A Practical Introduction to Mechanistic Modeling of Disease Transmission in Veterinary Science
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A Practical Introduction to Mechanistic Modeling of Disease Transmission in Veterinary Science. / Kirkeby, Carsten; Brookes, Victoria J.; Ward, Michael P.; Dürr, Salome; Halasa, Tariq.
I: Frontiers in Veterinary Science, Bind 7, 546651, 2021.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - A Practical Introduction to Mechanistic Modeling of Disease Transmission in Veterinary Science
AU - Kirkeby, Carsten
AU - Brookes, Victoria J.
AU - Ward, Michael P.
AU - Dürr, Salome
AU - Halasa, Tariq
PY - 2021
Y1 - 2021
N2 - Computer-based disease spread models are frequently used in veterinary science to simulate disease spread. They are used to predict the impacts of the disease, plan and assess surveillance, or control strategies, and provide insights about disease causation by comparing model outputs with real life data. There are many types of disease spread models, and here we present and describe the implementation of a particular type: individual-based models. Our aim is to provide a practical introduction to building individual-based disease spread models. We also introduce code examples with the goal to make these techniques more accessible to those who are new to the field. We describe the important steps in building such models before, during and after the programming stage, including model verification (to ensure that the model does what was intended), validation (to investigate whether the model results reflect the modeled system), and convergence analysis (to ensure models of endemic diseases are stable before outputs are collected). We also describe how sensitivity analysis can be used to assess the potential impact of uncertainty about model parameters. Finally, we provide an overview of some interesting recent developments in the field of disease spread models.
AB - Computer-based disease spread models are frequently used in veterinary science to simulate disease spread. They are used to predict the impacts of the disease, plan and assess surveillance, or control strategies, and provide insights about disease causation by comparing model outputs with real life data. There are many types of disease spread models, and here we present and describe the implementation of a particular type: individual-based models. Our aim is to provide a practical introduction to building individual-based disease spread models. We also introduce code examples with the goal to make these techniques more accessible to those who are new to the field. We describe the important steps in building such models before, during and after the programming stage, including model verification (to ensure that the model does what was intended), validation (to investigate whether the model results reflect the modeled system), and convergence analysis (to ensure models of endemic diseases are stable before outputs are collected). We also describe how sensitivity analysis can be used to assess the potential impact of uncertainty about model parameters. Finally, we provide an overview of some interesting recent developments in the field of disease spread models.
KW - disease dynamics
KW - disease model
KW - mechanistic model
KW - simulation model
KW - transmission model
UR - https://www.frontiersin.org/articles/10.3389/fvets.2023.1129870/full
U2 - 10.3389/fvets.2020.546651
DO - 10.3389/fvets.2020.546651
M3 - Journal article
C2 - 33575275
AN - SCOPUS:85100955424
VL - 7
JO - Frontiers in Veterinary Science
JF - Frontiers in Veterinary Science
SN - 2297-1769
M1 - 546651
ER -
ID: 257876092