Using cultural, historical, and epidemiological data to inform, calibrate, and verify model structures in agent-based simulations
Agent-based simulation models are excellent tools for addressing questions about the spread of infectious diseases in human populations because realistic, complex behaviors as well as random factors can readily be incorporated. Agent-based models are flexible and allow for a wide variety of behavior...
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ftdoajarticles:oai:doaj.org/article:c80907ad4d6f4027a4187e861c8ce706 2023-05-15T17:22:44+02:00 Using cultural, historical, and epidemiological data to inform, calibrate, and verify model structures in agent-based simulations Lisa Sattenspiel Jessica Dimka Carolyn Orbann 2019-04-01T00:00:00Z https://doi.org/10.3934/mbe.2019152 https://doaj.org/article/c80907ad4d6f4027a4187e861c8ce706 EN eng AIMS Press https://www.aimspress.com/article/doi/10.3934/mbe.2019152?viewType=HTML https://doaj.org/toc/1551-0018 doi:10.3934/mbe.2019152 1551-0018 https://doaj.org/article/c80907ad4d6f4027a4187e861c8ce706 Mathematical Biosciences and Engineering, Vol 16, Iss 4, Pp 3071-3093 (2019) agent-based modeling model calibration model verification sensitivity analysis replication analysis epidemic model Biotechnology TP248.13-248.65 Mathematics QA1-939 article 2019 ftdoajarticles https://doi.org/10.3934/mbe.2019152 2022-12-31T07:20:34Z Agent-based simulation models are excellent tools for addressing questions about the spread of infectious diseases in human populations because realistic, complex behaviors as well as random factors can readily be incorporated. Agent-based models are flexible and allow for a wide variety of behaviors, time-related variables, and geographies, making the calibration process an extremely important step in model development. Such calibration procedures, including verification and validation, may be complicated, however, and usually require incorporation of substantial empirical data and theoretical knowledge of the populations and processes under study. This paper describes steps taken to build and calibrate an agent-based model of epidemic spread in an early 20th century fishing village in Newfoundland and Labrador, including a description of some of the detailed ethnographic and historical data available. We illustrate how these data were used to develop the structure of specific parts of the model. The resulting model, however, is designed to reflect a generic small community during the early 20th century and the spread of a directly transmitted disease within such a community, not the specific place that provided the data. Following the description of model development, we present the results of a replication study used to confirm the model behaves as intended. This study is also used to identify the number of simulations necessary for high confidence in average model output. We also present selected results from extensive sensitivity analyses to assess the effect that variation in parameter values has on model outcomes. After careful calibration and verification, the model can be used to address specific practical questions of interest. We provide an illustrative example of this process. Article in Journal/Newspaper Newfoundland Directory of Open Access Journals: DOAJ Articles Newfoundland Mathematical Biosciences and Engineering 16 4 3071 3093 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
agent-based modeling model calibration model verification sensitivity analysis replication analysis epidemic model Biotechnology TP248.13-248.65 Mathematics QA1-939 |
spellingShingle |
agent-based modeling model calibration model verification sensitivity analysis replication analysis epidemic model Biotechnology TP248.13-248.65 Mathematics QA1-939 Lisa Sattenspiel Jessica Dimka Carolyn Orbann Using cultural, historical, and epidemiological data to inform, calibrate, and verify model structures in agent-based simulations |
topic_facet |
agent-based modeling model calibration model verification sensitivity analysis replication analysis epidemic model Biotechnology TP248.13-248.65 Mathematics QA1-939 |
description |
Agent-based simulation models are excellent tools for addressing questions about the spread of infectious diseases in human populations because realistic, complex behaviors as well as random factors can readily be incorporated. Agent-based models are flexible and allow for a wide variety of behaviors, time-related variables, and geographies, making the calibration process an extremely important step in model development. Such calibration procedures, including verification and validation, may be complicated, however, and usually require incorporation of substantial empirical data and theoretical knowledge of the populations and processes under study. This paper describes steps taken to build and calibrate an agent-based model of epidemic spread in an early 20th century fishing village in Newfoundland and Labrador, including a description of some of the detailed ethnographic and historical data available. We illustrate how these data were used to develop the structure of specific parts of the model. The resulting model, however, is designed to reflect a generic small community during the early 20th century and the spread of a directly transmitted disease within such a community, not the specific place that provided the data. Following the description of model development, we present the results of a replication study used to confirm the model behaves as intended. This study is also used to identify the number of simulations necessary for high confidence in average model output. We also present selected results from extensive sensitivity analyses to assess the effect that variation in parameter values has on model outcomes. After careful calibration and verification, the model can be used to address specific practical questions of interest. We provide an illustrative example of this process. |
format |
Article in Journal/Newspaper |
author |
Lisa Sattenspiel Jessica Dimka Carolyn Orbann |
author_facet |
Lisa Sattenspiel Jessica Dimka Carolyn Orbann |
author_sort |
Lisa Sattenspiel |
title |
Using cultural, historical, and epidemiological data to inform, calibrate, and verify model structures in agent-based simulations |
title_short |
Using cultural, historical, and epidemiological data to inform, calibrate, and verify model structures in agent-based simulations |
title_full |
Using cultural, historical, and epidemiological data to inform, calibrate, and verify model structures in agent-based simulations |
title_fullStr |
Using cultural, historical, and epidemiological data to inform, calibrate, and verify model structures in agent-based simulations |
title_full_unstemmed |
Using cultural, historical, and epidemiological data to inform, calibrate, and verify model structures in agent-based simulations |
title_sort |
using cultural, historical, and epidemiological data to inform, calibrate, and verify model structures in agent-based simulations |
publisher |
AIMS Press |
publishDate |
2019 |
url |
https://doi.org/10.3934/mbe.2019152 https://doaj.org/article/c80907ad4d6f4027a4187e861c8ce706 |
geographic |
Newfoundland |
geographic_facet |
Newfoundland |
genre |
Newfoundland |
genre_facet |
Newfoundland |
op_source |
Mathematical Biosciences and Engineering, Vol 16, Iss 4, Pp 3071-3093 (2019) |
op_relation |
https://www.aimspress.com/article/doi/10.3934/mbe.2019152?viewType=HTML https://doaj.org/toc/1551-0018 doi:10.3934/mbe.2019152 1551-0018 https://doaj.org/article/c80907ad4d6f4027a4187e861c8ce706 |
op_doi |
https://doi.org/10.3934/mbe.2019152 |
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Mathematical Biosciences and Engineering |
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16 |
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4 |
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3071 |
op_container_end_page |
3093 |
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