Evidence map›Paper›PMID 35987608›Full record

ArticleBMC medical education2022

Simulation applications to support teaching and research in epidemiological dynamics.

Wayne M Getz, Richard Salter, Ludovica Luisa Vissat

Open access · goldAbstract read
In one paragraph

Article in BMC medical education, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 32% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

3 authors at 3 institutions in 2 countries.

Wayne M GetzDepartment Environmental Science, Policy and Management, University of California, Berkeley, 94720, CA, USA. wgetz@berkeley.edu.ORCID http://orcid.org/0000-0001-8784-9354
Richard SalterNumerus Inc, 850 Iron Point Road, Folsom, 95630, CA, USA.
Ludovica Luisa VissatDepartment Environmental Science, Policy and Management, University of California, Berkeley, 94720, CA, USA.
Oberlin College · USSave Ourselves Breast Cancer Organization · USUniversity of California, Berkeley · US

Funding

National Science Foundation 2032264
6 · The paper itself

Abstract

backgroundAn understanding of epidemiological dynamics, once confined to mathematical epidemiologists and applied mathematicians, can be disseminated to a non-mathematical community of health care professionals and applied biologists through simple-to-use simulation applications. We used Numerus Model Builder RAMP

resultsWe take the reader through simulations used to demonstrate the following concepts: 1) disease prevalence curves of unmitigated outbreaks have a single peak and result in epidemics that 'burn' through the population to become extinguished when the proportion of the susceptible population drops below a critical level; 2) if immunity in recovered individuals wanes sufficiently fast then the disease persists indefinitely as an endemic state, with possible dampening oscillations following the initial outbreak phase; 3) the steepness and initial peak of the prevalence curve are influenced by the basic reproductive value R

conclusionOur presentation makes transparent the key assumptions underlying SIR epidemic models. Our RAMP simulators are meant to augment rather than replace classroom material when teaching epidemiological dynamics. They are sufficiently versatile to be used by students to address a range of research questions for term papers and even dissertations.

Indexed as

Communicable DiseasesEpidemicsComputer SimulationHumansModels, BiologicalStochastic ProcessesCompartmental modelsPopulation modeling instructionPublic health educationSIR modelsStochastic simulation

Identifiers

PMID35987608
PMCPMC9391658
OpenAlexW4294094016

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.