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Preliminary results of COVID-19 vaccines: a Bayesian analysis

Nowadays, the COVID-19 pandemic pushed scientists from several countries to investigate/develop vaccines. Many countries, such as China, UK, India and US, are in a race to develop trustable vaccines, indicating high efficiencies.

                                                            Marcus Duarte - 20/11/2020
                                                            Data Scientist
                                                            mvcduarte at gmail.com    
                                                            https://www.linkedin.com/in/marcus-duarte-478bab81/    

Context

Recently, some health companies pointed out that their vaccines (e.g. Oxford, Sinovac, Pfizer and BioNtech) presented efficienty of ~90%-95% in premilinary results, being quite promissing! It means the rate of people who got the vaccine and got immunized by COVID-19 is around 95%, much higher than expected by WHO (World Health Organization).

Our study aim to evaluate how reliable those numbers are and calculate a probability that, base on those numbers, the vaccines fail. The PyMC3 package will be used to employ the MCMC (Monte Carlo Markov Chain) technique and define probabilities.

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A Bayesian Analysis to COVI19 vaccine

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