Calculate R0 and Rc on an incidence dataset — calculate_r0_rc_fromdata

Uses the compartmental model to calculate R0 and Rc using data on incidence and the proportion of imported cases

calculate_r0_rc_fromdata_delay(
  df,
  f = 1/72,
  gamma = 1/223,
  r = 1/60,
  return.all = F,
  h.cutoff = 5e-08
)

Arguments

df: a dataframe containing the data, with one column called h containing the daily incidence and one variable called prop_import containing the proportion of imported cases among new infections. additional optional variables are alpha (effective care), beta (proportion of liver stage cure), rho (reporting rate) and omega (intensity of vector control)
f: relapse frequency
gamma: liver clearance rate
r: blood clearance rate
return.all: if TRUE, also returns delta and I estimates
h.cutoff: R0/Rc are not calculated for h values which are strictly inferior to h.cutoff

Value

A dataframe with 3 additional columns: lambda is the transmission rate, R0 is the basic reproduction number, Rc is the controlled reproduction number.

If lambda = -2, it means that the parameter combination does not correspond to a positive lambda solution with the model.

If lambda = -3, it means the incidence data contains missing values or infinite values or values below h.cutoff.

If return.all=T, delta and I are also included.

Details

If alpha is not provided in df, alpha=0. If beta is not provided in df, beta=1. If rho is not provided in df, rho=1. If omega is not provided in df, omega=1.