Analysis of the seasonal incidence of acute respiratory infections including influenza (ARI) in the Czech Republic – Possible contribution of the functional data boxplot in epidemiology

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F17%3A73586460" target="_blank" >RIV/61989592:15310/17:73586460 - isvavai.cz</a>

Alternative codes found

RIV/75010330:_____/17:00011870

Result on the web

<a href="http://biomed.papers.upol.cz/pdfs/bio/2017/04/08.pdf" target="_blank" >http://biomed.papers.upol.cz/pdfs/bio/2017/04/08.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5507/bp.2017.042" target="_blank" >10.5507/bp.2017.042</a>

Result language

angličtina

Original language name

Analysis of the seasonal incidence of acute respiratory infections including influenza (ARI) in the Czech Republic – Possible contribution of the functional data boxplot in epidemiology

Original language description

Aims: The detection of an epidemic outbreak is possible only if the baseline incidence level of a given disease is well defined. The determination of the baseline is complicated by the presence of epidemic outbreaks in historical data. The aim of the paper is to provide a new way of determining the baseline. Methods: The analyzed data containing weekly records on the incidence of acute respiratory infections including influenza (ARI) in the Czech Republic and its regions are taken from the nationwide surveillance system; data on 15 seasons from 2001/02 to 2015/16 are included. Functional boxplots of the data are constructed and five distinct methods (componentwise mean, componentwise median, median, trimmed mean, and adjusted mean) were used for the computation of the baseline level function. Results: It was shown that the methods based on functional data analysis could successfully overcome the problems that arise when the conventional methods are used for the determination of the baseline function. Conclusion: The functional boxplot - a new statistical tool - can bring not only a transparent visualisation of comprehensive data, but can also help epidemiologists and other public health experts to determine the baseline incidence level of a given disease as well as to detect unusual epidemic seasons.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10103 - Statistics and probability

Project

<a href="/en/project/GA15-06991S" target="_blank" >GA15-06991S: Functional data analysis and related topics</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Biomedical Papers-Olomouc

ISSN

1213-8118

e-ISSN

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Volume of the periodical

161

Issue of the periodical within the volume

4

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

8

Pages from-to

381-388

UT code for WoS article

000418005200008

EID of the result in the Scopus database

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