TY - JOUR T1 - A new mathematical model to identify contacts with recent and remote latent tuberculosis JF - ERJ Open Research JO - erjor DO - 10.1183/23120541.00078-2019 VL - 5 IS - 2 SP - 00078-2019 AU - Gabrielle Fröberg AU - Emilie Wahren Borgström AU - Erja Chryssanthou AU - Margarida Correia-Neves AU - Gunilla Källenius AU - Judith Bruchfeld Y1 - 2019/04/01 UR - http://openres.ersjournals.com/content/5/2/00078-2019.abstract N2 - Tuberculosis (TB) elimination programmes need to target preventive treatment to groups with an increased risk of TB activation, such as individuals with a latent tuberculosis infection (LTBI) acquired recently. Current diagnostic tests for LTBI have poor predictive values for TB activation and there is, at present, no reference method to evaluate new LTBI diagnostic and prognostic tools. Thus, our objective was to develop a mathematical model, independent of currently available diagnostic tests, to estimate the individual probability of recent and/or remote LTBI.Estimations of recent LTBI were based on the contagiousness of index case, proximity and time of exposure, and environmental factors. Estimation of remote LTBI was based on country of origin, previous stays in high-risk environments or known exposure to TB. Individual probabilities were calculated and compared with tuberculin skin test (TST) and interferon-γ release assay results for 162 contacts of 42 index TB cases.Probabilities of remote LTBI were 16% for European/American contacts and 38% for African/Asian contacts. The probability of recent LTBI was 35% for close contacts to smear microscopy positive index cases. A higher probability of remote LTBI was seen among TST-positive contacts.This model may, with further validation, be used as an independent tool to evaluate new diagnostic markers for recent LTBI.This mathematical model to estimate probability of recent and remote latent TB was based on clinical and epidemiological risk factors of exposure and may be used in the evaluation of new diagnostic markers with enhanced predictive values for TB activation http://bit.ly/2IWi6Ru ER -