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      The association between socioeconomic status and pandemic influenza: protocol for a systematic review and meta-analysis

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          Abstract

          Background

          Pandemic mortality rates in 1918 and in 2009 were highest among those with the lowest socioeconomic status (SES). Despite this, low SES groups are not included in the list of groups prioritized for pandemic vaccination, and the ambition to reduce social inequality in health does not feature in international and national pandemic preparedness plans. We describe plans for a systematic review and meta-analysis of the association between SES and pandemic outcomes during the last five pandemics.

          Method

          The planned review will cover studies of pandemic influenza that report associations between morbidity, hospitalization, or mortality with socioeconomic factors such as education and income. The review will include published studies in the English, Danish, Norwegian, and Swedish languages, regardless of geographical location. Relevant records were identified through systematic literature searches in MEDLINE, Embase, Cinahl, SocIndex, Scopus, and Web of Science. Reference lists of relevant known studies will be screened and experts in the field consulted in order to identify other additional sources. Two investigators will independently screen and select studies, and discrepancies will be resolved through discussion until consensus is reached. Covidence will be used. Results will be summarized narratively and using three meta-analytic strategies: coefficients expressing the difference between the highest and lowest socioeconomic groups reported will be pooled using (a) fixed and random effects meta-analysis where studies involve similar outcome and exposure measures and (b) meta-regression where studies involve similar outcome measures. In addition, we will attempt to use all reported estimates for SES differences in (c) a Bayesian meta-analysis to estimate the underlying SES gradient and how it differs by outcome and exposure measure.

          Discussion

          This study will provide the first systematic review of research on the relation between SES and pandemic outcomes. The findings will be relevant for health policy in helping to assess whether people of low socioeconomic status should be prioritized for vaccines in preparedness plans for pandemic influenza. The review will also contribute to the research literature by providing pooled estimates of effect sizes as inputs into power calculations of future studies.

          Systematic review registration

          PROSPERO 87922

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          Most cited references 20

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          Conducting Meta-Analyses inRwith themetaforPackage

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            PRESS Peer Review of Electronic Search Strategies: 2015 Guideline Statement.

            To develop an evidence-based guideline for Peer Review of Electronic Search Strategies (PRESS) for systematic reviews (SRs), health technology assessments, and other evidence syntheses.
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              Estimation of potential global pandemic influenza mortality on the basis of vital registry data from the 1918-20 pandemic: a quantitative analysis.

              The threat of an avian influenza pandemic is causing widespread public concern and health policy response, especially in high-income countries. Our aim was to use high-quality vital registration data gathered during the 1918-20 pandemic to estimate global mortality should such a pandemic occur today. We identified all countries with high-quality vital registration data for the 1918-20 pandemic and used these data to calculate excess mortality. We developed ordinary least squares regression models that related excess mortality to per-head income and absolute latitude and used these models to estimate mortality had there been an influenza pandemic in 2004. Excess mortality data show that, even in 1918-20, population mortality varied over 30-fold across countries. Per-head income explained a large fraction of this variation in mortality. Extrapolation of 1918-20 mortality rates to the worldwide population of 2004 indicates that an estimated 62 million people (10th-90th percentile range 51 million-81 million) would be killed by a similar influenza pandemic; 96% (95% CI 95-98) of these deaths would occur in the developing world. If this mortality were concentrated in a single year, it would increase global mortality by 114%. This analysis of the empirical record of the 1918-20 pandemic provides a plausible upper bound on pandemic mortality. Most deaths will occur in poor countries--ie, in societies whose scarce health resources are already stretched by existing health priorities.
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                Author and article information

                Affiliations
                [1 ]ISNI 0000 0000 9151 4445, GRID grid.412414.6, Work Research Institute at OsloMet - Oslo Metropolitan University, ; PO. Box 4, St. Olavs plass, 0130 Oslo, Norway
                [2 ]Frisch Centre, Gaustadalleen 21, 0349 Oslo, Norway
                Contributors
                ORCID: http://orcid.org/0000-0002-3980-3818, Svenn-Erik.Mamelund@oslomet.no
                Clare.Shelley-Egan@oslomet.no
                ole.rogeberg@frisch.uio.no
                Journal
                Syst Rev
                Syst Rev
                Systematic Reviews
                BioMed Central (London )
                2046-4053
                4 January 2019
                4 January 2019
                2019
                : 8
                30609940 6318944 931 10.1186/s13643-018-0931-2
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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                Protocol
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                © The Author(s) 2019

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