Postpartum rubella vaccination for sero-negative women

  • Protocol
  • Intervention



This is the protocol for a review and there is no abstract. The objectives are as follows:

To determine the effectiveness of postpartum rubella vaccination in preventing the congenital rubella infection.


Description of the condition

Rubella, also known as German Measles is an acute viral disease that causes fever and rash (CDC 2011). Rubella was discovered in the 1750s (Cooper 2001) and its teratogenic effect was observed by Gregg in 1941 (Gregg 1991). Further studies confirmed the association with other congenital defects with rubella such as cataracts, deafness and congenital heart defects (Overall 1998).

The rubella virus is an RNA virus (CDC 2005) that is transmitted by droplets and can be transmitted and replicated in the placenta during maternal viraemia, which usually occurs five to seven days after maternal infection. The infection of the fetus can occur at any time during pregnancy but the outcome depends on the gestational age at which the infection takes place (Duszak 2009). There is no risk to the fetus if rubella infection occurred before conception (Enders 1988). However, if rubella infection occurs during pregnancy, the virus spreads through the blood and multiple maternal tissues may be infected including the placenta. Subsquently, maternal antibodies get rid of the virus from the blood but it may persist for months in the placenta. About 80% of fetuses exposed to the rubella virus at or before 12 weeks of pregnancy will become infected and 85% of them will develop congenital rubella infection. Most of the infections occur during the first eight weeks, with rapid decline in the risk of congenital infection after 12 weeks' gestation (Miller 1982).

During the first 12 weeks of pregnancy, when the fetus is incapable of producing immunoglobulin (IG), maximum damage can occur in 80% of fetuses (Webster 1998). In the second trimester, the risk of fetal infection decreases significantly to 25%. This is due to the well developed immune response of the fetus and the structural changes of the placenta leading to increased resistance to the rubella virus. In the last trimester of pregnancy, the rate of fetal infection rises back to 100%, but fetal damage is rare due to the fully developed immune system of the fetus (Webster 1998).

Congenital rubella infection may result in intrauterine fetal death, premature delivery or congenital rubella syndrome (CRS). The classic CRS is characterised by deafness, cataract and congenital heart defects. Other manifestations of the congenital rubella infection may be found in newborns and infants as developmental and late-onset anomalies. Such abnormalities can be permanent structural defects, or transient abnormalities; permanent abnormalities include heart and eye defects, central nervous system abnormalities and deafness. Transient manifestations include poor growth of baby during pregnancy (intrauterine growth restriction), loss of transparency of cornea (cloudy cornea), enlargements of the baby's liver and spleen (hepatosplenomegaly), low platelets level (thrombocytopaenia) and an infection or inflammation of brain (meningoencephalitis) (Plotkin 2011).

In 1969, the rubella virus was isolated and the first successful vaccine was approved in the United States of America (USA), with subsequent reduction in rubella infection and CRS (Duszak 2009). Despite many national, rubella-containing vaccine (RCV) immunisation programmes, the burden of CRS still exists and it is estimated that about 238,000 children are born with CRS each year, with the majority reported in the developing countries (Vijayalakshmi 2002). In contrast, during the years 2001 to 2004, only five infants with CRS were reported in the USA (Reef 2006).The proportion of women of childbearing age who are susceptible to the rubella virus infection varies greatly among nations and depends on the population density. In areas with low-density population and low risk of contacting the rubella infection, more women are susceptible at childbearing age to the rubella virus, whereas women in crowded urban areas develop immunity secondary to infection early during their childhood (Plotkin 2004).

Description of the intervention

The first three vaccines developed for rubella were withdrawn from the market due to the high incidence of side effects including arthritis, neuropathy and arthralgia (joint pain), and were replaced in by the RA27/3 (human diploid fibroblast) vaccine when it was licensed in 1979. RA 27/3 rubella vaccine is a live attenuated virus and was first isolated in 1969 (Preblud 1980) and is currently the only licensed vaccine in USA and most of the world  (Preblud 1980). Rubella vaccine is available as a single vaccine or in combination with other vaccines such as measles and mumps (MMR), or mumps, measles, and varicella vaccine (MMRV).

