Long-term Association of 13-Valent Pneumococcal Conjugate Vaccine Implementation With Rates of Community-Acquired Pneumonia in Children

Naïm Ouldali; Corinne Levy; Philippe Minodier; Laurence Morin; Sandra Biscardi; Marie Aurel; François Dubos; Marie Alliette Dommergues; Ellia Mezgueldi; Karine Levieux; Fouad Madhi; Laure Hees; Irina Craiu; Chrystèle Gras Le Guen; Elise Launay; Ferielle Zenkhri; Mathie Lorrot; Yves Gillet; Stéphane Béchet; Isabelle Hau; Alain Martinot; Emmanuelle Varon; François Angoulvant; Robert Cohen

doi:10.1001/jamapediatrics.2018.5273

. 2019 Feb 4;173(4):362–370. doi: 10.1001/jamapediatrics.2018.5273

Long-term Association of 13-Valent Pneumococcal Conjugate Vaccine Implementation With Rates of Community-Acquired Pneumonia in Children

Naïm Ouldali ^1,^2,^3,⁴, Corinne Levy ^1,^2,^5,^6,^✉, Philippe Minodier ^2,⁷, Laurence Morin ^2,⁸, Sandra Biscardi ^2,^5,^6,⁹, Marie Aurel ^2,⁸, François Dubos ^2,¹⁰, Marie Alliette Dommergues ^2,¹¹, Ellia Mezgueldi ^2,¹², Karine Levieux ^2,¹³, Fouad Madhi ^2,^5,¹⁴, Laure Hees ^2,¹⁵, Irina Craiu ^2,¹⁶, Chrystèle Gras Le Guen ^2,¹³, Elise Launay ^2,¹³, Ferielle Zenkhri ^2,¹⁶, Mathie Lorrot ^2,¹⁷, Yves Gillet ^2,¹⁵, Stéphane Béchet ^1,⁵, Isabelle Hau ^2,^5,¹⁴, Alain Martinot ^2,¹⁰, Emmanuelle Varon ^2,¹⁸, François Angoulvant ^2,^3,⁴, Robert Cohen ^1,^2,^5,^6,¹⁹

¹Association Clinique et Thérapeutique Infantile du Val-de-Marne, St Maur-des-Fossés, France

²Groupe de Pathologie Infectieuse Pédiatrique, Paris, France

³Unité d’Épidémiologie Clinique, Assistance Publique–Hôpitaux de Paris, Hôpital Robert Debré, Unité Mixte de Recherche 1123–Epidémiologie Clinique et Évaluation Économique Appliquées aux Populations Vulnérables, Institut National de la Santé et de la Recherche Médicale, Paris, France

⁴Urgences Pédiatriques, Hôpital Necker Enfants Malades, Université Paris Descartes, Paris, France

⁵Université Paris Est, L’Institut Mondor de Recherche Biomédicale Groupement de Recherche Clinique Groupe d'Etude de Maladies Infectieuses Néonatales et Infantiles, Créteil, France

⁶Clinical Research Center, Centre Hospitalier Intercommunal de Créteil, Créteil, France

⁷Department of Pediatric Emergency, Centre Hospitalier Universitaire Nord, Marseille, France

⁸Department of General Pediatrics, Assistance Publique–Hôpitaux de Paris, Hôpital Robert Debré, Université Paris Diderot, Sorbonne Paris Cité, Paris, France

⁹Department of Pediatric Emergency, Hôpital Intercommunal, Créteil, France

¹⁰Pediatric Emergency Unit and Infectious Diseases, Université de Lille, Centre Hospitalier Universitaire Lille, Lille, France

¹¹Department of General Pediatrics, Centre Hospitalier de Versailles, Le Chesnay, France

¹²Pediatric Nephrology, Rheumatology, Dermatology Unit, Femme Mère Enfant Hospital, Hospices Civils de Lyon, University Lyon 1 Lyon, Lyon, France

¹³Department of Pediatrics, Centre Hospitalier Universitaire Nantes, Nantes, France

¹⁴Department of General Pediatrics, Hôpital Intercommunal, Créteil, France

¹⁵Department of Pediatric Emergency, L'Hôpital Femme Mère Enfant Lyon, Lyon, France

¹⁶Department of Pediatric Emergency, Assistance Publique–Hôpitaux de Paris, Hôpital Le Kremlin-Bicêtre, Université Paris, Paris, France

¹⁷Department of General Pediatrics, Assistance Publique–Hôpitaux de Paris, Hôpital Armand Trousseau, Université Sorbonne Paris Cité, Paris, France

¹⁸National Reference Center for Pneumococci, Laboratoire de Microbiologie, Assistance Publique–Hôpitaux de Paris, Hôpital Européen Georges-Pompidou, Paris, France

¹⁹Unité Court Séjour, Petits Nourrissons, Service de Néonatologie, Centre Hospitalier Intercommunal de Créteil, Créteil, France

Accepted for Publication: November 28, 2018.

^✉

Corresponding Author: Corinne Levy, MD, Association Clinique et Thérapeutique Infantile du Val-de-Marne, 27 rue d’Inkermann, 94100 St-Maur-des-Fossés, France (corinne.levy@activ-france.fr).

Published Online: February 4, 2019. doi:10.1001/jamapediatrics.2018.5273

Author Contributions: Dr Levy had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Levy, Morin, Dubos, Levieux, Angoulvant, Cohen.

Acquisition, analysis, or interpretation of data: Ouldali, Levy, Minodier, Biscardi, Aurel, Dubos, Dommergues, Mezgueldi, Levieux, Madhi, Hees, Craiu, Gras Le Guen, Launay, Zenkhri, Lorrot, Gillet, Béchet, Hau, Martinot, Varon, Angoulvant, Cohen.

Drafting of the manuscript: Ouldali, Levy, Levieux, Angoulvant, Cohen.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Ouldali, Levy, Craiu, Béchet, Angoulvant.

Obtained funding: Levy, Hees, Cohen.

Administrative, technical, or material support: Levy, Minodier, Morin, Biscardi, Aurel, Mezgueldi, Madhi, Gras Le Guen, Launay, Zenkhri, Gillet, Béchet, Hau, Martinot, Varon, Angoulvant.

Supervision: Levy, Dubos, Varon, Angoulvant, Cohen.

Conflict of Interest Disclosures: Drs Cohen, Levy, Varon, Angoulvant, and Dommergues report having received personal fees and nonfinancial support from Pfizer, and Drs Gras Le Guen, Lorrot, Zenkhri, Hau, Martinot, Minodier, Biscardi, and Gillet report having received nonfinancial support from Pfizer. Dr Cohen reports having received personal fees from Merck Sharp & Dohme Corporation, GlaxoSmithKline, Sanofi, and AstraZeneca, outside the submitted work. Dr Dubos reports receiving nonfinancial support from Pfizer and GlaxoSmithKline, receiving personal fees from Biocodex, and attending annual meetings paid for by Pfizer with the National Observatory of Pneumonia. Dr Ouldali reports receiving grants from GlaxoSmithKline. Dr Levy reports receiving grants from GlaxoSmithKline, Sanofi Pasteur, Merck, and AstraZeneca and grants, personal fees, and nonfinancial support from Pfizer outside the submitted work. Dr Biscardi reports receiving grants from Pfizer outside the submitted work. Dr Dommergues reported personal fees from Pfizer, nonfinancial support from Pfizer, personal fees from GlaxoSmithKline, personal fees from Merck Sharp & Dohme Corporation, and nonfinancial support from Merck Sharp & Dohme Corporation outside the submitted work. Dr Mezgueldi reports receiving personal fees from Pfizer outside the submitted work. Dr Hau reported grants from Pfizer, nonfinancial support and other support from Novartis, nonfinancial support and other support from Sanofi Pasteur and Merck Sharp & Dohme Corporation, nonfinancial support and other support from Pfizer, and nonfinancial support and other from GlaxoSmithKline during the conduct of the study. Dr Martinot reports receiving personal fees from GlaxoSmithKline outside the submitted work. Dr Varon reports receiving grants from French Public Health Agency during the conduct of the study and grants and personal fees from Pfizer outside the submitted work. Dr Angoulvant reports receiving personal fees from Pfizer during the conduct of the study. Dr Cohen reports receiving grants, personal fees, and nonfinancial support from Pfizer, GlaxoSmithKline, Merck, and Sanofi and grants and personal fees from AstraZeneca outside the submitted work. No other disclosures were reported.

