WP4 SCCS sensitivity code for publication/Zenodo

WP4 SCCS sensitivity code for publication/Zenodo

Based on Readiness v3.0.1

Instructions:

To run the script this is the checklist of what to do:

1. Download the release and extract the folder.
2. Open the file 01_parameters_program.R inside the folder p_parameters
3. Open the to_run.R file and run just the parameters.
4. Check if everything is working correctly. Especially:
   • Missing packages should be installed automatically by the script but sometimes updating an existing one may cause an error.
   • If the script does not find the output of the pregnancy it produces an error (if the folder has been specified.
5. If everything is ok, run the script.

*In case of problems, please open an issue in this same repository.

Features to be aware of:

1. A computational graph is provided on this page which shows the interdependence between steps and outputs. This is useful if you need to understand what each step produces, and to rerun only a part of the script.
2. Data models for each intermediate dataset (D3, D4, D5) and final tables are stored in the documentation of the project available here
3. Every step is independent of the other. This means that if a bug occurs in a step, the previous ones can be skipped when the need to rerun comes.
4. Most final tables are exported in csv, RData, html and rtf
5. After each step the environment cleans itself automatically. This consequence is, if there is a RAM shortage issue then it is useless to try and rerun only a single step at a time. Instead, quickly open an issue and we will try to find a solution.

WP4 SCCS sensitivity code for publication

WP4 SCCS sensitivity code for publication

Based on Readiness v3.0.1

Instructions:

To run the script this is the checklist of what to do:

1. Download the release and extract the folder.
2. Open the file 01_parameters_program.R inside the folder p_parameters
3. Open the to_run.R file and run just the parameters.
4. Check if everything is working correctly. Especially:
   • Missing packages should be installed automatically by the script but sometimes updating an existing one may cause an error.
   • If the script does not find the output of the pregnancy it produces an error (if the folder has been specified.
5. If everything is ok, run the script.

*In case of problems, please open an issue in this same repository.

Features to be aware of:

1. A computational graph is provided on this page which shows the interdependence between steps and outputs. This is useful if you need to understand what each step produces, and to rerun only a part of the script.
2. Data models for each intermediate dataset (D3, D4, D5) and final tables are stored in the documentation of the project available here
3. Every step is independent of the other. This means that if a bug occurs in a step, the previous ones can be skipped when the need to rerun comes.
4. Most final tables are exported in csv, RData, html and rtf
5. After each step the environment cleans itself automatically. This consequence is, if there is a RAM shortage issue then it is useless to try and rerun only a single step at a time. Instead, quickly open an issue and we will try to find a solution.

Readiness v3.3.1

Readiness v3.3.1

Instructions:

To run the script this is the checklist of what to do:

1. Download the release and extract the folder.
2. Open the file 01_parameters_program.R inside the folder p_parameters
3. Open the to_run.R file and run just the parameters.
4. Check if everything is working correctly. Especially:
   • Missing packages should be installed automatically by the script but sometimes updating an existing one may cause an error.
   • If the script does not find the output of the pregnancy it produces an error (if the folder has been specified.
5. If everything is ok, run the script.

*In case of problems, please open an issue in this same repository.

Features to be aware of:

1. A computational graph is provided on this page which shows the interdependence between steps and outputs. This is useful if you need to understand what each step produces and to rerun only a part of the script.
2. Data models for each intermediate dataset (D3, D4, D5) and final tables are stored in the documentation of the project available here
3. Every step is independent of the others. If a bug occurs in a step, the previous ones can be skipped when the need to rerun comes.
4. Most final tables are exported in csv, RData, html and rtf
5. After each step the environment cleans itself automatically. This consequence is, if there is a RAM shortage issue then it is useless to try and rerun only a single step at a time. Instead, quickly open an issue and we will try to find a solution.

Readiness v2.0.1

Readiness v.2.0.1 @VAC4EU/cvm-readiness-daps @VAC4EU/cvm-readiness-important-persons

Full Changelog:

Minor fixes:

• Fixed stability issue regarding the importation of D3_pregnancy_final in step 03_T2_30

Major fixes

• IRs are now calculated just yearly in step 05_T3_30. This should sharply decrease RAM utilization for that step.

IMPORTANT:
minor fixes are ones that improve the stability of the script or are specific to a single datasource.
In this case, if you have already run step 03_T2_30 without errors you don't need to rerun it.

On the other hand, major fixes are almost always connected to the final outputs of the script and condition multiple DAPs.
This time, results are NOT impacted however intermediate datamodels are. So, if you are running or have finished running the script continue as is and post the results to DRE as usual. After that, or in case of an error in step 05_T3_30, run v2.0.1 (just steps after 05_T3_30, obviously).

Instructions:

I've updated instructions on how to run the script by including what to do in case of an updated version.
https://github.com/VAC4EU/CVM/wiki/Instruction-on-how-to-run-the-script

Readiness v2.0

This release should be run by everyone @VAC4EU/cvm-readiness-daps except PHARMO

Changelog

• updated codelist and variable names to adapt to the VAC4EU standards
• Major changes in most of the steps

To run the script this is the checklist of what to do:

1. Download the binary file (.zip) included in this release, extract the folder, and copy it to your server
2. Open the file 01_parameters_program.R inside the folder p_parameters
3. Modify the parameters dirinput and dirpregnancy with the folder where are stored the CDM tables and the output of the pregnancy script respectively
4. Open the to_run file and run just the parameters
5. Check if everything is working correctly. Especially:
   a) Missing packages should be installed automatically by the script but sometimes updating an existing one may cause an error.
   b) If the script does not find the output of the pregnancy in the specified folder it produces an error.
6. If everything is ok, run the script

Features to be aware of:

1. Every step is independent of each other (not independent from previous outputs obviously). This means that if you a bug occur in a step, the previous ones can be skipped when the need to rerun comes.
2. Most final tables are exported in csv, RData, html and rtf
3. After each step the environment cleans itself automatically. This consequence is, if there is a RAM shortage issue then it is useless to try and rerun only a single step at a time. Instead, quickly open an issue and we will try to find a solution.
4. A computational graph is provided on this page which shows the interdependence between steps and outputs. This is useful if you need to rerun only a part of the script.
5. Datamodels for each dataset are stored in the codebook on the ROC20 Sharepoint (here)

In case of problems open an issue on GitHub