MMR and MMRV are provided as a lyophilised (freeze-dried) powder and reconstituted with 0.5 mL sterile water, preservative free. The vaccine contains a small amount of human albumin (Kroger 2011). RCVs should be stored in the refrigerator at 2 to 8oC and the diluents (sterile water) can be stored with the vaccine in the refrigerator or at the room temperature. The vaccine is given as a subcutaneous injection in the deltoid muscle (Kroger 2011). Because the rubella vaccine is a live attenuated vaccine, it is not given during pregnancy due to the theoretical risk of congenital infection (Zimmerman 2007), and women should be  counselled to avoid pregnancy for four weeks after rubella vaccination. However, if pregnancy occurs during this time it is not an indication to terminate the pregnancy (CDC 2007). Pregnant women should be screened, and those who are found to be sero-negative should be offered the MMR vaccine in the postpartum period to prevent congenital rubella infection during the subsequent pregnancies.

Around 2% of RCV recipients develop all or some of the following side effects; post auricular swelling, cough, rhinitis, and influenza like illness, while 4% may develop allergy and fever. A rare side effect is severe allergic reaction (anaphylaxis) (Castro 2005).

Usually after vaccination, sero-conversion is induced in more than 95% of the vaccinated population (Weibel 1980). However, only two-thirds of the vaccinated population continue to have lifelong immunity against rubella infection (Johnson 1996). Hence, a considerable proportion of women who were vaccinated during childhood will be susceptible to rubella infection by the time they reach childbearing age. For instance, sero-negativity among women of childbearing age was 23% in Nigeria in women vaccinated in childhood (Onyenekwe 2000),14% in Taiwan (Lin 2010) and 6.7% in Japan (Okuda 2008); while 15% of unvaccinated population in Turkiy were sero-negative (Aksit 1999), which indicates a variable response to childhood vaccination in different communities.

Postpartum rubella vaccination is recommended to reduce the risk of congenital rubella infection in subsequent pregnancies (Canadian NACI 1998; Watson 1998). This strategy has advantages as women are vaccinated while in hospital, thus increasing the uptake of vaccination. In addition, the fecundity rate is reduced during the postpartum period, giving the mother time to build immunity against rubella (Valeggia 2009). However, studies have documented a poor compliance to postpartum rubella vaccination of sero-negative women; with resultant CRS in subsequent pregnancies (Schluter 1998). Additionally, earlier reports have linked postpartum rubella immunisation to an increased rate of arthritis (Tingle 1985) but recent reports did not find the condition to be more prevalent in vaccinated women than those who were not vaccinated (Ray 1997).

The strategy of postpartum rubella vaccination entails screening of all women who attend for delivery in any health facility to detect those who are sero-negative then to offer them vaccination. However, the cost of screening for sero-negative and immunisation of women of childbearing age, might be a major barrier for implementing such a strategy in many countries with limited resources (Onakewhor 2011).

How the intervention might work

The RA27/3 rubella vaccine is well tolerated, and induces sero-conversion in more than 95% of those vaccinated (Weibel 1980). Hemagglutination inhibition (HAI) antibodies typically develop 10 to 28 days after vaccination (Meegan 1983). The HAI antibodies are specific for three structural proteins, the virus capsid (C protein) and envelope proteins E1 and E2, and can be detected one month after vaccination. However, about 5% of those vaccinated fail to sero-convert (Best 2007).

Why it is important to do this review

In the year 2000, the World Health Organization (WHO) introduced RCV into the national childhood immunisation program, and 130 member countries out of 195 joined the program. Consequently, the incidence of rubella decreased by 82% in developed countries. Nevertheless, around 10% to 20% of the post-teenager populations remain susceptible to rubella in developed countries, and up to 68% are susceptible in developing countries (Karakoc 2003). It is estimated that CRS affects 283,000 infants every year (Vijayalakshmi 2002). This is due to rubella re-infection, lack of universal vaccination, and the primary and secondary vaccine failure (Miller 1991). Hence, screening women during pregnancy to identify susceptible women and vaccinating them is expected to reduce the incidence of CRS further.


