Conditional logistic individual-level models of spatial infectious disease dynamics
Here, we introduce a novel framework for modelling the spatiotemporal dynamics of disease spread known as conditional logistic individual-level models (CL-ILM's). This framework alleviates much of the computational burden associated with traditional spatiotemporal individual-level models for ep...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2025-03-01
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| Series: | Infectious Disease Modelling |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2468042724001234 |
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| Summary: | Here, we introduce a novel framework for modelling the spatiotemporal dynamics of disease spread known as conditional logistic individual-level models (CL-ILM's). This framework alleviates much of the computational burden associated with traditional spatiotemporal individual-level models for epidemics, and facilitates the use of standard software for fitting logistic models when analysing spatiotemporal disease patterns. The models can be fitted in either a frequentist or Bayesian framework. Here, we apply the new spatial CL-ILM to simulated data, semi-real data from the UK 2001 foot-and-mouth disease epidemic, and real data from a greenhouse experiment on the spread of tomato spotted wilt virus. |
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| ISSN: | 2468-0427 |