retrieve parameters from a CSV file
make_state(
N = params[["N"]],
E0 = params[["E0"]],
type = "ICU1h",
state_names = NULL,
use_eigvec = NULL,
params = NULL,
x = NULL,
normalize = FALSE,
ageify = NULL,
vaxify = NULL,
testify = NULL
)population size
initial number exposed
(character) specify what model type this is intended
for (e.g., "ICU1", "CI"); determines state names
vector of state names, must include S and E
use dominant eigenvector to distribute non-Susc values
to zero: default is to set this to TRUE if params is non-NULL
parameter vector (looked in for N and E0)
proposed (named) state vector; missing values will be set
(logical) should the state vector be normalized to sum to 1?
expand state vector to include different age groups (??)
expand state vector to include groups that have 1-2 vaccine doses (??)
expand state vector to include testing compartments (untested, neg waiting, pos waiting, pos received) ?
The parameters that must be set are:
\( N: \) population size
\( \beta_0: \) transmission rate
\( 1/\sigma: \) mean latent period
\( 1/\gamma_a: \) mean infectious period for asymptomatic individuals
\( ... \)
generate initial state vector
"CI" refers to the Stanford group's
"covid intervention" model.
Other classic_macpan:
add_d_log(),
add_updated_vaxrate(),
aggregate_agecats(),
calibrate_comb(),
calibrate(),
check_age_cat_compatibility(),
check_contact_rate_setting(),
col_multiply(),
condense_age(),
condense_params_vax(),
condense_state(),
condense_vax(),
dev_is_tikz(),
do_step(),
expand_params_age(),
expand_params_desc_age(),
expand_params_desc_variant(),
expand_params_desc_vax(),
expand_params_mistry(),
expand_params_variant(),
expand_params_vax(),
expand_state_age(),
expand_state_vax(),
expand_stateval_testing(),
fix_pars(),
fix_stored(),
forecast_ensemble(),
forecast_sim(),
getData(),
get_GI_moments(),
get_Gbar(),
get_R0(),
get_doses_per_day(),
get_evec(),
get_kernel_moments(),
get_opt_pars(),
get_r(),
invlink_trans(),
make_betavec(),
make_beta(),
make_jac(),
make_ratemat(),
make_test_wtsvec(),
make_vaxrate(),
mk_Nvec(),
mk_agecats(),
mk_contact_rate_setting(),
mk_mistry_Nvec(),
mk_pmat(),
mk_vaxcats(),
mle_fun(),
non_expanded_states,
rExp(),
read_params(),
repair_names_age(),
restore(),
run_sim_ageify(),
run_sim_break(),
run_sim_loglin(),
run_sim_mobility(),
run_sim_range(),
run_sim(),
show_ratemat(),
testify(),
texify(),
trans_state_vars(),
update_contact_rate_setting(),
update_foi(),
update_params_mistry(),
vis_model(),
write_params()
p <- read_params("ICU1.csv")
make_state(N=1e6,E0=1)
#> S E Ia Ip Im Is H H2 ICUs ICUd D
#> 999999 1 0 0 0 0 0 0 0 0 0
#> R X V
#> 0 0 0
#> attr(,"epi_cat")
#> [1] "S" "E" "Ia" "Ip" "Im" "Is" "H" "H2" "ICUs" "ICUd"
#> [11] "D" "R" "X" "V"
#> attr(,"class")
#> [1] "state_pansim"
make_state(params=p)
#> S E Ia Ip Im Is H H2 ICUs ICUd D
#> 999995 3 1 0 1 0 0 0 0 0 0
#> R X V
#> 0 0 0
#> attr(,"epi_cat")
#> [1] "S" "E" "Ia" "Ip" "Im" "Is" "H" "H2" "ICUs" "ICUd"
#> [11] "D" "R" "X" "V"
#> attr(,"class")
#> [1] "state_pansim"