To determine the effectiveness of postpartum rubella vaccination in preventing the congenital rubella infection.


Criteria for considering studies for this review

Types of studies

We will include all randomised controlled, quasi-randomised, cluster-randomised trials of rubella vaccination in the first six weeks following delivery compared with vaccination after six weeks following delivery, for the prevention of congenital rubella infection in sero-negative women. We will exclude cross-over trials and studies presented only as abstracts.

Types of participants

Sero-negative women in the immediate postpartum period and up to six weeks following delivery.

Types of interventions

Rubella-containing vaccines administered within six weeks post delivery compared with rubella-containing vaccine administered after six weeks from delivery.

Types of outcome measures

Primary outcomes
  1. Rate of congenital rubella infection following postpartum rubella vaccination (as defined by the trialists).

  2. Rate of maternal sero-positivity following postpartum rubella vaccination.

Secondary outcomes
  1. Any adverse effect of rubella vaccination.

  2. Incidence of congenital rubella infection secondary to vaccination (as defined by the trialists).

Search methods for identification of studies

Electronic searches

We will contact the Trials Search Co-ordinator to search the Cochrane Pregnancy and Childbirth Group’s Trials Register. 

The Cochrane Pregnancy and Childbirth Group’s Trials Register is maintained by the Trials Search Co-ordinator and contains trials identified from:

  1. monthly searches of the Cochrane Central Register of Controlled Trials (CENTRAL);

  2. weekly searches of MEDLINE;

  3. weekly searches of Embase;

  4. handsearches of 30 journals and the proceedings of major conferences;

  5. weekly current awareness alerts for a further 44 journals plus monthly BioMed Central email alerts.

Details of the search strategies for CENTRAL, MEDLINE and Embase, the list of handsearched journals and conference proceedings, and the list of journals reviewed via the current awareness service can be found in the ‘Specialized Register’ section within the editorial information about the Cochrane Pregnancy and Childbirth Group.

Trials identified through the searching activities described above are each assigned to a review topic (or topics). The Trials Search Co-ordinator searches the register for each review using the topic list rather than keywords.

We will not apply any language restrictions.

Data collection and analysis

Selection of studies

Two review authors will independently assess for inclusion all the potential studies we identify as a result of the search strategy. We will resolve any disagreement through discussion or, if required, we will consult a third review author.

Data extraction and management

We will design a form to extract data. For eligible studies, at least two review authors will extract the data using the agreed form. We will resolve discrepancies through discussion or, if required, we will consult a third review author. We will enter data into Review Manager software (RevMan 2011) and check for accuracy.

When information regarding any of the above is unclear, we will attempt to contact authors of the original reports to provide further details.

Assessment of risk of bias in included studies

Two review authors will independently assess risk of bias for each study using the criteria outlined in the Cochrane Handbook for systematic Reviews of Interventions (Higgins 2011). We will resolve any disagreement by discussion or by involving a third assessor.

(1) Random sequence generation (checking for possible selection bias)

We will describe for each included study the method used to generate the allocation sequence in sufficient detail to allow an assessment of whether it should produce comparable groups.

We will assess the method as:

  • low risk of bias (any truly random process, e.g. random number table; computer random number generator);

  • high risk of bias (any non-random process, e.g. odd or even date of birth; hospital or clinic record number);

  • unclear risk of bias.   

(2) Allocation concealment (checking for possible selection bias)

We will describe for each included study the method used to conceal allocation to interventions prior to assignment and will assess whether intervention allocation could have been foreseen in advance of, or during recruitment, or changed after assignment.

We will assess the methods as:

  • low risk of bias (e.g. telephone or central randomisation; consecutively numbered sealed opaque envelopes);

  • high risk of bias (open random allocation; unsealed or non-opaque envelopes, alternation; date of birth);

  • unclear risk of bias.   

