A Practical Introduction to Mechanistic Modeling of Disease Transmission in Veterinary Science

被引:7
|
作者
Kirkeby, Carsten [1 ]
Brookes, Victoria J. [2 ,3 ,4 ]
Ward, Michael P. [5 ]
Durr, Salome [6 ]
Halasa, Tariq [1 ]
机构
[1] Univ Copenhagen, Fac Hlth & Med Sci, Dept Vet & Anim Sci, Frederiksberg, Denmark
[2] Charles Sturt Univ, Sch Anim & Vet Sci, Fac Sci, Wagga, NSW, Australia
[3] Charles Sturt Univ, Graham Ctr Agr Innovat, Wagga, NSW, Australia
[4] NSW Dept Primary Ind, Wagga, NSW, Australia
[5] Univ Sydney, Sydney Sch Vet Sci, Fac Vet Sci, Sydney, NSW, Australia
[6] Univ Bern, Vet Publ Hlth Inst, Dept Clin Res & Publ Hlth, Bern, Switzerland
关键词
simulation model; transmission model; disease dynamics; mechanistic model; disease model; AFRICAN-SWINE-FEVER; MOUTH-DISEASE; EVALUATE STRATEGIES; SIMULATION-MODEL; ECONOMIC-IMPACT; DYNAMICS; INFECTION; EPIDEMIC; DIARRHEA; SPREAD;
D O I
10.3389/fvets.2020.546651
中图分类号
S85 [动物医学(兽医学)];
学科分类号
0906 ;
摘要
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.
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页数:13
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