Heterogeneity in Estimates of the Impact of Influenza on Population Mortality: A Systematic Review
Abstract Influenza viruses are associated with a substantial global burden of morbidity and mortality every year. Estimates of influenza-associated mortality often vary between studies due to differences in study settings, methods, and measurement of outcomes. We reviewed 103 published articles asse...
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Veröffentlicht in: | American journal of epidemiology 2018-02, Vol.187 (2), p.378-388 |
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description | Abstract
Influenza viruses are associated with a substantial global burden of morbidity and mortality every year. Estimates of influenza-associated mortality often vary between studies due to differences in study settings, methods, and measurement of outcomes. We reviewed 103 published articles assessing population-based influenza-associated mortality through searches of PubMed and Embase, and we identified considerable variation in the statistical methods used across studies. Studies using regression models with an influenza activity proxy applied 4 approaches to estimate influenza-associated mortality. The estimates increased with age and ranged widely, from −0.3–1.3 and 0.6–8.3 respiratory deaths per 100,000 population for children and adults, respectively, to 4–119 respiratory deaths per 100,000 population for older adults. Meta-regression analysis identified that study design features were associated with the observed variation in estimates. The estimates increased with broader cause-of-death classification and were higher for older adults than for children. The multiplier methods tended to produce lower estimates, while Serfling-type models were associated with higher estimates than other methods. No “average” estimate of excess mortality could reliably be made due to the substantial variability of the estimates, partially attributable to methodological differences in the studies. Standardization of methodology in estimation of influenza-associated mortality would permit improved comparisons in the future. |
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Influenza viruses are associated with a substantial global burden of morbidity and mortality every year. Estimates of influenza-associated mortality often vary between studies due to differences in study settings, methods, and measurement of outcomes. We reviewed 103 published articles assessing population-based influenza-associated mortality through searches of PubMed and Embase, and we identified considerable variation in the statistical methods used across studies. Studies using regression models with an influenza activity proxy applied 4 approaches to estimate influenza-associated mortality. The estimates increased with age and ranged widely, from −0.3–1.3 and 0.6–8.3 respiratory deaths per 100,000 population for children and adults, respectively, to 4–119 respiratory deaths per 100,000 population for older adults. Meta-regression analysis identified that study design features were associated with the observed variation in estimates. The estimates increased with broader cause-of-death classification and were higher for older adults than for children. The multiplier methods tended to produce lower estimates, while Serfling-type models were associated with higher estimates than other methods. No “average” estimate of excess mortality could reliably be made due to the substantial variability of the estimates, partially attributable to methodological differences in the studies. Standardization of methodology in estimation of influenza-associated mortality would permit improved comparisons in the future.</description><identifier>ISSN: 0002-9262</identifier><identifier>EISSN: 1476-6256</identifier><identifier>DOI: 10.1093/aje/kwx270</identifier><identifier>PMID: 28679157</identifier><language>eng</language><publisher>United States: Oxford University Press</publisher><subject>Adults ; Children ; Estimates ; Fatalities ; Global Health - statistics & numerical data ; Heterogeneity ; Humans ; Identification methods ; Influenza ; Influenza A virus ; Influenza, Human - mortality ; Measurement methods ; Morbidity ; Mortality ; Older people ; Population ; Production methods ; Regression Analysis ; Regression models ; Standardization ; Statistical analysis ; Statistical methods ; Statistics as Topic - methods ; Systematic review ; Systematic Reviews, Meta- and Pooled Analyses ; Viruses</subject><ispartof>American journal of epidemiology, 2018-02, Vol.187 (2), p.378-388</ispartof><rights>The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. 