run_backnow {linelistBayes}

Run Back Calculation and Estimate Reproduction Numbers

Description

This function performs a back-calculation based on provided epidemic case count data, estimating the time distribution of infections and reproduction numbers (r(t)). It utilizes extensive input checks and parameter validation to ensure robust model execution.

Usage

run_backnow(
  input,
  MAX_ITER,
  norm_sigma,
  sip,
  NB_maxdelay,
  NB_size,
  n_trunc = NB_size,
  workerID = NULL,
  printProgress = 0,
  preCalcTime = TRUE,
  ...
)

Arguments

input

A data frame or list that includes epidemic data with either class 'caseCounts' or 'lineList'. The input type determines initial processing steps.

MAX_ITER

Integer, maximum number of iterations for the back-calculation model. Requires at least 2000 iterations; high numbers can significantly increase runtime.

norm_sigma

Numeric, the standard deviation for the normal distribution in the Bayesian framework.

sip

Vector of numeric values specifying the serial interval probabilities.

NB_maxdelay

Integer, the maximum delay for the right-truncated negative binomial distribution used in modeling.

NB_size

Integer, the size parameter for the negative binomial distribution.

n_trunc

Integer, the truncation number for the final result matrices (defaults to 'NB_size').

workerID

Optional integer to specify a worker ID for parallel processing frameworks; defaults to 0.

printProgress

Binary integer (0 or 1), specifying whether to print progress to console; affects performance.

preCalcTime

Boolean, if TRUE, the function calculates a preliminary runtime estimate before full execution.

...

Additional arguments passed to underlying functions when converting input to the required format.

Details

The function ensures input data is of the correct class and processes it accordingly. It handles different input classes by either converting 'caseCounts' to 'lineList' or directly using ‘lineList'. The function stops with an error if the input doesn’t meet expected standards. It performs simulations to estimate both the back-calculation of initial infections and reproduction numbers over time, while checking and adjusting for potential NA values and ensuring that all conditions for the model parameters are met. Output includes estimates of initial infections and reproduction numbers along with diagnostic statistics.

Value

an object of class 'backnow' with the following structure

- est_back: back-calculated case counts

- est_back_date: dates for back-calculated case counts

- est_rt: back-calculated R(r)

- est_rt_date: dates for back-calculated R(t)

- geweke_back: Geweke diagnostics for the estimated back-calculation of cases

- geweke_rt; Geweke diagnostics for R(t)

- report_date: a vector of dates, matches reported_cases

- report_cases: a vector of reported cases

- MAX_ITER: the input for 'MAX_ITER'

- norm_sigma: the input for 'norm_sigma'

- NB_maxdelay: the input for 'NB_maxdelay'

- si: the input for serial interval 'si'

- NB_size: the input for 'NB_size'

Examples

data("sample_onset_dates")
data("sample_report_dates")
line_list <- create_linelist(sample_report_dates, sample_onset_dates)
sip <- si(14, 4.29, 1.18)
results <- run_backnow(
  line_list, 
  MAX_ITER = as.integer(2000), 
  norm_sigma = 0.5, 
  sip = sip,
  NB_maxdelay = as.integer(20), 
  NB_size = as.integer(6), 
  workerID = 1, 
  printProgress = 1, 
  preCalcTime = TRUE)