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Computer-Aided Design Nathaniel Hupert, M.D., M.P.H. Assistant Professor of Public Health and Medicine Division of Outcomes and Effectiveness Research.

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Presentation on theme: "Computer-Aided Design Nathaniel Hupert, M.D., M.P.H. Assistant Professor of Public Health and Medicine Division of Outcomes and Effectiveness Research."— Presentation transcript:

1 Computer-Aided Design Nathaniel Hupert, M.D., M.P.H. Assistant Professor of Public Health and Medicine Division of Outcomes and Effectiveness Research Weill Medical College of Cornell University

2 Guiding Questions What are the critical components of a mass vaccination campaign? What role can spreadsheet models play in forecasting resource requirements for mass vaccination campaigns? What are the limitations of computer modeling in developing mass vaccination plans?

3 Components of Mass Prophylaxis Plan

4 Created by the Department of Public Health, Weill Medical College of Cornell University, NYCOEM, and NYCDOHMH SAMPLE PATIENT FLOW DIAGRAM FOR MASS ANTIBIOTIC DISPENSING VERY SICK GET TRANSPORT TO MEDICAL FACILITY HEALTHY PEOPLE GET PROPHYLAXIS AMBULATORY SICK GET TREATMENT SAMPLE PATIENT FLOW DIAGRAM FOR MASS ANTIBIOTIC DISPENSING Created by the Department to Public Health, Weill Medical College of Cornell Univeristy, NYCOEM, and NYCDOHMH

5 SCHEMATIC FLOW THROUGH SIMPLE DISPENSING MODEL

6 Steady-state assumption Steady state develops if  = R/ST  whereR  =  patient arrival rate S = # staff T  =  mean service time T  =  mean service time When  =  then S = RT, orWhen  =  then S = RT, or Staff required at a station = Rate of patient arrival at that station Mean station processing time per patient X

7 SCHEMATIC FLOW THROUGH WEILL/CORNELL SMALLPOX VACCINATION MODEL R

8 Weill/Cornell Smallpox Vaccination Staffing Model R PRE-EVENT

9 Weill/Cornell Smallpox Vaccination Staffing Model R POST-EVENT

10 SAMPLE OUTPUT OF WEILL/CORNELL SMALLPOX VACCINATION MODEL

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12 4 Days

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14 Limitations Accuracy of any model depends on the quality of the underlying data Processing times are critical variable Processing times are critical variable Output is design-specific A differently designed vaccination center may give a different result A differently designed vaccination center may give a different result Multiple scalable centers with externally controlled patient flow Feasible but requires law enforcement input Feasible but requires law enforcement input These numbers reflect only critical dispensing staff and do not include support staff for the centers or distribution and logistics staff

15 Conclusions Spreadsheet modeling allows planners to “think with numbers” when designing mass prophylaxis response strategies Modeling forces critical examination of: Assumptions about vaccination center layout and processes Assumptions about vaccination center layout and processes Availability of resources Availability of resources Model estimates are useful data to guide planning but do not replace the real thing: LIVE, REALISTIC EXERCISES

16 AcknowledgmentsCo-Investigators Jason Cuomo, MPH Jason Cuomo, MPH Mark A. Callahan, MD Mark A. Callahan, MD Alvin I. Mushlin, MD, ScM Alvin I. Mushlin, MD, ScM NYC Office of Emergency Management Edward Gabriel, MPA, AEMT-P Sam Benson, AEMT-P Anita Sher, MIA U.S. DHHS, Office of the Asst. Sec’y for Public Health Preparedness Capt. Ann Knebel, RN, DNSc NYC Dept. of Health, Communicable Disease Unit Marci Layton, MD Sue Blank, MD, MPH NY Presbyterian Healthcare System Eliot Lazar, MD Arthur Klein, MD Neal Flomenbaum, MD


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