HMS_Final: Model Validation

General Info:

• Code Refactoring: Model Output Valuation
• Team members: Sameer Ali, Ana Pereda
• Format: Refactoring a piece of existing code (Option 2)

Overall Goal:

To create an R script that simulates a population, disease incidence, mortality data and vaccine coverage and then automates validation of model valuation

Detailed Plans and timeline:

30/11/22 Submit proposal/ discuss structure

3/12/22 Data Simulation

8/12/22 Code Refactoring

~ Time permitting ~ CLI / Graph output / Final validation report output

12/12/22 Present

14/12/22 Submit

How to Run

Simulation

If running a simulation, run the Simulation.R script which will autopopulate the test_files

Test Files

If including preprocessed data, add the following files:

• mu.csv = Mortality Rate
• coverage.csv = Vaccine Coverage
• incidence.csv = Incidence
• population.csv = Population
• model_out.csv = Model Output

Running With Simulation

Within the "Data" file there is a simulation.R script that will create the necessary .csv for data validation.

Running refact_script_validation

With the simulation data prepared and correctly named, the validation can be executed by running the refact_script_validation.R script. This script will create a gui for inputting the model parameters, and calls functions.R for data reshapping. refact_script_validation.R will output a dataframe of the comparison between the expected and calculated models. This dataframe can be used for making plots, or can be otherwise outputted (not implemented).