A Bayesian ensemble approach for epidemiological projections
T Lindström, M Tildesley, C Webb - PLoS computational biology, 2015 - journals.plos.org
Mathematical models are powerful tools for epidemiology and can be used to compare
control actions. However, different models and model parameterizations may provide …
control actions. However, different models and model parameterizations may provide …
Accelerating Bayesian inference for stochastic epidemic models using incidence data
We consider the case of performing Bayesian inference for stochastic epidemic
compartment models, using incomplete time course data consisting of incidence counts that …
compartment models, using incomplete time course data consisting of incidence counts that …
A tutorial introduction to Bayesian inference for stochastic epidemic models using Markov chain Monte Carlo methods
PD O'Neill - Mathematical biosciences, 2002 - Elsevier
Recent Bayesian methods for the analysis of infectious disease outbreak data using
stochastic epidemic models are reviewed. These methods rely on Markov chain Monte Carlo …
stochastic epidemic models are reviewed. These methods rely on Markov chain Monte Carlo …
Bayesian reconstruction of disease outbreaks by combining epidemiologic and genomic data
Recent years have seen progress in the development of statistically rigorous frameworks to
infer outbreak transmission trees (“who infected whom”) from epidemiological and genetic …
infer outbreak transmission trees (“who infected whom”) from epidemiological and genetic …
Simulation-based Bayesian inference for epidemic models
A powerful and flexible method for fitting dynamic models to missing and censored data is to
use the Bayesian paradigm via data-augmented Markov chain Monte Carlo (DA-MCMC) …
use the Bayesian paradigm via data-augmented Markov chain Monte Carlo (DA-MCMC) …
Approximate Bayesian computation and simulation-based inference for complex stochastic epidemic models
Approximate Bayesian Computation and Simulation-Based Inference for Complex Stochastic
Epidemic Models Page 1 Statistical Science 2018, Vol. 33, No. 1, 4–18 https://doi.org/10.1214/17-STS618 …
Epidemic Models Page 1 Statistical Science 2018, Vol. 33, No. 1, 4–18 https://doi.org/10.1214/17-STS618 …
A tutorial introduction to Bayesian inference for stochastic epidemic models using Approximate Bayesian Computation
Likelihood-based inference for disease outbreak data can be very challenging due to the
inherent dependence of the data and the fact that they are usually incomplete. In this paper …
inherent dependence of the data and the fact that they are usually incomplete. In this paper …
Comparison and assessment of epidemic models
GJ Gibson, G Streftaris, D Thong - Statistical Science, 2018 - JSTOR
Model criticism is a growing focus of research in stochastic epidemic modelling, following
the successful addressing of model fitting and parameter estimation via powerful …
the successful addressing of model fitting and parameter estimation via powerful …
Broadwick: a framework for computational epidemiology
Background Modelling disease outbreaks often involves integrating the wealth of data that
are gathered during modern outbreaks into complex mathematical or computational models …
are gathered during modern outbreaks into complex mathematical or computational models …
Assessing parameter identifiability in compartmental dynamic models using a computational approach: application to infectious disease transmission models
K Roosa, G Chowell - Theoretical Biology and Medical Modelling, 2019 - Springer
Background Mathematical modeling is now frequently used in outbreak investigations to
understand underlying mechanisms of infectious disease dynamics, assess patterns in …
understand underlying mechanisms of infectious disease dynamics, assess patterns in …