1. Contemporary statistical inference for infectious disease models using Stan.
- Author
-
Chatzilena A, van Leeuwen E, Ratmann O, Baguelin M, and Demiris N
- Subjects
- Algorithms, Bayes Theorem, Humans, Markov Chains, Monte Carlo Method, Communicable Diseases epidemiology, Communicable Diseases transmission, Disease Outbreaks, Models, Statistical, Software
- Abstract
This paper is concerned with the application of recent statistical advances to inference of infectious disease dynamics. We describe the fitting of a class of epidemic models using Hamiltonian Monte Carlo and variational inference as implemented in the freely available Stan software. We apply the two methods to real data from outbreaks as well as routinely collected observations. Our results suggest that both inference methods are computationally feasible in this context, and show a trade-off between statistical efficiency versus computational speed. The latter appears particularly relevant for real-time applications., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)
- Published
- 2019
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