Introduction
Methods
Study type
Selection criteria
Data sources and variables
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EDO system: data such as date of birth, sex, date of onset of symptoms and microbiological results (serotype and antibiotic sensitivity) collected using a structured form. Serotypes were identified using the Quellung reaction, and antibiotic sensitivity was assessed using the criteria established by the European Committee on Antimicrobial Susceptibility Testing (EUCAST) [14].
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Vaccination information system: date of birth, sex, date of vaccination and type of vaccine prescribed.
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Information and analysis system of the pharmaceutical service: community consumption of beta-lactam antibiotics, dispensed by prescription in pharmacy offices. Consumption was expressed as a defined daily dose number (DDD), which is a standardised measure formulated by the WHO (classification system with defined daily doses (ATC/DDD) [15]. For beta-lactam antibiotics, the DDD for the entire Community of Madrid were added together.
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Continuous census of the Institute of Statistics of the CM: population by age, sex and year of study recorded in the CM.
Indicators
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Cumulative incidence (CMI) of cases of the groups of RAS and penicillin-sensitive serotypes per 100,000 people. The denominator used was the annual number of adults over 59 years residing in the CM.
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Childhood vaccination coverage (CVC): We estimated the annual first-vaccinated in the 2-year-old cohort, this being the age at which first vaccination with two or three doses was theoretically received under the current vaccination schedule. First-vaccinated was defined as children vaccinated without the booster dose. Vaccination coverage was categorised into three levels for multivariate analysis (< 85%, 86–90% and > 90%). Vaccination coverage was calculated for VCN13 (VC13) and for the sum of the two vaccines (VC7 + 13).
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Daily defined dose per 1000 persons per day (DHD) of adults over 59 years of age: calculated for each study year. The following formula was used: DHD = (DDD*1000) / population*365 [15].
Analysis
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PCV13 specific with RAS-Pen/total PCV13 with RAS-Pen
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Specific sensitive PCV13/total PCV13 sensitive
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Specific non-PCV13 with RAS/total of non-PCV13 with RAS-Pen
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Specific non-PCV13 sensitive/total non-PCV13 sensitive
Results
Evolution of CI, CVC and DHD trends
Evolution of CI, CVC and DHD using JointPoint models.
CMI 100,000 pax | AAPC CI 95% | APC CI 95% | ||||||
---|---|---|---|---|---|---|---|---|
2007 | 2016 | 2007–2016 | First period | Second period | ||||
IPD | 15.01 | 14.1 | -1% | (-4.8; 3.1) | ||||
RAS-Pen | ||||||||
STtotal | 4.57 | 2.64 | -2.4% | (-6.7; 2.1) | ||||
PCV13 | 3.62 | 0.76 | -14.4%* | (-19.4; -9.2) | ||||
Non-PCV13 | 0.95 | 1.88 | 11.5%* | (3; 20.7) | ||||
PCV13no7 | 1.38 | 0.39 | -12.1%* | (-22.6; -0.1) | 2007–2009 | 32.7% (-31.2; 155) | 2009 –2016. | -21.8%* (-29.7; -13) |
PCV7 | 2.24 | 0.28 | -15.5%* | (-23; -7) | ||||
SENSITIVE | ||||||||
STtotal | 10.44 | 11.46 | -0.2% | (-4.6; 4.4) | ||||
PCV13 | 6.56 | 2.64 | -11.4%* | (-14.5; -8.2) | ||||
Non-PCV13 | 3.88 | 8.82 | 8%* | (2.3; 14.1) | ||||
PCV13no7 | 5.26 | 2.01 | -12%* | (-15.8; -7.9) | ||||
PCV7 | 1.29 | 0.63 | -7.7% | (-20.9; 7.7) | ||||
Population variables | ||||||||
DHD | 15.64 | 17.93 | 2.3% | (1.3; 3.3) | ||||
VC13 | 1.34%^ | 91.69% | 98.6% | (56.2; 152.5) | 2010–2012 | 681%* (62.2; 3666) | 2012–2016 | 0.1 (-8.1;9) |
VC7 + 13 | 32.21% | 91.69% | 8.3% | (4.7;12) | 2007–2009 | 56.7%* (29.5; 89.5) | 2009–2016 | -2.5%* (-4.2; -0.8) |
Evolution of CMI of cases by the five groups of serotypes using Poisson models
RAS-Pen | Serotypes | CMI × 100,000 pax | RR | CI 95% | ||
---|---|---|---|---|---|---|
Pre-vaccination | Vaccination period | |||||
YES | STtotal | 4.85 (175) | 4.08 (335) | 0.840 | 0.698 | 1.015 |
PCV13 | 3.69 (133) | 1.41 (116) | 0.382 | 0.295 | 0.495 | |
non-PCV13 | 1.16 (42) | 2.66 (219) | 2.289 | 1.639 | 3.266 | |
PCV13no7 | 1.66 (60) | 0.75 (62) | 0.454 | 0.313 | 0.658 | |
PCV7 | 2.02 (73) | 0.66 (51) | 0.324 | 0.224 | 0.468 | |
NO | STtotal | 11.64 (420) | 10.05 (826) | 0.863 | 0.767 | 0.973 |
PCV13 | 6.40 (221) | 3.12 (256) | 0.487 | 0.406 | 0.584 | |
Non-PCV13 | 5.24 (189) | 6.94 (570) | 1.324 | 1.121 | 1.569 | |
PCV13no7 | 5.48 (198) | 2.70 (222) | 0.492 | 0.405 | 0.599 | |
PCV7 | 0.915 (33) | 0.413 (34) | 0.452 | 0.272 | 0.753 |
Evolution of differences in individual serotype distribution
Distribution of individual serotypes
Evolution of CMI of individual serotypes using Poisson models (Table 3)
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The inter-period IRR (pre-vaccine/vaccine) for all cases by vaccine serotypes was negative. There was a notable reduction of serotypes 19A and 14 among the cases with RAS-Pen. 7F and 1 were prominent among the sensitive serotypes.
