Time Series Analysis of Incidence Data of Influenza in Japan
Identifieur interne : 000A01 ( Pmc/Curation ); précédent : 000A00; suivant : 000A02Time Series Analysis of Incidence Data of Influenza in Japan
Auteurs : Ayako Sumi [Japon] ; Ken-Ichi Kamo [Japon] ; Norio Ohtomo [Japon] ; Keiji Mise [Japon] ; Nobumichi Kobayashi [Japon]Source :
- Journal of Epidemiology [ 0917-5040 ] ; 2011.
Abstract
Much effort has been expended on interpreting the mechanism of influenza epidemics, so as to better predict them. In addition to the obvious annual cycle of influenza epidemics, longer-term incidence patterns are present. These so-called interepidemic periods have long been a focus of epidemiology. However, there has been less investigation of the interepidemic period of influenza epidemics. In the present study, we used spectral analysis of influenza morbidity records to indentify the interepidemic period of influenza epidemics in Japan.
We used time series data of the monthly incidence of influenza in Japan from January 1948 through December 1998. To evaluate the incidence data, we conducted maximum entropy method (MEM) spectral analysis, which is useful in investigating the periodicities of shorter time series, such as that of the incidence data used in the present study. We also conducted a segment time series analysis and obtained a 3-dimensional spectral array.
Based on the results of power spectral density (PSD) obtained from MEM spectral analysis, we identified 3 periodic modes as the interepidemic periods of the incidence data. Segment time series analysis revealed that the amount of amplitude of the interepidemic periods increased during the occurrence of influenza pandemics and decreased when vaccine programs were introduced.
The findings suggest that the temporal behavior of the interepidemic periods of influenza epidemics is correlated with the magnitude of cross-reactive immune responses.
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DOI: 10.2188/jea.JE20090162
PubMed: 21088372
PubMed Central: 3899513
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Ltd.,<addr-line>Sapporo, Japan</addr-line></nlm:aff><country xml:lang="fr">Japon</country><wicri:regionArea>Sapporo</wicri:regionArea></affiliation></author><author><name sortKey="Mise, Keiji" sort="Mise, Keiji" uniqKey="Mise K" first="Keiji" last="Mise">Keiji Mise</name><affiliation wicri:level="1"><nlm:aff id="aff04">Center for Medical Education, Department of Admissions, Sapporo Medical University,<addr-line>Sapporo, Japan</addr-line></nlm:aff><country xml:lang="fr">Japon</country><wicri:regionArea>Sapporo</wicri:regionArea></affiliation></author><author><name sortKey="Kobayashi, Nobumichi" sort="Kobayashi, Nobumichi" uniqKey="Kobayashi N" first="Nobumichi" last="Kobayashi">Nobumichi Kobayashi</name><affiliation wicri:level="1"><nlm:aff id="aff01">Department of Hygiene, Sapporo Medical University School of Medicine,<addr-line>Sapporo, Japan</addr-line></nlm:aff><country xml:lang="fr">Japon</country><wicri:regionArea>Sapporo</wicri:regionArea></affiliation></author></analytic><series><title level="j">Journal of Epidemiology</title><idno type="ISSN">0917-5040</idno><idno type="eISSN">1349-9092</idno><imprint><date when="2011">2011</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Much effort has been expended on interpreting the mechanism of influenza epidemics, so as to better predict them. In addition to the obvious annual cycle of influenza epidemics, longer-term incidence patterns are present. These so-called interepidemic periods have long been a focus of epidemiology. However, there has been less investigation of the interepidemic period of influenza epidemics. In the present study, we used spectral analysis of influenza morbidity records to indentify the interepidemic period of influenza epidemics in Japan.</p></sec><sec><title>Methods</title><p>We used time series data of the monthly incidence of influenza in Japan from January 1948 through December 1998. To evaluate the incidence data, we conducted maximum entropy method (MEM) spectral analysis, which is useful in investigating the periodicities of shorter time series, such as that of the incidence data used in the present study. We also conducted a segment time series analysis and obtained a 3-dimensional spectral array.</p></sec><sec><title>Results</title><p>Based on the results of power spectral density (PSD) obtained from MEM spectral analysis, we identified 3 periodic modes as the interepidemic periods of the incidence data. Segment time series analysis revealed that the amount of amplitude of the interepidemic periods increased during the occurrence of influenza pandemics and decreased when vaccine programs were introduced.</p></sec><sec><title>Conclusions</title><p>The findings suggest that the temporal behavior of the interepidemic periods of influenza epidemics is correlated with the magnitude of cross-reactive immune responses.