This folder contains several files related to the Hackathon One - Air Quality.
A_Bayesian_Framework_for_Analysing_Air_Pollution_Effect_on_COVID_19_Infection_Rate.pdf - Document explaining the work done by the team. It contains the main ideas and conclusions as well as the description of the proposed model and its implementation.
BathAirSquad_summary_presentation - presentation, with description of the proposed model and its implementation. Link for video: https://drive.google.com/file/d/1itT-drrkAx7QJ3Zgf228DalWeQRMALTj/view
USA_Bayesian_Framework - is the main folder containing all the data, R files to run the proposed INLA Bayesian Model.
Folders:
raw_data - data as downloaded from the resources as described in the report.
processed_data - cleaned data ready to use as input for the model
INLA_results - contains folders automatically generatedby the model with the results for each type of model
as explained in the report.
Files:
INLA_Bayesian_Framework - main R file. Model proposed for this challenge. Details are described in the summary.
INLA_data_preprocessing - file for cleaning the raw data and creating the data frames used in INLA_Bayesian_Framework.R
Pollutant_data_preprocessing - file for cleaning the raw pollutant data
Italy_Bayesian_Framework - Additional implementation of the INLA Bayesian model proposed. It contains data for Italy and the corresponding R files to run the INLA Bayesian model as in the folder USA_Bayesian_Framework.
Folders:
raw_data - data as downloaded from the resources as described in the report.
processed_data - cleaned data ready to use as input for the model.
INLA_results - contains folders automatically generated by the model with the results for each type
of model as explained in the report.
Files:
INLA_Bayesian_Framework - main R file modified for Italy input data.
INLA_data_preprocessing - file for cleaning the raw data and creating the data frames used in INLA_Bayesian_Framework.R