Literature DB >> 22094336

Comparing three basic models for seasonal influenza.

Stefan Edlund1, James Kaufman, Justin Lessler, Judith Douglas, Michal Bromberg, Zalman Kaufman, Ravit Bassal, Gabriel Chodick, Rachel Marom, Varda Shalev, Yossi Mesika, Roni Ram, Alex Leventhal.   

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.
Copyright © 2011 Elsevier B.V. All rights reserved.

Mesh:

Year:  2011        PMID: 22094336     DOI: 10.1016/j.epidem.2011.04.002

Source DB:  PubMed          Journal:  Epidemics        ISSN: 1878-0067            Impact factor:   4.396


  5 in total

1.  A dynamic pandemic model evaluating reopening strategies amid COVID-19.

Authors:  Ling Zhong
Journal:  PLoS One       Date:  2021-03-26       Impact factor: 3.240

2.  4Flu - an individual based simulation tool to study the effects of quadrivalent vaccination on seasonal influenza in Germany.

Authors:  Martin Eichner; Markus Schwehm; Johannes Hain; Helmut Uphoff; Bernd Salzberger; Markus Knuf; Ruprecht Schmidt-Ott
Journal:  BMC Infect Dis       Date:  2014-07-03       Impact factor: 3.090

3.  STEM: An Open Source Tool for Disease Modeling.

Authors:  Judith V Douglas; Simone Bianco; Stefan Edlund; Tekla Engelhardt; Matthias Filter; Taras Günther; Kun Maggie Hu; Emily J Nixon; Nereyda L Sevilla; Ahmad Swaid; James H Kaufman
Journal:  Health Secur       Date:  2019 Jul/Aug

4.  A global model of malaria climate sensitivity: comparing malaria response to historic climate data based on simulation and officially reported malaria incidence.

Authors:  Stefan Edlund; Matthew Davis; Judith V Douglas; Arik Kershenbaum; Narongrit Waraporn; Justin Lessler; James H Kaufman
Journal:  Malar J       Date:  2012-09-18       Impact factor: 2.979

5.  Causality in scale space as an approach to change detection.

Authors:  Stein Olav Skrøvseth; Johan Gustav Bellika; Fred Godtliebsen
Journal:  PLoS One       Date:  2012-12-27       Impact factor: 3.240

  5 in total

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