Evidence map›Paper›PMID 26090860›Full record

ArticlePloS one2015

Pools versus Queues: The Variable Dynamics of Stochastic "Steady States".

Eric T Lofgren

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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.

Eric T LofgrenNetwork Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute Virginia Tech, Blacksburg, Virginia, United States of America.

Funding

Synthetic Information Systems for Better Informing Public Health PolicymakersU01GM070694 · NIGMS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI EUBANK, STEPHEN G, MARATHE, MADHAV VISHNU · 2004 to 2016
$8.6M
NIGMS NIH HHS 5U01GM070694-11NIGMS NIH HHS U01 GM070694
6 · The paper itself

Abstract

Mathematical models in ecology and epidemiology often consider populations "at equilibrium", where in-flows, such as births, equal out-flows, such as death. For stochastic models, what is meant by equilibrium is less clear--should the population size be fixed or growing and shrinking with equal probability? Two different mechanisms to implement a stochastic steady state are considered. Under these mechanisms, both a predator-prey model and an epidemic model have vastly different outcomes, including the median population values for both predators and prey and the median levels of infection within a hospital (P < 0.001 for all comparisons). These results suggest that the question of how a stochastic steady state is modeled, and what it implies for the dynamics of the system, should be carefully considered.

Indexed as

Models, TheoreticalCross InfectionHumansPopulation DynamicsStochastic Processes

Identifiers

PMID26090860
PMCPMC4474550

What OpenQuestion holds

Textmetadata
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.