Evidence map›Paper›PMID 33904344›Full record

ArticleMedical decision making : an international journal of the Society for Medical Decision Making2021

Representing Tuberculosis Transmission with Complex Contagion: An Agent-Based Simulation Modeling Approach.

Erin D Zwick, Caitlin S Pepperell, Oguzhan Alagoz

Open access · greenAbstract read
In one paragraph

Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2021. 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
0.4field-weighted citation impact, top 45% 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, 5 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 1 institution in 1 country.

Erin D ZwickDepartment of Population Health Sciences, University of Wisconsin-Madison, Madison, WI, USA.
Caitlin S PepperellDepartment of Medicine and Department of Medical Microbiology and Immunology, University of Wisconsin-Madison, Madison, WI, USA.
Oguzhan AlagozDepartment of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA, PhD.ORCID 0000-0002-5133-1382
University of Wisconsin–Madison · US

Funding

University of Wisconsin Institute for Clinical and Translational ResearchUL1TR002373 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI ELIZABETH S BURNSIDE, Allan R. Brasier · 2017 to 2026
$75.9M
Institutional Clinical and Translational Science AwardUL1TR000427 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2012 to 2016
$32.2M
Research Training for Computation and Informatics in Biology and MedicineT15LM007359 · NLM · UNIVERSITY OF WISCONSIN-MADISON · PI Mark W. Craven, Colin Noel Dewey · 2002 to 2026
$22.6M
Drifting to victory: resolving the paradox of M.tuberculosis evolutionR01AI113287 · NIAID · UNIVERSITY OF WISCONSIN-MADISON · PI Caitlin S Pepperell · 2015 to 2026
$6.5M
NCATS NIH HHS UL1 TR000427NCATS NIH HHS UL1 TR002373NIAID NIH HHS R01 AI113287NLM NIH HHS T15 LM007359
6 · The paper itself

Abstract

objectiveA recent study reported a tuberculosis (TB) outbreak in which, among newly infected individuals, exposure to additional active infections was associated with a higher probability of developing active disease. Referred to as

methodsWe built an ABM of a TB epidemic using data from a series of outbreaks recorded in the 20th century in Saskatchewan, Canada. We fit 3 dynamical schemes: base, with no complex contagion; additive, in which each reexposure confers an independent risk of activated infection; and threshold, in which a small number of reexposures confers a low risk and a high number of reexposures confers a high risk of activation.

resultsWe find that the base model fits the mortality and incidence output targets best, followed by the threshold and then the additive models. The threshold model fits the incidence better than the base model does but overestimates mortality. All 3 models produce qualitatively realistic epidemic curves.

conclusionWe find that complex contagion qualitatively changes the trajectory of a TB epidemic, although data from a high-incidence setting are reproduced better with the base model. Results from this model demonstrate the feasibility of using ABM to capture nuances in TB transmission.

Indexed as

TuberculosisComputer SimulationDisease OutbreaksHumansIncidenceSystems Analysisagent-based modelingcomplex contagioninfectious diseasemodelingsimulationtuberculosis

Identifiers

PMID33904344
PMCPMC8295181
OpenAlexW3157855096

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.