This function returns a nested list containing the model specifications in the function arguments. All defaults are set for the case of fitting a post-omicron COVID-19 model with joint inference of hospital admissions and data on wastewater viral concentrations
Usage
get_model_spec(
generation_interval = wwinference::default_covid_gi,
inf_to_count_delay = wwinference::default_covid_inf_to_hosp,
infection_feedback_pmf = wwinference::default_covid_gi,
include_ww = TRUE,
compute_likelihood = TRUE,
params = get_params(system.file("extdata", "example_params.toml", package =
"wwinference"))
)Arguments
- generation_interval
vector of a simplex (must sum to 1) describing the daily probability of onwards transmission, default is package data provided for the COVID-19 generation interval post-Omicron
- inf_to_count_delay
vector of a simplex (must sum to 1) describing the daily probability of transitioning from infection to whatever the count variable is, e.g. hospital admissions or cases. Default corresonds to the delay distribution from COVID-19 infection to hospital admission
- infection_feedback_pmf
vector of a simplex (must sum to 1) describing the delay from incident infection to feedback in the transmission dynamics. The default is the COVID-19 generation interval
- include_ww
Boolean indicating whether or not to include the wastewater data into the model, default is
TRUEwhich will get passed to stan and tell the model to evaluate the likelihood with the wastewater data- compute_likelihood
Boolean indicating whether or not to compute the likelihood using the data, default is
TRUEwhich will fit the model to the data. If set toFALSE, the model will sample from the priors.- params
a list of parameters corresponding to model priors and disease/data specific parameters. Default is for COVID-19 hospital admissions and viral concentrations in wastewater
Value
a list of model specs to be passed to the get_stan_data() function