(3.1) Blinding of participants and personnel (checking for possible performance bias)

We will describe for each included study the methods used, if any, to blind study participants and personnel from knowledge of which intervention a participant received. We will consider that studies are at low risk of bias if they were blinded, or if we judge that the lack of blinding would be unlikely to affect results. We will assess blinding separately for different outcomes or classes of outcomes.

We will assess the methods as:

  • low, high or unclear risk of bias for participants;

  • low, high or unclear risk of bias for personnel.

(3.2) Blinding of outcome assessment (checking for possible detection bias)

We will describe for each included study the methods used, if any, to blind outcome assessors from knowledge of which intervention a participant received. We will assess blinding separately for different outcomes or classes of outcomes.

We will assess methods used to blind outcome assessment as:

  • low, high or unclear risk of bias.

(4) Incomplete outcome data (checking for possible attrition bias due to the amount, nature and handling of incomplete outcome data)

We will describe for each included study, and for each outcome or class of outcomes, the completeness of data including attrition and exclusions from the analysis. We will state whether attrition and exclusions were reported and the numbers included in the analysis at each stage (compared with the total randomised participants), reasons for attrition or exclusion where reported, and whether missing data were balanced across groups or were related to outcomes. Where sufficient information is reported, or can be supplied by the trial authors, we will re-include missing data in the analyses which we undertake.

We will assess methods as:

  • low risk of bias (e.g. no missing outcome data; missing outcome data balanced across groups);

  • high risk of bias (e.g. numbers or reasons for missing data imbalanced across groups; ‘as treated’ analysis done with substantial departure of intervention received from that assigned at randomisation);

  • unclear risk of bias.

(5) Selective reporting (checking for reporting bias)

We will describe for each included study how we investigated the possibility of selective outcome reporting bias and what we found.

We will assess the methods as:

  • low risk of bias (where it is clear that all of the study’s pre-specified outcomes and all expected outcomes of interest to the review have been reported);

  • high risk of bias (where not all the study’s pre-specified outcomes have been reported; one or more reported primary outcomes were not pre-specified; outcomes of interest are reported incompletely and so cannot be used; study fails to include results of a key outcome that would have been expected to have been reported);

  • unclear risk of bias.

(6) Other bias (checking for bias due to problems not covered by (1) to (5) above)

We will describe for each included study any important concerns we have about other possible sources of bias.

We will assess whether each study was free of other problems that could put it at risk of bias:

  • low risk of other bias;

  • high risk of other bias;

  • unclear whether there is risk of other bias.

(7) Overall risk of bias

We will make explicit judgements about whether studies are at high risk of bias, according to the criteria given in the Cochrane Handbook (Higgins 2011). With reference to (1) to (6) above, we will assess the likely magnitude and direction of the bias and whether we consider it is likely to impact on the findings. We will explore the impact of the level of bias through undertaking sensitivity analyses - see Sensitivity analysis

Measures of treatment effect

Dichotomous data

For dichotomous data, we will present results as summary risk ratio with 95% confidence intervals. 

Continuous data

For continuous data, we will use the mean difference if outcomes are measured in the same way between trials. We will use the standardised mean difference to combine trials that measure the same outcome, but use different methods.  

Unit of analysis issues

Cluster-randomised trials

We will include cluster-randomised trials in the analyses along with individually-randomised trials. We will adjust their sample sizes using the methods described in the Cochrane Handbook using an estimate of the intra cluster correlation co-efficient (ICC) derived from the trial (if possible), from a similar trial or from a study of a similar population. If we use ICCs from other sources, we will report this and conduct sensitivity analyses to investigate the effect of variation in the ICC. If we identify both cluster-randomised trials and individually-randomised trials, we plan to synthesise the relevant information. We will consider it reasonable to combine the results from both if there is little heterogeneity between the study designs and the interaction between the effect of intervention and the choice of randomisation unit is considered to be unlikely.

