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The Efficacy and Duration of Protection of Pneumococcal Conjugate Vaccines Against Nasopharyngeal Carriage: A Meta-regression Model

Le Polain De Waroux, Olivier MD*; Flasche, Stefan PhD*; Prieto-Merino, David PhD; Goldblatt, David MBChB, PhD; Edmunds, W. John PhD*


The Efficacy and Duration of Protection of Pneumococcal Conjugate Vaccines Against Nasopharyngeal Carriage A Meta-regression Model: ERRATUM

In the article on page 858, volume 34, issue 8, the author funding statement for David Goldblatt was incomplete. The following statement should be added to the article’s disclosure:

David Goldblatt received funding from the National Institute of Health Research (NIHR) Biomedical Research Centre (BRC) at Great Ormond Street Hospital for Children NHS Foundation Trust and University College London.

The Pediatric Infectious Disease Journal. 35(5):591, May 2016.

The Pediatric Infectious Disease Journal: August 2015 - Volume 34 - Issue 8 - p 858–864
doi: 10.1097/INF.0000000000000717
Vaccine Reports

Background: Pneumococcal conjugate vaccines (PCVs) reduce disease largely through their impact on nasopharyngeal (NP) carriage acquisition of Streptococcus pneumoniae, a precondition for developing any form of pneumococcal disease. We aimed to estimate the vaccine efficacy (VEC) and duration of protection of PCVs against S. pneumoniae carriage acquisition through meta-regression models.

Methods: We identified intervention studies providing NP carriage estimates among vaccinated and unvaccinated children at any time after completion of a full vaccination schedule. We calculated VEC for PCV7 serotypes, grouped as well as individually, and explored cross-protective efficacy against 6A. Efficacy estimates over time were obtained using a Bayesian meta-logistic regression approach, with time since completion of vaccination as a covariate.

Results: We used data from 22 carriage surveys (15 independent studies) from 5 to 64 months after the last PCV dose, including 14,298 children. The aggregate VEC for all PCV7 serotypes 6 months after completion of the vaccination schedule was 57% (95% credible interval: 50–65%), varying by serotype from 38% (19F) to 80%. Our model provides evidence of sustained protection of PCVs for several years, with an aggregate VEC of 42% (95% credible interval: 19–54%) at 5 years, although the waning differed between serotypes. We also found evidence of cross-protection against 6A, with a VEC of 39% 6 months after a complete schedule, decreasing to 0 within 5 years postvaccination.

Conclusion: Our results suggest that PCVs confer reasonable protection against acquisition of pneumococcal carriage of the 7 studied serotypes, for several years after vaccination, albeit with differences across serotypes.

Supplemental Digital Content is available in the text.

From the *Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine; Clinical Trials Unit, London School of Hygiene and Tropical Medicine; and Institute of Child Health, University College London, London, United Kingdom.

Accepted for publication December 21, 2014.

For this work W. was supported by a doctoral research fellowship from the AXA Research fund. The funders had no role in the study design, analysis, writing or publication. D.G. has served on ad-hoc advisory boards for Pfizer, GlaxoSmithKline and Merck, and the University College London Institute of Child Health Laboratory receives contract research funding from Pfizer, GlaxoSmithKline and Merck. W.J.E.'s partner works for GSK, who manufacture PCV10.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (

Address for correspondence: Olivier Le Polain De Waroux, MD, Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine Keppel Street, London, WC1E 7HT, United Kingdom. E-mail:

Pneumococcal conjugate vaccines (PCVs) reduce disease largely through their impact on nasopharyngeal (NP) carriage acquisition of S. pneumoniae (the pneumococcus), a precondition for developing any form of pneumococcal disease.1 Additionally, PCVs reduce the progression to disease of vaccine-type (VT) serotypes carriers.1 The effect of PCV on carriage also drives the herd immunity effect of the vaccine in routine immunization, through a reduction in the transmission of VT in the community.2 Recently, emphasis has been put on the importance of carriage as a proxy measure for PCV impact assessments and for using carriage as an additional and essential biomarker in the licensure pathway of new pneumococcal vaccines.3,4

