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Assessment of two complementary influenza surveillance systems: sentinel primary care influenza-like illness versus severe hospitalized laboratory-confirmed influenza using the moving epidemic method.

Identifieur interne : 000038 ( Main/Exploration ); précédent : 000037; suivant : 000039

Assessment of two complementary influenza surveillance systems: sentinel primary care influenza-like illness versus severe hospitalized laboratory-confirmed influenza using the moving epidemic method.

Auteurs : Núria Torner [Espagne] ; Luca Basile [Espagne] ; Ana Martínez [Espagne] ; Cristina Rius [Espagne] ; Pere Godoy [Espagne] ; Mireia Jané [Espagne] ; Ángela Domínguez [Espagne]

Source :

RBID : pubmed:31409397

Descripteurs français

English descriptors

Abstract

BACKGROUND

Monitoring seasonal influenza epidemics is the corner stone to epidemiological surveillance of acute respiratory virus infections worldwide. This work aims to compare two sentinel surveillance systems within the Daily Acute Respiratory Infection Information System of Catalonia (PIDIRAC), the primary care ILI and Influenza confirmed samples from primary care (PIDIRAC-ILI and PIDIRAC-FLU) and the severe hospitalized laboratory confirmed influenza system (SHLCI), in regard to how they behave in the forecasting of epidemic onset and severity allowing for healthcare preparedness.

METHODS

Epidemiological study carried out during seven influenza seasons (2010-2017) in Catalonia, with data from influenza sentinel surveillance of primary care physicians reporting ILI along with laboratory confirmation of influenza from systematic sampling of ILI cases and 12 hospitals that provided data on severe hospitalized cases with laboratory-confirmed influenza (SHLCI-FLU). Epidemic thresholds for ILI and SHLCI-FLU (overall) as well as influenza A (SHLCI-FLUA) and influenza B (SHLCI-FLUB) incidence rates were assessed by the Moving Epidemics Method.

RESULTS

Epidemic thresholds for primary care sentinel surveillance influenza-like illness (PIDIRAC-ILI) incidence rates ranged from 83.65 to 503.92 per 100.000 h. Paired incidence rate curves for SHLCI -FLU / PIDIRAC-ILI and SHLCI-FLUA/ PIDIRAC-FLUA showed best correlation index' (0.805 and 0.724 respectively). Assessing delay in reaching epidemic level, PIDIRAC-ILI source forecasts an average of 1.6 weeks before the rest of sources paired. Differences are higher when SHLCI cases are paired to PIDIRAC-ILI and PIDIRAC-FLUB although statistical significance was observed only for SHLCI-FLU/PIDIRAC-ILI (p-value Wilcoxon test = 0.039).

CONCLUSIONS

The combined ILI and confirmed influenza from primary care along with the severe hospitalized laboratory confirmed influenza data from PIDIRAC sentinel surveillance system provides timely and accurate syndromic and virological surveillance of influenza from the community level to hospitalization of severe cases.


DOI: 10.1186/s12889-019-7414-9
PubMed: 31409397
PubMed Central: PMC6691547


Affiliations:

