Hamley, Jonathan I D; Beldi, Guido; Sánchez-Taltavull, Daniel (2024). Infectious Disease in the Workplace: Quantifying Uncertainty in Transmission. Bulletin of mathematical biology, 86(3) Springer 10.1007/s11538-023-01249-x
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Understanding disease transmission in the workplace is essential for protecting workers. To model disease outbreaks, the small populations in many workplaces require that stochastic effects are considered, which results in higher uncertainty. The aim of this study was to quantify and interpret the uncertainty inherent in such circumstances. We assessed how uncertainty of an outbreak in workplaces depends on i) the infection dynamics in the community, ii) the workforce size, iii) spatial structure in the workplace, iv) heterogeneity in susceptibility of workers, and v) heterogeneity in infectiousness of workers. To address these questions, we developed a multiscale model: A deterministic model to predict community transmission, and a stochastic model to predict workplace transmission. We extended this basic workplace model to allow for spatial structure, and heterogeneity in susceptibility and infectiousness in workers. We found a non-monotonic relationship between the workplace transmission rate and the coefficient of variation (CV), which we use as a measure of uncertainty. Increasing community transmission, workforce size and heterogeneity in susceptibility decreased the CV. Conversely, increasing the level of spatial structure and heterogeneity in infectiousness increased the CV. However, when the model predicts bimodal distributions, for example when community transmission is low and workplace transmission is high, the CV fails to capture this uncertainty. Overall, our work informs modellers and policy makers on how model complexity impacts outbreak uncertainty. In particular: workforce size, community and workplace transmission, spatial structure and individual heterogeneity contribute in a specific and individual manner to the predicted workplace outbreak size distribution.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > Department of Gastro-intestinal, Liver and Lung Disorders (DMLL) > Clinic of Visceral Surgery and Medicine 04 Faculty of Medicine > Department of Gastro-intestinal, Liver and Lung Disorders (DMLL) > Clinic of Visceral Surgery and Medicine > Visceral Surgery |
UniBE Contributor: |
Hamley, Jonathan Ian Douglas, Beldi, Guido Jakob Friedrich, Sánchez Taltavull, Daniel |
Subjects: |
600 Technology > 610 Medicine & health |
ISSN: |
1522-9602 |
Publisher: |
Springer |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
05 Feb 2024 14:03 |
Last Modified: |
06 Feb 2024 05:50 |
Publisher DOI: |
10.1007/s11538-023-01249-x |
PubMed ID: |
38302803 |
Uncontrolled Keywords: |
Coefficient of variation Epidemiology Multiscale modelling Stochastic modelling Uncertainty |
BORIS DOI: |
10.48350/192352 |
URI: |
https://boris.unibe.ch/id/eprint/192352 |