Funding/Support: This work was supported by the Pediatric Infectious Diseases Group of the French Pediatrics Society, Association Clinique et Thérapeutique Infantile du Val-de-Marne, and the Foundation for Medical Research (grant FDM201806006407) and Investigator Initiated Research from Pfizer (grant WS1112279). The National Reference Center for Pneumococci was funded by the French National Health Agency.

Role of the Funder/Sponsor: Pfizer, the Pediatric infectious Disease Group, the Foundation for Medical Research, and the French National Health Agency had no role in the design and conduct of the study, collection management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Association Clinique et Thérapeutique Infantile du Val-de-Marne had input into the design and conduct of the study, collection, management, analysis, and interpretation of the data; preparation, review, approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We are grateful to Michel Boucherat, MD, Association Clinique et Thérapeutique Infantile du Val-de-Marne (ACTIV), who designed the study database; Manuela Fernandes, Isabelle Ramay, and Claire Prieur, License of Science, and Aurore Prieur, ACTIV, and Melissa Azaouaou, License of Science, National Reference Center for Pneumococci, who served as clinical research assistants; Jameel Batah, PhD, National Reference Center for Pneumococci, who contributed to serotyping and microbiologic analysis; Cecile Culeux, License of Science, and Assyia El-Mniai, License of Science, National Reference Center for Pneumococci, who provided technical assistance with serotyping; Nadia Hamouda, License of Science, ACTIV, who provided assistance for serotyping and susceptibility techniques; and Claire Janoir, PhD, National Reference Center for Pneumococci, who provided assistance for microbiologic analysis; and Corinne Alberti, MD, PhD, Unité Mixte de Recherche 1123 Institut National de la Santé et de la Recherche Médicale, who provided help and logistic support. We thank the Foundation for Medical Research for its support. Dr Boucherat and Mss Fernandes, Ramay, C. Prieur, A. Prieur, and Hamouda received compensation from ACTIV. All others were not compensated by funders for their contributions.

^✉

Corresponding author.

PMCID: PMC6450280 PMID: 30715140

Key Points

Question

In a context of the emergence of nonvaccine serotypes, has the long-term protective outcome of 13-valent pneumococcal conjugate vaccine (PCV13) on community-acquired pneumonia in children eroded?

Findings

This time-series analysis of an 8-year prospective multicenter study finds a significant decrease in the frequency of community-acquired pneumonia over 4 years after PCV13 implementation, followed by a slight increase thereafter. The frequency of the most severe cases decreased more markedly, without any rebound.

Meaning

Seven years after PVC13 implementation, the protection against pneumonia seems unthreatened by the increase in nonvaccine serotypes recently reported in several countries.

This time-series analysis of community-acquired pneumonia diagnosed in 8 pediatric emergency departments in France assesses the rate of infection in children 15 years and younger before and after implement of a 13-valent pneumococcal conjugate vaccine.

Abstract

Importance

In several countries, 5 years after 13-valent pneumococcal conjugate vaccine (PCV13) implementation, serotype replacement has been reported for invasive pneumococcal disease, which raises concerns about the long-term outcome of PCV13 implementation. The long-term effect of vaccination on community-acquired pneumonia (CAP) remains unknown.

Objective

To assess the long-term outcome of PCV13 implementation on CAP in children.

Design, Setting, and Participants

This quasi-experimental, population-based, interrupted time-series analysis was based on a prospective multicenter study conducted from June 2009 to May 2017 in 8 French pediatric emergency departments. All patients 15 years and younger with chest radiography–confirmed CAP were included.

Exposures

Community-acquired pneumonia.

Main Outcomes and Measures

The number of CAP cases per 1000 pediatric emergency department visits over time, analyzed using a segmented regression model, adjusted for influenza-like illness syndromes.

Results

We enrolled 12 587 children with CAP, including 673 cases of CAP with pleural effusion (5.3%), 4273 cases of CAP requiring hospitalization (33.9%), 2379 cases of CAP with high inflammatory biomarkers (18.9%), and 221 cases of proven pneumococcal CAP (1.8%). The implementation of PCV13 in 2010 was followed by a sharp decrease in the frequency of CAP (−0.8% per month [95% CI, −1.0% to −0.5% per month]), from 6.3 to 3.5 cases of CAP per 1000 pediatric emergency department visits until May 2014, then a slight increase since June 2014 (0.9% per month [95% CI, 0.4%-1.4% per month]), until 3.8 cases of CAP per 1000 pediatric emergency department visits in May 2017. There were marked immediate decreases in cases of CAP with pleural effusion (−48% [95% CI, −84% to −12%]), CAP requiring hospitalization (−30% [95% CI, −56% to −5%]), and CAP with high inflammatory biomarkers (−30% [95% CI, −54% to −6%]), without any rebound thereafter.

Conclusions and Relevance

The changes associated with PCV13 use 7 years after implementation remain substantial, especially for CAP with pleural effusion, CAP requiring hospitalization, and CAP with high inflammatory biomarkers. Emerging non-PCV13 serotypes may be less likely involved in severe CAP than invasive pneumococcal disease.

Introduction

Worldwide, pneumonia is a major cause of childhood morbidity and mortality. A 2015 report found that children younger than 5 years experienced more than 100 million cases each year, and it was the leading cause of death (700 000 deaths each year), particularly in low-income countries.^1,2 In high-income countries, it is also one of the leading causes of hospitalization in children.³ Community-acquired pneumonia (CAP) is considered to be most frequently caused by pneumococci,^1,4 and Streptococcus pneumoniae is a leading cause of death from pneumonia² in both adults and children.

Before the implementation of pneumococcal conjugate vaccines (PCVs), a few pneumococcal serotypes (mainly serotypes 1, 3, 5, 7F, 14, and 19A) were implicated in proven pneumococcal pneumonia and empyema in children.^5,6,7,8 The implementation of PCV7 led to a transient reduction in the frequency of CAP,^9,10 rapidly followed by an increase in that of CAP with pleural effusion and empyema,^6,11 mainly owing to serotypes 1 and 7F, and an increase in frequency of serotype 19A.⁶ When PCV13, which included these additional serotypes, replaced PCV7, the frequency of both CAP and empyema greatly decreased worldwide.¹²

Up to 4 years after PCV13 implementation, the frequency of invasive pneumococcal disease was strongly reduced worldwide.¹³ However, with a recent increase in its frequency owing to highly invasive non-PCV13 serotypes in England,¹⁴ Germany,¹⁵ and Israel^16,17 and in pneumococcal meningitis in France,¹⁸ the serotype replacement has raised concerns about the long-term outcome of PCV13 use beyond 5 years after its implementation. However, recent trends observed in invasive pneumococcal disease cannot be extrapolated to CAP.^19,20

To date, to our knowledge, the association of PCV13 with pneumococcal CAP rates more than 5 years after its implementation remains unknown. We used a time-series analysis of data for children visiting pediatric emergency departments (PEDs) to assess the long-term outcome of PCV13 use on CAP evolution.

Methods

We conducted a quasi-experimental, population-based, interrupted time-series analysis using a multicenter prospective study over 8 years. The data collection was approved by the French National Data Protection Commission. The Robert Debré Hospital ethics committee also approved the study. French legislation does not require any informed consent for this type of study; a mandatory information form validated by the ethics committee was given to all participants.

Study Data and Setting

This prospective, multicenter study was conducted specifically to survey CAP in 8 French PEDs, which were asked to report all cases of CAP from June 2009 to May 2017. The 8 participating hospitals were located in large cities throughout France. We also cross-checked our database with the French hospital system’s medicoadministrative database (Programme de Medicalisation des Systems d’Information) to ensure that no case of hospitalized CAP was missed in our data collection.

All pediatric patients in the PEDs who were ages 1 month to 15 years and had chest radiography–confirmed CAP were included. As previously published,^5,21 CAP was defined by the association of fever with chest radiography showing consolidation with or without pleural effusion, diagnosed by a pediatrician and confirmed by a pediatric radiologist. Data collected included clinical characteristics (ie, age, sex, vaccination status, comorbidities), presence of pleural effusion, biological results (including C-reactive protein and/or procalcitonin level, if tested), microbiology samples, hospital admission and/or discharge status, and short-term outcomes.

