https://github.com/suahjl/vemethod-simulation-frictions

This repository contains files required to replicate the study "A Simulation Assessment of Vaccine Effectiveness Estimation Bias with Time-Varying Vaccine Coverage, and Heterogeneous Testing and Baseline Attack Rates" by Jing Lian Suah, Naor Bar-Zeev and Maria Deloria Knoll. Latest preprint can be found here at https://doi.org/10.1101/2022.08.25.22279235.
https://github.com/suahjl/vemethod-simulation-frictions

epidemiology methodology vaccine-effectiveness

Last synced: 5 months ago
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This repository contains files required to replicate the study "A Simulation Assessment of Vaccine Effectiveness Estimation Bias with Time-Varying Vaccine Coverage, and Heterogeneous Testing and Baseline Attack Rates" by Jing Lian Suah, Naor Bar-Zeev and Maria Deloria Knoll. Latest preprint can be found here at https://doi.org/10.1101/2022.08.25.22279235.

• Host: GitHub
• URL: https://github.com/suahjl/vemethod-simulation-frictions
• Owner: suahjl
• License: mit
• Created: 2022-06-21T01:58:47.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2024-11-04T08:20:39.000Z (over 1 year ago)
• Last Synced: 2024-11-04T09:22:10.262Z (over 1 year ago)
• Topics: epidemiology, methodology, vaccine-effectiveness
• Language: Python
• Homepage:
• Size: 36.2 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# vemethod-simulation-frictions

This repository contains files required to replicate the study "A Simulation Assessment of Vaccine Effectiveness Estimation Bias with Time-Varying Vaccine Coverage, and Heterogeneous Testing and Baseline Attack Rates" by Jing Lian Suah, Naor Bar-Zeev and Maria Deloria Knoll.

Link to the preprint can be found [here](https://doi.org/10.1101/2022.08.25.22279235).

This repository contains the following.

1. Python scripts required to replicate the study. These are in the main directory.

2. Output files from scripts. These are in the ```Output``` directory.

3. Latest draft article of the study, which is in the ```Article``` directory.

4. Latest slides summarising the study, which is in the ```Presentation``` directory.

# Ethical consideration

As this research uses only simulated data, and does not involve any human participants, no institutional review board (IRB) approval is required.

# Declaration of interests

JLS received support for attending academic meetings from AstraZeneca for work outside this paper. NB-Z received research grants from Merck, personal fees from Merck, and a research grant from Johnson & Johnson, all for unrelated work outside the scope of this paper. MDK received reports grants from Merck, personal fees from Merck, and grants from Pfizer, outside the submitted work.

# Computation

1. Simulation scripts (```VEMethod_Sim1b_Parallel_NoCI_CloudVersion.py``` and ```VEMethod_Sim1b_Parallel_NoCI_CloudVersion_ReSeed.py```) were run on a AWS EC2 c6i.32xLarge Amazon Linux instance (128 vCPUs); entire process took 415516 seconds (115.42 hours).

2. Post-simulation analyses (the remaining ```py``` files with ```VEMethod_``` suffixes) were run on Windows 10, 4-core (8 logical processors) 10th gen i7 and 11th gen i5 local machines, as no parallel processing is required.

# Replication

0. ```git clone suahjl/vemethod-simulation-frictions```

1. ```pip install -r requirements.txt```

2. ```VEMethod_Sim1b_Parallel_NoCI_CloudVersion```

3. ```VEMethod_Sim1b_Parallel_NoCI_CloudVersion_ReSeed```

4. Execute the following in any order.

	- ```VEMethod_Sim1b_Heatmap_GreekLetters.py```

	- ```VEMethod_Sim1b_PureDesignBias_Heatmap.py```

	- ```VEMethod_Sim1b_WaveSpecific_Heatmap.py```

	- ```VEMethod_Drivers1b.py```

	- ```VEMethod_RelDirection1b.py```


 \*Note 1: You may consider running the simulation using different seeds.


 \*Note 2: All output files are placed in the 'Output' folder for ease of navigation.

# Large (>100MB) output files

Due to file size limits on GitHub, 3 large output files can be accessed via dropbox [here](https://www.dropbox.com/sh/7sxgwfymrbkexb9/AADc4E3wb-FEsMr7SMIRqH4Ba?dl=0). These files are:

1. The full VE estimation bias heatmap of all study designs and all parameter sets from the simulation: *VEMethod_Sim1b_Parallel_NoCI_Wide_Gradient*

2. The above but with VE estimation biases rescaled to that the survival analysis cohort with true outcomes being observable: *VEMethod_Sim1b_Parallel_NoCI_Wide_Relative_Gradient*

3. The above but using absolute VE estimation biases: *VEMethod_Sim1b_Parallel_NoCI_Wide_Relative_Absolute Gradient*