnecessarily placed in respiratory isolation, but also creates substantial resource burdens for health care institutions. Hospitals that serve populations with a high prevalence of TB are particularly affected by these issues. The investigators have previously derived a clinical prediction rule, based on data collected in a retrospective fashion, to identify patients who will require isolation on admission to the hospital. The objective of the study described in the current application is to obtain data on a cohort of patients, placed in respiratory isolation on admission to two different New York City hospitals, to prospectively refine and validate a clinical prediction rule for the need for respiratory isolation of patients at risk for pulmonary TB. This information could be used to design new isolation policies that will accomplish the important objectives of reducing nosocomial transmission of TB while reducing hospital costs.