Microbiology Study

Proven pneumococcal CAP (PP-CAP) was defined by at least 1 of the following 3 conditions: (1) blood or pleural culture positive for S pneumoniae, (2) polymerase chain reaction–positive results for pneumococci on a pleural sample, or (3) pneumococcal antigen test (Binax; Abbott) positivity on a pleural sample. Isolates were serotyped at the National Pneumococcal Reference Center by the capsular swelling method with commercial antisera (Statens Serum Institut). Details of microbiology analyses were previously published.⁵ Nasopharyngeal wash specimens were obtained for viral testing. The diagnostic process for viral detection was direct immunofluorescence assay and/or polymerase chain reaction for respiratory syncytial virus, influenza A and B, parainfluenza virus, and adenovirus.²²

Intervention

In June 2010, PCV7 vaccination was replaced by PCV13 vaccination for all infants younger than 2 years, without a catchup program. The current French schedule involves doses at ages 2 months, 4 months, and 12 months, for a total of 3 doses. The coverage with PCV13 was 91.7% among infants aged 9 months in 2011 and remained at levels greater than 91% thereafter. Vaccine coverage was provided by the national public health institute Santé Publique France.²³ Three periods of PCV13 implementation in France were defined: the pre-PCV13 period, from June 2009 to May 2010 (before PCV13 vaccination); the early PCV13 period, from June 2011 to May 2014 (during general PCV13 vaccination⁵); and the late PCV13 period, from June 2014 to May 2017.

Outcome Measure

The main outcome was the number of CAP cases in children 15 years and younger, per 1000 PED visits. We chose this outcome to take into account the constant increase in total PED visits over time in France. (The evolution of total PED visits in the 8 participating centers is provided in eFigure 1 in the Supplement.) The secondary outcomes were the number of cases of CAP with pleural effusion per 1000 PED visits, the number of cases of CAP with high inflammatory biomarkers (defined as C-reactive protein levels >100 mg/L [to convert to nmol/L, multiply by 9.524] and/or procalcitonin level >4 ng/mL²¹) per 1000 PED visits, and the number of cases of CAP requiring hospitalization per 1000 PED visits. We also analyzed the number of CAP cases by age group, the number of PP-CAP cases, the serotype distribution, and the rate of virus detection among CAP cases over time.

Control Outcome

Because this study was specifically conducted to analyze CAP, no other pathology was recorded with the same methodology, to provide a control outcome. However, to assess the data quality over time, we analyzed the rate of inflammatory biomarker testing and the rate of virus testing of patients with CAP over time to ensure that changes observed were not because of a change in biologic testing rate.⁵

Statistical Analysis

The outcomes were analyzed by segmented linear regression with autoregressive error.²⁴ The time unit chosen was 1 month, to provide optimal precision for the model.²⁵ Data from the 8 PEDs were aggregated and analyzed together. Because of the overlap between PCV7 and PCV13 implementation during 2010, we defined a 1-year transition period during PCV13 implementation, as previously described.^5,9 We did not define a transition period between the early PCV13 period and late PCV13 period, because neither changes in PCV implementation nor changes in recommendations or regulations occurred. A sensitivity analysis not excluding the transitional period was also performed. All outcomes were adjusted on a national monthly number of influenza-like illness syndromes over time, to take into account influenza epidemics. Data for this adjustment were provided by the French Sentinelle Network.²⁶

The segmented linear regression with an autoregressive error model took into account autocorrelation, seasonality, and trends before and after PCV13 implementation.^24,25,27,28 Seasonality was taken into account using an additive model. The intervention assessment was performed by including 2 dummy variables in the model for each period (early PCV13 and late PCV13), estimating the immediate change after the intervention and the postintervention trend.^25,27 Thus, the segmented regression model allowed the estimation of each of the immediate changes or trends between periods. In case of CAP number rebound, we determined the knot of CAP increase by using the Akaike information criterion and the maximum likelihood ratio to select the model that provided the best fit.²⁹

All statistical tests were 2-sided, with P < .05 considered statistically significant. The validity of the segmented regression model was assessed by visual inspection of correlograms and residuals analysis. All statistical analyses involved using R version 3.4.3 (R Foundation for Statistical Computing).

Results

Population and CAP Number per 1000 PED Visits

From 2009 to 2017, among a dataset of 2 756 986 PED visits, we included 12 587 cases of confirmed CAP, including 673 cases of CAP with pleural effusion (5.3%), 4273 cases of CAP requiring hospitalization (33.9%), 2379 cases of CAP with high inflammatory biomarkers (18.9%), and 221 cases of PP-CAP (1.8%) (Table 1). Before PCV13 implementation, the mean CAP cases per 1000 PED visits estimated by the time-series model was 6.3 cases per month, with a trend of decreasing rates (Figure 1). The implementation of PCV13 was followed by a persistent and significant decrease in CAP cases during the first 3 years (early PCV13 period, −0.8% [95% CI, −1.0% to −0.5%] per month), with a cumulative 44% decrease (95% CI, −56% to −32%) until May 2014 (from 6.3 to 3.5 cases of CAP per 1000 PED visits). Then, we observed a slight but significant increase per 1000 PED visits during the final 3 years of the study (late PCV13 period, 0.9% [95% CI, 0.4%-1.4%] per month), until 3.8 cases of CAP per 1000 PED visits in May 2017. The model with a knot at June 2014 provided the best fit. Correlograms and residuals analysis indicated a satisfactory quality of the final model (eFigure 2 in the Supplement).

Table 1. General Characteristics of Cases of Community-Acquired Pneumonia in Children 15 Years and Younger Pre-PCV13 and Post–Vaccine Implementation (2009-2017).

Characteristic	Patients, No. (%)
Characteristic	Pre-PCV13 Period (June 2009-May 2010)	Early PCV13 Period (June 2011-May 2014)	Late PCV13 Period (June 2014-May 2017)	All Study Periods, Including Transition (June 2009-May 2017)
Total cases	2051 (16.3)	4258 (33.8)	4443 (35.3)	12 587 (100)
Age, mean (IQR), y	2.8 (1.4-4.6)	3.1 (1.4-5.0)	2.8 (1.4-5.0)	3.0 (1.4-5.0)
Age groups, y
<2.0	765 (37.3)	1517 (35.6)	1674 (37.7)	4600 (36.5)
2.0-4.9	834 (40.7)	1692 (39.7)	1643 (37.0)	4880 (38.8)
5.0-15.9	452 (22.0)	1049 (24.6)	1126 (25.3)	3107 (24.7)
Sex ratio, male:female	1.2	1.1	1.1	1.1
Pleural effusion	172 (8.4)	175 (4.1)	207 (4.7)	673 (5.3)
C-reactive protein and/or procalcitonin tested, No.	971 (47.3)	2054 (48.2)	2390 (53.8)	6235 (49.5)
C-reactive protein level, median (IQR), mg/L	86 (29-210)	59 (22-144)	56 (23-122)	61 (24-151)
Procalcitonin level, median (IQR), ng/mL	2.0 (0.4-9.2)	0.7 (0.2-4.1)	0.8 (0.2-4.0)	0.9 (0.3-5.1)
Hospitalization	750 (36.6)	1455 (34.2)	1477 (33.2)	4273 (33.9)

Open in a new tab

Abbreviations: CAP, community-acquired pneumonia; IQR, interquartile range; PCV13, 13-valent pneumococcal conjugate vaccine.

SI conversion factor: To convert C-reactive protein to nmol/L, multiply by 9.524.

Figure 1. — N = 12 587 children with cases of community-acquired pneumonia. The bold slope lines were estimated by the segmented regression model. The orange shading shows the 95% CIs estimated by the segmented regression model. The pre-PCV13 period was June 2009 through May 2010; the early PCV13 period, June 2011 through May 2014; and the late PCV13 period, June 2014 through May 2017. The vertical blue lines show the transition period of PCV13 implementation (June 2010–May 2011). The vertical arrow shows the knot of slope change in June 2014.

