Exact calculation of end-of-outbreak probabilities using contact tracing data

Abstract

AbstractA key challenge for public health policy makers is determining when an infectious disease outbreak has finished. Following a period without cases, an estimate of the probability that no further cases will occur in future (the end-of-outbreak probability) can be used to inform whether or not to declare an outbreak over. An existing quantitative approach, based on a branching process transmission model, allows the end-of-outbreak probability to be approximated from disease incidence time series, the offspring distribution and the serial interval of the pathogen (the Nishiura method). Here, we show how the end-of-outbreak probability under the same transmission model can be calculated exactly if data describing who-infected-whom (the outbreak transmission tree) are available alongside the disease incidence time series. When such data are available, for example from contact tracing studies, our novel approach (the traced transmission method) is straightforward to use. We demonstrate this by applying the traced transmission method to data from previous outbreaks of Ebola virus disease and Nipah virus infection. For both outbreak datasets considered, we find that the traced transmission method would have determined that the outbreak was over more quickly than the Nishiura method. This highlights that consideration of contact tracing data may allow stringent control interventions to be relaxed quickly at the end of an outbreak, with only a limited risk of outbreak resurgence.