run_booster: Run the vaccine model

In mrc-ide/squire.page: Functions used in global-lmic-reports-orderly and other repos

Run the vaccine model

Description

Run the vaccine model

Usage

run_booster(
  country = NULL,
  population = NULL,
  tt_contact_matrix = 0,
  contact_matrix_set = NULL,
  R0 = 3,
  tt_R0 = 0,
  beta_set = NULL,
  time_period = 365,
  replicates = 10,
  seed = stats::runif(1, 0, 1e+08),
  prob_hosp = probs_booster$prob_hosp,
  prob_hosp_multiplier = probs_booster$prob_hosp_multiplier,
  tt_prob_hosp_multiplier = probs_booster$tt_prob_hosp_multiplier,
  prob_severe = probs_booster$prob_severe,
  prob_severe_multiplier = probs_booster$prob_severe_multiplier,
  tt_prob_severe_multiplier = probs_booster$tt_prob_severe_multiplier,
  prob_non_severe_death_treatment = probs_booster$prob_non_severe_death_treatment,
  prob_non_severe_death_no_treatment = probs_booster$prob_non_severe_death_no_treatment,
  prob_severe_death_treatment = probs_booster$prob_severe_death_treatment,
  prob_severe_death_no_treatment = probs_booster$prob_severe_death_no_treatment,
  rel_infectiousness = probs_booster$rel_infectiousness,
  rel_infectiousness_vaccinated = probs_booster$rel_infectiousness_vaccinated,
  dur_E = durs_booster$dur_E,
  tt_dur_E = durs_booster$tt_dur_E,
  dur_IMild = durs_booster$dur_IMild,
  tt_dur_IMild = durs_booster$tt_dur_IMild,
  dur_ICase = durs_booster$dur_ICase,
  tt_dur_ICase = durs_booster$tt_dur_ICase,
  dur_get_ox_survive = durs_booster$dur_get_ox_survive,
  tt_dur_get_ox_survive = durs_booster$tt_dur_get_ox_survive,
  dur_get_ox_die = durs_booster$dur_get_ox_die,
  tt_dur_get_ox_die = durs_booster$tt_dur_get_ox_die,
  dur_not_get_ox_survive = durs_booster$dur_not_get_ox_survive,
  dur_not_get_ox_die = durs_booster$dur_not_get_ox_die,
  dur_get_mv_survive = durs_booster$dur_get_mv_survive,
  tt_dur_get_mv_survive = durs_booster$tt_dur_get_mv_survive,
  dur_get_mv_die = durs_booster$dur_get_mv_die,
  tt_dur_get_mv_die = durs_booster$tt_dur_get_mv_die,
  dur_not_get_mv_survive = durs_booster$dur_not_get_mv_survive,
  dur_not_get_mv_die = durs_booster$dur_not_get_mv_die,
  dur_rec = durs_booster$dur_rec,
  dur_R = vaccine_pars_booster$dur_R,
  tt_dur_R = vaccine_pars_booster$tt_dur_R,
  dur_V = vaccine_pars_booster$dur_V,
  tt_dur_V = vaccine_pars_booster$tt_dur_V,
  vaccine_efficacy_infection = vaccine_pars_booster$vaccine_efficacy_infection,
  tt_vaccine_efficacy_infection = vaccine_pars_booster$tt_vaccine_efficacy_infection,
  vaccine_efficacy_disease = vaccine_pars_booster$vaccine_efficacy_disease,
  tt_vaccine_efficacy_disease = vaccine_pars_booster$tt_vaccine_efficacy_disease,
  primary_doses = vaccine_pars_booster$primary_doses,
  tt_primary_doses = vaccine_pars_booster$tt_primary_doses,
  booster_doses = vaccine_pars_booster$booster_doses,
  tt_booster_doses = vaccine_pars_booster$tt_booster_doses,
  second_dose_delay = vaccine_pars_booster$second_dose_delay,
  vaccine_coverage_mat = vaccine_pars_booster$vaccine_coverage_mat,
  vaccine_booster_initial_coverage =
    vaccine_pars_booster$vaccine_booster_initial_coverage,
  vaccine_booster_follow_up_coverage =
    vaccine_pars_booster$vaccine_booster_follow_up_coverage,
  protection_delay_rate = vaccine_pars_booster$protection_delay_rate,
  protection_delay_shape = vaccine_pars_booster$protection_delay_shape,
  hosp_bed_capacity = NULL,
  ICU_bed_capacity = NULL,
  tt_hosp_beds = 0,
  tt_ICU_beds = 0,
  seeding_cases = 20,
  seeding_age_order = NULL,
  init = NULL,
  use_dde = TRUE,
  ...
)

