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Fitting mechanistic epidemic models to data: A comparison of simple Markov chain Monte Carlo approaches.

ABSTRACT: Simple mechanistic epidemic models are widely used for forecasting and parameter estimation of infectious diseases based on noisy case reporting data. Despite the widespread application of models to emerging infectious diseases, we know little about the comparative performance of standard computational-statistical frameworks in these contexts. Here we build a simple stochastic, discrete-time, discrete-state epidemic model with both process and observation error and use it to characterize the effectiveness of different flavours of Bayesian Markov chain Monte Carlo (MCMC) techniques. We use fits to simulated data, where parameters (and future behaviour) are known, to explore the limitations of different platforms and quantify parameter estimation accuracy, forecasting accuracy, and computational efficiency across combinations of modeling decisions (e.g. discrete vs. continuous latent states, levels of stochasticity) and computational platforms (JAGS, NIMBLE, Stan).

SUBMITTER: Li M

PROVIDER: S-EPMC6027774 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Fitting mechanistic epidemic models to data: A comparison of simple Markov chain Monte Carlo approaches.

Li Michael M Dushoff Jonathan J Bolker Benjamin M BM

Statistical methods in medical research 20180701 7

Simple mechanistic epidemic models are widely used for forecasting and parameter estimation of infectious diseases based on noisy case reporting data. Despite the widespread application of models to emerging infectious diseases, we know little about the comparative performance of standard computational-statistical frameworks in these contexts. Here we build a simple stochastic, discrete-time, discrete-state epidemic model with both process and observation error and use it to characterize the eff ...[more]

PMID: 29846150

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Dataset Information

Fitting mechanistic epidemic models to data: A comparison of simple Markov chain Monte Carlo approaches.

Publications

Fitting mechanistic epidemic models to data: A comparison of simple Markov chain Monte Carlo approaches.

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