SPARSEMODr (version 1.2.0)

covid19_control: COVID19 Parameters Control Data Structure

Description

The COVID19 model uses parameters which are specific to the COVID19 model. This data structure affirms that required parameters are supplied, provides default values for optional parameters, and validates the data of each parameter.

Usage

covid19_control(
        input_N_pops=NULL,
        input_S_pops=NULL,
        input_E_pops=NULL,
        input_I_asym_pops=NULL,
        input_I_presym_pops=NULL,
        input_I_sym_pops=NULL,
        input_I_home_pops=NULL,
        input_I_hosp_pops=NULL,
        input_I_icu1_pops=NULL,
        input_I_icu2_pops=NULL,
        input_R_pops=NULL,
        input_D_pops=NULL,
        frac_beta_asym=0.55,
        frac_beta_hosp=0.05,
        delta=1/3.0,
        recov_a=1/6.0,
        recov_p=1/2.0,
        recov_s=1/6.0,
        recov_home=1/3.0,
        recov_icu1=1/8.0,
        recov_icu2=1/4.0,
        asym_rate=0.40,
        sym_to_icu_rate=0.015
    )

Value

Returns a named list of vectors that must be supplied to model_interface.

Arguments

input_N_pops

Integer Vector representing the total population for each county.

input_S_pops

Integer Vector representing the susceptible population for each county.

input_E_pops

Integer Vector representing the exposed population for each county.

input_I_asym_pops

Integer Vector representing the asymptomatic infected population for each county.

input_I_presym_pops

Integer Vector representing the presymptomatic infected population for each county.

input_I_sym_pops

Integer Vector representing the symptomatic infected population for each county.

input_I_home_pops

Integer Vector representing the infected and isolated at home population for each county.

input_I_hosp_pops

Integer Vector representing the hospitalized population for each county.

input_I_icu1_pops

Integer Vector representing the population for each county in ICU.

input_I_icu2_pops

Integer Vector representing the population for each county in ICU recovery.

input_R_pops

Integer Vector representing the recovered population for each county.

input_D_pops

Integer Vector representing the deaths for each county.

frac_beta_asym

An adjustment to beta accounting for asymptomatic individuals being less likely to transmit than symptomatic individuals. Default value is 0.55. Must be greater than zero and less than or equal to one.

frac_beta_hosp

An adjustment to beta accounting for hospitalized individuals being less likely to transmit than non-hospitalized individuals. Default value is 0.05. Must be greater than zero and less than or equal to one.

delta

Incubation period. Default value is 1/3.0. Must be greater than or equal to zero. Values above one are unusual.

recov_a

Recovery rate of asymptomatic individuals. Default value is 1/6.0. Must be greater than or equal to zero. Values above one are unusual.

recov_p

Recovery rate of presymptomatic individuals. Default value is 1/2.0. Must be greater than or equal to zero. Values above one are unusual.

recov_s

Recovery rate of symptomatic individuals. Default value is 1/6.0. Must be greater than or equal to zero. Values above one are unusual.

recov_home

Recovery rate of infected individuals in home isolation. Default value is 1/3.0. Must be greater than or equal to zero. Values above one are unusual.

recov_icu1

Recovery rate of individuals in ICU. Default value is 1/8.0. Must be greater than or equal to zero. Values above one are unusual.

recov_icu2

Recovery rate of individuals in ICU recovery. Default value is 1/4.0. Must be greater than or equal to zero. Values above one are unusual.

asym_rate

Proportion of presymtomatic individuals entering the asymptomatic stage. Default value is 0.40. Must be greater than zero and less than or equal to one.

sym_to_icu_rate

Proportion of symptomatic individuals entering ICU. Default value is 0.015. Must be greater than zero and less than or equal to one.

Author

Seth Borkovec, ; Joseph Mihaljevic,

Details

Defines a set of parameters specific to the COVID19 model. Adjustments to the model calculations can be made by specifying any or all of the optional parameters. If an optional parameter is not set, it will use the default value as specified above. If a parameter is outside the specified limits, execution will stop and an error message will be displayed. Some parameters may have values greater than one. While these situations may be unusual, execution will not stop but a warning message will be displayed.

Note: At least one of input_N_pops or input_S_pops must be supplied. If one is not supplied, it will be calculated within the class.

Note: At least one of input_E_pops, input_I_asym_pops, input_I_presym_pops, input_I_sym_pops, input_I_home_pops, input_I_hosp_pops, input_I_icu1_pops, and input_I_icu2_pops must be supplied with a nonzero population. Any of these population parameters not supplied will be assumed to be a vector of zeroes.

See Also

seir_control

Examples

## Data set for the examples:
N_pops <- rep(100000, 10)
E_pops <- c(0, 1, 0, 3, 2, 0, 14, 3, 0, 0)
S_pops <- N_pops - E_pops
I_asym_pops <- rep(0, 10)
I_presym_pops <- rep(0, 10)
I_sym_pops <- c(1, 0, 11, 0, 0, 5, 0, 0, 9, 0)
I_home_pops <- rep(0, 10)
I_hosp_pops <- rep(0, 10)
I_icu1_pops <- rep(0, 10)
I_icu2_pops <- rep(0, 10)
R_pops <- rep(0, 10)
D_pops <- rep(0, 10)

## Example using the default parameters:
covid19_control <- covid19_control(input_S_pops         = S_pops,
                                   input_E_pops         = E_pops)

## Example specifying some parameters:
covid19_control <- covid19_control(input_N_pops         = N_pops,
                                   input_I_sym_pops     = I_sym_pops,
                                   input_I_home_pops    = I_home_pops,
                                   input_I_hosp_pops    = I_hosp_pops,
                                   input_I_icu2_pops    = I_icu2_pops,
                                   input_D_pops         = D_pops,
                                   frac_beta_hosp       = 0.03)

## Example specifying all possible parameters:
covid19_control <- covid19_control(input_S_pops         = S_pops,
                                   input_E_pops         = E_pops,
                                   input_I_asym_pops    = I_asym_pops,
                                   input_I_presym_pops  = I_presym_pops,
                                   input_I_sym_pops     = I_sym_pops,
                                   input_I_home_pops    = I_home_pops,
                                   input_I_hosp_pops    = I_hosp_pops,
                                   input_I_icu1_pops    = I_icu1_pops,
                                   input_I_icu2_pops    = I_icu2_pops,
                                   input_R_pops         = R_pops,
                                   input_D_pops         = D_pops,
                                   frac_beta_asym       = 0.50,
                                   frac_beta_hosp       = 0.06,
                                   delta                = 0.25,
                                   recov_a              = 0.57,
                                   recov_p              = 0.62,
                                   recov_s              = 0.11,
                                   recov_home           = 0.28,
                                   recov_icu1           = 0.12,
                                   recov_icu2           = 0.29,
                                   asym_rate            = 0.65,
                                   sym_to_icu_rate      = 0.122)