Evidence map›Paper›PMID 36962284›Full record

ArticlePLOS global public health2022

Data quality of reported child immunization coverage in 194 countries between 2000 and 2019.

Cornelius Rau, Daniel Lüdecke, Laure B Dumolard, Jan Grevendonk, Brenton M Wiernik, Robin Kobbe, Marta Gacic-Dobo, M Carolina Danovaro-Holliday

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Article in PLOS global public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Cornelius RauImmunization Analysis & Insights (IAI), Department of Immunization, Vaccines and Biologicals (IVB), World Health Organization, Geneva, Switzerland.ORCID https://orcid.org/0000-0002-8173-1096
Daniel LüdeckeInstitute of Medical Sociology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.ORCID https://orcid.org/0000-0002-8895-3206
Laure B DumolardImmunization Analysis & Insights (IAI), Department of Immunization, Vaccines and Biologicals (IVB), World Health Organization, Geneva, Switzerland.
Jan GrevendonkImmunization Analysis & Insights (IAI), Department of Immunization, Vaccines and Biologicals (IVB), World Health Organization, Geneva, Switzerland.
Brenton M WiernikDepartment of Psychology, University of South Florida, Tampa, FL, United States of America.ORCID https://orcid.org/0000-0001-9560-6336
Robin KobbeDivision of Infectious Diseases, First Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.ORCID https://orcid.org/0000-0001-6067-3408
Marta Gacic-DoboImmunization Analysis & Insights (IAI), Department of Immunization, Vaccines and Biologicals (IVB), World Health Organization, Geneva, Switzerland.
M Carolina Danovaro-HollidayImmunization Analysis & Insights (IAI), Department of Immunization, Vaccines and Biologicals (IVB), World Health Organization, Geneva, Switzerland.

Funding

World Health Organization 001
6 · The paper itself

Abstract

Analyzing immunization coverage data is crucial to guide decision-making in national immunization programs and monitor global initiatives such as the Immunization Agenda 2030. We aimed to assess the quality of reported child immunization coverage data for 194 countries over 20 years. We analyzed child immunization coverage as reported to the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF) between 2000-2019 by all WHO Member States for Bacillus Calmette-Guérin (BCG) vaccine birth dose, first and third doses of diphtheria-tetanus-pertussis-containing vaccine (DTP1, DTP3), and first dose of measles-containing vaccine (MCV1). We assessed completeness, consistency, integrity, and congruence and assigned data quality flags in case anomalies were detected. Generalized linear mixed-effects models were used to estimate the probability of flags worldwide and for different country groups over time. The probability of data quality flags was 18.2% globally (95% confidence interval [CI] 14.8-22.3). The lowest probability was seen in South-East Asia (6.3%, 3.3-11.8, p = 0.002), the highest in the Americas (29.7%, 22.7-37.9, p < 0.001). The probability of data quality flags declined by 5.1% per year globally (3.2-7.0, p < 0.001). The steepest decline was seen in Africa (-9.6%, -13.0 to -5.8, p < 0.001), followed by Europe (-5.4%, -9.2 to -1.6, p = 0.0055), and the Americas (-4.9%, -9.2 to -0.6, p = 0.026). Most country groups showed a statistically significant decline, and none had a statistically significant increase. Over the past two decades, the quality of global immunization coverage data appears to have improved. However, progress has not been universal. The results highlight the need for joint efforts so that all countries collect, report, and use high-quality data for action in immunization.

Identifiers

PMID36962284
PMCPMC10022119

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.