The epidemia package allows researchers to flexibly
specify and fit Bayesian epidemiological models in the style of
Flaxman et al. (2020)
. The
package leverages R's formula interface to parameterize the reproduction rate
in terms of covariates, and allows pooling of parameters.
The design of the package has been inspired by, and borrowed from, the rstanarm
package (Goodrich et al. 2020)
.
epidemia uses rstan (Stan Development Team 2020)
as the backend for fitting the models.
The primary model fitting function in epidemia is epim.
Flaxman S, Mishra S, Gandy A, Unwin HJT, Mellan TA, Coupland H, Whittaker C, Zhu H, Berah T, Eaton JW, Monod M, Perez-Guzman PN, Schmit N, Cilloni L, Ainslie KEC, Baguelin M, Boonyasiri A, Boyd O, Cattarino L, Cooper LV, Cucunubá Z, Cuomo-Dannenburg G, Dighe A, Djaafara B, Dorigatti I, van Elsland SL, FitzJohn RG, Gaythorpe KAM, Geidelberg L, Grassly NC, Green WD, Hallett T, Hamlet A, Hinsley W, Jeffrey B, Knock E, Laydon DJ, Nedjati-Gilani G, Nouvellet P, Parag KV, Siveroni I, Thompson HA, Verity R, Volz E, Walters CE, Wang H, Wang Y, Watson OJ, Winskill P, Xi X, Walker PGT, Ghani AC, Donnelly CA, Riley SM, Vollmer MAC, Ferguson NM, Okell LC, Bhatt S, Team ICCR (2020).
“Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe.”
Nature.
ISSN 1476-4687, doi: 10.1038/s41586-020-2405-7
.
Goodrich B, Gabry J, Ali I, Brilleman S (2020).
“rstanarm: Bayesian applied regression modeling via Stan.”
https://mc-stan.org/rstanarm/.
Stan Development Team (2020).
“RStan: the R interface to Stan.”
https://mc-stan.org/.
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