Thread by @kathmoreilly

New paper: Tooling-up for infectious disease transmission modelling. The Intro to the #Epidemics special issue on Computational Methods for Modelling an Infectious Disease (COMMAND) doi-org.ez.lshtm.ac.uk/10.1016/j.epid… @GrahamMedley @EleanorMRees @N_R_Waterlow @cmmid_lshtm In the series:

1. Choices and trade-offs in inference with infectious disease models by @sbfnk and A King doi.org/10.1016/j.epid… #IDmodelling #modelchoice

2. Desirable BUGS in models of infectious diseases by @kathmoreilly @drrachellowe and others doi.org/10.1016/j.epid… #JAGS #graphs

3. Approximate Bayesian Computation for infectious disease modelling by @amanda_minter and R Retkute doi.org/10.1016/j.epid… #ABCmethods #likelihoodfree

4. Introduction to particle Markov-chain
Monte Carlo for disease dynamics modellers. by @_akiraendo and others doi.org/10.1016/j.epid… #MCMC

5. Contemporary statistical inference for infectious disease models using Stan by Chatzilena and others doi.org/10.1016/j.epid… #Stan #statisticalinference

6. Spatial analysis made easy with linear regression and kernels by Milton and others doi.org/10.1016/j.epid… #spatialanalysis

And finally, huge thanks and kudos to those involved in reviewing the papers, and putting together the special issue. Funded by #HPRU modelling and methodology. (Intro was written late, due to, well, all hands to the #COVID19 deck) Thoughts / comments are encouraged 👍