Spatio-temporal analysis of tuberculous infection risk among clients of a homeless shelter during an outbreak.

British Columbia (BC) has a low incidence of tuberculosis (TB), with the burden of endogenously acquired disease concentrated among vulnerable populations, including the homeless. In May 2008, a TB outbreak began in a BC homeless shelter, with a single index case seeding multiple secondary cases within the shelter.To use nightly shelter records to quantify the risk of latent tuberculous infection (LTBI) among shelter clients as a function of their sleeping distance from and duration of exposure to the index case.Distance and duration of exposure were visualised and assessed using logistic regression with LTBI status as outcome. We used a novel machine learning approach to establish exposure thresholds that optimally separated infected and non-infected individuals.Of 161 exposed shelter clients, 58 had a recorded outcome of infected (n = 39) or non-infected (n = 19). Only duration of exposure to the index was associated with increased odds of infection (OR 1.26); stays of ⩾ 5 nights put shelter clients at higher odds of infection (OR 4.97).The unique data set and analytical approach suggested that, in a shelter environment, long-term clients are at highest risk of LTBI and should be prioritised for screening during an outbreak investigation.