Sensitivity Analysis

The segmented regression analysis including the 1-year transition period showed similar results, with a significant decrease in CAP cases per 1000 PED visits during the first 3 years after PCV13 implementation (early PCV13 period, −0.8% [95% CI, −1.0% to −0.6%] per month). This was followed by a slight increase per 1000 PED visits in the late PCV13 period (0.9% [95% CI, 0.4%-1.3%] per month; Table 2).

Table 2. Association of Vaccine Implementation With Community-Associated Pneumonia Rates in Children 15 Years and Younger.

Outcome	% Change per 1000 Pediatric Emergency Room Visits (95% CI)
Outcome	Early PCV13 Period (June 2011-May 2014)	Late PCV13 Period (June 2014-May 2017)
Cases, No. (%)	4258 (34)	4443 (35)
Total CAP cases^a
Overall change	−44.3 (−56.1 to −31.7)	6.7 (2.8-10.2)
Trend^b	−0.8 (−1.0 to −0.5)	0.9 (0.4-1.4)
Segmented regression without transition period, trend^a^,^b	−0.8 (−1.0 to −0.6)	0.9 (0.4-1.3)
Trend by age groups, y^a^,^b
<2.0	−0.8 (−1.0 to −0.5)	0.8 (0.3-1.4)
2.0-4.9	−0.8 (−1.1 to −0.4)	0.8 (0.4-1.6)
5.0-15.9	−0.7 (−1.1 to −0.3)	0.9 (0.0-1.8)
Change in CAP cases with pleural effusion^a
Overall	−47.6 (−83.5 to −11.9)	5.8 (−6.0 to 17.6)
Trend^b	NA	0.7 (−0.7 to 2.0)
Immediate^c	−47.6 (−83.5 to −11.9)	NA
Change in CAP cases requiring hospitalization^a
Overall	−30.2 (−56.0 to −4.8)	−8.2 (−39.2 to 22.9)
Trend^b	NA	−0.2 (−1.2 to 0.7)
Immediate^c	−30.2 (−56.0 to −4.8)	NA
Change in CAP cases with high inflammatory biomarkers^a^,^d
Overall	−30.2 (−54.2 to −6.2)	3.1 (−2.0 to 6.1)
Trend^b	NA	0.5 (−0.4 to 1.4)
Immediate^c	−30.2 (−54.2 to −6.2)	NA
Change in proven pneumococcal CAP cases^a
Overall	−54.3 (−97.4 to −11.2)	6.0 (−52.7 to 64.8)
Trend^b	NA	0.2 (−1.5 to 1.8)
Immediate^c	−54.3 (−97.4 to −11.2)	NA
Trend in rate of virus detection in CAP^a	1.4 (0.3-2.6)	0.5 (−3.8 to 5.0)
Trend in testing
Proportion of inflammatory biomarker testing among all CAP cases^a^,^d	0.2 (−1.6 to 1.9)	0.0 (−0.6 to 0.6)
Proportion of virus testing among all CAP cases^a^,^d	−0.1 (−0.7 to 0.5)	0.1 (−1.4 to 1.6)

Open in a new tab

Abbreviations: CAP, community acquired pneumonia; NA, not applicable; PCV13, 13-valent pneumococcal conjugate vaccine.

SI conversion factor: To convert C-reactive protein to nmol/L, multiply by 9.524.

^{^a}

Sensitivity analysis; analysis by segmented regression with autoregressive error.

^{^b}

A trend is the progressive monthly change in the slope of the outcomes after implementation of PCV13.

^{^c}

Immediate change is a change within 1 month in outcomes after implementation of PCV13.

^{^d}

Inflammatory biomarkers: C-reactive protein level greater than 100 mg/L and/or procalcitonin level greater than 4 ng/mL.

CAP With Pleural Effusion

The implementation of PCV13 was followed by a marked immediate decrease in cases of CAP with pleural effusion per 1000 PED visits in the early PCV13 period (−48% [95% CI, −84% to −12%]; Figure 2A). We did not observe any significant trend in the final 3 years (0.7% [95% CI, −0.7% to 2.0%] per month; Figure 2A; Table 2).

Figure 2. — A, CAP with pleural effusion (n = 673). B, CAP requiring hospitalization (n = 4273); C, CAP with high inflammatory biomarkers (n = 2379); D, Proven pneumococcal CAP (n = 221). The bold slope lines were estimated by the segmented regression model. The orange shading shows the 95% CIs estimated by the segmented regression model. The vertical blue broken lines show the transition period of PCV13 implementation (June 2010-May 2011). The vertical arrow shows the knot of slope change in June 2014.

CAP Requiring Hospitalization

The implementation of PCV13 was followed by a sharp immediate decrease in cases of CAP requiring hospitalization per 1000 PED visits in the early PCV13 period (−30% [95% CI, −56% to −5%]; Figure 2B). We did not observe any change in the final 3 years (−0.2% per month [95% CI, −1.2% to 0.7%]; Figure 2B; Table 2).

CAP With High Inflammatory Biomarkers

The implementation of PCV13 was followed by a strong immediate decrease in the number of CAP cases with high inflammatory biomarkers per 1000 PED visits in the early PCV13 period (−30% [95% CI, −54% to −6%]; Figure 2C). We did not observe any change in the final 3 years (0.5% [95% CI, −0.4% to 1.4%] per month; Figure 2C; Table 2).

Proven Pneumococcal CAP Cases

The implementation of PCV13 was followed by a significant immediate decrease in PP-CAP cases per 1000 PED visits in the early PCV13 period (−54% [95% CI, −97% to −11%]; P = .01; Figure 2D). We did not observe any change in trend in the final 3 years (0.2% [95% CI, −1.5% to 1.8%] per month; Figure 2D; Table 2).

CAP Cases by Age Group

The number of CAP cases followed the same pattern in the 3 age groups (<2.0 years, 2.0 to 4.9 years, and 5.0 to 15.9 years). The use of PCV13 was followed by a sustained significant decrease in CAP cases per 1000 PED visits in the early PCV13 period (patients younger than 2.0 years, −0.8% [95% CI, −1.0% to −0.5%] per month; patients 2.0 to 4.9 years old, −0.8% [95% CI, −1.1% to −0.4%] per month; patients 5.0 to 15.9 years old, −0.7% [95% CI, −1.1% to −0.3%] per month) and a significant but slight increase from June 2014 to May 2017 (patients younger than 2.0 years, 0.8% [95% CI, 0.3%-1.4%] per month; patients 2.0 to 4.9 years old, 0.8% [95% CI, 0.4%-1.6%] per month; patients 5.0 to 15.9 years old, 0.9% [95% CI, 0.0%-1.8%] per month; Figure 3; Table 2).

Figure 3. — A, Children younger than 2.0 years (n = 4600). B, Children 2.0 to 4.9 years old (n = 4880); C, Children 5.0 to 15.9 years old (n = 3107). The bold slope lines were estimated by the segmented regression model. The orange shading shows the 95% CIs estimated by the segmented regression model. The vertical blue lines show the transition period of PCV13 implementation (June 2010-May 2011). The vertical arrow shows the knot of slope change in June 2014.

Serotype Evolution

In the pre-PCV13 period, serotypes 1, 3, 7F, and 19A were predominant, accounting for 38 of the 45 cases (84%) of documented CAP with a serotype identified. These serotypes accounted for 23 of 34 cases (68%) in the early PCV13 period and 3 of 13 case (23%) in the late PCV13 period. Serotype 1 accounted for 32 of 69 cases (46%) between 2009 and 2012 and only 4 of 23 cases (17%) after 2013. After PCV13 implementation, 11 different non-PCV13 serotypes were isolated; none were isolated in more than 4 cases (eTable in the Supplement).

Virus Detection

During the study period, we observed a significant steady increase in rate of virus detection among CAP cases (1.4% [95% CI, 0.3%-2.6%] per month; eFigure 3 in the Supplement). These mainly involved respiratory syncytial virus (446 of 904 viruses [48%] identified).

Control Outcomes

The proportion of virus testing among all CAP cases did not significantly change over the study period (after PCV13 implementation, −0.1% [95% CI, −0.7% to 0.5%] per month; eFigure 4 in the Supplement). Neither did the proportion of inflammatory biomarker testing after PCV13 implementation (0.2% [95% CI, 1.6% to 1.9%] per month; eFigure 4 in the Supplement).

