The Impact of Seasonal Changes on Mortality Rates in Toronto

Overview

This project explores the potential correlation between seasonal changes and mortality rates in Toronto, specifically focusing on the winter and summer seasons. By analyzing death records, environmental factors, and temporal data, we aim to uncover whether extreme temperatures during these seasons contribute to a noticeable difference in the number of deaths. The findings from this research could have implications for public health policies, particularly in urban areas susceptible to temperature extremes.

File Structure

The repo is structured as:

• data/raw_data contains the raw as obtained from Death Registry Statistics by Open Data Toronto and simulated data.
• data/analysis_data contains the cleaned dataset and summarized dataset that was constructed.
• other contains details about LLM chat interactions and sketches.
• paper contains the files used to generate the paper, including the Quarto document and reference bibliography file, as well as the PDF of the paper.
• scripts contains the R scripts used to simulate, download, clean, and test data.

LLM (Large Language Model) Usage

This project used assistance from OpenAI’s GPT-4 model for guidance on structuring the project, writing code, and generating some of the textual content for documentation. The entire chat history is available in other/llms/usage.txt.

Acknowledgments

The main structure of this GitHub repository is based on the notes in Rohan Alexander's book and the stater folder in his Github, available at https://github.com/RohanAlexander/starter_folder and https://tellingstorieswithdata.com/. Special thanks to Rohan Alexander for making these resources available and for guiding the structuring of this project.