[Incorporation of geostatistical methodology for influenza surveillance in a sentinel network].
Identifieur interne : 000644 ( Main/Exploration ); précédent : 000643; suivant : 000645[Incorporation of geostatistical methodology for influenza surveillance in a sentinel network].
Auteurs : J J Abellán [Espagne] ; O. Zurriaga ; M A Martínez-Beneito ; J. Pe Alver ; T. MolinsSource :
- Gaceta sanitaria [ 0213-9111 ]
Descripteurs français
- KwdFr :
- MESH :
- prévention et contrôle : Grippe humaine.
- épidémiologie : Grippe humaine.
- Espagne, Humains, Surveillance sentinelle, Systèmes d'information géographique.
- Wicri :
- geographic : Espagne.
English descriptors
- KwdEn :
- MESH :
- geographic : Spain.
- epidemiology : Influenza, Human.
- prevention & control : Influenza, Human.
- Geographic Information Systems, Humans, Sentinel Surveillance.
Abstract
OBJECTIVES
To evaluate geostatistical description of influenza data from the Valencian Sentinel Network (VSN) in Spain using the kringing method and to assess the possibility of incorporating this method into routine surveillance.
METHODS
We use influenza surveillance data on three influenza seasons (1997-1998, 1998-1999 and 1999-2000) from the VSN to construct a geocodified data matrix of the incidence of this disease. The geographic distribution was studied using the kringing method, which enables estimation of the incidence in a few strategically distributed points. Influenza isoincidence maps for each week were plotted. Cross validation was used to evaluate the method.
RESULTS
In most of the weeks, the values of reduced standard deviation and reduced mean were close to the optimal values (0 and 1, respectively). Out of range reduced standard deviation values were found in 12 of 20 weeks in the last season only. The estimation of rates in all three seasons showed coherence in spatial distribution and temporal evolution.
CONCLUSIONS
In most situations the results were acceptable. The method does not require extra computer resources or an excessive amount of time and requires only annual adaptation. Because it is easy to use, the technique is appropriate for routine use but the accuracy of estimations could be improved by increasing the complexity of the model.
DOI: 10.1016/s0213-9111(02)71932-8
PubMed: 12106552
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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Zurriaga</name></author><author><name sortKey="Martinez Beneito, M A" sort="Martinez Beneito, M A" uniqKey="Martinez Beneito M" first="M A" last="Martínez-Beneito">M A Martínez-Beneito</name></author><author><name sortKey="Pe Alver, J" sort="Pe Alver, J" uniqKey="Pe Alver J" first="J" last="Pe Alver">J. Pe Alver</name></author><author><name sortKey="Molins, T" sort="Molins, T" uniqKey="Molins T" first="T" last="Molins">T. Molins</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2002">2002 Jul-Aug</date><idno type="RBID">pubmed:12106552</idno><idno type="pmid">12106552</idno><idno type="doi">10.1016/s0213-9111(02)71932-8</idno><idno type="wicri:Area/Main/Corpus">00650</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">00650</idno><idno type="wicri:Area/Main/Curation">000650</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">000650</idno><idno type="wicri:Area/Main/Exploration">000650</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">[Incorporation of geostatistical methodology for influenza surveillance in a sentinel network].</title><author><name sortKey="Abellan, J J" sort="Abellan, J J" uniqKey="Abellan J" first="J J" last="Abellán">J J Abellán</name><affiliation wicri:level="1"><nlm:affiliation>Servicio de Epidemiología, Dirección General para la Salud Pública, Conselleria de Sanitat, Generalitat Valenciana, Spain.</nlm:affiliation><country xml:lang="fr">Espagne</country><wicri:regionArea>Servicio de Epidemiología, Dirección General para la Salud Pública, Conselleria de Sanitat, Generalitat Valenciana</wicri:regionArea><wicri:noRegion>Generalitat Valenciana</wicri:noRegion></affiliation></author><author><name sortKey="Zurriaga, O" sort="Zurriaga, O" uniqKey="Zurriaga O" first="O" last="Zurriaga">O. Zurriaga</name></author><author><name sortKey="Martinez Beneito, M A" sort="Martinez Beneito, M A" uniqKey="Martinez Beneito M" first="M A" last="Martínez-Beneito">M A Martínez-Beneito</name></author><author><name sortKey="Pe Alver, J" sort="Pe Alver, J" uniqKey="Pe Alver J" first="J" last="Pe Alver">J. Pe Alver</name></author><author><name sortKey="Molins, T" sort="Molins, T" uniqKey="Molins T" first="T" last="Molins">T. Molins</name></author></analytic><series><title level="j">Gaceta sanitaria</title><idno type="ISSN">0213-9111</idno></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Geographic Information Systems (MeSH)</term><term>Humans (MeSH)</term><term>Influenza, Human (epidemiology)</term><term>Influenza, Human (prevention & control)</term><term>Sentinel Surveillance (MeSH)</term><term>Spain (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Espagne (MeSH)</term><term>Grippe humaine (prévention et