Comparing approaches for modelling indirect contact transmission of infectious diseases

Author:

Wilson Amanda M.123ORCID,Weir Mark H.4ORCID,King Marco-Felipe5ORCID,Jones Rachael M.12ORCID

Affiliation:

1. Department of Family and Preventive Medicine, School of Medicine, University of Utah, Salt Lake City, UT, USA

2. Rocky Mountain Center for Occupational and Environmental Health, University of Utah, Salt Lake City, UT, USA

3. Department of Community, Environment and Policy, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA

4. Division of Environmental Health Sciences, School of Public Health, The Ohio State University, Columbus, OT, USA

5. School of Civil Engineering, University of Leeds, Woodhouse Lane, Leeds LS2 9JT, UK

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.

Funder

National Institute for Occupational Safety and Health

Royal Society

UK Research and Innovation

Publisher

The Royal Society

Subject

Biomedical Engineering,Biochemistry,Biomaterials,Bioengineering,Biophysics,Biotechnology

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