Discussion

This 8-year population-based multicenter prospective study is, to our knowledge, the first to provide data about the long-term association of PCV13 implementation with the frequency of CAP in children more than 5 years after its implementation, with the robust design of a time-series analysis. This study confirmed the association of PCV13 implementation with a decrease in pediatric CAP, with a sharp decline per 1000 PED visits (−44% [95% CI, −56% to −32%]) between June 2010 and May 2014. In the late PCV13 period (June 2014 to May 2017), the number of CAP cases per 1000 PED visits remained far below the pre-PCV13 level, despite a slight but significant increase (0.9% per month; P < .001). In contrast, the late PCV13 period showed no rebound in the frequency of CAP with pleural effusion, CAP requiring hospitalization, CAP with high inflammatory biomarkers, or PP-CAP, which all remained stable at low levels. These results contrast with the recent increase in frequency of invasive pneumococcal disease observed in several countries during the same period^14,15,18 linked to serotype replacement beyond 5 years after PCV13 implementation.^14,15,18

This difference in the trends suggests different consequences of serotype replacement on pneumococcal CAP vs invasive pneumococcal disease.^19,20 Moreover, no dominant serotype seems to have emerged, because after PCV13 implementation, none of the 11 non-PCV13 serotypes isolated in CAP were involved in more than 4 cases. The recent slight increase in the number of all CAP cases and virus involvement may reflect changes in the epidemiology of other pathogens and/or serotype replacement with less pathogenic serotypes.

These findings should be put in perspective with recent findings from Greenberg et al,²² who found that during CAP, the most invasive S pneumoniae serotypes, such as 1 and 7F, were carried in nasopharyngeal flora more frequently when no viral coinfection was detected. In contrast, in patients with viral coinfection, carriage rates of the less invasive serotypes (namely, serotypes 33F, 17F, 15 B/C, and 35B) tended to be more frequent. The authors²² speculated that less invasive serotypes do not typically cause disease unless a virus is present, whereas more invasive pneumonia serotypes may be sufficiently virulent to cause disease without a preceding or concomitant viral infection. The implementation of PCV13 has led to the quasi-disappearance of the more invasive serotypes and increase in others in nasopharyngeal flora,³⁰ which greatly reduces the frequency of the more severe forms of CAP, but could also play a role in the slight increase in frequency of the more benign forms.

A recent systematic review found a global reduction of 31% in CAP cases in children younger than 2 years¹² at 4 years after PCV13 or PCV10 implementation. Six of the 12 studies included in this meta-analysis¹² used the robust design of a time-series analysis, and 5 were based on administrative databases. The most recent data provided were collected in 2014.¹² Several recent studies showed that the early association of PCV13 implementation with rates of pneumonia in children was stronger for CAP with pleural effusion or empyema,^31,32 which agreed with our results. This finding also highlights that the early outcome of PCV13 implementation was stronger with severe pneumonia, which frequently involved the most invasive pneumococcal strains.¹

The strength of the study was to provide data from a multicenter population-based prospective study with the same methodology over 8 years, which allowed for the use of the robust design of time series.²⁷ This study was specifically conducted to analyze the evolution of CAP over time, thereby avoiding the risks of bias affecting studies based on administrative database recording.¹² The 8 participating PEDs accounted for 9% of all PED annual visits in France.⁵ Considering the high number of patients enrolled and the inclusion of both secondary and tertiary PED centers, these data may reflect features of CAP in all French PEDs. Finally, our results appear to be robust and consistent regarding the recent slight increase in global CAP cases in all age groups, the sustaining long-term outcomes of PCV13 implementation on all of the most severe forms of CAP, and the increasing role of viral coinfections.

Limitations

Our study has several limitations. First, the rate of positive blood cultures (4.0%)²¹ did not allow for revealing a high proportion of PP-CAP cases. However, a recent large cohort from the United States reported a 2.5% rate of positive blood culture in pediatric CAP,³³ which is consistent with our data. We did not use molecular-based methods for the diagnosis of pneumococcal invasive disease in blood, given their low specificity in children, even if they seem promising.³⁴ However, our diagnostic process for microbiologic detection did not change over the study period, which enhances the robustness of our findings.

Second, given the lack of a control group, we cannot rule out a change in case reporting. However, the analysis of 2 control outcomes reduced the risk of bias owing to any change in biologic testing rate or microbiologic process over time.^35,36 Moreover, an increased reporting of mild CAP cases and decreased or stable reporting of severe CAP seems unlikely. Furthermore, participating physicians were encouraged to not change their practice, including test use, and no other potential interfering intervention.

Third, the pre-PCV13 period only included the year 2009 to 2010. However, our findings in the early PCV13 period were in line with previous studies assessing the evolution of CAP at 4 years after PCV13 implementation,¹² which attests to the quality and validity of our data and argues for the accuracy of our pre-PCV13 CAP rate.

Conclusions

Despite a slight increase in the overall frequency of CAP cases seen in PEDs since June 2014, 7 years after PCV13 implementation, the association of PCV13 with decreased rates of CAP remains substantial. For the most severe CAP cases (CAP with pleural effusion, CAP requiring hospitalization, and PP-CAP), for which the most invasive pneumococcal serotypes are often implicated, the early substantial decrease was sustained in the later period. The recent reports in several countries of an increase in invasive pneumococcal disease frequency seem not to substantially threaten the long-term benefit of PCV13 implementation on CAP rates. The increasing role of CAP with viral detection suggests an increase in frequency of CAP with viral involvement.

Supplement.

eFigure 1. Evolution of total PED visits in the eight participating centers over the study period, June 2009 to May 2017.

eFigure 2. Correlograms and residuals analysis of the final segmented regression model for monthly number of children with CAP under 15 years of age per 1,000 PED visits.

eFigure 3. Evolution of virus detection among all CAP cases over the study period, June 2009 to May 2017.

eFigure 4. Control outcomes.

eTable. Evolution of pneumococcal serotypes isolated over the study period, June 2009 to May 2017.

