This R package contains functions to help interested researchers to estimate hospital resources required to treat patients infected by SARS-CoV-2.
This project is partly supported by the SPHINx project, funded by French National Research Agency.
Step 0: Installing the package:
- To install packages from GitHub, the package “devtools” needs to be installed first
install.packages("devtools")
library(“devtools”)- Then install the package from GitHub. Update or install all the required packages.
This command will install the latest “released” version of the package.
Step 1: Preparing the data
To use run the model for a specific country, you must provide the following inputs:
- Pre-infected table: a table with a number of infected cases by location (it can be a unique location)
- Population table: a table of the age-stratified population for each location. The population must be stratified into the same 17 age groups as the contact matrix.
Age-specific contact matrices are made available for 152 countries by Prem et al.
The tables must follow a specific format for the model to run:
-
Pre-infected table must have three columns (case sensitive):
- “Region”: a name of region, or location
- “Date”: must be identical for all rows, and in ISO-8601 format: “YYYY-MM-DD” (e.g. 2020-03-10)
- “preInfected”: an integer, the number of infected cases.
| Region | Date | preInfected |
|---|---|---|
| Auvergne-Rhone-Alpes | 2020-03-10 | 211 |
| Bourgogne-Franche-Comte | 2020-03-10 | 146 |
| Bretagne | 2020-03-10 | 81 |
-
Population table must have 18 columns:
- one column “Region”, which matches the column “Region” of the Pre-infected table
- 17 columns corresponding to the 17 age groups below, with the corresponding population for each region
Age groups: 0-4, 5-9, 10-14, 15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75-79, 80P
| Region | 0-4 | 5-9 | 10-14 | 15-19 | 20-24 | 25-29 | 30-34 | 35-39 | 40-44 | 45-49 | 50-54 | 55-59 | 60-64 | 65-69 | 70-74 | 75-79 | 80P |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Auvergne-Rhone-Alpes | 457173.55 | 479982.02 | 473564.70 | 446192.66 | 451363.51 | 479052.66 | 480439.02 | 514600.38 | 527126.18 | 514953.9 | 480081.26 | 484827.77 | 459145.57 | 438335.49 | 316475.54 | 255891.89 | 463162.94 |
| Bourgogne-Franche-Comte | 170161.14 | 193332.63 | 186968.52 | 157957.75 | 165824.19 | 178446.31 | 180879.02 | 200356.16 | 212177.87 | 213846.9 | 210669.37 | 188609.66 | 210515.08 | 201724.68 | 139177.96 | 117005.82 | 215064.96 |
| Bretagne | 182318.23 | 211639.94 | 208746.84 | 177964.79 | 172585.84 | 188743.31 | 198296.36 | 221251.36 | 226498.73 | 225150.0 | 222865.06 | 204764.17 | 222899.55 | 217450.95 | 145081.51 | 126929.06 | 227832.33 |
