Types of studies

We will include the following studies (listed in the order of the strength of evidence).

1. Randomized controlled trials (RCTs)

2. Quasi‐randomized trials

3. Cohort studies

4. Case‐control studies

5. Cross‐sectional studies

6. Case series/case reports

During the initial phase of this pandemic, it is unlikely that RCTs and quasi‐randomized trials will be available. As our knowledge of this virus evolves, it remains unlikely that RCTs will be achievable given national differences of practice and the relatively low number of infants and mothers we have seen thus far. The other studies will be described narratively as depicted in Table 3 and Table 4. Studies will be categorized by the bundled interventions carried out in those particular cases. Individual cases or groups of cases described will be isolated if possible and early neonatal infection identified. Authors will be contacted to clarify information if able. If clarification is not possible, this will also be noted.

Types of participants

We will include newborn infants at any gestational age or birth weight born to women with confirmed SARS‐CoV‐2 infection.

Types of interventions

A. Physical environment (aerosolization and droplet management):

1. Negative pressure in delivery area

2. Separate room from delivery room

3. Distance of ≥ 6 feet from mother during resuscitation

4. Maternal masking during delivery compared to no maternal masking during delivery

B. Delivery‐specific interventions (minimization of contact during delivery with maternal fluids):

1. Caesarean section for infection prevention

2. Early cord clamping (< 30 seconds) compared to delayed cord clamping (≥ 30 seconds)

C. Infant care practices (minimizing infant skin contact):

1. Infant cleaning/decontamination as soon as possible after resuscitation compared to routine skin care

2. Prevention of skin‐to‐skin contact after stabilization compared to skin‐to‐skin contact after stabilization

As previously discussed, these individual interventions are bundled into guidelines for delivery management by country, region, hospital or society recommendations. Some delivery management alterations may be linked based on structural limitations of delivery area design as well as local obstetric practice. For instance, negative pressure and a separate area for neonatal resuscitation may not be available for most hospitals and will not be provided even if desired. If a decision is made to do caesarean section for infection prevention purposes, early cord clamping is also more likely. On evaluation of available guidelines, we classified the interventions into seven combinations where one or more interventions were conducted from each category to compare to routine care (Table 2). 

Types of outcome measures

Electronic searches

We will conduct a comprehensive search including:

1. Cochrane Central Register of Controlled Trials (CENTRAL 2020, current issue) in the Cochrane Library;

2. Cochrane COVID‐19 Study Register, via CRS Web;

3. Ovid MEDLINE(R) and Epub Ahead of Print, In‐Process & Other Non‐Indexed Citations, Daily and Versions(R) (1946 to current);

4. CINAHL (1981 to current);

5. World Health Organization (WHO) COVID‐19 Global Research Database;

6. Centers for Disease Control and Prevention COVID‐19 Research Article Database;

7. International Standard Randomized Controlled Trial Number (ISRCTN) Registry (www.isrctn.com).

We will include the MEDLINE search (Appendix 2), which will be translated into the other databases.

We will not apply language restrictions.

We will repeat the search every six months.

Searching other resources

We will also search the references cited in the identified articles for relevant articles not located in the primary search and conference proceedings. We also plan to contact experts if necessary to identify further relevant studies.

Selection of studies

We will accept peer‐reviewed published and unpublished studies, both in full article and abstract forms, as long as a complete 'Risk of bias' assessment is possible. We will contact the authors of studies identified to be relevant to obtain further information on study design, patient characteristics, co‐interventions and follow‐up data if the published data are insufficient. We will also include non‐English language studies including abstracts and full‐text reports. If non‐English records are identified, we will obtain a translation of the full‐text report of the record to assess eligibility.

We will record the selection process in sufficient detail to complete a PRISMA flow diagram and 'Characteristics of excluded studies' table (Moher 2009).

Data extraction and management

We will carry out data extraction using a pilot‐tested Microsoft Excel spreadsheet, with each data point reviewed twice. We will record data which include the following information:

1. study design;

2. setting of hospital;

3. maternal characteristics;

4. newborn characteristics;

5. intervention characteristics;

6. outcomes;

7. numerical data of interest.

We will screen for duplicate entry of patients by matching the initial number of patients recruited against the total number along each step in the conduct of the study. We will also screen for duplication of cases in different publications by matching demographic data, specific identifiers e.g. date of birth, date of admission, admission hospital and others, if available in the article. We will also contact the authors of the study for clarification if necessary. We will resolve any disagreement among the review authors by discussions leading to a consensus.

In addition, we will separately analyze studies with different designs. Regional case series and national data reports may include patients listed in case reports and local case series. The latter may have more granularity than national data.

