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Public Health and RealOpt. Introduction Objectives & Challenges Solutions OR Models Computational Advances Benefits Future Outlook and Challenges. CONTENT. What kind of catastrophes? Biological Disasters Radiological Disasters Chemical Disasters Earthquakes Floods Tsunamis Fires
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Introduction • Objectives & Challenges • Solutions • OR Models • Computational Advances • Benefits • Future Outlook and Challenges CONTENT
What kind of catastrophes? Biological Disasters Radiological Disasters Chemical Disasters Earthquakes Floods Tsunamis Fires Epidemics Tropical cyclones Constraints • Time • Staff • Financial Resources • Medical equipment • Geographic availability The Overall Picture
RealOpt combines… • Large scale computational engine • Advanced graph drawing tools • 3D geographical spatial information • Federal census data • Demographic and socioeconomic data What is RealOpt?
Dynamic operational planning and execution • Strategic and tactical decision making • Policy making • Establishment of knowledge database Facilities & Content
POD : Point of dispensing service • Walk-in • Drive-through • Mobile • Private • Dispensing to large area • Scarce staffing • Tight timing • Feasibility in terms of people hour • Cycle time of implementation • Decentralized US health system • Non-standardized operations Challenges
OR Models Cognitive-analytic systems Can be used by large audience system Automatic translation from mouse clicks Easy user interfaces Effective cognitive-analytic integration • Large scale simulator optimizer • Real time nonlinear mixed integer program resource allocation capability • Real time simulator • Optimization theory • Large scale optimizer • Rapid heuristic Solutions
Facility Location Module • Determines • #of PODsthat should be set up • Assignmentof households tobe serviced by each site • Region • Seperatedand discretizedstrategically based on population density • Constraints • Physicallimitations at each site • Householdassignments • Householdtravel time • Household distanceto the POD Regional Network
Facility Location Module 1st Stage • Optimizes thenumber of facilities opened 2nd Stage • Optimizesthe time and distance traveled The results are very large-scale instances withthe number of 0-1 decision variables ranging from40 thousand to 10 million. Regional Network
SolutionStrategies forReal-TimeDecisionMaking • Developa theorybased on conflict hyper graph structures and apply branch-and-cut techniques to exactly solveour problems • We develop rapid heuristicsthat can achieve near-optimal solutions for real-timeonline decision support. • A site with a high pediatric population needsextra pharmacy and medical personnel because eachdose must be calculated based on the weight of eachchild. • A site with a low socioeconomic populationmay require buses to transport citizens to the PODand may require additional staff to help people fillout paperwork. Some Critical Features for Medical Preparedness Regional Network
First implementation – 2004 • For a chosen pilot countywithpoorrecords • Afterimplementation– highestscoreswithfeweststaff • Nationwidepublic dissemination of theRealOpt - 2007 Public Dissemination
Quantative Qualitative • Widespread adoption • Use in planning and actual operations • Preventing illness and saving lives • Reduction of labor requirements and number of dispensingfacilities • Establishment of knowledge data bank • National security and emergency response capability • Quality assurance and training • Quality of service and worker morale • Reduction in planning time • OR scientific and technology advances Benefits
Quantitiesof supplies at the Haiti airport Beyond Public Health
Distributionpaths and supply items at thePort au Prince airport Beyond Public Health
By RealOpt’smodular structure, it • Allows newtechnologies • Allowsnew components to be incorporatedeasily • Benefits from OR advances Continuing to validate and testis necessarytomaintain • Relevance • quality • practicality of RealOpt’s output Future Outlook and Challenges