A recent systematic review of the direct impact of PCVs by dosing schedules5 showed consistent reductions in carriage of the serotypes targeted by the vaccine, including a few years after vaccination, with evidence favoring 3-dose schedules over fewer doses. However, systematic estimates of the efficacy of PCVs against carriage and the duration of protection conferred are lacking. Such estimates will help improve predictions about the likely impact of introducing the vaccine in routine immunization under different epidemiological scenarios. Estimates of the rate of waning efficacy are important to quantify not only the level of individual protection over time but also the degree to which vaccinated children contribute to reducing community transmission as they age. Efficacy against carriage estimates also provide a benchmark against which new vaccines and vaccines under development can be evaluated.3

We studied the vaccine efficacy and duration of protection of pneumococcal vaccines against carriage, through meta-regression models.

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Search Strategy

We identified intervention studies reported by Fleming-Dutra et al5 in a recent systematic review of PCV vaccination schedules, which was based on data published between 1994 and September 2010, with post-hoc supplementation of studies published from 2011. We searched for any additional study published between 2011 and May 31, 2014 using a similar strategy as reported by Fleming-Dutra et al,5 using EMBASE and MEDLINE databases. Details are provided in Appendix, Supplemental Digital Content 1,

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Inclusion Criteria

We considered the following initial criteria for inclusion: (i) intervention studies, (ii) providing NP carriage estimates in vaccinated and unvaccinated children and (iii) with children vaccinated as per routine schedule, including 3 primary doses (“3 + 0” schedule) or at least 2 primary doses with a booster dose (“2 + 1” and “3 + 1” schedules). We further restricted our analysis to studies of either 7-valent, 10-valent or 13-valent licensed vaccines (PCV7, PCV10 and PCV13) or unlicensed vaccines (eg, PCV9 and PCV11) linked to similar carrier proteins as licensed vaccines, including the Corynebacterium diphtheria toxin mutant 197, meningococcal outer membrane protein complex or the nontypeable Haemophilus Influenzae derived protein D. Studies based on vaccines conjugated to other proteins or for which immunological equivalence is unclear (such as tetravalent and pentavalent vaccines6–8) were not included.

Given that PCVs are not known to affect carriage clearance9,10 that the average duration of VT carriage in infants and young children is somewhere around 2 months but may vary by setting and serotype,11–14 and that 2–4 weeks are required for the antibody response to peak after vaccination, we excluded any data collected earlier than 4 months after complete vaccination, when the prevalence and serotype distribution was considered nonstationary, as detailed elsewhere.15,16

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Data Extraction

All but 4 studies were PCV7 trials, with 3 other trials based on PCV9 and 1 on PCV10. We extracted data on the group of PCV7 serotypes, and each individual PCV7 serotype (4, 6B, 9V, 14, 18C, 19F, 23F). We also extracted data on serotype 6A, one of the most common serotypes, which shares immunological traits with 6B but is not included in PCV7, PCV9 or PCV10, to explore possible cross-reactive protective efficacy. Other potential cross-reactive serotypes, such as 19A, were not studied, because of limited data.

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We defined the vaccine efficacy against carriage acquisition (VEC) as the relative reduction in the rate of carriage acquisition among vaccinated compared with unvaccinated children, in trial conditions. Although acquisition events cannot directly be observed, it is possible to obtain a robust estimate of VEC from cross-sectional data based on 1 − odds ratio (OR), under general assumptions, with the OR defined as the odds of vaccination among the (group of) VT(s) (henceforth, the “target” group) to the odds of vaccination among those not carrying any VT (henceforth, the “reference” group).15–17 Hence, in calculating the VEC for each individual PCV7 serotype, we included in the target group all vaccinated and unvaccinated carriers of the particular serotype and in the reference group all non-vaccine serotype (NVT) carriers and noncarriers. Other VT were excluded from the serotype-specific analysis to account for vaccine-induced within-host changes in the pneumococcal flora, as explained elsewhere.15 We also excluded all VT from the analysis of VEC against 6A. Similarly, in trials based on vaccines with higher valency than PCV7, data on the additional VT were excluded. Further details about the methods and assumptions underpinning the estimation of VEC from cross-sectional data are described elsewhere.15–17 The analysis was based on summary data by (group of) serotype(s), rather than individual-level data.

