A primer on stochastic epidemic models: Formulation, numerical simulation, and analysis
Some mathematical methods for formulation and numerical simulation of stochastic epidemic models are presented. Specifically, models are formulated for continuous-time Markov chains and stochastic differential equations. Some well-known examples are used for illustration such as an SIR epidemic mode...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2017-05-01
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| Series: | Infectious Disease Modelling |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2468042716300495 |
| _version_ | 1797203636733870080 |
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| author | Linda J.S. Allen |
| author_facet | Linda J.S. Allen |
| author_sort | Linda J.S. Allen |
| collection | DOAJ |
| description | Some mathematical methods for formulation and numerical simulation of stochastic epidemic models are presented. Specifically, models are formulated for continuous-time Markov chains and stochastic differential equations. Some well-known examples are used for illustration such as an SIR epidemic model and a host-vector malaria model. Analytical methods for approximating the probability of a disease outbreak are also discussed. Keywords: Branching process, Continuous-time Markov chain, Minor outbreak, Stochastic differential equation, 2000 MSC: 60H10, 60J28, 92D30 |
| first_indexed | 2024-04-24T08:22:29Z |
| format | Article |
| id | doaj.art-5845300186c24bda93928d86d9b7dcf3 |
| institution | Directory Open Access Journal |
| issn | 2468-0427 |
| language | English |
| last_indexed | 2024-04-24T08:22:29Z |
| publishDate | 2017-05-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Infectious Disease Modelling |
| spelling | doaj.art-5845300186c24bda93928d86d9b7dcf32024-04-17T00:34:27ZengKeAi Communications Co., Ltd.Infectious Disease Modelling2468-04272017-05-0122128142A primer on stochastic epidemic models: Formulation, numerical simulation, and analysisLinda J.S. Allen0Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409-1042, USASome mathematical methods for formulation and numerical simulation of stochastic epidemic models are presented. Specifically, models are formulated for continuous-time Markov chains and stochastic differential equations. Some well-known examples are used for illustration such as an SIR epidemic model and a host-vector malaria model. Analytical methods for approximating the probability of a disease outbreak are also discussed. Keywords: Branching process, Continuous-time Markov chain, Minor outbreak, Stochastic differential equation, 2000 MSC: 60H10, 60J28, 92D30http://www.sciencedirect.com/science/article/pii/S2468042716300495 |
| spellingShingle | Linda J.S. Allen A primer on stochastic epidemic models: Formulation, numerical simulation, and analysis Infectious Disease Modelling |
| title | A primer on stochastic epidemic models: Formulation, numerical simulation, and analysis |
| title_full | A primer on stochastic epidemic models: Formulation, numerical simulation, and analysis |
| title_fullStr | A primer on stochastic epidemic models: Formulation, numerical simulation, and analysis |
| title_full_unstemmed | A primer on stochastic epidemic models: Formulation, numerical simulation, and analysis |
| title_short | A primer on stochastic epidemic models: Formulation, numerical simulation, and analysis |
| title_sort | primer on stochastic epidemic models formulation numerical simulation and analysis |
| url | http://www.sciencedirect.com/science/article/pii/S2468042716300495 |
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