Alternating patterns of seasonal influenza activity in the WHO European Region following the 2009 pandemic, 2010‐2018
Identifieur interne : 002042 ( Ncbi/Curation ); précédent : 002041; suivant : 002043Alternating patterns of seasonal influenza activity in the WHO European Region following the 2009 pandemic, 2010‐2018
Auteurs : Piers Mook ; Tamara Meerhoff ; Sonja J. Olsen ; René Snacken ; Cornelia Adlhoch ; Dmitriy Pereyaslov ; Eeva K. Broberg ; Angeliki Melidou ; Caroline Brown ; Pasi PenttinenSource :
- Influenza and Other Respiratory Viruses [ 1750-2640 ] ; 2020.
Abstract
Influenza virus infections are common and lead to substantial morbidity and mortality worldwide. We characterized the first eight influenza epidemics since the 2009 influenza pandemic by describing the distribution of viruses and epidemics temporally and geographically across the WHO European Region.
We retrospectively analyzed laboratory‐confirmed influenza detections in ambulatory patients from sentinel sites. Data were aggregated by reporting entity and season (weeks 40‐20) for 2010‐2011 to 2017‐2018. We explored geographical spread using correlation coefficients.
There was variation in the regional influenza epidemics during the study period. Influenza A virus subtypes alternated in dominance, except for 2013‐2014 during which both cocirculated, and only one season (2017‐2018) was B virus dominant. The median start week for epidemics in the Region was week 50, the time to the peak ranged between four and 13 weeks, and the duration of the epidemic ranged between 19 and 25 weeks. There was evidence of a west‐to‐east spread across the Region during epidemics in 2010‐2011 (
Aggregated influenza detection data from sentinel surveillance sites by season between 2010 and 2018 have been presented for the European Region for the first time. Substantial diversity exists between influenza epidemics. These data can inform prevention and control efforts at national, sub‐national, and international levels. Aggregated, regional surveillance data from early affected reporting entities may provide an early warning function and be helpful for early season forecasting efforts.
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DOI: 10.1111/irv.12703
PubMed: 31944604
PubMed Central: 7040975
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Olsen</name><affiliation><nlm:aff id="irv12703-aff-0001"></nlm:aff></affiliation></author><author><name sortKey="Snacken, Rene" sort="Snacken, Rene" uniqKey="Snacken R" first="René" last="Snacken">René Snacken</name><affiliation><nlm:aff id="irv12703-aff-0003"></nlm:aff></affiliation></author><author><name sortKey="Adlhoch, Cornelia" sort="Adlhoch, Cornelia" uniqKey="Adlhoch C" first="Cornelia" last="Adlhoch">Cornelia Adlhoch</name><affiliation><nlm:aff id="irv12703-aff-0003"></nlm:aff></affiliation></author><author><name sortKey="Pereyaslov, Dmitriy" sort="Pereyaslov, Dmitriy" uniqKey="Pereyaslov D" first="Dmitriy" last="Pereyaslov">Dmitriy Pereyaslov</name><affiliation><nlm:aff id="irv12703-aff-0001"></nlm:aff></affiliation></author><author><name sortKey="Broberg, Eeva K" sort="Broberg, Eeva K" uniqKey="Broberg E" first="Eeva K." last="Broberg">Eeva K. Broberg</name><affiliation><nlm:aff id="irv12703-aff-0003"></nlm:aff></affiliation></author><author><name sortKey="Melidou, Angeliki" sort="Melidou, Angeliki" uniqKey="Melidou A" first="Angeliki" last="Melidou">Angeliki Melidou</name><affiliation><nlm:aff id="irv12703-aff-0003"></nlm:aff></affiliation></author><author><name sortKey="Brown, Caroline" sort="Brown, Caroline" uniqKey="Brown C" first="Caroline" last="Brown">Caroline Brown</name><affiliation><nlm:aff id="irv12703-aff-0001"></nlm:aff></affiliation></author><author><name sortKey="Penttinen, Pasi" sort="Penttinen, Pasi" uniqKey="Penttinen P" first="Pasi" last="Penttinen">Pasi Penttinen</name><affiliation><nlm:aff id="irv12703-aff-0003"></nlm:aff></affiliation></author></analytic><series><title level="j">Influenza and Other Respiratory Viruses</title><idno type="ISSN">1750-2640</idno><idno type="eISSN">1750-2659</idno><imprint><date when="2020">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><title>Abstract</title><sec id="irv12703-sec-0001"><title>Background</title><p>Influenza virus infections are common and lead to substantial morbidity and mortality worldwide. We characterized the first eight influenza epidemics since the 2009 influenza pandemic by describing the distribution of viruses and epidemics temporally and geographically across the WHO European Region.</p></sec><sec id="irv12703-sec-0002"><title>Methods</title><p>We retrospectively analyzed laboratory‐confirmed influenza detections in ambulatory patients from sentinel sites. Data were aggregated by reporting entity and season (weeks 40‐20) for 2010‐2011 to 2017‐2018. We explored geographical spread using correlation coefficients.</p></sec><sec id="irv12703-sec-0003"><title>Results</title><p>There was variation in the regional influenza epidemics during the study period. Influenza A virus subtypes alternated in dominance, except for 2013‐2014 during which both cocirculated, and only one season (2017‐2018) was B virus dominant. The median start week for epidemics in the Region was week 50, the time to the peak ranged between four and 13 weeks, and the duration of the epidemic ranged between 19 and 25 weeks. There was evidence of a west‐to‐east spread across the Region during epidemics in 2010‐2011 (<italic>r</italic> = .365; <italic>P</italic> = .019), 2012‐2013 (<italic>r</italic> = .484; <italic>P</italic> = .001), 2014‐2015 (<italic>r</italic> = .423; <italic>P</italic> = .006), and 2017‐2018 (<italic>r</italic> = .566; <italic>P</italic> < .001) seasons. Variation in virus distribution and timing existed within reporting entities across seasons and across reporting entities for a given season.</p></sec><sec id="irv12703-sec-0004"><title>Conclusions</title><p>Aggregated influenza detection data from sentinel surveillance sites by season between 2010 and 2018 have been presented for the European Region for the first time. Substantial diversity exists between influenza epidemics. These data can inform prevention and control efforts at national, sub‐national, and international levels. Aggregated, regional surveillance data from early affected reporting entities may provide an early warning function and be helpful for early season forecasting efforts.</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></listBibl></div1></back></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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