get_r_effective_df: Create a data frame with R effective, varying parameters

In HopkinsIDD/tti: Test-trace-isolate Recursive Equations

Create a data frame with R effective, varying parameters

Description

This function allows you to input numeric scalars or vectors for each parameter to examine how the effective R will vary across configurations. Two values (stoch, n_iter) require single values.

Usage

get_r_effective_df(
  alpha = 0.2,
  R = 2.5,
  kappa = 0.5,
  eta = 0.5,
  nu = 4,
  t_ds = 3,
  t_da = 3,
  t_qcs = 3,
  t_qca = 3,
  t_qhs = 3,
  t_qha = 3,
  t_q = 3,
  omega_c = 0.5,
  omega_h = 0.5,
  omega_q = 0.5,
  quarantine_days = Inf,
  rho_s = 0.1,
  rho_a = 0.05,
  t_incubation = 5.5,
  offset = -2.31,
  shape = 1.65,
  rate = 0.5,
  isolation_days = Inf,
  stoch = FALSE,
  theta = NULL,
  n_inf = NULL,
  n_iter = NULL
)

Arguments

alpha	Numeric value or vector of numeric values between 0 and 1. The probability of an asymptomatic infection. Default 0.2.
R	Positive numeric value or vector of positive numeric values. Reproduction number. Default: 2.5.
kappa	Positive numeric value or vector of positive numeric values. Relative transmissibility of an asymptomatic individual compared to a symptomatic individual. Default: 0.5.
eta	Numeric value or vector of numeric values between 0 and 1. Probability contact is a household contact. Default: 0.5
nu	Positive numeric value or vector of positive numeric values. Relative risk of infection for a household contact compared to a community contact. Default: 4.
t_ds	Non-negative numeric value. Time delay from symptom onset to isolation in detected symptomatic person. Default: 3.
t_da	Non-negative numeric value. Time delay from symptom onset to isolation in detected asymptomatic person. Default: 3.
t_qcs	Non-negative numeric value. Time delay from symptomatic index cases's symptom onset to quarantine of community contacts. Default: 3.
t_qca	Non-negative numeric value. Time delay from asymptomatic index cases's symptom onset to quarantine of community contacts. Default: 3.
t_qhs	Non-negative numeric value. Time delay from symptomatic index cases's symptom onset to quarantine of household contacts. Default: 3.
t_qha	Non-negative numeric value. Time delay from asymptomatic index cases's symptom onset to quarantine of community contacts. Default: 3.
t_q	Non-negative numeric value. Time delay from quarantined index cases's symptom onset to quarantine of contacts. Default: 3.
omega_c	Numeric value or vector of numeric values between 0 and 1. The probability of being traced and quarantined given community contact of a person. Default: 0.5.
omega_h	Numeric value or vector of numeric values between 0 and 1. The probability of being traced and quarantined given household contact of a person. Default: 0.5.
omega_q	Numeric value or vector of numeric values between 0 and 1. The probability of being traced and quarantined given quarantine contact of a person. Default: 0.5.
quarantine_days	Positive numeric value. The number of days contacts are told to quarantine. Default: Inf.
rho_s	Numeric value or vector of numeric values between 0 and 1. The probability of detection and isolation given symptomatic. Default: 0.1.
rho_a	Numeric value or vector of numeric values between 0 and 1. The probability of detection and isolation given asymptomatic. Default: 0.05.
t_incubation	Non-negative numeric value. The estimated average incubation time. Default: 5.5.
offset	Numeric. Offset of infectiousness compared to symptoms onset. Default is -2.31.
shape	Numeric. Shape of the gamma distribution of infectious period. Default is 1.65.
rate	Numeric. Rate of the gamma distribution of infectious period. Default is 0.5.
isolation_days	Numeric greater than 0. Number of days from symptom onset to end of isolation. Default is Inf implying isolation until no longer infectious.
stoch	Logical. Whether to run stochastic model with overdispersion. Default is FALSE.
theta	Non-negative numeric. Required only if stoch=TRUE. Overdispersion parameter for negative binomial distribution. Default NULL.
n_inf	Non-negative numeric. Required only if stoch=TRUE. Number of infections (or effective population size of infected individuals). Default NULL.
n_iter	Non-negative numeric. Required only if stoch=TRUE. Number of iterations of stochastic model to run for each unique parameter value. Default NULL.

Value

Data frame with columns:

• r_effective: The R effective value

• prop_identified: The proportion of infections identified

• alpha

• R

• kappa

• eta

• nu

• t_ds

• t_da

• t_qcs

• t_qca

• t_qhs

• t_qha

• t_q

• omega_c

• omega_h

• omega_q

• quarantine_days

• isolation_days

• rho_s

• rho_a

• theta if stoch=TRUE

• n_inf if stoch=TRUE

Examples

get_r_effective_df(alpha = c(0.1, 0.2), kappa = c(0.5, 0.6))
get_r_effective_df(stoch = TRUE, theta = c(0.1, 0.3), n_inf = 100, n_iter = 100)

HopkinsIDD/tti documentation built on May 24, 2022, 1:11 a.m.