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Le document en format XML

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<p>
<b>BACKGROUND</b>
</p>
<p>Monitoring seasonal influenza epidemics is the corner stone to epidemiological surveillance of acute respiratory virus infections worldwide. This work aims to compare two sentinel surveillance systems within the Daily Acute Respiratory Infection Information System of Catalonia (PIDIRAC), the primary care ILI and Influenza confirmed samples from primary care (PIDIRAC-ILI and PIDIRAC-FLU) and the severe hospitalized laboratory confirmed influenza system (SHLCI), in regard to how they behave in the forecasting of epidemic onset and severity allowing for healthcare preparedness.</p>
</div>
<div type="abstract" xml:lang="en">
<p>
<b>METHODS</b>
</p>
<p>Epidemiological study carried out during seven influenza seasons (2010-2017) in Catalonia, with data from influenza sentinel surveillance of primary care physicians reporting ILI along with laboratory confirmation of influenza from systematic sampling of ILI cases and 12 hospitals that provided data on severe hospitalized cases with laboratory-confirmed influenza (SHLCI-FLU). Epidemic thresholds for ILI and SHLCI-FLU (overall) as well as influenza A (SHLCI-FLUA) and influenza B (SHLCI-FLUB) incidence rates were assessed by the Moving Epidemics Method.</p>
</div>
<div type="abstract" xml:lang="en">
<p>
<b>RESULTS</b>
</p>
<p>Epidemic thresholds for primary care sentinel surveillance influenza-like illness (PIDIRAC-ILI) incidence rates ranged from 83.65 to 503.92 per 100.000 h. Paired incidence rate curves for SHLCI -FLU / PIDIRAC-ILI and SHLCI-FLUA/ PIDIRAC-FLUA showed best correlation index' (0.805 and 0.724 respectively). Assessing delay in reaching epidemic level, PIDIRAC-ILI source forecasts an average of 1.6 weeks before the rest of sources paired. Differences are higher when SHLCI cases are paired to PIDIRAC-ILI and PIDIRAC-FLUB although statistical significance was observed only for SHLCI-FLU/PIDIRAC-ILI (p-value Wilcoxon test = 0.039).</p>
</div>
<div type="abstract" xml:lang="en">
<p>
<b>CONCLUSIONS</b>
</p>
<p>The combined ILI and confirmed influenza from primary care along with the severe hospitalized laboratory confirmed influenza data from PIDIRAC sentinel surveillance system provides timely and accurate syndromic and virological surveillance of influenza from the community level to hospitalization of severe cases.</p>
</div>
</front>
</TEI>
<pubmed>
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<PMID Version="1">31409397</PMID>
<DateCompleted>
<Year>2019</Year>
<Month>11</Month>
<Day>08</Day>
</DateCompleted>
<DateRevised>
<Year>2020</Year>
<Month>02</Month>
<Day>25</Day>
</DateRevised>
<Article PubModel="Electronic">
<Journal>
<ISSN IssnType="Electronic">1471-2458</ISSN>
<JournalIssue CitedMedium="Internet">
<Volume>19</Volume>
<Issue>1</Issue>
<PubDate>
<Year>2019</Year>
<Month>Aug</Month>
<Day>13</Day>
</PubDate>
</JournalIssue>
<Title>BMC public health</Title>
<ISOAbbreviation>BMC Public Health</ISOAbbreviation>
</Journal>
<ArticleTitle>Assessment of two complementary influenza surveillance systems: sentinel primary care influenza-like illness versus severe hospitalized laboratory-confirmed influenza using the moving epidemic method.</ArticleTitle>
<Pagination>
<MedlinePgn>1089</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1186/s12889-019-7414-9</ELocationID>
<Abstract>
<AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Monitoring seasonal influenza epidemics is the corner stone to epidemiological surveillance of acute respiratory virus infections worldwide. This work aims to compare two sentinel surveillance systems within the Daily Acute Respiratory Infection Information System of Catalonia (PIDIRAC), the primary care ILI and Influenza confirmed samples from primary care (PIDIRAC-ILI and PIDIRAC-FLU) and the severe hospitalized laboratory confirmed influenza system (SHLCI), in regard to how they behave in the forecasting of epidemic onset and severity allowing for healthcare preparedness.</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">Epidemiological study carried out during seven influenza seasons (2010-2017) in Catalonia, with data from influenza sentinel surveillance of primary care physicians reporting ILI along with laboratory confirmation of influenza from systematic sampling of ILI cases and 12 hospitals that provided data on severe hospitalized cases with laboratory-confirmed influenza (SHLCI-FLU). Epidemic thresholds for ILI and SHLCI-FLU (overall) as well as influenza A (SHLCI-FLUA) and influenza B (SHLCI-FLUB) incidence rates were assessed by the Moving Epidemics Method.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">Epidemic thresholds for primary care sentinel surveillance influenza-like illness (PIDIRAC-ILI) incidence rates ranged from 83.65 to 503.92 per 100.000 h. Paired incidence rate curves for SHLCI -FLU / PIDIRAC-ILI and SHLCI-FLUA/ PIDIRAC-FLUA showed best correlation index' (0.805 and 0.724 respectively). Assessing delay in reaching epidemic level, PIDIRAC-ILI source forecasts an average of 1.6 weeks before the rest of sources paired. Differences are higher when SHLCI cases are paired to PIDIRAC-ILI and PIDIRAC-FLUB although statistical significance was observed only for SHLCI-FLU/PIDIRAC-ILI (p-value Wilcoxon test = 0.039).</AbstractText>
<AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">The combined ILI and confirmed influenza from primary care along with the severe hospitalized laboratory confirmed influenza data from PIDIRAC sentinel surveillance system provides timely and accurate syndromic and virological surveillance of influenza from the community level to hospitalization of severe cases.</AbstractText>
</Abstract>
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<LastName>Torner</LastName>
<ForeName>Núria</ForeName>
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<Affiliation>Department of Health, Public Health Agency of Catalonia, Generalitat of Catalonia, Salvany Building, Roc Boronat 81-95, 08005, Barcelona, Catalonia, Spain. nuria.torner@gencat.cat.</Affiliation>
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<AffiliationInfo>
<Affiliation>CIBER Epidemiología y Salud Pública (CIBERESP) Institute Carlos III, Madrid, Spain. nuria.torner@gencat.cat.</Affiliation>
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<AffiliationInfo>
<Affiliation>Medicine Department, University of Barcelona, Barcelona, Spain. nuria.torner@gencat.cat.</Affiliation>
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<Affiliation>CIBER Epidemiología y Salud Pública (CIBERESP) Institute Carlos III, Madrid, Spain.</Affiliation>
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<AffiliationInfo>
<Affiliation>Medicine Department, University of Barcelona, Barcelona, Spain.</Affiliation>
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<Language>eng</Language>
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<Grant>
<GrantID>2017/SGR 1342</GrantID>
<Agency>Grants for University Research (AGAUR)</Agency>
<Country></Country>
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<Grant>
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<MeshHeading>
<DescriptorName UI="D058872" MajorTopicYN="Y">Epidemics</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D006760" MajorTopicYN="N">Hospitalization</DescriptorName>
<QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName>
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<MeshHeading>
<DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
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<MeshHeading>
<DescriptorName UI="D009980" MajorTopicYN="N">Influenza A virus</DescriptorName>
<QualifierName UI="Q000302" MajorTopicYN="Y">isolation & purification</QualifierName>
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<DescriptorName UI="D009981" MajorTopicYN="N">Influenza B virus</DescriptorName>
<QualifierName UI="Q000302" MajorTopicYN="Y">isolation & purification</QualifierName>
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<MeshHeading>
<DescriptorName UI="D007251" MajorTopicYN="N">Influenza, Human</DescriptorName>
<QualifierName UI="Q000175" MajorTopicYN="N">diagnosis</QualifierName>
<QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName>
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<MeshHeading>
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<MeshHeading>
<DescriptorName UI="D012621" MajorTopicYN="N">Seasons</DescriptorName>
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<DescriptorName UI="D018571" MajorTopicYN="Y">Sentinel Surveillance</DescriptorName>
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<DescriptorName UI="D012720" MajorTopicYN="N">Severity of Illness Index</DescriptorName>
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<MeshHeading>
<DescriptorName UI="D013030" MajorTopicYN="N" Type="Geographic">Spain</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
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<Keyword MajorTopicYN="N">Epidemic</Keyword>
<Keyword MajorTopicYN="N">Hospitalization</Keyword>
<Keyword MajorTopicYN="N">Influenza</Keyword>
<Keyword MajorTopicYN="N">Influenza like illness</Keyword>
<Keyword MajorTopicYN="N">Primary health care</Keyword>
<Keyword MajorTopicYN="N">Sentinel surveillance</Keyword>
<Keyword MajorTopicYN="N">Threshold</Keyword>
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