Evidence map›Paper›PMID 30416017›Full record

ArticleVaccine2018

Coverage and timeliness of vaccination and the validity of routine estimates: Insights from a vaccine registry in Kenya.

Ifedayo M O Adetifa, Boniface Karia, Alex Mutuku, Tahreni Bwanaali, Anne Makumi, Jackline Wafula, Martina Chome, Pauline Mwatsuma, Evasius Bauni, Laura L Hammitt and 5 more

Open access · hybridAbstract read
In one paragraph

Article in Vaccine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
7.0field-weighted citation impact, top 3% of its field
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

26 citing papers in PubMed, 63 citations in OpenAlex.

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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

15 authors at 3 institutions in 4 countries.

Ifedayo M O AdetifaEpidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, PO Box 230-80108, Kilifi, Kenya; Infectious Diseases Epidemiology, London School of Hygiene and Tropical Medicine, WC1E 7HT London, UK. Electronic address: IAdetifa@kemri-wellcome.org.
Boniface KariaEpidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, PO Box 230-80108, Kilifi, Kenya. Electronic address: BKaria@kemri-wellcome.org.
Alex MutukuEpidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, PO Box 230-80108, Kilifi, Kenya.
Tahreni BwanaaliEpidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, PO Box 230-80108, Kilifi, Kenya.
Anne MakumiEpidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, PO Box 230-80108, Kilifi, Kenya.
Jackline WafulaEpidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, PO Box 230-80108, Kilifi, Kenya. Electronic address: JWafula@kemri-wellcome.org.
Martina ChomeEpidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, PO Box 230-80108, Kilifi, Kenya. Electronic address: MChome@kemri-wellcome.org.
Pauline MwatsumaEpidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, PO Box 230-80108, Kilifi, Kenya.
Evasius BauniEpidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, PO Box 230-80108, Kilifi, Kenya.
Laura L HammittCentre for International Health, Johns Hopkins University, Baltimore, MD, United States. Electronic address: lhammitt@jhu.edu.
Christine MatazaCounty Department of Health, Kilifi County Hospital, PO Box 491-80108, Kilifi, Kenya. Electronic address: CMataza@kemri-wellcome.org.
Collins TabuNational Vaccines and Immunisations Programme, Ministry of Health, Kenya.
Tatu KamauVector Borne Diseases Control Unit, Ministry of Health, Kenya.
Thomas N WilliamsEpidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, PO Box 230-80108, Kilifi, Kenya; Department of Medicine, Imperial College, St Mary's Hospital, Praed Street, London, United Kingdom; INDEPTH Network, Accra, Ghana. Electronic address: TWilliams@kemri-wellcome.org.
J Anthony G ScottEpidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, PO Box 230-80108, Kilifi, Kenya; Infectious Diseases Epidemiology, London School of Hygiene and Tropical Medicine, WC1E 7HT London, UK; INDEPTH Network, Accra, Ghana. Electronic address: ascott@ikilifi.org.
Kenya Medical Research Institute · KEMinistry of Health · KEJohns Hopkins University · US

Funding

Wellcome Trust
6 · The paper itself

Abstract

backgroundThe benefits of childhood vaccines are critically dependent on vaccination coverage. We used a vaccine registry (as gold standard) in Kenya to quantify errors in routine coverage methods (surveys and administrative reports), to estimate the magnitude of survivor bias, contrast coverage with timeliness and use both measures to estimate population immunity.

methodsVaccination records of children in the Kilifi Health and Demographic Surveillance System (KHDSS), Kenya were combined with births, deaths, migration and residence data from 2010 to 17. Using inverse survival curves, we estimated up-to-date and age-appropriate vaccination coverage, calculated mean vaccination coverage in infancy as the area under the inverse survival curves, and estimated the proportion of fully immunised children (FIC). Results were compared with published coverage estimates. Risk factors for vaccination were assessed using Cox regression models.

resultsWe analysed data for 49,090 infants and 48,025 children aged 12-23 months in 6 birth cohorts and 6 cross-sectional surveys respectively, and found 2nd year of life surveys overestimated coverage by 2% compared to birth cohorts. Compared to mean coverage in infants, static coverage at 12 months was exaggerated by 7-8% for third doses of oral polio, pentavalent (Penta3) and pneumococcal conjugate vaccines, and by 24% for the measles vaccine. Surveys and administrative coverage also underestimated the proportion of the fully immunised child by 10-14%. For BCG, Penta3 and measles, timeliness was 23-44% higher in children born in a health facility but 20-37% lower in those who first attended during vaccine stock outs.

conclusionsStandard coverage surveys in 12-23 month old children overestimate protection by ignoring timeliness, and survivor and recall biases. Where delayed vaccination is common, up-to-date coverage will give biased estimates of population immunity. Surveys and administrative methods also underestimate FIC prevalence. Better measurement of coverage and more sophisticated analyses are required to control vaccine preventable diseases.

Indexed as

Immunization ProgramsRegistriesChild, PreschoolCohort StudiesCross-Sectional StudiesFemaleHumansInfantKenyaMaleMeasles VaccinePneumococcal VaccinesRegression AnalysisRisk FactorsTime FactorsVaccination CoverageMeasles VaccinePneumococcal VaccinesVaccines, ConjugateAdministrative coverageMethodologySurveysVaccination coverageVaccineVaccine registry

Identifiers

PMID30416017
PMCPMC6288063
OpenAlexW2895641541

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.