Tau-leaped Particle Learning

Authors

  • Jarad Niemi Iowa State University
  • Michael Ludkovski University of California, Santa Barbara

DOI:

https://doi.org/10.5210/ojphi.v5i1.4575

Abstract

Development of effective policy interventions to stem disease outbreaks requires knowledge of the current state of affairs, e.g. how many individuals are currently infected, a strain's virulence, etc, as well as our uncertainty of these values. A Bayesian inferential approach provides this information, but at a computational expense. We develop a sequential Bayesian approach based on an epidemiological compartment model and noisy count observations of the transitions between compartments.

Author Biography

Jarad Niemi, Iowa State University

Dr. Jarad Niemi is an assistant professor in the Department of Statistics and Statistical Laboratory at Iowa State University. He is an expert on Bayesian analysis and computational statistics. As an applied area of interest, Dr. Niemi is interested on optimal control of disease outbreaks based on surveillance data.

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Published

2013-03-24

How to Cite

Niemi, J., & Ludkovski, M. (2013). Tau-leaped Particle Learning. Online Journal of Public Health Informatics, 5(1). https://doi.org/10.5210/ojphi.v5i1.4575

Issue

Section

Oral Presentations: Analytical Methods - Bayesian