2017</rights><rights>The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c436t-148776aaa2d58bda30b88d3979d5954760f582eee76e0ceeaab64c2f69442ece3</citedby><cites>FETCH-LOGICAL-c436t-148776aaa2d58bda30b88d3979d5954760f582eee76e0ceeaab64c2f69442ece3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,778,782,883,1581,27907,27908</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28679157$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Li</creatorcontrib><creatorcontrib>Wong, Jessica Y</creatorcontrib><creatorcontrib>Wu, Peng</creatorcontrib><creatorcontrib>Bond, Helen S</creatorcontrib><creatorcontrib>Lau, Eric H Y</creatorcontrib><creatorcontrib>Sullivan, Sheena G</creatorcontrib><creatorcontrib>Cowling, Benjamin J</creatorcontrib><title>Heterogeneity in Estimates of the Impact of Influenza on Population Mortality: A Systematic Review</title><title>American journal of epidemiology</title><addtitle>Am J Epidemiol</addtitle><description>Abstract
Influenza viruses are associated with a substantial global burden of morbidity and mortality every year. Estimates of influenza-associated mortality often vary between studies due to differences in study settings, methods, and measurement of outcomes. We reviewed 103 published articles assessing population-based influenza-associated mortality through searches of PubMed and Embase, and we identified considerable variation in the statistical methods used across studies. Studies using regression models with an influenza activity proxy applied 4 approaches to estimate influenza-associated mortality. The estimates increased with age and ranged widely, from −0.3–1.3 and 0.6–8.3 respiratory deaths per 100,000 population for children and adults, respectively, to 4–119 respiratory deaths per 100,000 population for older adults. Meta-regression analysis identified that study design features were associated with the observed variation in estimates. The estimates increased with broader cause-of-death classification and were higher for older adults than for children. The multiplier methods tended to produce lower estimates, while Serfling-type models were associated with higher estimates than other methods. No “average” estimate of excess mortality could reliably be made due to the substantial variability of the estimates, partially attributable to methodological differences in the studies. Standardization of methodology in estimation of influenza-associated mortality would permit improved comparisons in the future.</description><subject>Adults</subject><subject>Children</subject><subject>Estimates</subject><subject>Fatalities</subject><subject>Global Health - statistics & numerical data</subject><subject>Heterogeneity</subject><subject>Humans</subject><subject>Identification methods</subject><subject>Influenza</subject><subject>Influenza A virus</subject><subject>Influenza, Human - mortality</subject><subject>Measurement methods</subject><subject>Morbidity</subject><subject>Mortality</subject><subject>Older people</subject><subject>Population</subject><subject>Production methods</subject><subject>Regression Analysis</subject><subject>Regression models</subject><subject>Standardization</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>Statistics as Topic - methods</subject><subject>Systematic review</subject><subject>Systematic Reviews, Meta- and Pooled Analyses</subject><subject>Viruses</subject><issn>0002-9262</issn><issn>1476-6256</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kV1rFDEUhoModlu98QdIQAQpjE0yk69eCKVUu1Cp-HEdMpkzbdbZyZhk2q6_vilbi3rRqyScJw_n5UXoFSXvKdH1gV3Bwc_rGybJE7SgjRSVYFw8RQtCCKs0E2wH7aa0IoRSzclztMOUkJpyuUDtKWSI4QJG8HmD_YhPUvZrmyHh0ON8CXi5nqzLd6_l2A8zjL8tDiP-EqZ5sNmX6-cQsx3K_0N8hL9tUoYi8A5_hSsP1y_Qs94OCV7en3vox8eT78en1dn5p-Xx0VnlmlrkijZKSmGtZR1XbWdr0irV1VrqjmteUpGeKwYAUgBxANa2onGsF7ppGDio99CHrXea2zV0DsYc7WCmWOLEjQnWm38no780F-HKcCWIYLII3t0LYvg1Q8pm7ZODYbAjhDkZqqmQRJNaFPTNf-gqzHEs8Qyri6xWquGF2t9SLoaUIvQPy1Bi7qozpTqzra7Ar_9e_wH901UB3m6BME-PiW4BENWjtw</recordid><startdate>20180201</startdate><enddate>20180201</enddate><creator>Li, Li</creator><creator>Wong, Jessica Y</creator><creator>Wu, Peng</creator><creator>Bond, Helen S</creator><creator>Lau, Eric H Y</creator><creator>Sullivan, Sheena G</creator><creator>Cowling, Benjamin J</creator><general>Oxford University Press</general><general>Oxford Publishing Limited (England)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QP</scope><scope>7T2</scope><scope>7TK</scope><scope>7U7</scope><scope>7U9</scope><scope>C1K</scope><scope>H94</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20180201</creationdate><title>Heterogeneity