We will also acknowledge heterogeneity in the randomisation unit and perform a sensitivity analysis to investigate the effects of the randomisation unit.

Dealing with missing data

For included studies, we will note levels of attrition. We will explore the impact of including studies with high levels of missing data in the overall assessment of treatment effect by using sensitivity analysis.

For all outcomes, we will carry out analyses, as far as possible, on an intention-to-treat basis, i.e. we will attempt to include all participants randomised to each group in the analyses, and all participants will be analysed in the group to which they were allocated, regardless of whether or not they received the allocated intervention. The denominator for each outcome in each trial will be the number randomised minus any participants whose outcomes are known to be missing.

Assessment of heterogeneity

We will assess statistical heterogeneity in each meta-analysis using the T², I² and Chi² statistics. We will regard heterogeneity as substantial if an I² is greater than 30% and either the T² is greater than zero, or there is a low P value (less than 0.10) in the Chi² test for heterogeneity. 

Assessment of reporting biases

If there are 10 or more studies in the meta-analysis we will investigate reporting biases (such as publication bias) using funnel plots. We will assess funnel plot asymmetry visually, and use formal tests for funnel plot asymmetry. For continuous outcomes we will use the test proposed by Egger 1997, and for dichotomous outcomes we will use the test proposed by Harbord 2006. If asymmetry is detected in any of these tests or is suggested by a visual assessment, we will perform exploratory analyses to investigate it.

Data synthesis

We will carry out statistical analysis using the Review Manager software (RevMan 2011). We will use fixed-effect meta-analysis for combining data where it is reasonable to assume that studies are estimating the same underlying treatment effect: i.e. where trials are examining the same intervention, and the trials’ populations and methods are judged sufficiently similar. If there is clinical heterogeneity sufficient to expect that the underlying treatment effects differ between trials, or if substantial statistical heterogeneity is detected, we will use random-effects meta-analysis to produce an overall summary if an average treatment effect across trials is considered clinically meaningful. The random-effects summary will be treated as the average range of possible treatment effects and we will discuss the clinical implications of treatment effects differing between trials. If the average treatment effect is not clinically meaningful, we will not combine trials.

If we use random-effects analyses, the results will be presented as the average treatment effect with 95% confidence intervals, and the estimates of  T² and I².

Subgroup analysis and investigation of heterogeneity

If we identify substantial heterogeneity, we will investigate it using subgroup analyses and sensitivity analyses. We will consider whether an overall summary is meaningful, and if it is, use random-effects analysis to produce it.

We plan to carry out the following subgroup analyses.

  1. Rubella single vaccine versus rubella in combination with other vaccines.

  2. Study design as randomised/quasi-randomised, or cluster-randomised.

The following outcomes will be used in subgroup analysis.

  1. Rate of congenital rubella infection following postpartum rubella vaccination.

  2. Rate of maternal sero-positivity following postpartum rubella vaccination.

We will assess subgroup differences by interaction tests available within RevMan (RevMan 2011). We will report the results of subgroup analyses quoting the χ2 statistic and P value, and the interaction test I² value.

Sensitivity analysis

Sensitivity analysis will be carried out to explore the effect of the overall trial quality by removing those trials rated as 'high risk of bias' or 'unclear risk of bias' to establish whether it is likely to impact on the findings. We will restrict sensitivity analyses to the primary outcomes.


We acknowledge the assistance of "Shiekh Bahmdan research chair for Evidance -based healthcare and Knowledge translation" for bridging the gap between the best evidence based research and Best Practices in Health.

As part of the pre-publication editorial process, this protocol has been commented on by four peers (an editor and three referees who are external to the editorial team) and the Group's Statistical Adviser.

The National Institute for Health Research (NIHR) is the largest single funder of the Cochrane Pregnancy and Childbirth Group. The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the NIHR, NHS or the Department of Health.

Contributions of authors

Rasmieh A Alzeidan drafted the protocol, Hayfaa A Wahabi, Amel A Fayed, and Samia A Esmaeil revised and approved the final version of the protocol.

Declarations of interest

None known.