Package index

Model function

Run the DAEDALUS integrated economic-epidemiological model

daedalus(): DAEDALUS model for health, social and economic costs of a pandemic

Class `<daedalus_country>`

Represent and access country or territory characteristics

daedalus_country() is_daedalus_country() print(<daedalus_country>): Represent countries and territories for DAEDALUS

Class `<daedalus_infection>`

Represent and access infection characteristics

daedalus_infection() is_daedalus_infection() print(<daedalus_infection>): Represent infection parameters for DAEDALUS

Class `<daedalus_vaccination>`

Represent and access vaccine investment scenarios

daedalus_vaccination() is_daedalus_vaccination() print(<daedalus_vaccination>): Represent vaccine investment scenarios for DAEDALUS

Class `<daedalus_output>`

Class to store model output for further processing

as_daedalus_output() validate_daedalus_output() is_daedalus_output() print(<daedalus_output>): Create and work with <daedalus_output> objects

Model output post-processing

Functions to process model output to calculate pandemic costs and other characteristics

get_costs(): Get epidemic costs from a DAEDALUS model run

get_incidence() get_epidemic_summary() get_new_vaccinations(): Calculate daily incidences and summarise epidemic measures

Package generics

Generics with methods for package S3 classes

get_data(): Get parameters from DAEDALUS classes

set_data(): Set parameters in DAEDALUS classes

Package data

Data included with the package

closure_data: Pandemic response strategy data for DAEDALUS

country_data: Country demographic data for DAEDALUS

infection_data infection_parameter_names epidemic_names: Infection characteristics for model epidemics

vaccination_scenario_data vaccination_scenario_names vaccination_parameter_names: Vaccine investment scenario parameters

economic_contacts: Economic sector contacts data for DAEDALUS

country_names country_codes_iso3c country_codes_iso2c: Country names and ISO codes for DAEDALUS

life_value country_gni: Values of statistical lives lost

Model constants

Useful constant used internally

N_AGE_GROUPS i_AGE_GROUPS N_VACCINE_STRATA N_VACCINE_DATA_GROUPS AGE_GROUPS i_WORKING_AGE i_SCHOOL_AGE N_ECON_SECTORS i_ECON_SECTORS i_EDUCATION_SECTOR N_ECON_STRATA i_NOT_WORKING DIM_AGE_GROUPS DIM_EPI_COMPARTMENTS DIM_ECON_SECTORS DIM_VACCINE_STRATA i_UNVACCINATED_STRATUM i_VACCINATED_STRATUM i_NEW_VAX_STRATUM VACCINE_GROUPS N_OUTPUT_COLS: DAEDALUS model constants

COMPARTMENTS N_MODEL_COMPARTMENTS N_EPI_COMPARTMENTS N_DATA_COMPARTMENTS i_EPI_COMPARTMENTS i_DATA_COMPARTMENTS i_S i_E i_Is i_Ia i_H i_R i_D i_dE i_dH i_dD N_INFECTION_SUBSYSTEM: Epidemiological compartments and indices

SUMMARY_MEASURES SUMMARY_GROUPS: Model output measures and groups for summaries and derived time-series

edu_effectiveness_remote edu_annual_ror work_expected_years earnings_loss_discount: Economic constants used in DAEDALUS

Internal functions

Functions used internally

country_name_from_arg(): Get country name from arg

daedalus-package: daedalus: Model health, social, and economic costs of a pandemic using DAEDALUS

daedalus_rhs(): DAEDALUS system of ODEs

get_beta(): Calculate transmission parameter from infection and contact parameters

get_closure_info(): Get closure time limits and calculate duration

get_distancing_coefficient(): Coefficient to scale transmission by public concern about the pandemic

get_hospitalisations(): Calculate total hospitalisations

get_value_lost_earnings(): Calculate the present value of lost earnings due to educational disruption

get_value_school_year(): Calculate the value of a school year

make_initial_state(): Generate a default initial state for DAEDALUS

make_response_threshold_event(): Event and root-finding functions to trigger response strategies

make_rt_end_event(): Event and root-finding functions to terminate epidemic responses

prepare_mutable_parameters(): Prepare mutable parameters for the DAEDALUS model

prepare_output(): Prepare DAEDALUS data

prepare_parameters(): Prepare country parameters for model

r_eff(): Calculate the effective R

scale_nu(): Scale vaccination rate by remaining eligibles

values_to_state(): Reshape a vector to the dimensions of the DAEDALUS state array