Literature DB >> 21218144

Assessing North American influenza dynamics with a statistical SIRS model.

Mevin B Hooten1, Jessica Anderson, Lance A Waller.   

Abstract

We present a general statistical modeling framework to characterize continental-level influenza dynamics in the United States for the purposes of examining state-level epidemiological sources and sinks. The methods we describe depend directly on state-level influenza data that are prepared on a weekly basis by Google Flu Trends. The Google Flu Trends team has provided a powerful new approach to collecting and reporting epidemiological data and, when used in conjunction with sophisticated statistical models, can allow for the identification and quantification of the flow of influenza across the continental United States. Our proposed methods, when conditioned on such a comprehensive search query product, can provide unprecedented scientific learning about large-scale pathways and barriers to disease transmission which can ultimately be helpful for policy, remediation, and response efforts.

Entities:  

Keywords:  Agent-Based Model; Dynamical Model; Epidemic; Flu; Hierarchical Model; Spatio-Temporal Statistics

Mesh:

Year:  2010        PMID: 21218144      PMCID: PMC3017469          DOI: 10.1016/j.sste.2010.03.003

Source DB:  PubMed          Journal:  Spat Spatiotemporal Epidemiol        ISSN: 1877-5845


  9 in total

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Journal:  Prev Vet Med       Date:  2005-09-26       Impact factor: 2.670

Review 4.  Seasonality and the dynamics of infectious diseases.

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5.  Hierarchical spatiotemporal matrix models for characterizing invasions.

Authors:  Mevin B Hooten; Christopher K Wikle; Robert M Dorazio; J Andrew Royle
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Review 6.  Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling.

Authors:  Noel Cressie; Catherine A Calder; James S Clark; Jay M Ver Hoef; Christopher K Wikle
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7.  Mountains, valleys, and rivers: The transmission of raccoon rabies over a heterogeneous landscape.

Authors:  David C Wheeler; Lance A Waller
Journal:  J Agric Biol Environ Stat       Date:  2008-01-01       Impact factor: 1.524

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
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9.  Detecting influenza epidemics using search engine query data.

Authors:  Jeremy Ginsberg; Matthew H Mohebbi; Rajan S Patel; Lynnette Brammer; Mark S Smolinski; Larry Brilliant
Journal:  Nature       Date:  2009-02-19       Impact factor: 49.962

  9 in total
  6 in total

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Journal:  Environ Int       Date:  2020-03-31       Impact factor: 9.621

2.  Approximate Bayesian computation for spatial SEIR(S) epidemic models.

Authors:  Grant D Brown; Aaron T Porter; Jacob J Oleson; Jessica A Hinman
Journal:  Spat Spatiotemporal Epidemiol       Date:  2017-11-22

3.  Linking mosquito surveillance to dengue fever through Bayesian mechanistic modeling.

Authors:  Clinton B Leach; Jennifer A Hoeting; Kim M Pepin; Alvaro E Eiras; Mevin B Hooten; Colleen T Webb
Journal:  PLoS Negl Trop Dis       Date:  2020-11-23

4.  A dynamic spatio-temporal model to investigate the effect of cattle movements on the spread of bluetongue BTV-8 in Belgium.

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5.  The Evolutionary Dynamics of Stochastic Epidemic Model with Nonlinear Incidence Rate.

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6.  Localized spatial distributions of disease phases yield long-term persistence of infection.

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Journal:  Sci Rep       Date:  2019-12-30       Impact factor: 4.379

  6 in total

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