We explored whether the proportion of carried VT out of all VT differed between studies, based on data in unvaccinated children, and used I2 values to quantify heterogeneity.18

We used a Bayesian logistic meta-regression model to estimate the aggregate and serotype-specific VEC and its waning. In the model, for each study i



are the proportion of vaccinated individuals in the reference and target groups, respectively,θi is the study-specific natural logarithm of the OR, and β1 represents the coefficient by which the log(OR) changes for each increase in the natural logarithm of time t since the peak VEC (ie, 4 months after vaccination), such that

, with time in months.

We used a random effect model taking the between-study heterogeneity into account by assuming that θi were independent and sampled from a normal distribution centered around the mean log(OR) of carriage (μ) with a precision τ, such that θi ~ N(μ,τ) and τ = 1/σ2, where σ2 is the between-study variance. A fixed effect was assumed for β1.

The VEC at time t can, therefore, be expressed as follows:

We assigned uniform priors to α [unif (−10; 10)], μ [unif (−10, 0)], σ [unif (0,10)] and β1 [unif (0,10)]. The time coefficient β1 was constrained to positive values, with the assumption that the efficacy should be declining. This assumption was further tested in a sensitivity analysis, by placing an unconstrained prior on β1 [unif (−10,10)].

Some studies provided more than 1 estimate. However, we did not adjust for the lack of independence because of the limited number of estimates from each study.

We explored the impact of schedule [booster (3 + 1 or 2 + 1) versus nonbooster (3 + 0)] by including schedule as a covariate in a multivariable model and assigned a normal uninformed prior to its coefficient [ ~ N(0,103)]. We used an interaction term between schedule and time to look for a difference in the waning by schedule, with a normal uninformed prior on the interaction coefficient [β3 ~ N(0,103)]. Studies in which a 23-valent polysaccharide vaccine (PPV23) booster dose was provided after a primary schedule (as given by Russell et al19 and Lakshman et al20) were considered part of the 3 + 0 group, given the lack of effect of PPV23 on carriage.19

Finally, we conducted sensitivity analyses to explore the impact on our pooled VEC estimates of omitting any 1 study. We also analyzed 2 additional models of waning VEC, including a model where time was included as a linear covariate and another model with an asymptotic function in which the VEC of carriage approaches 0 as time approaches infinity. Models were compared using the Deviance Information Criterion (DIC), a likelihood-based model fitting statistic for Bayesian models similar to the frequentist Akaike Information Criterion.21 Further details are presented in Appendix, Supplemental Digital Content 2,

Posterior distributions were obtained through a Markov Chain Monte Carlo Gibbs sampling algorithm based on 2 chains of 100,000 iterations running in parallel, after a burn-in of 5000 iterations. The model was implemented in R using the jags package.22

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Characteristics of the Studies Included

Of the 18 intervention studies identified by Fleming-Dutra et al,5 4 were based on nonequivalent vaccines6–8,23 and 1 provided carriage data 3 months after the last dose,24 and hence, we ended up with 13 studies. We identified 2 additional studies through our literature review, including a PCV7 trial with data 6 months after a 3 + 1 schedule25 and another PCV10 trial with data collected in the first26 and the second year27 after vaccination. Details of our search are provided in Figure, Supplemental Digital Content 3, and Appendix, Supplemental Digital Content 1, Our analysis, therefore, included 15 individual publications7,10,19,20,26–36 providing estimates from 22 different surveys, spanning from 5 to 64 months after vaccination, and including 7485 samples from vaccinated children and 6813 from unvaccinated children. All but 4 studies were based on PCV7. Three were PCV9 trials29,32,37 and 1 was a PCV10 trial.26,27 We were unable to restrict the latter to PCV7 serotypes only (as all data for PCV10 serotype were aggregated), and we explored the sensitivity of our model output to including (or not) data from that study. Nine data points were from surveys after booster vaccination (Table 1). Two studies10,33 were nested within a cluster randomized trial. The clustering was not adjusted for, and we explored the impact of those study estimates in the sensitivity analysis (see below). Serotype-specific data were obtained for 10 studies (7 PCV7 and 3 PCV9 studies), with 14 data points.10,20,25,28,29,31–35



