Anticipating the emergence of infectious diseases

In spite of medical breakthroughs, the emergence of pathogens continues to pose threats to both human and animal populations. To address this challenge, members of the Rohani lab, along with a collaboration with John Drake, present candidate approaches for anticipating disease emergence prior to large-scale outbreaks. Through use of ideas from the theories of dynamical systems and stochastic processes they developed approaches which are not specific to a particular disease system or model, but instead have general applicability. The indicators of disease emergence detailed in their paper can be classified into two parallel approaches: a set of early-warning signals based around the theory of critical slowing down and a likelihood-based approach. To test the reliability of these two approaches they contrasted theoretical predictions with simulated data. They concluded that their methods have meaningful applicability across a range of different model structures and parameter values.