Literature DB >> 25878297

Infectious disease modeling methods as tools for informing response to novel influenza viruses of unknown pandemic potential.

Manoj Gambhir1, Catherine Bozio2, Justin J O'Hagan3, Amra Uzicanin4, Lucinda E Johnson5, Matthew Biggerstaff5, David L Swerdlow6.   

Abstract

The rising importance of infectious disease modeling makes this an appropriate time for a guide for public health practitioners tasked with preparing for, and responding to, an influenza pandemic. We list several questions that public health practitioners commonly ask about pandemic influenza and match these with analytical methods, giving details on when during a pandemic the methods can be used, how long it might take to implement them, and what data are required. Although software to perform these tasks is available, care needs to be taken to understand: (1) the type of data needed, (2) the implementation of the methods, and (3) the interpretation of results in terms of model uncertainty and sensitivity. Public health leaders can use this article to evaluate the modeling literature, determine which methods can provide appropriate evidence for decision-making, and to help them request modeling work from in-house teams or academic groups.
© The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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Year:  2015        PMID: 25878297      PMCID: PMC4481577          DOI: 10.1093/cid/civ083

Source DB:  PubMed          Journal:  Clin Infect Dis        ISSN: 1058-4838            Impact factor:   9.079


  45 in total

1.  The construction and analysis of epidemic trees with reference to the 2001 UK foot-and-mouth outbreak.

Authors:  D T Haydon; M Chase-Topping; D J Shaw; L Matthews; J K Friar; J Wilesmith; M E J Woolhouse
Journal:  Proc Biol Sci       Date:  2003-01-22       Impact factor: 5.349

2.  Estimating in real time the efficacy of measures to control emerging communicable diseases.

Authors:  Simon Cauchemez; Pierre-Yves Boëlle; Guy Thomas; Alain-Jacques Valleron
Journal:  Am J Epidemiol       Date:  2006-08-03       Impact factor: 4.897

3.  The estimation of the effective reproductive number from disease outbreak data.

Authors:  Ariel Cintrón-Arias; Carlos Castillo-Chávez; Luís M A Bettencourt; Alun L Lloyd; H T Banks
Journal:  Math Biosci Eng       Date:  2009-04       Impact factor: 2.080

4.  Notes from the field: outbreak of 2009 pandemic influenza A (H1N1) virus at a large public university in Delaware, April-May 2009.

Authors:  A Danielle Iuliano; Carrie Reed; Alice Guh; Mitesh Desai; D L Dee; Preeta Kutty; L Hannah Gould; Mark Sotir; Gavin Grant; Michael Lynch; Tarissa Mitchell; Jane Getchell; Bo Shu; J Villanueva; Stephen Lindstrom; Mehran S Massoudi; Joseph Siebold; Paul R Silverman; Gregory Armstrong; David L Swerdlow
Journal:  Clin Infect Dis       Date:  2009-12-15       Impact factor: 9.079

Review 5.  A review of mathematical models of HIV/AIDS interventions and their implications for policy.

Authors:  Leigh F Johnson; Peter J White
Journal:  Sex Transm Infect       Date:  2011-06-16       Impact factor: 3.519

6.  Forecasting peaks of seasonal influenza epidemics.

Authors:  Elaine Nsoesie; Madhav Mararthe; John Brownstein
Journal:  PLoS Curr       Date:  2013-06-21

7.  Estimating the impact of school closure on influenza transmission from Sentinel data.

Authors:  Simon Cauchemez; Alain-Jacques Valleron; Pierre-Yves Boëlle; Antoine Flahault; Neil M Ferguson
Journal:  Nature       Date:  2008-04-10       Impact factor: 49.962

8.  The transmissibility and control of pandemic influenza A (H1N1) virus.

Authors:  Yang Yang; Jonathan D Sugimoto; M Elizabeth Halloran; Nicole E Basta; Dennis L Chao; Laura Matrajt; Gail Potter; Eben Kenah; Ira M Longini
Journal:  Science       Date:  2009-09-10       Impact factor: 47.728

9.  A novel sequence-based antigenic distance measure for H1N1, with application to vaccine effectiveness and the selection of vaccine strains.

Authors:  Keyao Pan; Krystina C Subieta; Michael W Deem
Journal:  Protein Eng Des Sel       Date:  2010-11-30       Impact factor: 1.650

10.  Novel framework for assessing epidemiologic effects of influenza epidemics and pandemics.

Authors:  Carrie Reed; Matthew Biggerstaff; Lyn Finelli; Lisa M Koonin; Denise Beauvais; Amra Uzicanin; Andrew Plummer; Joe Bresee; Stephen C Redd; Daniel B Jernigan
Journal:  Emerg Infect Dis       Date:  2013-01       Impact factor: 6.883

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  4 in total

1.  Modeling Infectious Behaviors: The Need to Account for Behavioral Adaptation in COVID-19 Models.

Authors:  Raffaele Vardavas; Pedro Nascimento de Lima; Paul K Davis; Andrew M Parker; Lawrence Baker
Journal:  Policy Complex Sys       Date:  2021

Review 2.  Modeling the coronavirus disease 2019 pandemic: A comprehensive guide of infectious disease and decision-analytic models.

Authors:  Stephen Mac; Sharmistha Mishra; Raphael Ximenes; Kali Barrett; Yasin A Khan; David M J Naimark; Beate Sander
Journal:  J Clin Epidemiol       Date:  2020-12-07       Impact factor: 6.437

Review 3.  Utility of Artificial Intelligence Amidst the COVID 19 Pandemic: A Review.

Authors:  Agam Bansal; Rana Prathap Padappayil; Chandan Garg; Anjali Singal; Mohak Gupta; Allan Klein
Journal:  J Med Syst       Date:  2020-08-01       Impact factor: 4.460

4.  Applying infectious disease forecasting to public health: a path forward using influenza forecasting examples.

Authors:  Chelsea S Lutz; Mimi P Huynh; Monica Schroeder; Sophia Anyatonwu; F Scott Dahlgren; Gregory Danyluk; Danielle Fernandez; Sharon K Greene; Nodar Kipshidze; Leann Liu; Osaro Mgbere; Lisa A McHugh; Jennifer F Myers; Alan Siniscalchi; Amy D Sullivan; Nicole West; Michael A Johansson; Matthew Biggerstaff
Journal:  BMC Public Health       Date:  2019-12-10       Impact factor: 3.295

  4 in total

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