Evidence map›Paper›PMID 32215368›Full record

ArticleVaccine: X2020

New analytic approaches for analyzing and presenting polio surveillance data to supplement standard performance indicators.

Kristin VanderEnde, Arend Voorman, Sara Khan, Abhijeet Anand, Cynthia J Snider, Ajay Goel, Steve Wassilak

Open access · goldAbstract read
In one paragraph

Article in Vaccine: X, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 19% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
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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

7 authors at 3 institutions in 2 countries.

Kristin VanderEndeCenters for Disease Control and Prevention, Atlanta 30329, USA.
Arend VoormanThe Bill and Melinda Gates Foundation, Seattle 98109, USA.
Sara KhanCenters for Disease Control and Prevention, Atlanta 30329, USA.
Abhijeet AnandCenters for Disease Control and Prevention, Atlanta 30329, USA.
Cynthia J SniderCenters for Disease Control and Prevention, Atlanta 30329, USA.
Ajay GoelThe World Health Organization, Geneva 1202, Switzerland.
Steve WassilakCenters for Disease Control and Prevention, Atlanta 30329, USA.
Centers for Disease Control and Prevention · USGates Foundation · USWorld Health Organization · CH

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundSensitive surveillance for acute flaccid paralysis (AFP) allows for rapid detection of polio outbreaks and provides essential evidence to support certification of the eradication of polio. However, accurately assessing the sensitivity of surveillance systems can be difficult due to limitations in the reliability of available performance indicators, including the rate of detection of non-polio AFP and the proportion of adequate stool sample collection. Recent field reviews have found evidence of surveillance gaps despite indicators meeting expected targets.

methodsWe propose two simple new approaches for AFP surveillance performance indicator analysis to supplement standard indicator analysis approaches commonly used by the Global Polio Eradication Initiative (GPEI): (1) using alternative groupings of low population districts in the country (spatial binning) and (2) flagging unusual patterns in surveillance data (surveillance flags analysis). Using GPEI data, we systematically compare AFP surveillance performance using standard indicator analysis and these new approaches.

resultsApplying spatial binning highlights areas meeting surveillance indicator targets that do not when analyzing performance of low population districts. Applying the surveillance flags we find several countries with unusual data patterns, in particular age groups which are not well-covered by the surveillance system, and countries with implausible rates of adequate stool specimen collection.

conclusionsAnalyzing alternate groupings of administrative units is a simple method to find areas where traditional AFP surveillance indicator targets are not reliably met. For areas where AFP surveillance indicator targets are met, systematic assessment of unusual patterns ('flags') can be a useful prompt for further investigation and field review.

Indexed as

Data qualityDisease surveillancePoliomyelitis

Identifiers

PMID32215368
PMCPMC7090369
OpenAlexW3012760249

What OpenQuestion holds

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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.