Secondary Reports Estimation

Functions for estimating secondary epidemiological reports. More...

Collaboration diagram for Secondary Reports Estimation:

Subgroups
	Estimates Smoothing
	Functions for smoothing estimates using Gaussian processes.
	Observation Model
	Functions for modeling the observation process.

Functions
vector	calculate_secondary (vector scaled_reports, vector conv_reports, array[] int obs, int cumulative, int historic, int primary_hist_additive, int current, int primary_current_additive, int predict)
	Calculate secondary reports from primary reports.

Description

Functions for estimating secondary epidemiological reports.

This group contains functions from secondary.stan for estimating secondary epidemiological reports based on primary reports, considering various options for combining historical and current data.

Function Documentation

calculate_secondary()

vector calculate_secondary	(	vector	scaled_reports,
		vector	conv_reports,
		array[]int	obs,
		int	cumulative,
		int	historic,
		int	primary_hist_additive,
		int	current,
		int	primary_current_additive,
		int	predict )

#include </github/workspace/inst/stan/functions/secondary.stan>

Calculate secondary reports from primary reports.

Secondary Reports Functions

This group of functions handles the calculation and manipulation of secondary reports in the model. Secondary reports are derived from primary reports through various transformations and can represent different epidemiological quantities.

This function calculates secondary reports based on primary reports, considering various options for how to combine historical and current data. It supports both cumulative and non-cumulative targets, and additive or subtractive relationships between primary and secondary reports.

Parameters

scaled_reports	Vector of scaled primary reports
conv_reports	Vector of convolved primary reports
obs	Array of observed secondary reports
cumulative	Whether to use cumulative target (1) or not (0)
historic	Whether to use historical primary reports (1) or not (0)
primary_hist_additive	Whether historical primary reports are additive (1) or subtractive (0)
current	Whether to use current primary reports (1) or not (0)
primary_current_additive	Whether current primary reports are additive (1) or subtractive (0)
predict	Number of time points to predict

Returns

A vector of secondary reports

Definition at line 31 of file secondary.stan.

  {
  int t = num_elements(scaled_reports);
  vector[t] secondary_reports = rep_vector(0.0, t);
  // if predicting and using a cumulative target
  // combine reports with previous secondary data
  for (i in 1:t) {
    // update cumulative target
    if (cumulative && i > 1) {
      if (i > predict) {
        secondary_reports[i] = secondary_reports[i - 1];
      } else{
        secondary_reports[i] = obs[i - 1];
      }
    }
    // update based on previous primary reports
    if (historic) {
      if (primary_hist_additive) {
        secondary_reports[i] += conv_reports[i];
      } else{
        secondary_reports[i] = fmax(0, secondary_reports[i] - conv_reports[i]);
      }
    }
    // update based on current primary reports
    if (current) {
      if (primary_current_additive) {
        secondary_reports[i] += scaled_reports[i];
      } else{
        secondary_reports[i] -= scaled_reports[i];
      }
    }
    secondary_reports[i] = 1e-6 + secondary_reports[i];
  }
  return(secondary_reports);
}