Evidence map›Paper›PMID 32532220›Full record

ArticleBMC infectious diseases2020

Simulating transmission of ESKAPE pathogens plus C. difficile in relevant clinical scenarios.

Katharina L Weber, Danielle S LeSassier, Anthony D Kappell, Kathleen Q Schulte, Nicole Westfall, Nicolette C Albright, Gene D Godbold, Veena Palsikar, Carlos A Acevedo, Krista L Ternus and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.2field-weighted citation impact, top 37% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. 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

11 authors at 1 institution in 1 country.

Katharina L WeberSignature Science, LLC, Austin, TX, USA.
Danielle S LeSassierSignature Science, LLC, Austin, TX, USA.
Anthony D KappellSignature Science, LLC, Austin, TX, USA.
Kathleen Q SchulteSignature Science, LLC, Austin, TX, USA.
Nicole WestfallSignature Science, LLC, Austin, TX, USA.
Nicolette C AlbrightSignature Science, LLC, Austin, TX, USA.
Gene D GodboldSignature Science, LLC, Austin, TX, USA.
Veena PalsikarSignature Science, LLC, Austin, TX, USA.
Carlos A AcevedoSignature Science, LLC, Austin, TX, USA.
Krista L TernusSignature Science, LLC, Austin, TX, USA.
F Curtis HewittSignature Science, LLC, Austin, TX, USA. chewitt@signaturescience.com.ORCID http://orcid.org/0000-0001-9546-5625
Signature Research (United States) · US

Funding

Centers for Disease Control and Prevention 200-2018-75D30118 C02922
6 · The paper itself

Abstract

backgroundThe prevalence of healthcare-acquired infections (HAI) and rising levels of antimicrobial resistance places significant economic and public health burdens on modern healthcare systems. A group of highly drug resistant pathogens known as the ESKAPE pathogens, along with C. difficile, are the leading causes of HAIs. Interactions between patients, healthcare workers, and environmental conditions impact disease transmission. Studying pathogen transfer under varying contact scenarios in a controlled manner is critical for understanding transmission and disinfectant strategies. In lieu of human subject research, this method has the potential to contribute to modeling the routes of pathogen transmission in healthcare settings.

methodsTo overcome these challenges, we have developed a method that utilizes a synthetic skin surrogate to model both direct (skin-to-skin) and indirect (skin-to fomite-to skin) pathogen transfer between infected patients and healthy healthcare workers. This surrogate material includes a background microbiome community simulating typical human skin flora to more accurately mimic the effects of natural flora during transmission events.

resultsWe demonstrate the ability to modulate individual bacterial concentrations within this microbial community to mimic bacterial concentrations previously reported on the hands of human subjects. We also explore the effect of various decontamination approaches on pathogen transfer between human subjects, such as the use of handwashing or surface disinfectants. Using this method, we identify a potential outlier, S. aureus, that may persist and retain viability in specific transfer conditions better than the overall microbial community during decontamination events.

conclusionsOur work describes the development of an in vitro method that uses a synthetic skin surrogate with a defined background microbiota to simulate skin-to-skin and skin-to fomite-to skin contact scenarios. These results illustrate the value of simulating a holistic microbial community for transfer studies by elucidating differences in different pathogen transmission rates and resistance to common decontamination practices. We believe this method will contribute to improvements in pathogen transmission modeling in healthcare settings and increase our ability to assess the risk associated with HAIs, although additional research is required to establish the degree of correlation of pathogen transmission by skin or synthetic alternatives.

Indexed as

Models, BiologicalClostridioides difficileCross InfectionDecontaminationDrug Resistance, MicrobialFomitesHumansMicrobial ViabilityMicrobiotaSkinSpecies SpecificityC. difficileDecontaminationEpidemiologyESKAPE pathogensHealthcare-acquired infectionsPathogen transmissionSynthetic skin

Identifiers

PMID32532220
PMCPMC7477864
OpenAlexW3034680717

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.