Click here for additional data file.^{(261.5KB, pdf)}

References

1.Walker CLF, Rudan I, Liu L, et al. Global burden of childhood pneumonia and diarrhoea. Lancet. 2013;381(9875):1405-1416. doi: 10.1016/S0140-6736(13)60222-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
2.GBD 2015 LRI Collaborators Estimates of the global, regional, and national morbidity, mortality, and aetiologies of lower respiratory tract infections in 195 countries: a systematic analysis for the Global Burden of Disease Study 2015. Lancet Infect Dis. 2017;17(11):1133-1161. doi: 10.1016/S1473-3099(17)30396-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Jain S, Williams DJ, Arnold SR, et al. ; CDC EPIC Study Team . Community-acquired pneumonia requiring hospitalization among U.S. children. N Engl J Med. 2015;372(9):835-845. doi: 10.1056/NEJMoa1405870 [DOI] [PMC free article] [PubMed] [Google Scholar]
4.O’Brien KL, Wolfson LJ, Watt JP, et al. ; Hib and Pneumococcal Global Burden of Disease Study Team . Burden of disease caused by Streptococcus pneumoniae in children younger than 5 years: global estimates. Lancet. 2009;374(9693):893-902. doi: 10.1016/S0140-6736(09)61204-6 [DOI] [PubMed] [Google Scholar]
5.Angoulvant F, Levy C, Grimprel E, et al. Early impact of 13-valent pneumococcal conjugate vaccine on community-acquired pneumonia in children. Clin Infect Dis. 2014;58(7):918-924. doi: 10.1093/cid/ciu006 [DOI] [PubMed] [Google Scholar]
6.Byington CL, Korgenski K, Daly J, Ampofo K, Pavia A, Mason EO. Impact of the pneumococcal conjugate vaccine on pneumococcal parapneumonic empyema. Pediatr Infect Dis J. 2006;25(3):250-254. doi: 10.1097/01.inf.0000202137.37642.ab [DOI] [PubMed] [Google Scholar]
7.Byington CL, Spencer LY, Johnson TA, et al. An epidemiological investigation of a sustained high rate of pediatric parapneumonic empyema: risk factors and microbiological associations. Clin Infect Dis. 2002;34(4):434-440. doi: 10.1086/338460 [DOI] [PubMed] [Google Scholar]
8.Hortal M, Estevan M, Meny M, Iraola I, Laurani H. Impact of pneumococcal conjugate vaccines on the incidence of pneumonia in hospitalized children after five years of its introduction in Uruguay. PLoS One. 2014;9(6):e98567. doi: 10.1371/journal.pone.0098567 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Grijalva CG, Nuorti JP, Arbogast PG, Martin SW, Edwards KM, Griffin MR. Decline in pneumonia admissions after routine childhood immunisation with pneumococcal conjugate vaccine in the USA: a time-series analysis. Lancet. 2007;369(9568):1179-1186. doi: 10.1016/S0140-6736(07)60564-9 [DOI] [PubMed] [Google Scholar]
10.Fitzwater SP, Chandran A, Santosham M, Johnson HL. The worldwide impact of the seven-valent pneumococcal conjugate vaccine. Pediatr Infect Dis J. 2012;31(5):501-508. doi: 10.1097/INF.0b013e31824de9f6 [DOI] [PubMed] [Google Scholar]
11.Grijalva CG, Nuorti JP, Zhu Y, Griffin MR. Increasing incidence of empyema complicating childhood community-acquired pneumonia in the United States. Clin Infect Dis. 2010;50(6):805-813. doi: 10.1086/650573 [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Alicino C, Paganino C, Orsi A, et al. The impact of 10-valent and 13-valent pneumococcal conjugate vaccines on hospitalization for pneumonia in children: a systematic review and meta-analysis. Vaccine. 2017;35(43):5776-5785. doi: 10.1016/j.vaccine.2017.09.005 [DOI] [PubMed] [Google Scholar]
13.Cohen R, Cohen JF, Chalumeau M, Levy C. Impact of pneumococcal conjugate vaccines for children in high- and non-high-income countries. Expert Rev Vaccines. 2017;16(6):625-640. doi: 10.1080/14760584.2017.1320221 [DOI] [PubMed] [Google Scholar]
14.Ladhani SN, Collins S, Djennad A, et al. Rapid increase in non-vaccine serotypes causing invasive pneumococcal disease in England and Wales, 2000-17: a prospective national observational cohort study. Lancet Infect Dis. 2018;18(4):441-451. doi: 10.1016/S1473-3099(18)30052-5 [DOI] [PubMed] [Google Scholar]
15.Weinberger R, von Kries R, van der Linden M, Rieck T, Siedler A, Falkenhorst G. Invasive pneumococcal disease in children under 16 years of age: incomplete rebound in incidence after the maximum effect of PCV13 in 2012/13 in Germany. Vaccine. 2018;36(4):572-577. doi: 10.1016/j.vaccine.2017.11.085 [DOI] [PubMed] [Google Scholar]
16.Dagan R, Ben-Shimol S, Benisty R, et al. A nationwide outbreak of invasive pneumococcal disease (IPD) caused by Streptococcus pneumoniae serotype 2 (Sp2) in the PCV13 era in Israel: abstract 039. 11th International Symposium on Pneumococci Pneumococcal Disease; Melbourne, Australia; April 16, 2018. [Google Scholar]
17.Rokney A, Ben-Shimol S, Korenman Z, et al. Emergence of Streptococcus pneumoniae serotype 12F after sequential introduction of 7- and 13-valent vaccines, Israel. Emerg Infect Dis. 2018;24(3):453-461. doi: 10.3201/eid2403.170769 [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Ouldali N, Levy C, Varon E, et al. ; French Pediatric Meningitis Network . Incidence of paediatric pneumococcal meningitis and emergence of new serotypes: a time-series analysis of a 16-year French national survey. Lancet Infect Dis. 2018;18(9):983-991. doi: 10.1016/S1473-3099(18)30349-9 [DOI] [PubMed] [Google Scholar]
19.Ben-Shimol S, Givon-Lavi N, Grisaru-Soen G, Megged O, Greenberg D, Dagan R; Israel Bacteremia and Meningitis Active Surveillance Group . Comparative incidence dynamics and serotypes of meningitis, bacteremic pneumonia and other-IPD in young children in the PCV era: insights from Israeli surveillance studies. Vaccine. 2018;36(36):5477-5484. doi: 10.1016/j.vaccine.2017.05.059 [DOI] [PubMed] [Google Scholar]
20.Ben-Shimol S, Greenberg D, Hazan G, et al. ; Israeli Bacteremia and Meningitis Active Surveillance Group . Differential impact of pneumococcal conjugate vaccines on bacteremic pneumonia versus other invasive pneumococcal disease. Pediatr Infect Dis J. 2015;34(4):409-416. doi: 10.1097/INF.0000000000000604 [DOI] [PubMed] [Google Scholar]
21.Levy C, Biscardi S, Dommergues MA, et al. ; Pneumonia study group . Impact of PCV13 on community-acquired pneumonia by C-reactive protein and procalcitonin levels in children. Vaccine. 2017;35(37):5058-5064. doi: 10.1016/j.vaccine.2017.06.057 [DOI] [PubMed] [Google Scholar]
22.Greenberg D, Givon-Lavi N, Faingelernt Y, et al. Nasopharyngeal pneumococcal carriage during childhood community-acquired alveolar pneumonia: relationship between specific serotypes and coinfecting viruses. J Infect Dis. 2017;215(7):1111-1116. doi: 10.1093/infdis/jiw613 [DOI] [PubMed] [Google Scholar]
23.Santé Publique France Couverture vaccinale du vaccin pneumococcique conjugué. http://invs.santepubliquefrance.fr/Dossiers-thematiques/Maladies-infectieuses/Maladies-a-prevention-vaccinale/Couverture-vaccinale/Donnees/Pneumocoque. Published April 18, 2018. Accessed July 1, 2018.
24.Jandoc R, Burden AM, Mamdani M, Lévesque LE, Cadarette SM. Interrupted time series analysis in drug utilization research is increasing: systematic review and recommendations. J Clin Epidemiol. 2015;68(8):950-956. doi: 10.1016/j.jclinepi.2014.12.018 [DOI] [PubMed] [Google Scholar]
25.Wagner AK, Soumerai SB, Zhang F, Ross-Degnan D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther. 2002;27(4):299-309. doi: 10.1046/j.1365-2710.2002.00430.x [DOI] [PubMed] [Google Scholar]
26.France Sentinelle Network France métropolitaine. https://websenti.u707.jussieu.fr/sentiweb/?site=fr. Published 2018. Accessed December 19, 2018.
27.Kontopantelis E, Doran T, Springate DA, Buchan I, Reeves D. Regression based quasi-experimental approach when randomisation is not an option: interrupted time series analysis. BMJ. 2015;350:h2750. doi: 10.1136/bmj.h2750 [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Simonsen L, Taylor RJ, Schuck-Paim C, Lustig R, Haber M, Klugman KP. Effect of 13-valent pneumococcal conjugate vaccine on admissions to hospital 2 years after its introduction in the USA: a time series analysis. Lancet Respir Med. 2014;2(5):387-394. doi: 10.1016/S2213-2600(14)70032-3 [DOI] [PubMed] [Google Scholar]
29.Watier L. A methodological review of specific techniques of time series analysis in epidemiology and public health [in French]. Rev Epidemiol Sante Publique. 1995;43(2):162-172. [PubMed] [Google Scholar]
30.Kaur R, Casey JR, Pichichero ME. Emerging Streptococcus pneumoniae strains colonizing the nasopharynx in children after 13-valent pneumococcal conjugate vaccination in comparison to the 7-valent era, 2006-2015. Pediatr Infect Dis J. 2016;35(8):901-906. doi: 10.1097/INF.0000000000001206 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Saxena S, Atchison C, Cecil E, Sharland M, Koshy E, Bottle A. Additive impact of pneumococcal conjugate vaccines on pneumonia and empyema hospital admissions in England. J Infect. 2015;71(4):428-436. doi: 10.1016/j.jinf.2015.06.011 [DOI] [PubMed] [Google Scholar]
32.Wiese AD, Griffin MR, Zhu Y, Mitchel EF Jr, Grijalva CG. Changes in empyema among U.S. children in the pneumococcal conjugate vaccine era. Vaccine. 2016;34(50):6243-6249. doi: 10.1016/j.vaccine.2016.10.062 [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Neuman MI, Hall M, Lipsett SC, et al. ; Pediatric Research in Inpatient Settings Network . Utility of blood culture among children hospitalized with community-acquired pneumonia. Pediatrics. 2017;140(3):e20171013. doi: 10.1542/peds.2017-1013 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Avni T, Mansur N, Leibovici L, Paul M. PCR using blood for diagnosis of invasive pneumococcal disease: systematic review and meta-analysis. J Clin Microbiol. 2010;48(2):489-496. doi: 10.1128/JCM.01636-09 [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Shardell M, Harris AD, El-Kamary SS, Furuno JP, Miller RR, Perencevich EN. Statistical analysis and application of quasi experiments to antimicrobial resistance intervention studies. Clin Infect Dis. 2007;45(7):901-907. doi: 10.1086/521255 [DOI] [PubMed] [Google Scholar]
36.Penfold RB, Zhang F. Use of interrupted time series analysis in evaluating health care quality improvements. Acad Pediatr. 2013;13(6)(Suppl):S38-S44. doi: 10.1016/j.acap.2013.08.002 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

eFigure 1. Evolution of total PED visits in the eight participating centers over the study period, June 2009 to May 2017.