in Estimates of the Impact of Influenza on Population Mortality: A Systematic Review</title><author>Li, Li ; Wong, Jessica Y ; Wu, Peng ; Bond, Helen S ; Lau, Eric H Y ; Sullivan, Sheena G ; Cowling, Benjamin J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c436t-148776aaa2d58bda30b88d3979d5954760f582eee76e0ceeaab64c2f69442ece3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Adults</topic><topic>Children</topic><topic>Estimates</topic><topic>Fatalities</topic><topic>Global Health - statistics & numerical data</topic><topic>Heterogeneity</topic><topic>Humans</topic><topic>Identification methods</topic><topic>Influenza</topic><topic>Influenza A virus</topic><topic>Influenza, Human - mortality</topic><topic>Measurement methods</topic><topic>Morbidity</topic><topic>Mortality</topic><topic>Older people</topic><topic>Population</topic><topic>Production methods</topic><topic>Regression Analysis</topic><topic>Regression models</topic><topic>Standardization</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><topic>Statistics as Topic - methods</topic><topic>Systematic review</topic><topic>Systematic Reviews, Meta- and Pooled Analyses</topic><topic>Viruses</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Li</creatorcontrib><creatorcontrib>Wong, Jessica Y</creatorcontrib><creatorcontrib>Wu, Peng</creatorcontrib><creatorcontrib>Bond, Helen S</creatorcontrib><creatorcontrib>Lau, Eric H Y</creatorcontrib><creatorcontrib>Sullivan, Sheena G</creatorcontrib><creatorcontrib>Cowling, Benjamin J</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>American journal of epidemiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Li</au><au>Wong, Jessica Y</au><au>Wu, Peng</au><au>Bond, Helen S</au><au>Lau, Eric H Y</au><au>Sullivan, Sheena G</au><au>Cowling, Benjamin J</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Heterogeneity in Estimates of the Impact of Influenza on Population Mortality: A Systematic Review</atitle><jtitle>American journal of epidemiology</jtitle><addtitle>Am J Epidemiol</addtitle><date>2018-02-01</date><risdate>2018</risdate><volume>187</volume><issue>2</issue><spage>378</spage><epage>388</epage><pages>378-388</pages><issn>0002-9262</issn><eissn>1476-6256</eissn><abstract>Abstract
Influenza viruses are associated with a substantial global burden of morbidity and mortality every year. Estimates of influenza-associated mortality often vary between studies due to differences in study settings, methods, and measurement of outcomes. We reviewed 103 published articles assessing population-based influenza-associated mortality through searches of PubMed and Embase, and we identified considerable variation in the statistical methods used across studies. Studies using regression models with an influenza activity proxy applied 4 approaches to estimate influenza-associated mortality. The estimates increased with age and ranged widely, from −0.3–1.3 and 0.6–8.3 respiratory deaths per 100,000 population for children and adults, respectively, to 4–119 respiratory deaths per 100,000 population for older adults. Meta-regression analysis identified that study design features were associated with the observed variation in estimates. The estimates increased with broader cause-of-death classification and were higher for older adults than for children. The multiplier methods tended to produce lower estimates, while Serfling-type models were associated with higher estimates than other methods. No “average” estimate of excess mortality could reliably be made due to the substantial variability of the estimates, partially attributable to methodological differences in the studies. Standardization of methodology in estimation of influenza-associated mortality would permit improved comparisons in the future.</abstract><cop>United States</cop><pub>Oxford University Press</pub><pmid>28679157</pmid><doi>10.1093/aje/kwx270</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adults Children Estimates Fatalities Global Health - statistics & numerical data Heterogeneity Humans Identification methods Influenza Influenza A virus Influenza, Human - mortality Measurement methods Morbidity Mortality Older people Population Production methods Regression Analysis Regression models Standardization Statistical analysis Statistical methods Statistics as Topic - methods Systematic review Systematic Reviews, Meta- and Pooled Analyses Viruses |
title | Heterogeneity in Estimates of the Impact of Influenza on Population Mortality: A Systematic Review |
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