Evidence map›Paper›PMID 42732098›Full record

ArticleGates open research2026

A mark and recapture perspective on vaccination touchpoints.

Niket Thakkar

Abstract read
In one paragraph

Article in Gates open research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Niket ThakkarBill & Melinda Gates Foundation, Seattle, Washington, 98109, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper considers large-scale vaccination campaigns, a major platform for vaccine access in a lot of the world, as a recapture estimate of the target population marked by routine immunization. Framing the campaign as a measurement, we learn about its properties, including the campaign's coverage of the target population and some implied sampling properties of post-campaign coverage surveys (PCCSs), the current gold-standard in implementation quality measurement. We develop this idea in the context of the 2023 measles campaign in Kano State, Nigeria, where we have detailed implementation data collected by vaccination teams involved in that effort. Looking specifically at the teams' tally sheets, the daily records of who they vaccinated, we find significant discrepancies between the recapture estimates and those from the corresponding PCCS. Exploring a variety of bias models applied to both the tally sheets and the PCCS helps clarify how anecdotal issues from the field relate to this discrepancy. Overall, we find that the tally sheets, despite being an unorthodox population sample, provide a tractable perspective on implementation and measurement, one that's in principle available nearly instantly and at high resolution for any vaccination touchpoint.

Indexed as

Immunization ProgramsMeaslesMeasles VaccineVaccinationVaccination CoverageBayes TheoremHumansNigeriaMeasles VaccineBayesian inferencecoverage measurementmax entropysurvey samplingVaccination campaigns

Identifiers

PMID42732098
PMCPMC13562088

What OpenQuestion holds

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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.