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Contains R code to reproduce simulations assessing the speed at which vaccines can pass through Phase III of vaccine trials during COVID-19 and the probability of success that these vaccines will have.

kieran-allsop/Vaccine-Efficacy

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Vaccine-Efficacy

Vaccine-Efficacy contains R code in markdown files that replicates all simulations and calculations in the AEI Economic Perspectives paper Awaiting the signal: Assessing the efficacy of COVID-19 vaccines and the article An October vaccine signal is possible but not certain, both written by Jim Capretta and Scott Ganz in addition to the article The Oxford Vaccine's True Efficacy Remains Uncertain written by Capretta, Ganz, and Kieran Allsop.

Overview

The markdown file vaccine_efficacy_replication.rmd makes it easy to reproduce all of the calculations in the paper Awaiting the signal: Assessing the efficacy of COVID-19 vaccines released October 1st 2020. In the paper Jim Capretta and Scott Ganz assess the length of time it takes for a vaccine to be approved through Phase III of testing and also assess other vaccine efficacy factors such as probability of success and the statistical power of different lengths of vaccine trials. All simulations in the file are based off of FDA and WHO guidelines for what is considered an effective vaccine.

The markdown file comparing_pfizer_replication.rmd reproduces all of the calculations in the article An October vaccine signal is possible but not certain released October 21st 2020. In this article, Capretta and Ganz assess the chances of success and the likelihood of observing an efficacy signal in the near future for the Pfizer vaccine candidate. They do so by comparing the statistical requirements set out by Pfizer and those set out by the WHO in each of their respective clinical protocols.

The markdown file astrazeneca_simulation.rmd runs the simulation in the article The Oxford Vaccine's True Efficacy Remains Uncertain released December 7th 2020. In this article, Kieran Allsop, Capretta, and Ganz assess the chances that the difference in vaccine efficacy rate of Oxford-AstraZeneca's different dosing regimens are luck rather than a true difference in effectiveness. They do so by using the preliminary results from Oxford-AstraZeneca's Phase III trials published on November 23rd 2020.

How to use Vaccine-Efficacy

View the code in vaccine_efficacy_replication.rmd. This markdown file contains all of the code and includes the part of the paper that that code relates to describing what is happening. Running each section in order will produce the desired simulations. There are sections for false positive analysis, required vaccine efficacy rates, estimating wait times, statistical power, and evaluating intermediate endpoints calculations. The file vaccine_efficacy_replication.html provides the same code and descriptions but in an easier to read format in a html compiler.

The markdown file comparing_pfizer_replication.rmd takes each estimation in the October 21st article calculated by the author and provides the code used to make those estimations. Be sure to install the packages listed at the start of the markdown file and define the functions used to make the calculations. The file comparing_pfizer_replication.html provides the same code and descriptions but in an easier to read format in a html compiler.

The markdown file astrazeneca_simulation.rmd will take you through the process of running the simulation found in the December 4th article. No additional packages should be needed to be installed to run this code. The file astrazeneca_simulation.html provides the same code and descriptions but in an easier to read format in a html compiler.

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Contains R code to reproduce simulations assessing the speed at which vaccines can pass through Phase III of vaccine trials during COVID-19 and the probability of success that these vaccines will have.

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