Arguments

country	Character for country beign simulated. WIll be used to generate population and contact_matrix_set if unprovided. Either country or population and contact_matrix_set must be provided.
population	Population vector (for each age group). Default = NULL, which will cause population to be sourced from country
tt_contact_matrix	Time change points for matrix change. Default = 0
contact_matrix_set	Contact matrices used in simulation. Default = NULL, which will generate this based on the country.
R0	Basic Reproduction Number. Default = 3
tt_R0	Change time points for R0. Default = 0
beta_set	Alternative parameterisation via beta rather than R0. Default = NULL, which causes beta to be estimated from R0
time_period	Length of simulation. Default = 365
replicates	Number of replicates. Default = 10
seed	Random seed used for simulations. Deafult = runif(1, 0, 10000)
prob_hosp	probability of hospitalisation by age. Default = c(0.000744192, 0.000634166,0.001171109, 0.002394593, 0.005346437, 0.010289885, 0.016234604, 0.023349169, 0.028944623, 0.038607042, 0.057734879, 0.072422135, 0.101602458, 0.116979814, 0.146099064, 0.176634654 ,0.180000000)
prob_hosp_multiplier	Time varying multiplier to probability of developing severe symptoms. Default = 1, which is no change to provided prob_hosp.
tt_prob_hosp_multiplier	Timing of changes to multiplier of probability of developing severe symptoms. Default = 0
prob_severe	Probability of developing severe symptoms by age. Default = c(0.05022296, 0.05022296, 0.05022296, 0.05022296, 0.05022296, 0.05022296, 0.05022296, 0.053214942, 0.05974426, 0.074602879, 0.103612417, 0.149427991, 0.223777304, 0.306985918, 0.385779555, 0.461217861, 0.709444444)
prob_severe_multiplier	Time varying multiplier to probability of hospitalisation. Default = 1, which is no change to provided prob_hosp.
tt_prob_severe_multiplier	Timing of changes to multiplier of probability of hospitalisation. Default = 0
prob_non_severe_death_treatment	Probability of death from non severe treated infection. Default = c(0.0125702, 0.0125702, 0.0125702, 0.0125702, 0.0125702, 0.0125702, 0.0125702, 0.013361147, 0.015104687, 0.019164124, 0.027477519, 0.041762108, 0.068531658, 0.105302319, 0.149305732, 0.20349534, 0.5804312)
prob_non_severe_death_no_treatment	Probability of death in non severe hospital inections that aren't treated
prob_severe_death_treatment	Probability of death from severe infection that is treated. Default = rep(0.5, 17)
prob_severe_death_no_treatment	Probability of death from severe infection that is not treated. Default = rep(0.95, 17)
rel_infectiousness	Relative infectiousness per age category relative to maximum infectiousness category. Default = rep(1, 17)
rel_infectiousness_vaccinated	Relative infectiousness per age category of vaccinated individuals relative to unvaccinated individuals. Default = rep(1, 17), which is no impact of vaccination on onwards transmissions
dur_E	Mean duration of incubation period (days). Default = 4.6
tt_dur_E	Times at which dur_E changes, default = 0.
dur_IMild	Mean duration of mild infection (days). Default = 2.1
tt_dur_IMild	Times at which dur_IMild changes, default = 0.
dur_ICase	Mean duration from symptom onset to hospital admission (days). Default = 4.5
tt_dur_ICase	Times at which dur_ICase changes, default = 0.
dur_get_ox_survive	Mean duration of oxygen given survive. Default = 5. Can be time varying, with timing of changes given by tt_dur_get_ox_survive.
tt_dur_get_ox_survive	Timing of changes in duration of oxygen given survive.
dur_get_ox_die	Mean duration of oxygen given death. Default = 5. Can be time varying, with timing of changes given by tt_dur_get_ox_die.
tt_dur_get_ox_die	Timing of changes in duration of oxygen given death.
dur_not_get_ox_survive	Mean duration without oxygen given survive. Default = 5
dur_not_get_ox_die	Mean duration without oxygen given death. Default = 5
dur_get_mv_survive	Mean duration of ventilation given survive. Default = 7.3. Can be time varying, with timing of changes given by tt_dur_get_mv_survive.
tt_dur_get_mv_survive	Timing of changes in duration of ventilation given survive.
dur_get_mv_die	Mean duration of ventilation given death. Default = 6. Can be time varying, with timing of changes given by tt_dur_get_mv_die.
tt_dur_get_mv_die	Timing of changes in duration of ventilation given death.
dur_not_get_mv_survive	Mean duration without ventilation given survive. Default = 7.3
dur_not_get_mv_die	Mean duration without ventilation given death. Default = 1
dur_rec	Duration of recovery after coming off ventilation. Default = 2
dur_R	Mean duration of naturally acquired immunity (days). Can be time varying, with timing of changes given by tt_dur_R.
tt_dur_R	Timing of changes in duration of natural immunity.