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct></listBibl></div1></back></TEI><pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">J Epidemiol</journal-id><journal-id journal-id-type="iso-abbrev">J Epidemiol</journal-id><journal-id journal-id-type="publisher-id">JE</journal-id><journal-title-group><journal-title>Journal of Epidemiology</journal-title></journal-title-group><issn pub-type="ppub">0917-5040</issn><issn pub-type="epub">1349-9092</issn><publisher><publisher-name>Japan Epidemiological Association</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">21088372</article-id><article-id pub-id-type="pmc">3899513</article-id><article-id pub-id-type="doi">10.2188/jea.JE20090162</article-id><article-id pub-id-type="publisher-id">JE20090162</article-id><article-categories><subj-group subj-group-type="heading"><subject>Original Article</subject></subj-group><subj-group subj-group-type="mainclass"><subject>Infectious Disease</subject></subj-group></article-categories><title-group><article-title>Time Series Analysis of Incidence Data of Influenza in Japan</article-title><alt-title alt-title-type="verso-running-head">Time Series Analysis of Incidence Data of Influenza in Japan</alt-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Sumi</surname><given-names>Ayako</given-names></name><xref ref-type="aff" rid="aff01"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Kamo</surname><given-names>Ken-ichi</given-names></name><xref ref-type="aff" rid="aff02"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Ohtomo</surname><given-names>Norio</given-names></name><xref ref-type="aff" rid="aff03"><sup>3</sup></xref></contrib><contrib contrib-type="author"><name><surname>Mise</surname><given-names>Keiji</given-names></name><xref ref-type="aff" rid="aff04"><sup>4</sup></xref></contrib><contrib contrib-type="author"><name><surname>Kobayashi</surname><given-names>Nobumichi</given-names></name><xref ref-type="aff" rid="aff01"><sup>1</sup></xref></contrib><aff id="aff01"><label>1</label>Department of Hygiene, Sapporo Medical University School of Medicine,<addr-line>Sapporo, Japan</addr-line></aff><aff id="aff02"><label>2</label>Department of Liberal Arts and Sciences, Sapporo Medical University,<addr-line>Sapporo, Japan</addr-line></aff><aff id="aff03"><label>3</label>Natural Energy Research Center Co. Ltd.,<addr-line>Sapporo, Japan</addr-line></aff><aff id="aff04"><label>4</label>Center for Medical Education, Department of Admissions, Sapporo Medical University,<addr-line>Sapporo, Japan</addr-line></aff></contrib-group><author-notes><corresp id="fn01">Address for correspondence. Ayako Sumi, Department of Hygiene, Sapporo Medical University School of Medicine, S-1, W-17, Chuo-ku, Sapporo 060-8556, Japan (e-mail: <email>sumi@sapmed.ac.jp</email>).</corresp></author-notes><pub-date pub-type="epub"><day>5</day><month>1</month><year>2011</year></pub-date><pub-date pub-type="epreprint"><day>13</day><month>11</month><year>2010</year></pub-date><pub-date pub-type="collection"><year>2011</year></pub-date><volume>21</volume><issue>1</issue><fpage>21</fpage><lpage>29</lpage><history><date date-type="received"><day>29</day><month>9</month><year>2009</year></date><date date-type="accepted"><day>8</day><month>7</month><year>2010</year></date></history><permissions><copyright-statement>© 2011 Japan Epidemiological Association.</copyright-statement><copyright-year>2011</copyright-year><copyright-holder>Japan Epidemiological Association</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/3.0/"><license-p>This is an open access article distributed under the terms of Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p></license></permissions><abstract><sec><title>Background</title><p>Much effort has been expended on interpreting the mechanism of influenza epidemics, so as to better predict them. In addition to the obvious annual cycle of influenza epidemics, longer-term incidence patterns are present. These so-called interepidemic periods have long been a focus of epidemiology. However, there has been less investigation of the interepidemic period of influenza epidemics. In the present study, we used spectral analysis of influenza morbidity records to indentify the interepidemic period of influenza epidemics in Japan.</p></sec><sec><title>Methods</title><p>We used time series data of the monthly incidence of influenza in Japan from January 1948 through December 1998. To evaluate the incidence data, we conducted maximum entropy method (MEM) spectral analysis, which is useful in investigating the periodicities of shorter time series, such as that of the incidence data used in the present study. We also conducted a segment time series analysis and obtained a 3-dimensional spectral array.</p></sec><sec><title>Results</title><p>Based on the results of power spectral density (PSD) obtained from MEM spectral analysis, we identified 3 periodic modes as the interepidemic periods of the incidence data. Segment time series analysis revealed that the amount of amplitude of the interepidemic periods increased during the occurrence of influenza pandemics and decreased when vaccine programs were introduced.</p></sec><sec><title>Conclusions</title><p>The findings suggest that the temporal behavior of the interepidemic periods of influenza epidemics is correlated with the magnitude of cross-reactive immune responses.</p></sec></abstract><kwd-group kwd-group-type="author"><title>Key words: </title><kwd>time series analysis</kwd><kwd>influenza</kwd><kwd>surveillance</kwd></kwd-group></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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