Pathogen transfer through environment–host contact: an agent-based queueing theoretic framework. (2nd November 2017)

• Record Type: Journal Article
• Authors: Chen, Shi; Lenhart, Suzanne; Day, Judy D; Lee, Chihoon; Dulin, Michael; Lanzas, Cristina
• Is Part Of: Mathematical medicine and biology. Volume 35:Number 3(2018)
• Page Start: 409
• Page End: 425
• Publication Date: 2017-11-02
• Subjects: queueing theory -- pathogen transfer and decay -- environment–host contact -- agent-based model -- health care contact process -- model framework; Biomathematics -- Periodicals; Medicine -- Mathematics -- Periodicals; Medicine -- Periodicals; Biology -- Periodicals; Biomedical Research -- Periodicals; Models, Theoretical -- Periodicals; 570.15195
• DOI: 10.1093/imammb/dqx014
• Languages: English
• ISSNs: 1477-8599

Abstract

Abstract: Queueing theory studies the properties of waiting queues and has been applied to investigate direct host-to-host transmitted disease dynamics, but its potential in modelling environmentally transmitted pathogens has not been fully explored. In this study, we provide a flexible and customizable queueing theory modelling framework with three major subroutines to study the in-hospital contact processes between environments and hosts and potential nosocomial pathogen transfer, where environments are servers and hosts are customers. Two types of servers with different parameters but the same utilization are investigated. We consider various forms of transfer functions that map contact duration to the amount of pathogen transfer based on existing literature. We propose a case study of simulated in-hospital contact processes and apply stochastic queues to analyse the amount of pathogen transfer under different transfer functions, and assume that pathogen amount decreases during the inter-arrival time. Different host behaviour (feedback and non-feedback) as well as initial pathogen distribution (whether in environment and/or in hosts) are also considered and simulated. We assess pathogen transfer and circulation under these various conditions and highlight the importance of the nonlinear interactions among contact processes, transfer functions and pathogen demography during the contact process. Our modelling framework can be readily extended to more complicated queueing networks to simulate more realistic situations by adjusting parameters such as the number and type of servers and customers, and adding extra subroutines.