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Vaccine Efficacy Against Carriage and its Waning

We estimated a peak VEC (ie, 4 months after complete vaccination) of 62% [95% credible interval (CrI): 52–72%] against all VT, decreasing to 57% (95% CrI: 50–65%) 6 months after vaccination, when the number of data points in the model is the highest, and 42% (95% CrI: 19–54%) 5 years after vaccination (Fig. 1 and Table 2).





There was no evidence of a confounding effect of schedule on VEC (with the coefficient β2 centered around 0 [−0.03 (95% CrI: −0.32; 0.63)] or that the waning rate differed by schedule [interaction term β3 0.01 (95% CrI: −0.24; 0.13)]. However, taken individually, the median waning coefficient β1 was smaller (ie, “flatter” slope) after a booster than after a 3 + 0 schedule (Fig., Supplemental Digital Content 4, and Table 2). Our model was insensitive to the assumption on the prior of β1.

The serotype distribution among the unvaccinated children was fairly stable across studies (see Fig., Supplemental Digital Content 5,, with little or moderate statistical heterogeneity in the distribution of serotypes among PCV7 positive samples (serotype-specific I2 values of heterogeneity ranging from 0% to 60%). Serotypes 6B, 23F and 19F were the VT most commonly found, contributing to 26%, 22% and 28%, respectively of the isolated PCV7 serotypes overall among unvaccinated children. Serotype 14 was found in 11% and serotypes 4, 9V and 18C in 3%, 6% and 3% of PCV7 samples, respectively. Serotype 6A was found in about 9% of unvaccinated children, a little higher than the prevalence of 6B (8%, P = 0.07).

Efficacy estimates differed across PCV7 serotypes. Six months after vaccination the highest VEC was measured for serotypes 4 (80%) and 9V (79%) and the lowest for 19F (38%; Fig. 2 and Table 2).



The decline in the efficacy over time varied by serotype (Table 2), with the slowest decline for serotypes 23F and 19F (median β1, 0.09) and more rapid declines for rarer serotypes, although CrIs overlapped for all serotypes (Table 1).

We found evidence of protection against 6A, with a peak VEC of 48% (95% CrI: 18–72%), decreasing to 0 within 5 years postvaccination (Table 2 and Fig. 2).

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Sensitivity Analysis

Our sensitivity analysis showed no significant impact of any study estimate on the coefficients. Estimates were similar after excluding the cluster randomized trial,10,33 with a VEC of 62% (51–73%) at 4 months, decreasing to 40% (12–54%) at 5 years. Excluding the 2 estimates from Cheung et al29 in the Gambia, which together accounted for about 28% of all children included in the analysis, did not affect model estimates [VEC of 62% (50–74%) at 4 months and 39% (12–54%) at 5 years]. Finally, overall and booster schedule VEC estimates and respective model coefficients were similar with and without data from the PCV10 trial.26,27

We explored 2 other models of waning, in addition to the main model (Appendix, Supplemental Digital Content 2, In all 3 models, there was good evidence of protective efficacy in the first few years after vaccination. A similar DIC was obtained for all 3 models estimating the aggregate VEC, as well as for serotype-specific models, except for serotypes 14 and 19F for which the model with the asymptotic time function was outperformed by the other 2. Further information can be found in Figure, Supplemental Digital Content 5, and Table, Supplemental Digital Content 6,

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We computed pooled aggregate and PCV7 serotype-specific vaccine efficacy against NP acquisition and its waning based on a meta-regression model of cross-sectional data. Our results suggest that PCVs confers reasonable protection against acquisition of pneumococcal carriage of the 7 studies serotypes, for several years after vaccination, albeit with differences across serotypes.