dur_V	Mean duration of vaccine-derived immunity (days) for partial protection and full protection. Should be a numeric vector of length 3, corresponding to the duration of time in each waned compartmenet after recieving a first dose and then for the two second dose compartments. Alternatively can be a list of values if this changes over time.
tt_dur_V	List of change times for dur_V.
vaccine_efficacy_infection	Efficacy of vaccine against infection. This parameter must either be a length 6 numeric (a single efficacy for each vaccine state (first dose, second dose, waned second dose, booster dose, and two waned second dose compartments)) or numeric vector with 17 columns and 6 rows (an efficacy for each age group and vaccine state). An efficacy of 1 will reduce FOI by 100 percent, an efficacy of 0.2 will reduce FOI by 20 percent etc. To specify changes in vaccine efficacy over time, vaccine efficacies must be provided as a list, with each list element being the efficacy at each time point specified by tt_vaccine_efficacy_infection. These efficacies must also be length 6 numeric or 6x17 numeric matrix.
tt_vaccine_efficacy_infection	Timing of changes in vaccine efficacy against infection. Default = 0, which assumes fixed efficacy over time. Must be the same length as the length of vaccine_efficacy_infection when provided as a list. Time changing efficacies can occur in response to changing vaccines being given and dosing strategy changes.
vaccine_efficacy_disease	Efficacy of partial vaccination against severe (requiring hospitilisation) disease (by age). This parameter must either be length 6 numeric (a single efficacy for each vaccine state (first dose, second dose, waned second dose, booster dose, and two waned second dose compartments)) or numeric vector with 17 columns and 6 rows (an efficacy for each age group and vaccine state). An efficacy of 1 will reduce the probability of hospitalisation by 100 percent, an efficacy of 0.2 will reduce the probability of hospitalisation by 20 percent etc. To specify changes in vaccine efficacy over time, vaccine efficacies must be provided as a list, with each list element being the efficacy at each time point specified by tt_vaccine_efficacy_disease. These efficacies must also be length 6 numeric or 5x17 numeric matrix.
tt_vaccine_efficacy_disease	Timing of changes in vaccine efficacy against disease. Default = 0, which assumes fixed efficacy over time. Must be the same length as the length of vaccine_efficacy_disease when provided as a list. Time changing efficacies can occur in response to changing vaccines being given and dosing strategy changes.
primary_doses	The maximum number of individuals who can be vaccinated with their first dose per day.
tt_primary_doses	Time change points for vaccine capacity (first_doses).
booster_doses	The maximum number of individuals who can be vaccinated with their booster dose per day.
tt_booster_doses	Time change points for vaccine capacity (booster_doses).
second_dose_delay	Delay between first dose and second dose in the initial series, this model assume all who get first doses get a second dose, default = 60 (days).
vaccine_coverage_mat	Vaccine coverage targets by age (columns) and priority (row)
vaccine_booster_initial_coverage	Age group eligibility for initial boosters (i.e. 1st booster dose), default = NULL means all are eligible. Format: 0 indicates not eligible, 1 indicates eligible.
vaccine_booster_follow_up_coverage	Age group eligibility for follow-up boosters (i.e. 2nd, 3rd, ... booster doses), default = NULL means all are eligible. Format: 0 indicates not eligible, 1 indicates eligible.
protection_delay_rate	Rate for the delay in development of vaccine protection, applied via gamma/erlang distribution, default = 1/14. If NULL no delay is applied.
protection_delay_shape	Shape for the delay in development of vaccine protection, applied via gamma/erlang distribution, default = 1/14. If NULL no delay is applied.
hosp_bed_capacity	General bed capacity. Can be single number of vector if capacity time-varies.
ICU_bed_capacity	ICU bed capacity. Can be single number of vector if capacity time-varies.
tt_hosp_beds	Times at which hospital bed capacity changes (Default = 0 = doesn't change)
tt_ICU_beds	Times at which ICU bed capacity changes (Default = 0 = doesn't change)
seeding_cases	Initial number of cases seeding the epidemic
seeding_age_order	Vector specifying the order in which seeds are allocated to ages. If NULL, seeds are distributed randomly within working ages. If specified, must be a vector of length 17 specifying the order seeds are allocated, e.g. 1:17 will allocate first seed to the youngest age group, then the second youngest and so on. Default = NULL
init	Initial conditions for simulation provided. Allows overriding if initial conditions start with an already infected population etc. Default = NULL.
use_dde	Use the dde solver (default is TRUE)
...	Additional arguments for solver

Value

Simulation output

mrc-ide/squire.page documentation built on May 27, 2023, 11:20 a.m.