Timely production of high quality and evidence based rapid risk/outbreak assessments in response to communicable disease threats is important not only in human, but also among animals.
Advances in computing power, together with the amount of data obtained from disease surveillance, registries, sensors or digital traces enable machine learning, complex system analytics and standard statistical tools as well as computer simulation to be applied to the field of Veterinary Epidemiology.
Our team member was visiting Australia (UNE) in middle of Novermber analyze animal contact networks (based on RFID tags) in poultry farms from an infectious disease modeling perspective i.e. to estimate critical detection times.
Andrzej has shown 3 case studies: 1) modelling, 2) infodemiology, 3) sensors: