Helper functions to create and work with S3 class
<daedalus_infection>
objects for use with daedalus()
.
These objects store infection parameters for reuse and have methods for easy
parameter access and editing, as well as processing raw infection
characteristics for the DAEDALUS model.
Usage
daedalus_infection(name, ...)
is_daedalus_infection(x)
# S3 method for class 'daedalus_infection'
print(x, ...)
Arguments
- name
An epidemic name from among epidemic_names. Selecting an epidemic automatically pulls in infection parameters associated with the epidemic; these are stored as packaged data in
daedalus::infection_data
. Default infection parameters for epidemics can be over-ridden by passing them as a named list to...
.- ...
Other parameters passed to
print()
.- x
An object of the
<daedalus_infection>
class.
Value
daedalus_infection()
returns an object of the S3 class<daedalus_infection>
.is_daedalus_infection()
returns a logical for whether an object is a<daedalus_infection>
.print.daedalus_infection()
invisibly returns the<daedalus_infection>
objectx
. Called for printing side-effects.
Details
Included epidemics
Epidemics for which data are available are given below (pathogen in
parentheses). The string indicates the name that must be passed to the name
argument.
"sars_cov_1"
: SARS 2004 (SARS-CoV-1),"influenza_2009"
: influenza 2009 (influenza A H1N1),"influenza_1957"
: influenza 1957 (influenza A H2N2),"influenza_1918"
: influenza 1918 (influenza A H1N1),"sars_cov_2_pre_alpha"
: Covid-19 wild type (SARS-Cov-2 wild type),"sars_cov_2_omicron"
: Covid-19 Omicron (SARS-CoV-2 omicron),"sars_cov_2_pre_delta"
: (SARS-CoV-2 delta).
Infection parameters
All infections have the following parameters, which take default values
stored in the package under infection_data. Users can pass
custom values for these parameters as arguments via ...
.
r0
: A single numeric value for the basic reproduction value of the infection \(R_0\).sigma
: A single numeric value > 0.0 for the rate of transition from the exposed compartment to one of two infectious compartments.p_sigma
: A single numeric value in the range \([0.0, 1.0]\) for the proportion of infectious individuals who are also symptomatic. Asymptomatic individuals can have a different contribution to the force of infection from symptomatic individuals.epsilon
: A single numeric value for the relative contribution of asymptomatic infectious individuals to the force of infection (compared to symptomatic individuals).gamma_Is
: A single numeric value for the recovery rate of infectious individuals who are not hospitalised.gamma_Ia
: A single numeric value for the recovery rate from asymptomatic infection.ifr
: A numeric vector of lengthN_AGE_GROUPS
(4) for the age-specific infection fatality risk.gamma_H
: A numeric vector of lengthN_AGE_GROUPS
(4) for the age-specific recovery rate for individuals who are hospitalised.eta
: A numeric vector of lengthN_AGE_GROUPS
(4) for the age-specific hospitalisation rate for individuals who are infectious and symptomatic.omega
: A numeric vector of lengthN_AGE_GROUPS
(4) for the age-specific mortality rate for individuals who are hospitalised.rho
: A single numeric value for the rate at which infection-derived immunity wanes, returning individuals in the 'recovered' compartment to the 'susceptible' compartment.
Examples
# make a <daedalus_infection> object with default parameter values
daedalus_infection("sars_cov_1")
#> <daedalus_infection>
#> • Epidemic name: sars_cov_1
#> • R0: 1.75
#> • sigma: 0.217
#> • p_sigma: 0.867
#> • epsilon: 0.58
#> • rho: 0.003
#> • eta: 0.018, 0.082, 0.018, and 0.246
#> • omega: 0.012, 0.012, 0.012, and 0.012
#> • gamma_Ia: 0.476
#> • gamma_Is: 0.25
#> • gamma_H: 0.034, 0.034, 0.034, and 0.034
# modify infection parameters R0 and immunity waning rate
daedalus_infection("influenza_1918", r0 = 2.5, rho = 0.01)
#> <daedalus_infection>
#> • Epidemic name: influenza_1918
#> • R0: 2.5
#> • sigma: 0.909
#> • p_sigma: 0.669
#> • epsilon: 0.58
#> • rho: 0.01
#> • eta: 0.073, 0.064, 0.02, and 0.152
#> • omega: 0.025, 0.025, 0.025, and 0.025
#> • gamma_Ia: 0.4
#> • gamma_Is: 0.4
#> • gamma_H: 0.175, 0.175, 0.175, and 0.175