Patch dynamics modeling framework from pathogens' perspective : Unified and standardized approach for complicated epidemic systems

Search for this publication on Google Scholar
Janies, D., Chen, S., Lo, E., & Dulin, M. (2020). Patch dynamics modeling framework from pathogens' perspective : Unified and standardized approach for complicated epidemic systems. Plos One. https://doi.org/doi:10.1371/journal.pone.0238186
Download PDF

Analytics

3 views ◎
0 downloads ⇓


Description

Faculty, Mathematical models are powerful tools to investigate, simulate, and evaluate potential interventions for infectious diseases dynamics. Much effort has focused on the Susceptible-Infected-Recovered (SIR)-type compartment models. These models consider host populations and measure change of each compartment. In this study, we propose an alternative patch dynamic modeling framework from pathogens' perspective. Each patch, the basic module of this modeling framework, has four standard mechanisms of pathogen population size change: birth (replication), death, inflow, and outflow. This framework naturally distinguishes between-host transmission process (inflow and outflow) and within-host infection process (replication) during the entire transmission-infection cycle. We demonstrate that the SIR-type model is actually a special cross-sectional and discretized case of our patch dynamics model in pathogens' viewpoint. In addition, this patch dynamics modeling framework is also an agent-based model from hosts' perspective by incorporating individual host's specific traits. We provide an operational standard to formulate this modular-designed patch dynamics model. Model parameterization is feasible with a wide range of sources, including genomics data, surveillance data, electronic health record, and from other emerging technologies such as multiomics. We then provide two proof-of-concept case studies to tackle some of the existing challenges of SIR-type models: sexually transmitted disease and healthcare acquired infections. This patch dynamics modeling framework not only provides theoretical explanations to known phenomena, but also generates novel insights of disease dynamics from a more holistic viewpoint. It is also able to simulate and handle more complicated scenarios across biological scales such as the current COVID-19 pandemic.

Details
Title

Patch dynamics modeling framework from pathogens' perspective : Unified and standardized approach for complicated epidemic systems

Author(s)

Janies, Daniel
Chen, Shi
Lo, Eugenia
Dulin, Michael

UNC Charlotte Affiliate Type

Faculty

Extent

1 online resource

Date Created

2020

Genre

articles

Resource Type

text

Abstract

Mathematical models are powerful tools to investigate, simulate, and evaluate potential interventions for infectious diseases dynamics. Much effort has focused on the Susceptible-Infected-Recovered (SIR)-type compartment models. These models consider host populations and measure change of each compartment. In this study, we propose an alternative patch dynamic modeling framework from pathogens' perspective. Each patch, the basic module of this modeling framework, has four standard mechanisms of pathogen population size change: birth (replication), death, inflow, and outflow. This framework naturally distinguishes between-host transmission process (inflow and outflow) and within-host infection process (replication) during the entire transmission-infection cycle. We demonstrate that the SIR-type model is actually a special cross-sectional and discretized case of our patch dynamics model in pathogens' viewpoint. In addition, this patch dynamics modeling framework is also an agent-based model from hosts' perspective by incorporating individual host's specific traits. We provide an operational standard to formulate this modular-designed patch dynamics model. Model parameterization is feasible with a wide range of sources, including genomics data, surveillance data, electronic health record, and from other emerging technologies such as multiomics. We then provide two proof-of-concept case studies to tackle some of the existing challenges of SIR-type models: sexually transmitted disease and healthcare acquired infections. This patch dynamics modeling framework not only provides theoretical explanations to known phenomena, but also generates novel insights of disease dynamics from a more holistic viewpoint. It is also able to simulate and handle more complicated scenarios across biological scales such as the current COVID-19 pandemic.

Subjects--Topics

Communicable diseases
Biology

Is Part Of

PLoS one

Language

English

Published Version (Please cite this version)

doi:10.1371/journal.pone.0238186

Publisher's Version

https://doi.org/10.1371/journal.pone.0238186

Permalink

http://hdl.handle.net/20.500.13093/work:1141

Rights

This item may be protected by copyright and other related rights. Atkins Library provides access to this item for educational and research purposes only; other uses require the permission of the copyright holder.