Evaluation of successful vaccination programs is important to combat potential pandemics in the future. Here, the countries were determined where herd immunity against COVID-19 was achieved, hence making these vaccination programs efficient. For this the end-date was predicted when each country can finish making vaccinations by modeling vaccination dinamics with logistic regression.

Dataframe from Kaggle was used that described COVID-19 World Vaccination Progress. Data was collected across every country and in the continents in general. The population ratio for herd immunity against common viruses including SARS-Cov-2 was found online.

The result of this project is a dataframe containing id the names of the countries and the predicted date when the population is fully vaccinated.

• Vaccination_rates.ipynb - Main notebook with description of the project, code, graphs, and commentaries.
• Vaccination_rates_supplementary.ipynb - Additional code needed to convert the notebook to html.