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Modelling COVID-19 daily case rates vs. vaccination rates using machine learning on a Canadian health dataset.

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Modeling COVID-19 Waves in Canada and Generating Predictions using FB Prophet

Using data from the Government of Canada on daily cases and to model the end of the pandemic in Canada

Data extraction and exploratory analysis

Data is extracted from Health Canada's website and explored in src/exploration.ipynb.

COVID Waves

Modeling

The data is modeled using Facebook's Prophet library in src/model.ipynb. The prediction plots are modeled with a PERIOD = 30 days using prophet's plotting function. As you can see, there's not much seasonality that can be modeled, since at the beginning of 2021 vaccines were made available in Canada.

Predictions

Next Steps and Further Questions

Using vaccination data, is it possible to finetune the models or would a more "complex" model be required to better predict COVID-19 cases in a longer time frame?


Disclaimer: Please note that this project is for my personal learning and is just for fun. Although the data is publicly accessible, these analyses should not be used to guide real-world decisions. Models used an idealized input and are not adequate representations of human behaviour.

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Modelling COVID-19 daily case rates vs. vaccination rates using machine learning on a Canadian health dataset.

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