Published October 26, 2020 | Version v1
Dataset Open

SARS-CoV-2 transmission and control in a hospital setting: an individual-based modelling study

  • 1. Case Western Reserve University
  • 2. Huazhong University of Science and Technology
  • 3. Texas A&M University

Description

Background: Development of strategies for mitigating the severity of COVID-19 is now a top public health priority. We sought to assess strategies for mitigating the COVID-19 outbreak in a hospital setting via the use of non-pharmaceutical interventions.

Methods: We developed an individual-based model for COVID-19 transmission in a hospital setting. We calibrated the model using data of a COVID-19 outbreak in a hospital unit in Wuhan. The calibrated model was used to simulate different intervention scenarios and estimate the impact of different interventions on outbreak size and workday loss.

Findings: The use of high efficacy facial masks was shown to be able to reduce infection cases and workday loss by 80% (90% CrI: 73.1% - 85.7%) and 87% (CrI: 80.0% - 92.5%), respectively. The use of social distancing alone, through reduced contacts between healthcare workers, had a marginal impact on the outbreak. Our results also indicated that a quarantine policy should be coupled with other interventions to achieve its effect. The effectiveness of all these interventions was shown to increase with their early implementation.

Conclusions: Our analysis shows that a COVID-19 outbreak in a hospital's non-COVID-19 unit can be controlled or mitigated by the use of existing non-pharmaceutical measures.

Notes

Individual-based model setup and hospital aggregated data. The code is implemented in Wolfram Mathematica, it can be opened and operated with Mathematica only. 

Funding provided by: Fundamental Research Funds for the Central Universities
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100012226
Award Number: 2020kfyXGYJ010

Funding provided by: National Science Foundation RAPID
Crossref Funder Registry ID:
Award Number: DEB-2028631

Files

Files (86.8 kB)

Name Size Download all
md5:38cf4e29c42ff7756275d5e1c1cd3084
86.8 kB Download

Additional details

Related works