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Record W3206667783 · doi:10.1007/s40121-021-00544-1

Clinical and Economic Burden of Pneumococcal Disease Due to Serotypes Contained in Current and Investigational Pneumococcal Conjugate Vaccines in Children Under Five Years of Age

2021· article· en· W3206667783 on OpenAlexaboutno aff
Matt Wasserman, Johnna Perdrizet, Lindsay R. Grant, Kyla Hayford, Shubhra Singh, P Saharia, Emily K. Horn, Raymond Farkouh

Bibliographic record

VenueInfectious Diseases and Therapy · 2021
Typearticle
Languageen
FieldMedicine
TopicPneumonia and Respiratory Infections
Canadian institutionsnot available
FundersPfizer
KeywordsPneumococcal diseaseMedicineSerotypeDiseasePneumococcal conjugate vaccineOtitisPneumoniaDisease surveillanceEpidemiologyEnvironmental healthPediatricsStreptococcus pneumoniaeVirologyInternal medicineAntibioticsSurgeryBiologyMicrobiology

Abstract

fetched live from OpenAlex

INTRODUCTION: The widespread implementation of pneumococcal conjugate vaccines (PCVs) has significantly reduced the burden of pneumococcal disease around the world. Although licensed 10-valent (PCV10) and 13-valent (PCV13) vaccines have considerably reduced mortality and morbidity, a sizeable disease burden attributable to serotypes not contained in these PCVs remains. This study aimed to estimate the annual clinical and economic burden of pneumococcal disease attributable to licensed (PCV10 and PCV13) and investigational PCVs, notably 15-valent (PCV15) and 20-valent (PCV20) vaccines, in 13 countries in children under 5 years of age. METHODS: A decision-analytic model was created to aggregate total cases [inclusive of invasive pneumococcal disease (IPD), pneumonia, and otitis media (OM)], deaths, and direct costs in each country of interest [stratified by PCV10/PCV13 countries, depending on national immunization programs (NIPs)] over 1 year, using up to the three most recent years of available serotype coverage data. Data inputs were sourced from local databases, surveillance reports, and published literature. RESULTS: In 5 PCV10 NIPs (Austria, Finland, Netherlands, New Zealand, Sweden), most remaining PCV20-type disease was due to PCV13-unique serotypes (30-85%), followed by PCV20-unique (9-50%), PCV15-unique (4-15%), and PCV10-unique (2-14%) serotypes. In 8 PCV13 NIPs (Australia, Canada, France, Germany, Italy, South Korea, Spain, United Kingdom), most remaining PCV20-type disease was caused by PCV20-unique serotypes (16-69%), followed by PCV13-unique (11-54%), PCV15-unique (2-33%), and PCV10-unique serotypes (3-19%). Across all countries, PCV20 serotypes caused 3000 to 345,000 cases of disease and cost between $1.3 and $44.9 million USD annually with variability driven by population size, NIP status, and epidemiologic inputs. In aggregate, PCV20 serotypes caused 1,234,000 cases and $213.5 million in annual direct medical costs in children under 5 years of age. CONCLUSION: Despite the success of PCV10 and PCV13 in reducing pneumococcal disease, a substantial clinical and economic burden remains due to serotypes contained in investigational vaccines.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.305
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations42
Published2021
Admission routes1
Has abstractyes

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