In this study, we present an interactive web-based real-time decision support suite, RealOpt©.e system integrates visualization, information and cognitive analytics, and dynamic large-scale computational modeling and optimization tools that allow public health emergency preparedness coordinators to determine optimal response facilities and locations, resource needs and supply-routes, and population ow in real time. With an eye towards exibility and future system expansion, RealOpt is designed in modular format allowing direct linkage to multiple functional modules. Currently, the system has twelve modules covering emergency response preparedness and operations for biological, chemical, radiological/nuclear incidents, biosurveillance, epidemiology, and decontamination models, operations logistics and networks, a real-time crowd sourcing data feed, and evacuation planning. RealOpt has been used for biodefense and H1N1 regional planning and operations, regional ood and hurricane responses, 2010 Haiti earthquake disaster relief, 2011 Japan Fukushima disaster, 2014-2015 Ebola containment assistance and a er-event public health preparedness training in West Africa, and current Zika virus containment analysis. e fast solution engines enable real-time use for rapid decision and scenario analysis, since it requires only one CPU minute to determine an optimal network of facilities and resource needs to serve a population of over 10 million.
CCS CONCEPTS•Information systems → Decision support systems; •Computing methodologies → Model development and analysis; •Applied computing → Health care information systems; * e ndings and conclusions in this report are those of the authors and do not necessarily represent the o cial position of the CDC. † Corresponding