Previous studies have explored PCV efficacy against carriage16 and compared schedules;5 however, a pooled estimate was not previously calculated. We found that the distribution of VT was relatively stable across settings, making the pooling of aggregate estimates possible despite differences in the VEC against individual serotypes. An analysis of the aggregate VEC based on the pooled individual serotype-specific estimates also showed results in line with that of the main model presented, albeit with wider confidence bounds given the uncertainty around serotype-specific estimates.

Three serotypes (6B, 19F and 23F) accounted for about 75% of all PCV7 serotypes, but the VEC for each of those differed, with high efficacy against 6B and a weaker anti-19F efficacy. A possible reason for this divergence is the difference in the amount of antibody required for protection as well as differences in the vaccine-induced opsonophagocytic activity (ie, the ingestion and killing of pathogens by phagocytes), despite similar antibody geometric mean concentrations following PCV7 vaccination.30,38 Interestingly, a recent study in the United Kingdom on the vaccine effectiveness and immune correlates of protection against invasive pneumococcal disease39 showed that much less antibody is required for 6B and 23F protection than for 19F protection. The polysaccharide capsule of 19F is more resistant to complement deposition than 6B and requires higher levels of antibodies for opsonophagocytosis.38 However, although trials37,40,41 have shown persistence of serum antibodies several years after vaccination, the exact mechanism underlying the protection against acquisition of carriage remains unclear. Such mechanisms could perhaps involve mucosal immunological responses42 in addition to preexisting circulating serum immunoglobulin (IgG), with serological markers incompletely capturing the mucosal response.

Although natural immunity to colonization in infancy is poor, conjugate vaccines stimulate B-cell responses and the generation of memory B-cells,43 which can be naturally boosted. If boosting does contribute to maintaining a protective efficacy against carriage, then one might expect efficacy to wane faster for rarer serotypes and slower for the more prevalent ones. Our results support such a hypothesis to some extent, showing a slower VEC decline for the most prevalent serotypes. This would also mean that VEC may wane more rapidly after routine implementation of the vaccine than in trial conditions.

We also found evidence of cross-protective efficacy against 6A acquisition based on data from PCV7 and PCV9 trials. Such evidence is supported by trials and observational studies showing an impact of PCV7 on 6A disease,44 as well as immunological evidence with the vaccine eliciting functional antibody (ie, antibodies inducing opsonophagocytosis) against 6A.45

Efficacy estimates against carriage and their waning have several implications for vaccination programs. Despite a stable distribution of serotypes across studies in this analysis, it is likely that some geographical variation occurs, and serotype-specific efficacies are, therefore, important in predicting the impact of PCV in various epidemiological settings. Our results show good evidence of a direct protection against carriage in the first 5 years of life, when the pneumococcal burden is particularly high, and vaccinated children, therefore, also contribute to reducing transmission for several years. This may be particularly important in settings with low vaccine uptake or interrupted delivery.

The population impact on carriage and disease of introducing PCVs under different epidemiological scenarios could be explored through dynamic transmission models of pneumococcal disease, and our estimates of VEC and their waning are essential parameters for such models.

The direct impact on disease is not solely conditioned on the VEC, but also on the efficacy of the vaccine against progressing to disease following carriage.1 This explains the higher efficacy of PCV against invasive disease, at around 80%.1,3,39 In contrast, the efficacy on disease progression against mucosal forms of disease, such as acute otitis media (AOM), is small with most of the disease impact predicted by VEC only.1,3 Interestingly, the efficacy against pneumococcal AOM diagnosed by myringotomy with middle ear fluid aspiration among Finnish children enrolled in a large PCV7 trial30 was 62% (48–72%) in the year following the booster dose, and serotype-specific efficacies were lowest for serotype 19F, at about 37%, and high for 6B (79%), 4 (75%) and 9V (82%). Those estimates are similar to our aggregate and serotype-specific VEC estimates, adding to the evidence that VEC is a close measure of the efficacy against AOM.