Assessment of risk of bias in included studies

Two review authors (CC, JK) will independently assess the risk of bias (low, high, or unclear) of all included randomized or quasi‐randomized trials using the Cochrane ‘Risk of bias’ tool for the following domains (Higgins 2011):

1. sequence generation (selection bias);

2. allocation concealment (selection bias);

3. blinding of participants and personnel (performance bias);

4. blinding of outcome assessment (detection bias);

5. incomplete outcome data (attrition bias);

6. selective reporting (reporting bias);

7. any other bias.

We will assess observational studies by the level of evidence:

1. design of the study: cohort studies > case‐control > cross‐sectional > case series or reports;

2. overall assessment of the study.

We will resolve any disagreements either by discussion, or by consulting with a third author. We have included further details of the risk of bias tool in Appendix 3.

Measures of treatment effect

We will perform the statistical analyses using Review Manager 5 (Review Manager 2014). We will analyze categorical data using risk ratio (RR) and risk difference (RD). For statistically significant outcomes, we will calculate the number needed to treat for an additional beneficial outcome (NNTB), or the number needed to treat for an additional harmful outcome (NNTH). We will calculate mean differences (MDs) between treatment groups where outcomes are measured in the same way for continuous data. Where outcomes are measured differently, we will report data as standardized mean differences (SMD). We will report 95% confidence intervals (CIs) for all outcomes.

Unit of analysis issues

The unit of analysis will be the participating infant in individually randomized trials, and an infant will be considered only once in the analysis. The participating neonatal unit or section of a neonatal unit or hospital will be the unit of analysis in cluster‐randomized trials. We will analyze them using an estimate of the intra‐cluster correlation coefficient (ICC) derived from the trial (if possible), or from a similar trial or from a study with a similar population as described in Section 23.1.4 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2019). If we use ICCs from a similar trial or from a study with a similar population, we will report this and conduct a sensitivity analysis to investigate the effect of variation in the ICC.

If we identify both cluster‐randomized trials and individually randomized trials, we will only combine the results from both if there is little heterogeneity between the study designs, and the interaction between the effect of the intervention and the choice of randomization unit is considered to be unlikely.

We will acknowledge any possible heterogeneity in the randomization unit and perform a sensitivity analysis to investigate possible effects of the randomization unit.

Dealing with missing data

If we find missing data with no reasonable explanation, we will assign the study as having high risk of bias in the criterion of "incomplete outcome data." If we consider the extent of missing data to be critical to the final estimates in our meta‐analysis, we will contact the authors to request further information. We will perform sensitivity analysis to assess how the overall results are affected with and without the inclusion of studies with high risk of attrition bias from incomplete outcome data.

Assessment of heterogeneity

For RCTs, we will estimate the treatment effects of individual trials and examine heterogeneity among trials by inspecting the forest plots and quantifying the impact of heterogeneity using the I² statistic. We will grade the degree of heterogeneity as: less than 25% no heterogeneity; 25% to 49% low heterogeneity; 50% to 75% moderate heterogeneity; more than 75% substantial heterogeneity. If we note statistical heterogeneity (I² > 50%), we will explore the possible causes (e.g. differences in study quality, participants, intervention regimens, or outcome assessments).

For observational studies, we will assess heterogeneity by reported information in the tables that are described in data synthesis.

Assessment of reporting biases

We intend to conduct a comprehensive search for eligible studies and will be alert for duplication of data. If we identify 10 or more trials for meta‐analysis, we will assess possible publication bias by inspection of a funnel plot. If we uncover reporting bias that could, in the opinion of the review authors, introduce serious bias, we will conduct a sensitivity analysis to determine the effect of including and excluding these studies in the analysis.

Data synthesis

Subgroup analysis and investigation of heterogeneity

We will consider the following groups for subgroup analysis, where data are available, and will describe the results in Table 5.

Sensitivity analysis

Where we identify substantial heterogeneity, we will conduct sensitivity analysis to determine if the findings are affected by inclusion of only those trials considered to have used adequate methodology with a low risk of bias (selection and performance bias). We will report results of sensitivity analyses for primary outcomes only.

Summary of findings and assessment of the certainty of the evidence

Two review authors (CC, JK) will independently assess the certainty of the evidence for specified primary and secondary outcomes. We will consider evidence from RCTs as high certainty, downgrading the evidence one level for serious (or two levels for very serious) limitations based upon the following: design (risk of bias), consistency across studies, directness of the evidence, precision of estimates, and presence of publication bias. We will apply the GRADE tool to studies that reported prespecified outcome data to assess our certainty in the evidence (Balshem 2011; Schünemann 2008). We will create a 'Summary of findings' table using outcomes that are available in the included studies using GRADEpro GDT.