Description Usage Arguments Value
View source: R/import_model_source.R
Run the full simulation of daily importations
1 2 3 4 5 6 7 8 9 10 11 12 13 | run_daily_import_model(
input_data,
travel_data_monthly,
travel_data_daily,
travel_dispersion = 3,
travel_restrictions = NULL,
allow_travel_variance = FALSE,
tr_inf_redux = 0,
get_detection_time = FALSE,
param_list = list(incub_mean_log = log(5.89), incub_sd_log = log(1.74),
inf_period_nohosp_mean = 15, inf_period_nohosp_sd = 5, inf_period_hosp_mean_log =
1.23, inf_period_hosp_sd_log = 0.79)
)
|
input_data |
full importation input data, including case, travel, and population data |
travel_data_monthly |
monthly travel data between sources and destinations |
travel_dispersion |
how evenly the monthly travel should be distributed across days |
travel_restrictions |
data.frame of travel restrictions |
allow_travel_variance |
whether to sample from the travel variance |
tr_inf_redux |
proportion reduction in travel when individuals are infected |
get_detection_time |
logical; return importation detection or not |
n_sim |
number of simulations to run |
meanD_mat |
matrix of mean duration during which infected individuals can travel |
u_origin |
reporting rate, origin |
time_inftodetect |
Time from infection to detection |
incub_mean_log |
log mean incubation period |
incub_sd_log |
log sd of incubation period |
inf_period_hosp_mean_log |
infectious period of hospitalized, log-mean |
inf_period_hosp_sd_log |
infectious period of hospitalized, log-sd |
inf_period_nohosp_mean |
infectious period of non-hospitalized, shape |
inf_period_nohosp_sd |
infectious period of non-hospitalized, scale |
project_name |
project name, if saving in the function |
batch |
run batch, if saving in the function |
version |
run version, if saving in the function |
print_progress |
logical, whether to print the progress of the simulations |
cores |
number of cores for parallel processing |
time_inftotravel |
time from infection to traveling |
list consisting of two objects: 1) an array of importations by date, location, and simulation, 2) a dataframe with negative binomial parameters for each location and date
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.