contrôle)</term><term>Grippe humaine (épidémiologie)</term><term>Humains (MeSH)</term><term>Surveillance sentinelle (MeSH)</term><term>Systèmes d'information géographique (MeSH)</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>Spain</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="prevention & control" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="prévention et contrôle" xml:lang="fr"><term>Grippe humaine</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Grippe humaine</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Geographic Information Systems</term><term>Humans</term><term>Sentinel Surveillance</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Espagne</term><term>Humains</term><term>Surveillance sentinelle</term><term>Systèmes d'information géographique</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>Espagne</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>OBJECTIVES</b></p><p>To evaluate geostatistical description of influenza data from the Valencian Sentinel Network (VSN) in Spain using the kringing method and to assess the possibility of incorporating this method into routine surveillance.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>We use influenza surveillance data on three influenza seasons (1997-1998, 1998-1999 and 1999-2000) from the VSN to construct a geocodified data matrix of the incidence of this disease. The geographic distribution was studied using the kringing method, which enables estimation of the incidence in a few strategically distributed points. Influenza isoincidence maps for each week were plotted. Cross validation was used to evaluate the method.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>In most of the weeks, the values of reduced standard deviation and reduced mean were close to the optimal values (0 and 1, respectively). Out of range reduced standard deviation values were found in 12 of 20 weeks in the last season only. The estimation of rates in all three seasons showed coherence in spatial distribution and temporal evolution.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b></p><p>In most situations the results were acceptable. The method does not require extra computer resources or an excessive amount of time and requires only annual adaptation. Because it is easy to use, the technique is appropriate for routine use but the accuracy of estimations could be improved by increasing the complexity of the model.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">12106552</PMID><DateCompleted><Year>2009</Year><Month>07</Month><Day>15</Day></DateCompleted><DateRevised><Year>2019</Year><Month>09</Month><Day>22</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">0213-9111</ISSN><JournalIssue CitedMedium="Print"><Volume>16</Volume><Issue>4</Issue><PubDate><MedlineDate>2002 Jul-Aug</MedlineDate></PubDate></JournalIssue><Title>Gaceta sanitaria</Title><ISOAbbreviation>Gac Sanit</ISOAbbreviation></Journal><ArticleTitle>[Incorporation of geostatistical methodology for influenza surveillance in a sentinel network].</ArticleTitle><Pagination><MedlinePgn>324-33</MedlinePgn></Pagination><Abstract><AbstractText Label="OBJECTIVES" NlmCategory="OBJECTIVE">To evaluate geostatistical description of influenza data from the Valencian Sentinel Network (VSN) in Spain using the kringing method and to assess the possibility of incorporating this method into routine surveillance.</AbstractText><AbstractText Label="METHODS" NlmCategory="METHODS">We use influenza surveillance data on three influenza seasons (1997-1998, 1998-1999 and 1999-2000) from the VSN to construct a geocodified data matrix of the incidence of this disease. The geographic distribution was studied using the kringing method, which enables estimation of the incidence in a few strategically distributed points. Influenza isoincidence maps for each week were plotted. Cross validation was used to evaluate the method.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">In most of the weeks, the values of reduced standard deviation and reduced mean were close to the optimal values (0 and 1, respectively). Out of range reduced standard deviation values were found in 12 of 20 weeks in the last season only. The estimation of rates in all three seasons showed coherence in spatial distribution and temporal evolution.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">In most situations the results were acceptable. The method does not require extra computer resources or an excessive amount of time and requires only annual adaptation. 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Molins</name><name sortKey="Pe Alver, J" sort="Pe Alver, J" uniqKey="Pe Alver J" first="J" last="Pe Alver">J. Pe Alver</name><name sortKey="Zurriaga, O" sort="Zurriaga, O" uniqKey="Zurriaga O" first="O" last="Zurriaga">O. Zurriaga</name></noCountry><country name="Espagne"><noRegion><name sortKey="Abellan, J J" sort="Abellan, J J" uniqKey="Abellan J" first="J J" last="Abellán">J J Abellán</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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