Run QMRA on initial situation — run_qmra_initial

Run the full QMRA workflow

simulate inflow concentration, volume of exposure
calculate initial dose
simulate log reduction for treatment processes
calculate final dose
calculate infection probability, illness probability and dalys reduction
calculate annual total risk

Usage

run_qmra_initial_situation(
  scenario,
  pathogen,
  regulationLog,
  regulationConcentration
)

Arguments

scenario: data.frame scenario obtained with create_scenario function path of the scenario file
pathogen: character Name of the pathogen to simulate
regulationLog: data.frame regulation value of the log reduction to compare with simulation result
regulationConcentration: data.frame regulation value of the log reduction to compare with simulation result

Value

all_plots list of ggplot

Examples

# \donttest{
library(dplyr)
scenario <- create_scenario(system.file("input_cas_apprentissage_complet.xlsx", package = "ambre"))
regulation_reduction <- config_ambre$regulation$regulation_value |> 
  dplyr::filter(Country == "France") |>
  dplyr::select(-c(Concentration, Country, RegulationID))
regulation_concentration <- config_ambre$regulation$regulation_value |> 
  dplyr::filter(Country == "France") |>
  dplyr::select(-c(Country, RegulationID, Reduction))
run_qmra_initial_situation(scenario = scenario, 
                   pathogen = c("Campylobacter jejuni", "Escherichia coli"),
                   regulationLog = regulation_reduction,
                   regulationConcentration = regulation_concentration)
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 60, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 60, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.01 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 48, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 48, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.01 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 20, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 20, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.00 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 20, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 20, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.00 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 60, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 60, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.01 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 10, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 10, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.00 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 20, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 20, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.00 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 20, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 20, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.00 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 182, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 182, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.02 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 60, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 60, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.01 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 20, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 20, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.00 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 20, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 20, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.00 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 182, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 182, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.02 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 60, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 60, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.01 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 48, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 48, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.01 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 10, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 10, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.00 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 20, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 20, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.00 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 182, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 182, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.02 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 60, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 60, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.01 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 48, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 48, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.01 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 10, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 10, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.00 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 20, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 20, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.00 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 182, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 182, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.02 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 60, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 60, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.01 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 48, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 48, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.01 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 10, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 10, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.00 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated pathogen: Campylobacter jejuni
#> Create 1000 random distribution(s): uniform (n: 182, min: 100.000000, max: 5000.000000)
#> Simulated pathogen: Escherichia coli
#> Create 1000 random distribution(s): uniform (n: 182, min: 10000000.000000, max: 1000000000.000000)
#> Providing inflow events ... ok. (0.02 secs) 
#> Providing inflow paras ... ok. (0.00 secs) 
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 60, min: 0.001000, max: 0.001000)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 48, min: 0.001000, max: 0.001000)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 20, min: 0.000100, max: 0.000100)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 20, min: 0.000200, max: 0.000200)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 60, min: 0.001000, max: 0.001000)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 10, min: 0.001000, max: 0.001000)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 20, min: 0.000100, max: 0.000100)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 20, min: 0.000200, max: 0.000200)
#> Simulated exposure: volume per event
#> Create 1000 random distribution(s): triangle (n: 182, min: 0.001000, max: 0.005000, mode = 0.003000)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 60, min: 0.001000, max: 0.001000)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 20, min: 0.000100, max: 0.000100)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 20, min: 0.000200, max: 0.000200)
#> Simulated exposure: volume per event
#> Create 1000 random distribution(s): triangle (n: 182, min: 0.001000, max: 0.005000, mode = 0.003000)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 60, min: 0.001000, max: 0.001000)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 48, min: 0.001000, max: 0.001000)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 10, min: 0.001000, max: 0.001000)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 20, min: 0.000200, max: 0.000200)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 182, min: 0.003600, max: 0.003600)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 60, min: 0.001000, max: 0.001000)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 48, min: 0.001000, max: 0.001000)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 10, min: 0.001000, max: 0.001000)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 20, min: 0.000200, max: 0.000200)
#> Simulated exposure: volume per event
#> Create 1000 random distribution(s): triangle (n: 182, min: 0.010000, max: 0.015000, mode = 0.012500)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 60, min: 0.001000, max: 0.001000)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 48, min: 0.001000, max: 0.001000)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 10, min: 0.001000, max: 0.001000)
#> Simulated exposure: volume per event
#> Distribution set from 'triangle' to 'uniform' because 'min' equals 'max'
#> Create 1000 random distribution(s): uniform (n: 182, min: 0.003600, max: 0.003600)
#> Create 1000 random distribution(s): uniform (n: 60, min: 1.000000, max: 2.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 48, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 48, min: 4.000000, max: 8.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: P.5 - Natural die-off for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: P.5 - Natural die-off for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 20, min: 1.000000, max: 2.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 20, min: 1.000000, max: 2.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 60, min: 1.000000, max: 2.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 10, min: 1.000000, max: 2.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 20, min: 1.000000, max: 2.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 20, min: 1.000000, max: 2.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 182, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 182, min: 5.000000, max: 7.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: P.7 - Cooking for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: P.7 - Cooking for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 60, min: 1.000000, max: 2.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 20, min: 1.000000, max: 2.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 20, min: 1.000000, max: 2.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 182, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 182, min: 2.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 182, min: 2.000000, max: 2.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: P.8 - Drying for Bacteria
#> Simulated treatment: P.9 - Peeling for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: P.8 - Drying for Bacteria
#> Simulated treatment: P.9 - Peeling for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 60, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 60, min: 1.000000, max: 1.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 48, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 48, min: 4.000000, max: 4.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 10, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 10, min: 4.000000, max: 4.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 20, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 20, min: 1.000000, max: 1.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 182, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 182, min: 4.000000, max: 4.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 60, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 60, min: 1.000000, max: 1.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 48, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 48, min: 1.000000, max: 1.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 10, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 10, min: 1.000000, max: 1.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 20, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 20, min: 1.000000, max: 1.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 182, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 182, min: 1.000000, max: 1.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.1 - Micro-sprinkler for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 60, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 60, min: 2.000000, max: 2.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.2 - Surface drip irrigation for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.2 - Surface drip irrigation for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 48, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 48, min: 2.000000, max: 2.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.2 - Surface drip irrigation for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.2 - Surface drip irrigation for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 10, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 10, min: 2.000000, max: 2.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.2 - Surface drip irrigation for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.2 - Surface drip irrigation for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> Create 1000 random distribution(s): uniform (n: 182, min: 1.000000, max: 2.000000)
#> Create 1000 random distribution(s): uniform (n: 182, min: 2.000000, max: 2.000000)
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.2 - Surface drip irrigation for Bacteria
#> Simulated treatment: Q.1 - Activated Sludge for Bacteria
#> Simulated treatment: E.1.2 - Surface drip irrigation for Bacteria
#> Joining with `by = join_by(TreatmentID)`
#> Joining with `by = join_by(TreatmentID)`
#> $logreduction
#> $logreduction$Bacteria

#> 
#> 
#> $dalys
#> $dalys$`Campylobacter jejuni`

#> 
#> $dalys$`Escherichia coli`

#> 
#> 
#> $regul_matrix_log
#> 
#> $regul_matrix_concentration
#> 
# }