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IRR was positive for cases of non-vaccine serotypes with RAS, with a notable increase in serotypes 6C, 23B and 11A. The increase in the vaccine period of serotype 8 was significant among the sensitive serotypes.
RAS TO PEN | Serotypes | CMI × 100.000 pax | IRR | CI 95% | ||
---|---|---|---|---|---|---|
Pre-vaccine | Vaccination period | |||||
Yes | PCV13 | |||||
19A1 | 1.52 (55) | 0.74 (61) | 0.487 | 0.333 | 0.714 | |
14 | 0.99 (36) | 0.34 (28) | 0.341 | 0.200 | 0.575 | |
9 V | 0.36 (13) | 0.18 (15) | 0.507 | 0.225 | 1.157 | |
19F | 0.19 (7) | 0.10 (8) | 0.502 | 0.159 | 1.625 | |
23F | 0.22 (8) | 0.02 (2) | 0.110 | 0.011 | 0.550 | |
6B | 0.25 (9) | 0.01 (1) | 0.049 | 0.001 | 0.352 | |
non-PCV13 | ||||||
6C | 0.25 (9) | 0.54 (44) | 2.146 | 1.034 | 5.00 | |
11A2 | 0.11 (4) | 0.57 (47) | 5.158 | 1.886 | 19.715 | |
15A | 0.25 (9) | 0.32 (26) | 1.268 | 0.576 | 3.076 | |
35B | 0.17 (6) | 0.29 (24) | 1.756 | 0.699 | 5.252 | |
24F | 0.17 (6) | 0.28 (23) | 1.683 | 0.666 | 5.053 | |
23B | 0.08 (3) | 0.26 (21) | 3.073 | 0.918 | 16.091 | |
No | PCV13 | |||||
31 | 2.27 (82) | 1.84 (151) | 0.809 | 0.613 | 1.071 | |
7F1 | 1.27 (46) | 0.34 (28) | 0.267 | 0.161 | 0.437 | |
11 | 0.78 (28) | 0.22 (18) | 0.282 | 0.147 | 0.528 | |
19A1 | 0.50 (18) | 0.27 (22) | 0.537 | 0.274 | 1.061 | |
non-PCV13 | ||||||
82 | 0.67 (24) | 1.63 (134) | 2.451 | 1.579 | 3.959 | |
22F2 | 0.64 (23) | 0.78 (64) | 1.222 | 0.748 | 2.062 | |
31 | 0.44 (16) | 0.63 (52) | 1.426 | 0.802 | 2.677 | |
12F2 | 0.64 (23) | 0.44 (36) | 0.687 | 0.396 | 1.215 | |
9N2 | 0.25 (9) | 0.62 (51) | 2.488 | 1.213 | 5.748 |
Association of CMI with VC13 and DHD.
Models | Variable | RAS-Pen | Sensitive to penicillin | ||||
---|---|---|---|---|---|---|---|
RR | CI 95% | RR | CI 95% | ||||
Model 1 | STtotal | ||||||
Beta-lactam DHD | 1.082 | 0.894 | 1.191 | 1.127* | 1.061 | 1.197 | |
VC13 | 0.833* | 0.722 | 0.963 | 0.912* | 0.832 | 0.999 | |
PCV13 | |||||||
Beta-lactam DHD | 0.989 | 0.842 | 1.162 | 0.94 | 0.843 | 1.050 | |
VC13 | 0.638* | 0.501 | 0.812 | 0.739* | 0.632 | 0.867 | |
STnoVCN13 | |||||||
Beta-lactam DHD | 1.156* | 1.025 | 1.304 | 1243* | 1.154 | 1.338 | |
VC13 | 0.994 | 0.155 | 0.828 | 1038 | 0.926 | 1164 | |
PCV13no7 | |||||||
Beta-lactam DHD | 0.845 | 0.67 | 1.067 | 0.916 | 0.814 | 1.032 | |
VC13 | 0.574* | 0.413 | 0.797 | 0.685* | 0.578 | 0.812 | |
Model 2 | STnoVCN13^ | ||||||
Beta-lactam DHD | 1.281* | 1.164 | 1.408 | 1.199* | 1.137 | 1.266 | |
VC7 + 13 | 1.164 | 0.975 | 1.390 | 0.987 | 0.898 | 1.085 | |
PCV7^ | |||||||
Beta-lactam DHD | 0.803* | 0.691 | 0.934 | 0.91 | 0.748 | 1.106 | |
VC7 + 13 | 0.632* | 0.522 | 0.765 | 0.647* | 0.491 | 0.851 |