1st International Congress on Environmental Modelling and Software - Lugano, Switzerland - June 2002
Keywords
ebola, computer simulation, modelling, system dynamics, feedback, information delays
Start Date
1-7-2002 12:00 AM
Abstract
This paper describes the application of the tools and techniques of the system dynamics method to the complex problem of understanding the spread of the Ebola virus. The main deliverable of this research is a computer simulation model in the system dynamics tradition. The essence of system dynamics is to act as a framework for formalising mental models of a problem. In this respect, the system dynamics simulation model presented here is a theory describing the structure of, and interrelationships between, the factors that impact an outbreak of the Ebola virus and the attempts to contain it. The model, comprising 57 interrelated variables, is structured to represent a group of rural villages served by one local hospital, remote from regional and national medical laboratories. Such a structure typifies the circumstances of recent Ebola outbreaks in central Africa. Model output examines the probable impacts of changes in the system delays. These delays consist mainly of incubation delays, delays to disease recognition, delays in travelling to hospital, delays to inform higher health authorities and delays to involve the Centre for Disease Control in the US.
Modelling the effect of information feedback on the spread of the Ebola virus
This paper describes the application of the tools and techniques of the system dynamics method to the complex problem of understanding the spread of the Ebola virus. The main deliverable of this research is a computer simulation model in the system dynamics tradition. The essence of system dynamics is to act as a framework for formalising mental models of a problem. In this respect, the system dynamics simulation model presented here is a theory describing the structure of, and interrelationships between, the factors that impact an outbreak of the Ebola virus and the attempts to contain it. The model, comprising 57 interrelated variables, is structured to represent a group of rural villages served by one local hospital, remote from regional and national medical laboratories. Such a structure typifies the circumstances of recent Ebola outbreaks in central Africa. Model output examines the probable impacts of changes in the system delays. These delays consist mainly of incubation delays, delays to disease recognition, delays in travelling to hospital, delays to inform higher health authorities and delays to involve the Centre for Disease Control in the US.
