A new TB case can be classified as: 1) a source case for transmission leading to other, secondary active TB cases; 2) a secondary case, resulting from recent transmission; or 3) an isolated case, uninvolved in recent transmission (i.e. neither source nor recipient). Source and secondary cases require more intense intervention due to their involvement in a chain of transmission; thus, accurate and rapid classification of new patients should help public health personnel to effectively prioritize control activities. However, currently accepted method for the classification, DNA fingerprint analysis, takes many weeks to produce the results; therefore, public health personnel often solely rely on their intuition to identify the case who is most likely to be involved in transmission. Various clinical and socio-demographic features are known to be associated with TB transmission. By using these readily available data at the time of diagnosis, it is possible to rapidly estimate the probabilities of the case being source, secondary, and isolated.
Objective
To develop and validate a prediction model which estimates the probability of a newly diagnosed tuberculosis (TB) case being involved in ongoing chain of transmission, based on the case's clinical and socio-demographic attributes available at the time of diagnosis.