An important question is the applicability of our results to 10-valent and 13-valent vaccines, given that many countries have introduced—or are planning to do so—those vaccines into their routine vaccination programs. Data on immunological correlates of protection from trials generally suggest comparable responses after PCV13 and PCV10 vaccination compared with PCV7.45–47 However, a recent study comparing IgG concentration and functional antibodies in PCV7 and PCV13 vaccinated Navajo and White Mountains Apache children in the US48 found higher functional antibody activity against 19F after PCV13 vaccination, compared with PCV7, possibly explained by the inclusion of 19A in PCV13 and the additional activity of anti-19A antibodies against 19F. Another trial in the UK showed lower IgG concentrations for serotypes 4 and 23F for PCV13 compared with PCV7 recipients after a booster dose at 12 months of age. Those differences could translate in differences in aggregate VEC.

The estimation of the efficacy against carriage acquisition from cross-sectional data relies on several assumptions, the most important being that of stationarity—ie, that the relationship between carriage incidence and carriage prevalence is stable.15,16 Vaccination will introduce some temporary disturbance in the carriage rates of different serotypes, with the average prevalence estimates stabilizing after some time.49 Auranen et al17 suggest that stationary levels should not be considered before at least twice the duration of carriage since vaccination. We included studies from 4 months after vaccination to account for this, which we considered to be a good trade-off between ensuring steady-state carriage levels and avoiding peak estimates to be affected by waning VEC.

The assumption that PCV do not affect clearance is based on limited evidence.9,10 Similarly, studies have suggested that the vaccine may also impact carriage density.10 In both scenarios (reduced duration and reduced density), VEC could represent a combined efficacy estimate against acquisition and transmission under the assumption that a reduction in duration of carriage and/or carriage density is associated with both a reduction in the likelihood of detection and of transmission, as discussed elsewhere.15,16

Our study has a number of additional limitations.

First, our analysis was limited by the number of data points, with wider uncertainty as time since vaccination increases and the smaller study sizes for serotype specific analyses, with substantial uncertainty around model estimates for the least prevalent serotypes. The small number of data points in each schedule subgroup may have limited our ability to detect any difference between schedules. In addition, we were unable to provide concise predictions about the waning later than 5 years after completion of the vaccination schedule. This was because of the lack of data and the absence of strong statistical evidence of the superiority of the main model of waning presented compared with the 2 other models tested.

Second, studies were based on the identification of the dominant serotype in single colonies, and multiple colonization was not taken into account. If the prevalence of multiple colonization is low and if there are no differences in the propensity of detecting 1 serotype over another, VEC estimates based on single colonization would nonetheless adequately capture VEC.15

There are several other factors related to vaccine schedules and delivery that may impact on VEC (and on the heterogeneity between studies), which we were unable to explore, including the timing and spacing of doses and the coadministration of PCV with different childhood vaccines.46 For example, a recent systematic review of the impact of PCV vaccination schedules on immunological responses46 suggests that immune responses to serotype 14 may be influenced by coadministration of PCV with DTP vaccines, with significantly higher geometric mean concentrations observed with acellular pertussis compared with the whole cell pertussis vaccine.

In addition, although the description of the swabbing and sample processing techniques used in the studies included—although sometimes limited—seem to conform to WHO guidelines,50 we cannot rule out that some of the between-study heterogeneity may be because of differences in such techniques.

Finally, further research to obtain more precise estimates of VEC after noncomplete schedules, particularly single catch-up doses, is warranted. This is particularly relevant in the context of PCV roll out in low-income settings, as some countries may opt for catch-up campaigns at the introduction of the vaccine.

In conclusion, through this study, we provide consistent evidence for a lasting efficacy against carriage acquisition of PCV in children during the first few years after completion of vaccination, although with differences in efficacy and duration of protection between serotypes.

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We would like to thank Shabir Madhi, Ron Dagan, Noga Givon-Lavi, Adam Finn and Arto Palmu for providing us with summary data from their studies.

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pneumococcus; conjugate vaccines; efficacy; carriage

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