Seniors Present Mass Prophylaxis Project at Undergraduate Research Forum

Public Health organizations must plan ahead to deal with possible epidemics like influenza or attacks like Anthrax. An essential part of that planning entails understanding of the staffing needed to innoculate large numbers of area residents in a mass prophylaxis campaign.

Two ORIE members of the class of 2008, Caitlin Hawkins and Cindie Wu, have developed a software tool that will help planners respond in the most effective way to such a challenge. They presented a poster about their work at the Cornell Undergraduate Research Board (CURB) Forum held in the Duffield Atrium on April 23, 2008.

In their presentation, the team emphasized that appropriate staffing can make a major difference in the effectiveness of a prophylaxis campaign. For an epidemic such as influenza, vaccinating within 48 hours can  reduce the spread and severity of the virus. With an Anthrax attack, rapid response can dramatically increase the chance of individual survival.  

As anyone who has suffered through prolonged waiting on line for service in by an inadequately staffed system knows, proper planning matters -- and even more so in an epidemic situation where waiting in line increases the possibility of exposure to the disease. But the human resources required to conduct a mass prophylaxis campaign are specialized and in short supply, so planners must be able to determine the best way to allocate these resources to specific work stations on a shift-by-shift basis.  Staffing allocations should be based on an assessment of the number of people arriving for vaccination in each time period, as well as an understanding that arrivals (and service times) are subject to random variability. 

Hawkins and Wu built a software model with an easy-to-use interface that enables planners to see how the waiting lines build up for a given scenario about minimum, maximum and mostly likely arrival rates and the numbers of workers at each location. Using formulas from queuing theory, the system makes suggestions about how many workers to place where, and it takes into account that different types of patients may require different service times (for example, families arriving together, non-English speakers, etc.). Once the input has been provided, planners can see the implications in terms of throughput, queue length, and other key measures, based on repeated simulation runs. 

Wu, who is from Holmdel, NJ, will continue her studies at Stanford, where she has been admitted to the Ph.D. program in Management Science and Engineering.  "We were able to learn a lot from the project because we were given a lot of freedom to produce a product." She notes that the product was built using Excel and Visual Basic skills learned in the new ORIE 484 course, "Spreadsheet Modelling and Data Analysis" taught by Dr. Kathryn Caggiano.

Hawkins, from Damon Texas, will also pursue a Ph.D. She will join the Decision, Operations and Technology Management Ph.D. program at the UCLA Anderson School of Management in the fall.   Although she built simulations in a course, "I really liked the creation of the simulation for this project, because the problem is so interesting," she said.

According to Professor Jack Muckstadt all of the published literature related to the research by Hawkins and Wu focuses on staffing requirements for innoculation drills rather than for actual mass casualty events. As a result, "they do not deal adequately with the dynamics of the situation as they unfold over time."

In a real situation, many dispensing points are required -- more than 200 in a city like New York, for example. Other research, being carried out under Muckstadt's direction by ORIE Ph.D. student Kathleen King is investigating a forward looking approach to allocating those seeking vaccination to dispensing points as well as how they might be transported.

The simulation model created by Hawkins and Wu will be an essential component of this broader analysis. Their project was advised by Professor Muckstadt with assistance from who advised the team along with Nathaniel Hupert, Professor of Clinical Public Health at Weill Cornell Medical College.