Colloquium

• Home
• Undergraduate Programs
  • Major
  • Minors
  • Advising
• Graduate Programs
  • Master's Degree
  • Ph.D. Degree
  • Certificate in Statistics
  • How to Apply
  • Handbook
  • FAQ
• Courses
• Four-year Offerings
• WMU Calendar
• Final Exams

---

• People
  • Faculty and Staff
  • Graduate Students
  • Alumni
• Statistical Consulting Center
• Newsletter
• Resources
• Careers in Statistics
• Contact Us

 

Statistics Colloquium
September 23 (Fri) 11 a.m.
Alavi Commons Room, 6625 Everett Tower

A viral count driven calibration approach for simulation models of concurrent pandemic and seasonal influenza outbreaks

Diana Prieto
IME, Western Michigan University

Influenza viruses imply major preparedness challenges for public health policymakers. With the uncertain epidemiology of these viruses, decision making often involves a tradeoff between the social costs resulting from the implementation of a mitigation strategy (e.g., school closure) and the harm caused by the uncontrolled spread of an influenza virus. To minimize the trade-off, policymakers often need to re-evaluate mitigation strategies as the disease progresses.

Simulations are useful tools to model disease spread and support re-evaluation of strategies. However, simulations are not yet adapted for operational response in progressing pandemic outbreaks.

One of the simulation features in need for operational adaptation is the model calibration. Usually, simulation models require human interaction to adjust the internal model parameters until obtaining a desired value. In this research, we propose a viral count driven approach to automate the calibration process and eliminate the need of the human component. The approach is based on the epidemiological and statistical principles underlying the pandemic and seasonal influenza viruses, and is tested in an agent-based model simulating the daily interaction of urban citizens.

All statistics students are expected to attend.