Package 'daedalus.compare'

A numeric vector.

The interval level as a numeric vector with values in the range $[0, 100]$. Defaults to 95 for the 95% interval.

A ⁠<data.table>⁠ resulting from run_scenarios().

A character vector giving names for replicates within each scenario.

A string for whether the data should be returned in "long" or "wide" format. Returning a 'wide' data.frame is only recommended when there is a small number of disease_tags, typically a triplet of "low", "medium", and "high" risk scenarios.

A ⁠<data.table>⁠ resulting from run_scenarios().

A ⁠<data.table>⁠ resulting from run_scenarios().

A character vector giving names for replicates within each scenario.

A string for whether the data should be returned in "long" or "wide" format. Returning a 'wide' data.frame is only recommended when there is a small number of disease_tags, typically a triplet of "low", "medium", and "high" risk scenarios.

A ⁠<data.table>⁠ resulting from run_scenarios().

A character vector giving names for replicates within each scenario.

A string for whether the data should be returned in "long" or "wide" format. Returning a 'wide' data.frame is only recommended when there is a small number of disease_tags, typically a triplet of "low", "medium", and "high" risk scenarios.

Additional arguments passed to daedalus::get_epidemic_summary(). If passing groups, only format = "long" is supported.

An infection name from among daedalus.data::epidemic_names.

A named list of ⁠<distribution>⁠ class objects provided by distributional, with names corresponding to daedalus.data::infection_parameter_names. These are used to generate samples draws from each distribution for the corresponding infection parameters. Arguments which vary by age are supported, with the drawn and scaled value treated as the median of the profile vector. See Examples.

An optional named list of two-element vectors, giving the ranges to which samples drawn using param_distributions should be rescaled. This allows easy rescaling of values drawn from bounded distributions (e.g. the Beta distribution). If passed, the list must have names corresponding to param_distribution names. When empty, the generated values are used without scaling. See Examples.

The number of samples to generate.

A country or territory object of class ⁠<daedalus_country>⁠, or a country or territory name from those included in the package; see daedalus.data::country_names, or a country ISO2 or ISO3 code; see daedalus.data::country_codes_iso2c and daedalus.data::country_codes_iso3c. Country-specific data such as the community and workplace contacts, the demography, and the distribution of the workforce into economic sectors is automatically accessed from package data for the relevant country name if it is passed as a string. To override package defaults for country characteristics, pass a ⁠<daedalus_country>⁠ object instead. See daedalus_country() for more.

A list of ⁠<daedalus_infection>⁠ objects. Must have a minimum length of 2.

A time-limited response strategy specified as a single ⁠<daedalus_npi>⁠ created using daedalus::daedalus_timed_npi(), or a list of such objects, or NULL for no response. Lists may include NULL, which is useful when comparing response scenarios against the no-response counterfactual. If a list is passed, all elements must be named, or the list may have no names, in which case synthetic names will be assigned and a message printed to screen. Lists with some elements named and some unnamed are not accepted.

A vaccination strategy specified as a single ⁠<daedalus_vaccination>⁠ created using daedalus::daedalus_vaccination(), or a list of such objects, or NULL for no response. Lists may include NULL, which is useful when comparing vaccination scenarios against the no-vaccination counterfactual. If a list is passed, all elements must be named, or the list may have no names, in which case synthetic names will be assigned and a message printed to screen. Lists with some elements named and some unnamed are not accepted.

A vector of integer-ish numbers giving the durations over which to run scenarios. Each scenario is run for each time_end. The intention is to be able to run response scenarios for different durations, to be able to generate a time-series of how different costs accumulate.

An optional named list with the names p_infectious, p_asymptomatic, and p_immune. p_infectious and p_asymptomatic give the proportion of infectious and symptomatic individuals in each age group and economic sector. Defaults to 1e-6 and 0.0 respectively. p_immune may be a single number in the range ⁠0.0 <= p_immune <= 1.0⁠ or a 4-element vector in that range (the number of age groups in the model), for the proportion of individuals in the population or in each age group that have some pre-existing immunity to infection (reduced susceptibility). See Details for more.