Evidence map›Paper›PMID 32532542›Full record

ArticleVaccine2020

Impact of state weights on national vaccination coverage estimates from household surveys in Nigeria.

Tracy Qi Dong, Dale A Rhoda, Laina D Mercer

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Vaccine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

3 authors.

Tracy Qi DongDepartment of Biostatistics, University of Washington, 1705 NE Pacific St, Seattle, WA 98195, USA. Electronic address: qd8@uw.edu.
Dale A RhodaBiostat Global Consulting, 870 High Street, Worthington, OH 43085, USA.
Laina D MercerInstitute for Disease Modeling, 3150 139th Ave SE, Bellevue, WA 98005, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

National vaccination coverage estimates from household surveys are widely used in monitoring and planning of immunization programs. In Nigeria, survey-reported national coverage estimates have shown large fluctuations in the past few years. In this paper, we examine the impact of state-level survey weighting on Nigeria's national vaccination coverage estimation. In particular, we focus three vaccination-related outcomes among children aged 12-23 months: the coverage of the third dose of diphtheria, pertussis, and tetanus vaccine (DPT3); the coverage of the first dose of measles-containing vaccine (MCV1); and the availability rate of home-based vaccination record (HBR). We compare the sample selection and weight assignment of three major survey programs in Nigeria, and show that considerable portions of the changes in survey-reported national coverage estimates can be explained by shifts in state-level weights. Our analysis demonstrates the importance of state weighting method in estimating aggregated national coverage figures and provides important context for interpreting changes in coverage estimates between surveys in the future.

Indexed as

Measles VaccineVaccination CoverageAdolescentAdultChildHumansImmunization ProgramsInfantNigeriaVaccinationYoung AdultMeasles VaccineDPT and MCV coverageHBR availabilityHousehold surveysNigeriaSurvey weightVaccination coverage

Identifiers

PMID32532542
PMCPMC7327524

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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.