Literature DB >> 19012277

Robust outbreak surveillance of epidemics in Sweden.

M Frisén1, E Andersson, L Schiöler.   

Abstract

Outbreak detection is of interest in connection with several diseases and syndromes. The aim is to detect the progressive increase in the incidence as soon as possible after the onset of the outbreak. A semiparametric method is applied to Swedish data on tularaemia and influenza. The method is constructed to detect a change from a constant level to a monotonically increasing incidence. If seasonal effects are present, the residuals from a model incorporating these can be used. The properties of the method are evaluated by application to Swedish data on tularaemia and influenza and by simulations. The suggested method is compared with subjective judgments as well as with other algorithms. The conclusion is that the method works well. A user-friendly computer program is described. Copyright (c) 2008 John Wiley & Sons, Ltd.

Mesh:

Year:  2009        PMID: 19012277     DOI: 10.1002/sim.3483

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  6 in total

1.  Some Dissimilarity Measures of Branching Processes and Optimal Decision Making in the Presence of Potential Pandemics.

Authors:  Niels B Kammerer; Wolfgang Stummer
Journal:  Entropy (Basel)       Date:  2020-08-08       Impact factor: 2.524

2.  Conditional predictive inference for online surveillance of spatial disease incidence.

Authors:  Ana Corberán-Vallet; Andrew B Lawson
Journal:  Stat Med       Date:  2011-09-05       Impact factor: 2.373

3.  Outcomes of cholera and measles outbreak alerts in the Democratic Republic of Congo.

Authors:  J P K Makelele; S Ade; K C Takarinda; M Manzi; J Gil Cuesta; A Acma; M M Yépez; M Mashako
Journal:  Public Health Action       Date:  2020-09-21

4.  Surveillance for endemic infectious disease outbreaks: Adaptive sampling using profile likelihood estimation.

Authors:  Michael Fairley; Isabelle J Rao; Margaret L Brandeau; Gary L Qian; Gregg S Gonsalves
Journal:  Stat Med       Date:  2022-05-08       Impact factor: 2.497

5.  CASE: a framework for computer supported outbreak detection.

Authors:  Baki Cakici; Kenneth Hebing; Maria Grünewald; Paul Saretok; Anette Hulth
Journal:  BMC Med Inform Decis Mak       Date:  2010-03-12       Impact factor: 2.796

6.  Evaluation and comparison of statistical methods for early temporal detection of outbreaks: A simulation-based study.

Authors:  Gabriel Bédubourg; Yann Le Strat
Journal:  PLoS One       Date:  2017-07-17       Impact factor: 3.240

  6 in total

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