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Published on: September 27, 2014
Comparing approaches for modelling indirect contact transmission of infectious diseases
Amanda M Wilson1,2,3, Mark H Weir4, Marco-Felipe King5
1Department of Family and Preventive Medicine, School of Medicine, University of Utah, Salt Lake City, UT, USA.
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.
Insights
Mathematical models for infectious disease transmission were compared. Mechanistic and Markov chain models estimated different pathogen doses, highlighting the importance of hand hygiene timing and contact patterns for accurate risk assessment.
Area of Science:
- Epidemiology
- Mathematical Modeling
- Infectious Disease Dynamics
Background:
- Mathematical models are crucial for understanding infectious disease transmission.
- Indirect contact transmission, involving fomites and hands, is a key pathway for pathogen spread.
- Accurate risk assessment relies on robust modeling of microorganism transfer.
Purpose of the Study:
- To compare ordinary differential equation/Markov chain models with mechanistic models of microorganism transfer.
- To evaluate how models estimate pathogen doses and concentration changes over time.
- To assess model performance in capturing hand hygiene and contact pattern impacts.
Main Methods:
- Benchmarking a compartment model (ODE/Markov chain) against a mechanistic model of surface-to-finger-to-mucosa transfer.
- Simulating scenarios with varying contamination levels and contact frequencies.
- Analyzing the influence of episodic events like hand hygiene and contact timing.
Main Results:
- Both models estimated higher pathogen doses in asymmetrical scenarios (more contaminated fomite touched more often).
- Hand hygiene representation in the Markov model affected pathogen concentration dynamics but not estimated doses.
- Discrete event modeling highlighted the significance of hand-to-mouth contact timing on dose.
Conclusions:
- Model design significantly influences estimated pathogen doses in indirect transmission.
- Handling hand hygiene as discrete events is crucial for accurate Markov model dynamics.
- Understanding these modeling differences is vital for advancing infectious disease risk assessment tools.
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