Comparing three basic models for seasonal influenza

Stefan Edlund, James Kaufman, Justin Lessler, Judith Douglas, Michal Bromberg, Zalman Kaufman, Ravit Bassal, Gabriel Chodick, Rachel Marom, Varda Shalev, Yossi Mesika, Roni Ram, Alex Leventhal

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper we report the use of the open source Spatiotemporal Epidemiological Modeler (STEM, www.eclipse.org/stem) to compare three basic models for seasonal influenza transmission. The models are designed to test for possible differences between the seasonal transmission of influenza A and B. Model 1 assumes that the seasonality and magnitude of transmission do not vary between influenza A and B. Model 2 assumes that the magnitude of seasonal forcing (i.e., the maximum transmissibility), but not the background transmission or flu season length, differs between influenza A and B. Model 3 assumes that the magnitude of seasonal forcing, the background transmission, and flu season length all differ between strains. The models are all optimized using 10 years of surveillance data from 49 of 50 administrative divisions in Israel. Using a cross-validation technique, we compare the relative accuracy of the models and discuss the potential for prediction. We find that accounting for variation in transmission amplitude increases the predictive ability compared to the base. However, little improvement is obtained by allowing for further variation in the shape of the seasonal forcing function.

Original languageEnglish
Pages (from-to)135-142
Number of pages8
JournalEpidemics
Volume3
Issue number3-4
DOIs
StatePublished - Sep 2011
Externally publishedYes

Keywords

  • Compartmental disease models
  • Epidemics
  • Predictive validity
  • Simulation

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