This protocol is registered under the PROSPERO database (CRD42020219771) and designed in accordance with standardized guidelines specified in the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) (see Additional file 1) (16). Findings will be reported using the PRISMA checklist and any amendments to the protocol will be documented in the final review.
Inclusion & exclusion criteria
To be included in the review, an article must meet the following criteria:
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Studies will capture data on persons of any age who are at risk for, or infected with, a respiratory viral pathogen (influenza virus, respiratory syncytial virus (RSV), middle east respiratory syndrome (MERS), severe acute respiratory syndrome coronavirus 1 (SARS), parainfluenza virus, measles virus, rubella virus, rhinovirus, and/or adenovirus).
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Studies will measure the following as an exposure: Non-white race/ethnicity, such as Black/African American, Asian, American Indian/Alaska Native, Native Hawaiian/other Pacific Islander, non-white Hispanic or Latinx, as defined by the United States Census Bureau (17).
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Studies will measure one or more of the primary or secondary outcomes listed above.
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Studies were publications in peer-reviewed journals or an abstract at a conference with peer-reviewed blinded abstract selection process.
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At a minimum, studies captured and reported information on racial/ethnic disparities in ARI and listed details regarding data sampling techniques.
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Articles published since January 1, 2002 with data collection started no later than January 1, 2000.
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All studies were conducted in English and based in the United States
Articles will be excluded based on the following criteria:
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Study only addresses disparities with the novel SARS-CoV-2 that causes COVID-19
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Study was conducted outside of the United States
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Study conducted among non-human, animal subjects
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Sample size is less than 100 persons
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Study does not mention race/ethnicity in the abstract
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Study is based on modelling data
Study designs
We will include primary studies of any design that describe racial/ethnic disparities associated with respiratory infections due to influenza virus, RSV, MERS, SARS, parainfluenza virus, measles virus, rubella virus, rhinovirus, and/or adenovirus. Studies will be included when non-white race/ethnicity is compared to the following: no comparison; white race/ethnicity; other non-white race/ethnicity
Information sources and search strategies
In partnership with an information specialist at Johns Hopkins University, we will search the following electronic databases: the National Library of Medicine's MEDLINE database using the PubMED interface, EBSCO Host- CINAHL Plus, PsycInfo, EMBASE, and Cochrane Library. Search criteria and terms were created based on validated peer-reviewed systematic reviews and articles regarding racial disparities and acute respiratory infections (8). We will search the gray literature by hand. Reference lists of identified articles and reports will be reviewed for additional articles.
We piloted multiple search strategies to optimize an approach that is highly sensitive yet prioritizes identifying relevant articles. The search strategies are comprised of a combination of controlled MeSH terms and other search terms that cover two independent concepts: acute respiratory infections and racial/ethnic disparities (see Additional file 2). Search terms pertaining to acute respiratory infections include terms relating to viral infections due to influenza, other coronaviruses (excluding SARS-CoV-2), other viral respiratory pathogens, and general terms for acute respiratory infection and/or influenza like illness. Terms associated with racial disparities include terms relating to general health disparities or inequities, race/ethnicity, socioeconomic factors (e.g. poverty, education), and historically marginalized communities (undocumented immigrants, incarcerated persons). We opted to not include search terms specific to racial/ethnic groups to mitigate the potential for missing articles due to improper indexing. Additionally, by including terms that are not limited to racial/ethnic groups (e.g. poverty, health care access), we hope to capture information on disparities associated with structural and systemic inequities, including structural racism, that overwhelmingly affect racial and ethnic minority communities in the United States.
Study selection & quality assessment
The literature review consists of an iterative title review, abstract review, and full text review for articles that meet the criteria (18). Two reviewers conduct parallel screening of titles found in the search. If either one or both of the two reviewers selects a title to move forward to abstract review, the abstract will be reviewed independently and assessed for inclusion in the full article review. If either one or both of reviewers selects the abstract for full article review, the article will be selected for full article review. If at the full article review there is a disagreement between the first two reviewers regarding data extraction, a third reviewer will review and solve the disagreement. All articles selected for review will be assessed for risk of bias using the Newcastle-Ottawa Scale, a quality assessment tool for non-randomized studies, that assesses articles according to three components: study group selection, group comparability, and outcome ascertainment (19).
Strategy for data extraction
Data will be extracted for each full article reviewed and entered into a pre-piloted data collection form based on COVIDENCE—a commercially available web-based tool for conducting and managing systematic reviews. Reviewers will be trained to abstract the relevant data from the articles using the data abstraction tool.
The following fields will be abstracted from all included studies:
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Source reference
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Source type (e.g. journal article, abstract) and publication year
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Population (adult ≥ 18, child < 18, and any qualifying characteristics such as race/ethnicity, sex/gender, etc.)
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Geographic setting (within the United States)
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Sample size
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Nature of study (descriptive, quantitative, qualitative)
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Study design (e.g. cross-sectional, etc.)
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Individual-, community-level, or structural-level factors discussed
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Type of individual-, community-, or structural-level factor discussed (e.g. race/ethnicity, socioeconomic status, healthcare coverage, housing, citizenship status, neighborhood location, food security)
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Measures of effect for all primary or secondary outcomes of interest, including proportions, relative risks, odds ratios, or hazard ratios if time series data available
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Summary of author interpretations/conclusions
Synthesis and feasibility for meta-analysis
Data will be analyzed according to study outcomes and race/ethnicity exposures. For qualitative research, we will present descriptive summaries, and if race/ethnicity exposures are similarly measured, we will assess consistency of thematic results. For quantitative studies reporting the same outcome, among populations deemed sufficiently similar, we will conduct meta-analysis using random effects meta-analytic models. We will evaluate heterogeneity within selected studies by examining forest plots and conducting Cochrane’s Q and I2 statistical tests. We will assess the quality of the body of evidence contributing to the pooled effect estimate for each outcome using criteria recommended by the GRADE Working Group: GRADE evidence certainty for individual outcomes (20–25). Funnel plots will be used to assess for risk of publication bias where 10 or more similar studies are included.