R Code for the paper "Estimating weekly excess mortality at sub-national level in Italy during the COVID-19 pandemic"

by Marta Blangiardo, Michela Cameletti, Monica Pirani, Gianni Corsetti, Marco Battaglini, Gianluca Baio https://www.medrxiv.org/content/10.1101/2020.06.08.20125211v2

Last version: 13/08/2020

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The following data are required for running the model:

• ./Data/MacroRegions.Rdata
• ./Data/mortality_temperature_data.Rdata
• ./Data/p20_att.txt
• ./Graphs/centro.graph
• ./Graphs/lombardia.graph
• ./Graphs/nordest.graph
• ./Graphs/nordovest.graph
• ./Graphs/sud.graph

For saving the outputs, create the following folders:

• ./Output/Females
• ./Output/Males

Requested R-packages: INLA, ggplot2, dyplyr, gridExtra. The file make.functions.R contains additional functions written specifically for the case study.

The code contained in model.run.R has to be run separately for each gender ("Females" or "Males") and area ("NordOvest","Lombardia","NordEst","Centro","Sud"). In particular, it:

1. prepares the data;
2. estimates the model by using r-inla and saves the output (creating files as ./Output/Sex/outputarea.Rdata, where Sex is "Females" or "Males" and area is one among "NordOvest","Lombardia","NordEst","Centro","Sud");
3. simulates from the posterior distributions by using the make.posteriors function (creating files as ./Output/Sex/posteriorsarea.Rdata, where Sex is "Females" or "Males" and area is one among "NordOvest","Lombardia","NordEst","Centro","Sud");
4. computes the predictions for 2020 by using the make.predictions function (creating files as ./Output/Sex/predictionsarea.Rdata, where Sex is "Females" or "Males" and area is one among "NordOvest","Lombardia","NordEst","Centro","Sud");
5. combines all the outcomes to produce the results for Italy. This creates the file ./Output/Sex/predItaly.Rdata" where Sex is "Females" or "Males";
6. produces plots saved as pdf files.