An object simulation model for modeling hypothetical disease epidemics – EpiFlex

<p>Abstract</p> <p>Background</p> <p>EpiFlex is a flexible, easy to use computer model for a single computer, intended to be operated by one user who need not be an expert. Its purpose is to study in-silico the epidemic behavior of a wide variety of diseases, both known...

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Main Author: Hanley Brian
Format: Article
Language:English
Published: BMC 2006-08-01
Series:Theoretical Biology and Medical Modelling
Online Access:http://www.tbiomed.com/content/3/1/32
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spelling doaj-729094d8cf0e4329a543dcefb971ad2b2020-11-24T21:54:11ZengBMCTheoretical Biology and Medical Modelling1742-46822006-08-01313210.1186/1742-4682-3-32An object simulation model for modeling hypothetical disease epidemics – EpiFlexHanley Brian<p>Abstract</p> <p>Background</p> <p>EpiFlex is a flexible, easy to use computer model for a single computer, intended to be operated by one user who need not be an expert. Its purpose is to study in-silico the epidemic behavior of a wide variety of diseases, both known and theoretical, by simulating their spread at the level of individuals contracting and infecting others. To understand the system fully, this paper must be read together in conjunction with study of the software and its results. EpiFlex is evaluated using results from modeling influenza A epidemics and comparing them with a variety of field data sources and other types of modeling.</p> <p>EpiFlex is an object-oriented Monte Carlo system, allocating entities to correspond to individuals, disease vectors, diseases, and the locations that hosts may inhabit. EpiFlex defines eight different contact types available for a disease. Contacts occur inside locations within the model. Populations are composed of demographic groups, each of which has a cycle of movement between locations. Within locations, superspreading is defined by skewing of contact distributions.</p> <p>Results</p> <p>EpiFlex indicates three phenomena of interest for public health: (1) R<sub>0 </sub>is variable, and the smaller the population, the larger the infected fraction within that population will be; (2) significant compression/synchronization between cities by a factor of roughly 2 occurs between the early incubation phase of a multi-city epidemic and the major manifestation phase; (3) if better true morbidity data were available, more asymptomatic hosts would be seen to spread disease than we currently believe is the case for influenza. These results suggest that field research to study such phenomena, while expensive, should be worthwhile.</p> <p>Conclusion</p> <p>Since EpiFlex shows all stages of disease progression, detailed insight into the progress of epidemics is possible. EpiFlex shows the characteristic multimodality and apparently random variation characteristic of real world data, but does so as an emergent property of a carefully constructed model of disease dynamics and is not simply a stochastic system. EpiFlex can provide a better understanding of infectious diseases and strategies for response.</p> http://www.tbiomed.com/content/3/1/32
collection DOAJ
language English
format Article
sources DOAJ
author Hanley Brian
spellingShingle Hanley Brian
An object simulation model for modeling hypothetical disease epidemics – EpiFlex
Theoretical Biology and Medical Modelling
author_facet Hanley Brian
author_sort Hanley Brian
title An object simulation model for modeling hypothetical disease epidemics – EpiFlex
title_short An object simulation model for modeling hypothetical disease epidemics – EpiFlex
title_full An object simulation model for modeling hypothetical disease epidemics – EpiFlex
title_fullStr An object simulation model for modeling hypothetical disease epidemics – EpiFlex
title_full_unstemmed An object simulation model for modeling hypothetical disease epidemics – EpiFlex
title_sort object simulation model for modeling hypothetical disease epidemics – epiflex
publisher BMC
series Theoretical Biology and Medical Modelling
issn 1742-4682
publishDate 2006-08-01
description <p>Abstract</p> <p>Background</p> <p>EpiFlex is a flexible, easy to use computer model for a single computer, intended to be operated by one user who need not be an expert. Its purpose is to study in-silico the epidemic behavior of a wide variety of diseases, both known and theoretical, by simulating their spread at the level of individuals contracting and infecting others. To understand the system fully, this paper must be read together in conjunction with study of the software and its results. EpiFlex is evaluated using results from modeling influenza A epidemics and comparing them with a variety of field data sources and other types of modeling.</p> <p>EpiFlex is an object-oriented Monte Carlo system, allocating entities to correspond to individuals, disease vectors, diseases, and the locations that hosts may inhabit. EpiFlex defines eight different contact types available for a disease. Contacts occur inside locations within the model. Populations are composed of demographic groups, each of which has a cycle of movement between locations. Within locations, superspreading is defined by skewing of contact distributions.</p> <p>Results</p> <p>EpiFlex indicates three phenomena of interest for public health: (1) R<sub>0 </sub>is variable, and the smaller the population, the larger the infected fraction within that population will be; (2) significant compression/synchronization between cities by a factor of roughly 2 occurs between the early incubation phase of a multi-city epidemic and the major manifestation phase; (3) if better true morbidity data were available, more asymptomatic hosts would be seen to spread disease than we currently believe is the case for influenza. These results suggest that field research to study such phenomena, while expensive, should be worthwhile.</p> <p>Conclusion</p> <p>Since EpiFlex shows all stages of disease progression, detailed insight into the progress of epidemics is possible. EpiFlex shows the characteristic multimodality and apparently random variation characteristic of real world data, but does so as an emergent property of a carefully constructed model of disease dynamics and is not simply a stochastic system. EpiFlex can provide a better understanding of infectious diseases and strategies for response.</p>
url http://www.tbiomed.com/content/3/1/32
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