Continuous Time Individual-Level Models of Infectious Disease: Package EpiILMCT
This paper describes the R package EpiILMCT, which allows users to study the spread of infectious disease using continuous time individual level models (ILMs). The package provides tools for simulation from continuous time ILMs that are based on either spatial demographic, contact network, or a comb...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Foundation for Open Access Statistics
2021-06-01
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| Series: | Journal of Statistical Software |
| Subjects: | |
| Online Access: | https://www.jstatsoft.org/index.php/jss/article/view/3405 |
| _version_ | 1797813957604409344 |
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| author | Waleed Almutiry Vineetha Warriyar K V Rob Deardon |
| author_facet | Waleed Almutiry Vineetha Warriyar K V Rob Deardon |
| author_sort | Waleed Almutiry |
| collection | DOAJ |
| description | This paper describes the R package EpiILMCT, which allows users to study the spread of infectious disease using continuous time individual level models (ILMs). The package provides tools for simulation from continuous time ILMs that are based on either spatial demographic, contact network, or a combination of both of them, and for the graphical summarization of epidemics. Model fitting is carried out within a Bayesian Markov Chain Monte Carlo framework. The continuous time ILMs can be implemented within either susceptible-infected-removed (SIR) or susceptible-infected-notified-removed (SIN R) compartmental frameworks. As infectious disease data is often partially observed, data uncertainties in the form of missing infection times - and in some situations missing removal times - are accounted for using data augmentation techniques. The package is illustrated using both simulated and an experimental data set on the spread of the tomato spotted wilt virus disease. |
| first_indexed | 2024-03-13T08:00:24Z |
| format | Article |
| id | doaj.art-b6647bda1d144d1faaec3e582e27f82a |
| institution | Directory Open Access Journal |
| issn | 1548-7660 |
| language | English |
| last_indexed | 2024-03-13T08:00:24Z |
| publishDate | 2021-06-01 |
| publisher | Foundation for Open Access Statistics |
| record_format | Article |
| series | Journal of Statistical Software |
| spelling | doaj.art-b6647bda1d144d1faaec3e582e27f82a2023-06-01T18:41:07ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602021-06-0198110.18637/jss.v098.i103272Continuous Time Individual-Level Models of Infectious Disease: Package EpiILMCTWaleed AlmutiryVineetha Warriyar K VRob DeardonThis paper describes the R package EpiILMCT, which allows users to study the spread of infectious disease using continuous time individual level models (ILMs). The package provides tools for simulation from continuous time ILMs that are based on either spatial demographic, contact network, or a combination of both of them, and for the graphical summarization of epidemics. Model fitting is carried out within a Bayesian Markov Chain Monte Carlo framework. The continuous time ILMs can be implemented within either susceptible-infected-removed (SIR) or susceptible-infected-notified-removed (SIN R) compartmental frameworks. As infectious disease data is often partially observed, data uncertainties in the form of missing infection times - and in some situations missing removal times - are accounted for using data augmentation techniques. The package is illustrated using both simulated and an experimental data set on the spread of the tomato spotted wilt virus disease.https://www.jstatsoft.org/index.php/jss/article/view/3405EpiILMCTinfectious diseaseindividual level modelingspatialcontact networkR |
| spellingShingle | Waleed Almutiry Vineetha Warriyar K V Rob Deardon Continuous Time Individual-Level Models of Infectious Disease: Package EpiILMCT Journal of Statistical Software EpiILMCT infectious disease individual level modeling spatial contact network R |
| title | Continuous Time Individual-Level Models of Infectious Disease: Package EpiILMCT |
| title_full | Continuous Time Individual-Level Models of Infectious Disease: Package EpiILMCT |
| title_fullStr | Continuous Time Individual-Level Models of Infectious Disease: Package EpiILMCT |
| title_full_unstemmed | Continuous Time Individual-Level Models of Infectious Disease: Package EpiILMCT |
| title_short | Continuous Time Individual-Level Models of Infectious Disease: Package EpiILMCT |
| title_sort | continuous time individual level models of infectious disease package epiilmct |
| topic | EpiILMCT infectious disease individual level modeling spatial contact network R |
| url | https://www.jstatsoft.org/index.php/jss/article/view/3405 |
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