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Title: Verification of Compartmental Epidemiological Models using Metamorphic Testing, Model Checking and Visual Analytics

Abstract

Compartmental models in epidemiology are widely used as a means to model disease spread mechanisms and understand how one can best control the disease in case an outbreak of a widespread epidemic occurs. However, a significant challenge within the community is in the development of approaches that can be used to rigorously verify and validate these models. In this paper, we present an approach to rigorously examine and verify the behavioral properties of compartmen- tal epidemiological models under several common modeling scenarios including birth/death rates and multi-host/pathogen species. Using metamorphic testing, a novel visualization tool and model checking, we build a workflow that provides insights into the functionality of compartmental epidemiological models. Our initial results indicate that metamorphic testing can be used to verify the implementation of these models and provide insights into special conditions where these mathematical models may fail. The visualization front-end allows the end-user to scan through a variety of parameters commonly used in these models to elucidate the conditions under which an epidemic can occur. Further, specifying these models using a process algebra allows one to automatically construct behavioral properties that can be rigorously verified using model checking. Taken together, our approach allows for detecting implementationmore » errors as well as handling conditions under which compartmental epidemiological models may fail to provide insights into disease spread dynamics.« less

Authors:
 [1];  [1];  [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
Work for Others (WFO); USDOE Laboratory Directed Research and Development (LDRD) Program
OSTI Identifier:
1055106
DOE Contract Number:  
DE-AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: 2012 Workshop on Verification and Validation of Epidemiological Models As part of 2012 ASE/IEEE International Conference on Biomedical Computing, Washington DC, DC, USA, 20121214, 20121214
Country of Publication:
United States
Language:
English

Citation Formats

Ramanathan, Arvind, Steed, Chad A, and Pullum, Laura L. Verification of Compartmental Epidemiological Models using Metamorphic Testing, Model Checking and Visual Analytics. United States: N. p., 2012. Web.
Ramanathan, Arvind, Steed, Chad A, & Pullum, Laura L. Verification of Compartmental Epidemiological Models using Metamorphic Testing, Model Checking and Visual Analytics. United States.
Ramanathan, Arvind, Steed, Chad A, and Pullum, Laura L. Sun . "Verification of Compartmental Epidemiological Models using Metamorphic Testing, Model Checking and Visual Analytics". United States.
@article{osti_1055106,
title = {Verification of Compartmental Epidemiological Models using Metamorphic Testing, Model Checking and Visual Analytics},
author = {Ramanathan, Arvind and Steed, Chad A and Pullum, Laura L},
abstractNote = {Compartmental models in epidemiology are widely used as a means to model disease spread mechanisms and understand how one can best control the disease in case an outbreak of a widespread epidemic occurs. However, a significant challenge within the community is in the development of approaches that can be used to rigorously verify and validate these models. In this paper, we present an approach to rigorously examine and verify the behavioral properties of compartmen- tal epidemiological models under several common modeling scenarios including birth/death rates and multi-host/pathogen species. Using metamorphic testing, a novel visualization tool and model checking, we build a workflow that provides insights into the functionality of compartmental epidemiological models. Our initial results indicate that metamorphic testing can be used to verify the implementation of these models and provide insights into special conditions where these mathematical models may fail. The visualization front-end allows the end-user to scan through a variety of parameters commonly used in these models to elucidate the conditions under which an epidemic can occur. Further, specifying these models using a process algebra allows one to automatically construct behavioral properties that can be rigorously verified using model checking. Taken together, our approach allows for detecting implementation errors as well as handling conditions under which compartmental epidemiological models may fail to provide insights into disease spread dynamics.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2012},
month = {1}
}

Conference:
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