eFigure 2. Correlograms and residuals analysis of the final segmented regression model for monthly number of children with CAP under 15 years of age per 1,000 PED visits.

eFigure 3. Evolution of virus detection among all CAP cases over the study period, June 2009 to May 2017.

eFigure 4. Control outcomes.

eTable. Evolution of pneumococcal serotypes isolated over the study period, June 2009 to May 2017.

Click here for additional data file.^{(261.5KB, pdf)}

[poi180094r1] 1.Walker CLF, Rudan I, Liu L, et al. Global burden of childhood pneumonia and diarrhoea. Lancet. 2013;381(9875):1405-1416. doi: 10.1016/S0140-6736(13)60222-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180094r2] 2.GBD 2015 LRI Collaborators Estimates of the global, regional, and national morbidity, mortality, and aetiologies of lower respiratory tract infections in 195 countries: a systematic analysis for the Global Burden of Disease Study 2015. Lancet Infect Dis. 2017;17(11):1133-1161. doi: 10.1016/S1473-3099(17)30396-1 [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180094r3] 3.Jain S, Williams DJ, Arnold SR, et al. ; CDC EPIC Study Team . Community-acquired pneumonia requiring hospitalization among U.S. children. N Engl J Med. 2015;372(9):835-845. doi: 10.1056/NEJMoa1405870 [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180094r4] 4.O’Brien KL, Wolfson LJ, Watt JP, et al. ; Hib and Pneumococcal Global Burden of Disease Study Team . Burden of disease caused by Streptococcus pneumoniae in children younger than 5 years: global estimates. Lancet. 2009;374(9693):893-902. doi: 10.1016/S0140-6736(09)61204-6 [DOI] [PubMed] [Google Scholar]

[poi180094r5] 5.Angoulvant F, Levy C, Grimprel E, et al. Early impact of 13-valent pneumococcal conjugate vaccine on community-acquired pneumonia in children. Clin Infect Dis. 2014;58(7):918-924. doi: 10.1093/cid/ciu006 [DOI] [PubMed] [Google Scholar]

[poi180094r6] 6.Byington CL, Korgenski K, Daly J, Ampofo K, Pavia A, Mason EO. Impact of the pneumococcal conjugate vaccine on pneumococcal parapneumonic empyema. Pediatr Infect Dis J. 2006;25(3):250-254. doi: 10.1097/01.inf.0000202137.37642.ab [DOI] [PubMed] [Google Scholar]

[poi180094r7] 7.Byington CL, Spencer LY, Johnson TA, et al. An epidemiological investigation of a sustained high rate of pediatric parapneumonic empyema: risk factors and microbiological associations. Clin Infect Dis. 2002;34(4):434-440. doi: 10.1086/338460 [DOI] [PubMed] [Google Scholar]

[poi180094r8] 8.Hortal M, Estevan M, Meny M, Iraola I, Laurani H. Impact of pneumococcal conjugate vaccines on the incidence of pneumonia in hospitalized children after five years of its introduction in Uruguay. PLoS One. 2014;9(6):e98567. doi: 10.1371/journal.pone.0098567 [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180094r9] 9.Grijalva CG, Nuorti JP, Arbogast PG, Martin SW, Edwards KM, Griffin MR. Decline in pneumonia admissions after routine childhood immunisation with pneumococcal conjugate vaccine in the USA: a time-series analysis. Lancet. 2007;369(9568):1179-1186. doi: 10.1016/S0140-6736(07)60564-9 [DOI] [PubMed] [Google Scholar]

[poi180094r10] 10.Fitzwater SP, Chandran A, Santosham M, Johnson HL. The worldwide impact of the seven-valent pneumococcal conjugate vaccine. Pediatr Infect Dis J. 2012;31(5):501-508. doi: 10.1097/INF.0b013e31824de9f6 [DOI] [PubMed] [Google Scholar]

[poi180094r11] 11.Grijalva CG, Nuorti JP, Zhu Y, Griffin MR. Increasing incidence of empyema complicating childhood community-acquired pneumonia in the United States. Clin Infect Dis. 2010;50(6):805-813. doi: 10.1086/650573 [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180094r12] 12.Alicino C, Paganino C, Orsi A, et al. The impact of 10-valent and 13-valent pneumococcal conjugate vaccines on hospitalization for pneumonia in children: a systematic review and meta-analysis. Vaccine. 2017;35(43):5776-5785. doi: 10.1016/j.vaccine.2017.09.005 [DOI] [PubMed] [Google Scholar]

[poi180094r13] 13.Cohen R, Cohen JF, Chalumeau M, Levy C. Impact of pneumococcal conjugate vaccines for children in high- and non-high-income countries. Expert Rev Vaccines. 2017;16(6):625-640. doi: 10.1080/14760584.2017.1320221 [DOI] [PubMed] [Google Scholar]

[poi180094r14] 14.Ladhani SN, Collins S, Djennad A, et al. Rapid increase in non-vaccine serotypes causing invasive pneumococcal disease in England and Wales, 2000-17: a prospective national observational cohort study. Lancet Infect Dis. 2018;18(4):441-451. doi: 10.1016/S1473-3099(18)30052-5 [DOI] [PubMed] [Google Scholar]

[poi180094r15] 15.Weinberger R, von Kries R, van der Linden M, Rieck T, Siedler A, Falkenhorst G. Invasive pneumococcal disease in children under 16 years of age: incomplete rebound in incidence after the maximum effect of PCV13 in 2012/13 in Germany. Vaccine. 2018;36(4):572-577. doi: 10.1016/j.vaccine.2017.11.085 [DOI] [PubMed] [Google Scholar]

[poi180094r16] 16.Dagan R, Ben-Shimol S, Benisty R, et al. A nationwide outbreak of invasive pneumococcal disease (IPD) caused by Streptococcus pneumoniae serotype 2 (Sp2) in the PCV13 era in Israel: abstract 039. 11th International Symposium on Pneumococci Pneumococcal Disease; Melbourne, Australia; April 16, 2018. [Google Scholar]

[poi180094r17] 17.Rokney A, Ben-Shimol S, Korenman Z, et al. Emergence of Streptococcus pneumoniae serotype 12F after sequential introduction of 7- and 13-valent vaccines, Israel. Emerg Infect Dis. 2018;24(3):453-461. doi: 10.3201/eid2403.170769 [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180094r18] 18.Ouldali N, Levy C, Varon E, et al. ; French Pediatric Meningitis Network . Incidence of paediatric pneumococcal meningitis and emergence of new serotypes: a time-series analysis of a 16-year French national survey. Lancet Infect Dis. 2018;18(9):983-991. doi: 10.1016/S1473-3099(18)30349-9 [DOI] [PubMed] [Google Scholar]

[poi180094r19] 19.Ben-Shimol S, Givon-Lavi N, Grisaru-Soen G, Megged O, Greenberg D, Dagan R; Israel Bacteremia and Meningitis Active Surveillance Group . Comparative incidence dynamics and serotypes of meningitis, bacteremic pneumonia and other-IPD in young children in the PCV era: insights from Israeli surveillance studies. Vaccine. 2018;36(36):5477-5484. doi: 10.1016/j.vaccine.2017.05.059 [DOI] [PubMed] [Google Scholar]

