An Analytics Framework to Support Surge Capacity Planning for Emerging Epidemics

Epidemics are a serious public health challenge, with epidemiologists and health analysts constantly trying to find more succinct ways to predict, and then prevent or minimize their impact. An important problem facing health systems is ensuring they are prepared for severe epidemics. Being able to predict an epidemic is only one part of the problem: resources need to be monitored in order to ensure their availability in the event of severe epidemics. Using System Dynamic modelling, health analysts can predict epidemics to a certain extent using previous infection dynamics, however mitigation strategies would be improved dramatically if the prediction was in real-time, utilizing the full potential of information from a range of sources: participatory surveillance systems, sentinel data from General Practitioners (GPs) etc. Using these techniques alongside Surge Capacity modelling allows the monitoring of resources for all areas of the health system, equipment levels, staff levels, and bed availability etc., ensuring better preparedness. This paper introduces a way to bring these concepts together, and highlights future work which will expand on these ideas allowing for the possible reallocation of resources in the event of shortage in some areas, and spare capacity in others.