Evidence map›Paper›PMID 30592720›Full record

ArticlePloS one2018

Assessing the sensitivity of the polio environmental surveillance system.

Steve J Kroiss, Maiwand Ahmadzai, Jamal Ahmed, Muhammad Masroor Alam, Guillaume Chabot-Couture, Michael Famulare, Abdirahman Mahamud, Kevin A McCarthy, Laina D Mercer, Salman Muhammad and 5 more

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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  17. Disease Surveillance Investments and Administration: Limits to Information Value in Pakistan Polio Eradication.Risk analysis : an official publication of the Society for Risk Analysis · 2021
    Article
  18. Article
  19. Tracking COVID-19 with wastewater.Nature biotechnology · 2020
    Article
  20. Review
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.

Steve J KroissInstitute for Disease Modeling, Bellevue, WA, United States of America.ORCID 0000-0003-2416-3667
Maiwand AhmadzaiNational Emergency Operations Centre for Polio Eradication, Kabul, Afghanistan.
Jamal AhmedWorld Health Organization, Geneva, Switzerland.
Muhammad Masroor AlamDepartment of Virology, National Institute of Health, Chak Shahzad, Islamabad, Pakistan.
Guillaume Chabot-CoutureInstitute for Disease Modeling, Bellevue, WA, United States of America.
Michael FamulareInstitute for Disease Modeling, Bellevue, WA, United States of America.ORCID 0000-0001-9275-7454
Abdirahman MahamudWorld Health Organization, Islamabad, Pakistan.ORCID 0000-0001-9316-6701
Kevin A McCarthyInstitute for Disease Modeling, Bellevue, WA, United States of America.ORCID 0000-0002-9148-8448
Laina D MercerInstitute for Disease Modeling, Bellevue, WA, United States of America.ORCID 0000-0002-2517-8900
Salman MuhammadDepartment of Virology, National Institute of Health, Chak Shahzad, Islamabad, Pakistan.
Rana M SafdarNational Emergency Operations Centre for Polio Eradication, Islamabad, Pakistan.
Salmaan SharifDepartment of Virology, National Institute of Health, Chak Shahzad, Islamabad, Pakistan.
Shahzad ShaukatDepartment of Virology, National Institute of Health, Chak Shahzad, Islamabad, Pakistan.
Hemant ShuklaNational Emergency Operations Centre for Polio Eradication, Kabul, Afghanistan.
Hil LyonsInstitute for Disease Modeling, Bellevue, WA, United States of America.ORCID 0000-0002-0325-006X

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundThe polio environmental surveillance (ES) system has been an incredible tool for advancing polio eradication efforts because of its ability to highlight the spatial and temporal extent of poliovirus circulation. While ES often outperforms, or is more sensitive than AFP surveillance, the sensitivity of the ES system has not been well characterized. Fundamental uncertainty of ES site sensitivity makes it difficult to interpret results from ES, particularly negative results. METHODS AND

findingsTo study ES sensitivity, we used data from Afghanistan and Pakistan to examine the probability that each ES site detected the Sabin 1, 2, or 3 components of the oral polio vaccine (OPV) as a function of virus prevalence within the same district (estimated from AFP data). Accounting for virus prevalence is essential for estimating site sensitivity because Sabin detection rates should vary with prevalence-high immediately after supplemental immunization activities (SIAs), but low in subsequent months. We found that most ES sites in Pakistan and Afghanistan are highly sensitive for detecting poliovirus relative to AFP surveillance in the same districts. For example, even when Sabin poliovirus is at low prevalence of ~0.5-3% in AFP surveillance, most ES sites have ~34-50% probability of detecting Sabin. However, there was considerable variation in ES site sensitivity and we flagged several sites for re-evaluation based on low sensitivity rankings and low wild polio virus detection rates. In these areas, adding new sites or modifying collection methods in current sites could improve sensitivity of environmental surveillance.

conclusionsRelating ES detections to virus prevalence significantly improved our ability to evaluate site sensitivity compared to evaluations based solely on ES detection rates. To extend our approach to new sites and regions, we provide a preliminary framework for relating ES and AFP detection rates, and descriptions of how detection rates might relate to SIAs and natural seasonality.

Indexed as

AfghanistanEnvironmental MonitoringHumansModels, TheoreticalPakistanPoliomyelitisPoliovirus Vaccine, OralPopulation SurveillancePoliovirus Vaccine, Oral

Identifiers

PMID30592720
PMCPMC6310268

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LicenceCC BY
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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.