Literature DB >> 20212071

Time series methods for obtaining excess mortality attributable to influenza epidemics.

Baltazar Nunes1, Isabel Natário, M Lucília Carvalho.   

Abstract

The occurrence of influenza epidemics during winters, in the northern hemisphere countries, is known to be associated with observed excess mortality for all causes. A large variety of methods have been developed in order to estimate, from weekly or monthly mortality time series, the number of influenza-associated deaths in each season. The present work focus on the group of methods characterised by fitting statistical models to interrupted mortality time series. The study objective is to find a common ground between these methods in order to describe and compare them. They are unified in a single class, being categorised according to three main parameters: the model used to fit the interrupted time series and obtain a baseline, the a priori chosen type of periods used to estimate the influenza epidemic periods and the procedure used to fit the model to the time series (iterative or non-iterative). This generalisation led quite naturally to the construction of a set of user friendly R-routines, package flubase, implementing all these models. These routines were applied to data on about 20 years of weekly Portuguese number of deaths by pneumonia and influenza showing that, in this case, the parameter that had the highest impact on influenza-associated deaths estimates was the a priori chosen type of period used.

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Year:  2010        PMID: 20212071     DOI: 10.1177/0962280209340201

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  10 in total

1.  Influenza as a proportion of pneumonia mortality: United States, 1959-2009.

Authors:  Andrew Noymer; Ann M Nguyen
Journal:  Biodemography Soc Biol       Date:  2013

2.  Excess mortality associated with influenza epidemics in Portugal, 1980 to 2004.

Authors:  Baltazar Nunes; Cecile Viboud; Ausenda Machado; Corinne Ringholz; Helena Rebelo-de-Andrade; Paulo Nogueira; Mark Miller
Journal:  PLoS One       Date:  2011-06-21       Impact factor: 3.240

3.  Model selection in time series studies of influenza-associated mortality.

Authors:  Xi-Ling Wang; Lin Yang; King-Pan Chan; Susan S Chiu; Kwok-Hung Chan; J S Malik Peiris; Chit-Ming Wong
Journal:  PLoS One       Date:  2012-06-20       Impact factor: 3.240

4.  Influenza-attributable deaths in south-eastern France (1999 to 2010): mortality predictions were undependable.

Authors:  Simon-Djamel Thiberville; Jean Gaudart; Didier Raoult; Remi N Charrel
Journal:  BMC Public Health       Date:  2015-06-07       Impact factor: 3.295

5.  Application of a novel grey self-memory coupling model to forecast the incidence rates of two notifiable diseases in China: dysentery and gonorrhea.

Authors:  Xiaojun Guo; Sifeng Liu; Lifeng Wu; Lingling Tang
Journal:  PLoS One       Date:  2014-12-29       Impact factor: 3.240

6.  Excess pneumonia and influenza hospitalizations associated with influenza epidemics in Portugal from season 1998/1999 to 2014/2015.

Authors:  Emanuel Rodrigues; Ausenda Machado; Susana Silva; Baltazar Nunes
Journal:  Influenza Other Respir Viruses       Date:  2018-01       Impact factor: 4.380

Review 7.  Methods, Applications and Challenges in the Analysis of Interrupted Time Series Data: A Scoping Review.

Authors:  Joycelyne E Ewusie; Charlene Soobiah; Erik Blondal; Joseph Beyene; Lehana Thabane; Jemila S Hamid
Journal:  J Multidiscip Healthc       Date:  2020-05-13

8.  Mortality attributable to seasonal and pandemic influenza, Australia, 2003 to 2009, using a novel time series smoothing approach.

Authors:  David J Muscatello; Anthony T Newall; Dominic E Dwyer; C Raina Macintyre
Journal:  PLoS One       Date:  2013-06-03       Impact factor: 3.240

9.  SLALOM, a flexible method for the identification and statistical analysis of overlapping continuous sequence elements in sequence- and time-series data.

Authors:  Roman Prytuliak; Friedhelm Pfeiffer; Bianca Hermine Habermann
Journal:  BMC Bioinformatics       Date:  2018-01-26       Impact factor: 3.169

10.  Excess of Mortality in Adults and Elderly and Circulation of Subtypes of Influenza Virus in Southern Brazil.

Authors:  André Ricardo Ribas Freitas; Maria Rita Donalisio
Journal:  Front Immunol       Date:  2018-01-08       Impact factor: 7.561

  10 in total

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