Evidence map›Paper›PMID 34465207›Full record

ArticleJournal of the Royal Society, Interface2021

Comparing approaches for modelling indirect contact transmission of infectious diseases.

Amanda M Wilson, Mark H Weir, Marco-Felipe King, Rachael M Jones

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

4 authors.

Amanda M WilsonDepartment of Family and Preventive Medicine, School of Medicine, University of Utah, Salt Lake City, UT, USA.ORCID 0000-0003-3259-8169
Mark H WeirDivision of Environmental Health Sciences, School of Public Health, The Ohio State University, Columbus, OT, USA.ORCID 0000-0002-6995-1037
Marco-Felipe KingSchool of Civil Engineering, University of Leeds, Woodhouse Lane, Leeds LS2 9JT, UK.ORCID 0000-0001-7010-476X
Rachael M JonesDepartment of Family and Preventive Medicine, School of Medicine, University of Utah, Salt Lake City, UT, USA.ORCID 0000-0003-1611-7900

Funding

University of Utah Education and Research CenterT42OH008414 · OH · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI HEGMANN, KURT · 2005 to 2025
$31.7M
NIOSH CDC HHS T42 OH008414
6 · The paper itself

Abstract

Mathematical models describing indirect contact transmission are an important component of infectious disease mitigation and risk assessment. A model that tracks microorganisms between compartments by coupled ordinary differential equations or a Markov chain is benchmarked against a mechanistic interpretation of the physical transfer of microorganisms from surfaces to fingers and subsequently to a susceptible person's facial mucosal membranes. The primary objective was to compare these models in their estimates of doses and changes in microorganism concentrations on hands and fomites over time. The abilities of the models to capture the impact of episodic events, such as hand hygiene, and of contact patterns were also explored. For both models, greater doses were estimated for the asymmetrical scenarios in which a more contaminated fomite was touched more often. Differing representations of hand hygiene in the Markov model did not notably impact estimated doses but affected pathogen concentration dynamics on hands. When using the Markov model, losses due to hand hygiene should be handled as separate events as opposed to time-averaging expected losses. The discrete event model demonstrated the effect of hand-to-mouth contact timing on the dose. Understanding how model design influences estimated doses is important for advancing models as reliable risk assessment tools.

Indexed as

Communicable DiseasesFomitesFingersHandHumansModels, Theoreticalexposureindirect contactinfectious disease modellingvirus

Identifiers

PMID34465207
PMCPMC8437226

What OpenQuestion holds

Textmetadata
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.