[poi180094r20] 20.Ben-Shimol S, Greenberg D, Hazan G, et al. ; Israeli Bacteremia and Meningitis Active Surveillance Group . Differential impact of pneumococcal conjugate vaccines on bacteremic pneumonia versus other invasive pneumococcal disease. Pediatr Infect Dis J. 2015;34(4):409-416. doi: 10.1097/INF.0000000000000604 [DOI] [PubMed] [Google Scholar]

[poi180094r21] 21.Levy C, Biscardi S, Dommergues MA, et al. ; Pneumonia study group . Impact of PCV13 on community-acquired pneumonia by C-reactive protein and procalcitonin levels in children. Vaccine. 2017;35(37):5058-5064. doi: 10.1016/j.vaccine.2017.06.057 [DOI] [PubMed] [Google Scholar]

[poi180094r22] 22.Greenberg D, Givon-Lavi N, Faingelernt Y, et al. Nasopharyngeal pneumococcal carriage during childhood community-acquired alveolar pneumonia: relationship between specific serotypes and coinfecting viruses. J Infect Dis. 2017;215(7):1111-1116. doi: 10.1093/infdis/jiw613 [DOI] [PubMed] [Google Scholar]

[poi180094r23] 23.Santé Publique France Couverture vaccinale du vaccin pneumococcique conjugué. http://invs.santepubliquefrance.fr/Dossiers-thematiques/Maladies-infectieuses/Maladies-a-prevention-vaccinale/Couverture-vaccinale/Donnees/Pneumocoque. Published April 18, 2018. Accessed July 1, 2018.

[poi180094r24] 24.Jandoc R, Burden AM, Mamdani M, Lévesque LE, Cadarette SM. Interrupted time series analysis in drug utilization research is increasing: systematic review and recommendations. J Clin Epidemiol. 2015;68(8):950-956. doi: 10.1016/j.jclinepi.2014.12.018 [DOI] [PubMed] [Google Scholar]

[poi180094r25] 25.Wagner AK, Soumerai SB, Zhang F, Ross-Degnan D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther. 2002;27(4):299-309. doi: 10.1046/j.1365-2710.2002.00430.x [DOI] [PubMed] [Google Scholar]

[poi180094r26] 26.France Sentinelle Network France métropolitaine. https://websenti.u707.jussieu.fr/sentiweb/?site=fr. Published 2018. Accessed December 19, 2018.

[poi180094r27] 27.Kontopantelis E, Doran T, Springate DA, Buchan I, Reeves D. Regression based quasi-experimental approach when randomisation is not an option: interrupted time series analysis. BMJ. 2015;350:h2750. doi: 10.1136/bmj.h2750 [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180094r28] 28.Simonsen L, Taylor RJ, Schuck-Paim C, Lustig R, Haber M, Klugman KP. Effect of 13-valent pneumococcal conjugate vaccine on admissions to hospital 2 years after its introduction in the USA: a time series analysis. Lancet Respir Med. 2014;2(5):387-394. doi: 10.1016/S2213-2600(14)70032-3 [DOI] [PubMed] [Google Scholar]

[poi180094r29] 29.Watier L. A methodological review of specific techniques of time series analysis in epidemiology and public health [in French]. Rev Epidemiol Sante Publique. 1995;43(2):162-172. [PubMed] [Google Scholar]

[poi180094r30] 30.Kaur R, Casey JR, Pichichero ME. Emerging Streptococcus pneumoniae strains colonizing the nasopharynx in children after 13-valent pneumococcal conjugate vaccination in comparison to the 7-valent era, 2006-2015. Pediatr Infect Dis J. 2016;35(8):901-906. doi: 10.1097/INF.0000000000001206 [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180094r31] 31.Saxena S, Atchison C, Cecil E, Sharland M, Koshy E, Bottle A. Additive impact of pneumococcal conjugate vaccines on pneumonia and empyema hospital admissions in England. J Infect. 2015;71(4):428-436. doi: 10.1016/j.jinf.2015.06.011 [DOI] [PubMed] [Google Scholar]

[poi180094r32] 32.Wiese AD, Griffin MR, Zhu Y, Mitchel EF Jr, Grijalva CG. Changes in empyema among U.S. children in the pneumococcal conjugate vaccine era. Vaccine. 2016;34(50):6243-6249. doi: 10.1016/j.vaccine.2016.10.062 [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180094r33] 33.Neuman MI, Hall M, Lipsett SC, et al. ; Pediatric Research in Inpatient Settings Network . Utility of blood culture among children hospitalized with community-acquired pneumonia. Pediatrics. 2017;140(3):e20171013. doi: 10.1542/peds.2017-1013 [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180094r34] 34.Avni T, Mansur N, Leibovici L, Paul M. PCR using blood for diagnosis of invasive pneumococcal disease: systematic review and meta-analysis. J Clin Microbiol. 2010;48(2):489-496. doi: 10.1128/JCM.01636-09 [DOI] [PMC free article] [PubMed] [Google Scholar]

[poi180094r35] 35.Shardell M, Harris AD, El-Kamary SS, Furuno JP, Miller RR, Perencevich EN. Statistical analysis and application of quasi experiments to antimicrobial resistance intervention studies. Clin Infect Dis. 2007;45(7):901-907. doi: 10.1086/521255 [DOI] [PubMed] [Google Scholar]

[poi180094r36] 36.Penfold RB, Zhang F. Use of interrupted time series analysis in evaluating health care quality improvements. Acad Pediatr. 2013;13(6)(Suppl):S38-S44. doi: 10.1016/j.acap.2013.08.002 [DOI] [PubMed] [Google Scholar]

PERMALINK

Long-term Association of 13-Valent Pneumococcal Conjugate Vaccine Implementation With Rates of Community-Acquired Pneumonia in Children

Naïm Ouldali, MD

Corinne Levy, MD

Philippe Minodier, MD

Laurence Morin, MD

Sandra Biscardi, MD

Marie Aurel, MD

François Dubos, PhD

Marie Alliette Dommergues, PhD

Ellia Mezgueldi, MD

Karine Levieux, MD

Fouad Madhi, MD

Laure Hees, MD

Irina Craiu, MD

Chrystèle Gras Le Guen, PhD

Elise Launay, PhD

Ferielle Zenkhri, MD

Mathie Lorrot, PhD

Yves Gillet, PhD

Stéphane Béchet, MSc

Isabelle Hau, MD

Alain Martinot, MD

Emmanuelle Varon, MD

François Angoulvant, PhD

Robert Cohen, MD

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Exposures

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Study Data and Setting

Microbiology Study

Intervention

Outcome Measure

Control Outcome

Statistical Analysis

Results

Population and CAP Number per 1000 PED Visits

Table 1. General Characteristics of Cases of Community-Acquired Pneumonia in Children 15 Years and Younger Pre-PCV13 and Post–Vaccine Implementation (2009-2017).

Figure 1. Association of 13-Valent Pneumococcal Conjugate Vaccine (PCV13) Implementation With Rates of Community-Acquired Pneumonia in Children 15 Years and Younger per 1000 Pediatric Emergency Department (PED) Visits.

Sensitivity Analysis

Table 2. Association of Vaccine Implementation With Community-Associated Pneumonia Rates in Children 15 Years and Younger.

CAP With Pleural Effusion

Figure 2. Association of 13-Valent Pneumococcal Conjugate Vaccine (PCV13) Implementation With the Number of Cases of Severe Community-Acquired Pneumonia (CAP) and Cases Likely Caused by Pneumococcus, per 1000 Pediatric Emergency Department (PED) Visits.

CAP Requiring Hospitalization

CAP With High Inflammatory Biomarkers

Proven Pneumococcal CAP Cases

CAP Cases by Age Group

Figure 3. Association of 13-Valent Pneumococcal Conjugate Vaccine (PCV13) Implementation With the Number of Community-Acquired Pneumonia (CAP) Cases per 1000 Pediatric Emergency Department (PED) Visits in Children, by Age Group.

Serotype Evolution

Virus Detection

Control Outcomes

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases