Giuseppe
Emeritus
[Source: ScienceDirect, Epidemics, full page: (LINK). Abstract, edited.]
doi:10.1016/j.epidem.2011.04.002
Copyright ? 2011 Published by Elsevier B.V.
Comparing three basic models for seasonal influenza
Stefan Edlund<SUP>a</SUP><SUP>, </SUP><SUP>, </SUP>, James Kaufman<SUP>a</SUP>, Justin Lessler<SUP>b</SUP>, Judith Douglas<SUP>a</SUP>, Michal Bromberg<SUP>c</SUP>, Zalman Kaufman<SUP>c</SUP>, Ravit Bassal<SUP>c</SUP>, Gabriel Chodick<SUP>d</SUP>, Rachel Marom<SUP>d</SUP>, Varda Shalev<SUP>d</SUP>, Yossi Mesika<SUP>e</SUP>, Roni Ram<SUP>e</SUP> and Alex Leventhal<SUP>f</SUP>
<SUP>a</SUP> IBM Almaden Research Center, 650 Harry Road, San Jose, California, 95120, USA
<SUP>b</SUP> Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, Maryland 21205, USA
<SUP>c</SUP> Israel Center for Disease Control, Gertner Institute, Sheba Medical Center, Tel Hashomer 52621, Israel
<SUP>d</SUP> Maccabi Healthcare Services, 27 Ha?Merad Street, Tel Aviv 50493, Israel
<SUP>e</SUP> IBM Haifa Research Labs, Haifa University Campus, Mount Carmel, Haifa 31905, Israel
<SUP>f</SUP> Israel Ministry of Health, 20 King David Street, Jerusalem 91010, Israel
Received 4 December 2009; revised 13 April 2011; accepted 13 April 2011. Available online 13 May 2011.
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.
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doi:10.1016/j.epidem.2011.04.002
Copyright ? 2011 Published by Elsevier B.V.
Comparing three basic models for seasonal influenza
Stefan Edlund<SUP>a</SUP><SUP>, </SUP><SUP>, </SUP>, James Kaufman<SUP>a</SUP>, Justin Lessler<SUP>b</SUP>, Judith Douglas<SUP>a</SUP>, Michal Bromberg<SUP>c</SUP>, Zalman Kaufman<SUP>c</SUP>, Ravit Bassal<SUP>c</SUP>, Gabriel Chodick<SUP>d</SUP>, Rachel Marom<SUP>d</SUP>, Varda Shalev<SUP>d</SUP>, Yossi Mesika<SUP>e</SUP>, Roni Ram<SUP>e</SUP> and Alex Leventhal<SUP>f</SUP>
<SUP>a</SUP> IBM Almaden Research Center, 650 Harry Road, San Jose, California, 95120, USA
<SUP>b</SUP> Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, Maryland 21205, USA
<SUP>c</SUP> Israel Center for Disease Control, Gertner Institute, Sheba Medical Center, Tel Hashomer 52621, Israel
<SUP>d</SUP> Maccabi Healthcare Services, 27 Ha?Merad Street, Tel Aviv 50493, Israel
<SUP>e</SUP> IBM Haifa Research Labs, Haifa University Campus, Mount Carmel, Haifa 31905, Israel
<SUP>f</SUP> Israel Ministry of Health, 20 King David Street, Jerusalem 91010, Israel
Received 4 December 2009; revised 13 April 2011; accepted 13 April 2011. Available online 13 May 2011.
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.
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