Methods
Search strategy and selection
criteria
This systematic review was reported according to the Preferred Reporting
Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline
(Text S1) and
Synthesis without meta-analysis in
systematic reviews (SWiM) reporting guideline (Text S2). The protocol of
this review was registered in International Prospective Register of
Systematic Review (PROSEPRO) with registration number CRD42021283045. We
searched the following electronic databases: MEDLINE, EMBASE, Web of
Science, the WHO COVID-19 Global literature on coronavirus disease
database, China National Knowledge Infrastructure (CNKI),
WanFang,
CqVip, and Sinomond for relevant
publications from January 1, 2020 to December 31, 2021 using a tailored
search strategy (Text S3). No restrictions on language were applied. The
reference lists of eligible
studies were also examined for eligibility. The following selection
criteria were applied.
Inclusion criteria
Population-based studies reporting any laboratory-confirmed
co-infections with influenza or RSV in COVID-19 patients; AND
At least one of the following outcomes should be reported separately
in co-infection group (i.e., SARS-CoV-2 and influenza / RSV) and
mono-infection group (i.e., SARS-CoV-2):
need or use of supplemental
oxygen, ICU admission, mechanical ventilation (including invasive and
non-invasive ventilation) and deaths.
Exclusion criteria
- Studies that focused on reporting nosocomial infections; OR
- Studies that only included patients with comorbidities (e.g., patients
with chronic obstructive pulmonary disease, or patients infected with
human immunodeficiency virus) OR
- Reviews or studies reporting data that were previously reported by
another study (in which case only the primary studies were considered
for inclusion).
Systematic literature
review
Two reviewers (BC and SD) independently screened titles, abstracts and
full-texts of the retrieved records from the literature search, and
extracted data using tailored data extraction template. The data
extraction template consisted of two parts: the first part collected
study-level characteristics such as the study location, period, number
of subjects, age of subjects, statistical method, disease severity
outcomes reported, clinical specimens, viral diagnostic techniques and
so on; the second part collected data on the clinical outcomes by mono-
infection group and co-infection group. Any discrepancies during data
screening and extraction were resolved among YL, BC and SD.
Quality assessment
Quality assessment was conducted for all included studies independently
by two reviewers (BC and SD). The questionnaire used for the quality
assessment was modified based on the Critical Appraisal Skills Programme
(CASP) checklist for cohort studies12. The modified
questionnaire contained the
following seven questions: 1. Did the study address a clearly focused
issue?, 2. Were the subjects recruited in an acceptable way?, 3. Was the
exposure accurately measured to minimize bias?, 4. Was the outcome
accurately measured to minimize bias?, 5. Have the authors used
multivariable analysis method to adjust for confounders?, 6. Can the
results be applied to the local population?, 7. Do the results of this
study fit with other available evidence? The questionnaire contained
seven questions and answer to each
of the questions could be “Yes”, “No”, or “Can’t tell”,
corresponding to 1, 0 and 0 points, respectively. We calculated the
overall score for each study after assessing each criterion as listed
above. Studies with 7, 5-6 and ≤4 points were defined as “high
quality”, “moderate quality” and “low quality”, respectively. Any
discrepancies during quality assessment were resolved among YL, BC and
SD.
Data analysis
A narrative synthesis
was conducted for all outcomes of interest. The outcomes were compared
between the mono-infection group and
the co-infection group. A
random-effect meta-analysis of the corresponding odds ratios was
conducted if three or more studies were available per comparison (i.e.,
influenza and SARS-CoV-2 co-infection vs SARS-CoV-2 mono-infection, and
RSV and SARS-CoV-2 co-infection vs SARS-CoV-2 mono-infection). The
choice of conducting a random-effect meta-analysis (rather than
fixed-effect meta-analysis) was based on the anticipation that
populations included in the studies differed by region, age, study
period (in relation to the COVID-19 pandemic), clinical specimens and
diagnostic methods. We applied a continuity correction of 0.5 if no one
had severity outcomes in any group 13. This allowed
calculation of an OR for these instances, and enabled inclusion within
subsequent meta–analyses. When odds ratios could be obtained both from
univariate analysis and multivariate analysis in a report, the one from
the multivariate analysis was included in the meta-analysis. For
influenza and SARS-CoV-2 co-infection, the subgroup analysis was
conducted by influenza type (i.e., influenza A and influenza B) if data
allowed. Sensitivity analyses excluding studies with small sample sizes
(defined as ≤ 5 subjects in any of the mono-infection and co-infection
groups) and excluding those low-quality studies were performed. Symmetry
of funnel plot and Egger’s regression method were used to evaluate the
presence of small study effects 14. Heterogeneity was
evaluated by I2 values; I2 value of
>50% and >75% suggested moderate and high
heterogeneity, respectively 15. All statistical
analyses and data visualizations were performed with R version 4.1.0.