Function reference • nimue

All functions
`add_age()`	Keep age groups
`add_weighted_efficacy()`	Extract weighted efficacies
`administer_first_dose()`	Administer first doses
`administer_second_dose()`	Administer second doses
`assign_doses()`	Assign N doses to age groups based on weightings by number of people eligible to be vaccinated
`beta_est_infectiousness()`	Estimate beta parameter for explicit model
`collapse_age()`	Collapse age groups
`coverage()`	Estimate coverage by age group
`default_durations()`	Return the default hospital durations for modelling defined in `squire` For more info see https://mrc-ide.github.io/squire/articles/parameters.html
`default_probs()`	Return the default probabilities for modelling defined in `squire` For more info see https://mrc-ide.github.io/squire/articles/parameters.html
`default_vaccine_pars()`	Return the default vaccine parameters for modelling
`eligable_for_second()`	Identify those eligible for a second dose
`extract_dose_number()`	Extract dose numbers administers
`format()`	Format vaccine model output
`format_internal()`	Internals of Format vaccine model output as data.frame
`init()`	Check and set up initial values for vaccine model
`nimue_deterministic_model()`	nimue model creation.
`p_all()`	Prioritise all
`p_elderly()`	Prioritise Elderly
`p_risk_elderly_working_children()`	Prioritise Working age risk group > Elderly > working age > Children
`p_risk_elderly_working_children_step()`	Prioritise Working age risk group > Elderly > working age > Children in a stepwise fashion
`p_working_elderly_children()`	Prioritise Working > Elderly > Children
`parameters()`	Vaccine parameters
`plot(<nimue_simulation>)`	nimue simulation plot
`run()`	Run the vaccine model
`strategy_matrix()`	Prioritisation matrix
`target_pop()`	Target number of individual in each age group to vaccinate
`weighted_efficacy()`	Estimate weighted efficacies

Reference

All functions