Evidence map›Paper›PMID 35507206›Full record

ArticleBulletin of mathematical biology2022

Effect of Population Partitioning on the Probability of Silent Circulation of Poliovirus.

Celeste Vallejo, Carl A B Pearson, James S Koopman, Thomas J Hladish

Open access · greenAbstract read
In one paragraph

Article in Bulletin of mathematical biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.2field-weighted citation impact, top 52% 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

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

  1. Pooled it
  2. Article
  3. Review
  4. 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

4 authors at 4 institutions in 3 countries.

Celeste VallejoMathematical Biosciences Institute, The Ohio State University, Columbus, OH, 43210, USA. celestervallejo@gmail.com.ORCID 0000-0001-7408-5690
Carl A B PearsonDepart of Infectious Disease Epidemiology and Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
James S KoopmanUniversity of Michigan, Ann Arbor, MI, 48109, USA.
Thomas J HladishDepartment of Biology, University of Florida, Gainesville, FL, 32611, USA.
Stellenbosch University · ZAThe Ohio State University · USUniversity of Florida · USUniversity of Michigan · US

Funding

Understanding Transmission with Integrated Genetic and Epidemiologic InferenceU54GM111274 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI VESPIGNANI, ALESSANDRO · 2014 to 2018
$12.5M
NIGMS NIH HHS U54 GM111274
6 · The paper itself

Abstract

Polio can circulate unobserved in regions that are challenging to monitor. To assess the probability of silent circulation, simulation models can be used to understand transmission dynamics when detection is unreliable. Model assumptions, however, impact the estimated probability of silent circulation. Here, we examine the impact of having distinct populations, rather than a single well-mixed population, with a discrete-individual model including environmental surveillance. We show that partitioning a well-mixed population into networks of distinct communities may result in a higher probability of silent circulation as a result of the time it takes for the detection of a circulation event. Population structure should be considered when assessing polio control in a region with many loosely interacting communities.

Indexed as

PoliomyelitisPoliovirusHumansMathematical ConceptsModels, BiologicalProbabilityAsymptomatic transmissionMarkov modelMetapopulationPoliovirus

Identifiers

PMID35507206
PMCPMC9482762
OpenAlexW4225390919

What OpenQuestion holds

Textmetadata
LicenceTDM
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.