tetano
Editor, Senior Moderator
Epidemics. 2019 Dec 20;30:100383. doi: 10.1016/j.epidem.2019.100383. [Epub ahead of print] [h=1]Choices and trade-offs in inference with infectious disease models.[/h]
Funk S[SUP]1[/SUP], King AA[SUP]2[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] Inference using mathematical models of infectious disease dynamics can be an invaluable tool for the interpretation and analysis of epidemiological data. However, researchers wishing to use this tool are faced with a choice of models and model types, simulation methods, inference methods and software packages. Given the multitude of options, it can be challenging to decide on the best approach. Here, we delineate the choices and trade-offs involved in deciding on an approach for inference, and discuss aspects that might inform this decision. We provide examples of inference with a dataset of influenza cases using the R packages pomp and rbi.
Copyright ? 2019. Published by Elsevier B.V.
[h=4]KEYWORDS:[/h] Bayesian; Frequentist; Infectious disease model; Inference; Model fitting
PMID: 32007792 DOI: 10.1016/j.epidem.2019.100383
Free full text
Funk S[SUP]1[/SUP], King AA[SUP]2[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] Inference using mathematical models of infectious disease dynamics can be an invaluable tool for the interpretation and analysis of epidemiological data. However, researchers wishing to use this tool are faced with a choice of models and model types, simulation methods, inference methods and software packages. Given the multitude of options, it can be challenging to decide on the best approach. Here, we delineate the choices and trade-offs involved in deciding on an approach for inference, and discuss aspects that might inform this decision. We provide examples of inference with a dataset of influenza cases using the R packages pomp and rbi.
Copyright ? 2019. Published by Elsevier B.V.
[h=4]KEYWORDS:[/h] Bayesian; Frequentist; Infectious disease model; Inference; Model fitting
PMID: 32007792 DOI: 10.1016/j.epidem.2019.100383
Free full text