Welcome to the Air Toxicity and Chronic Respiratory Diseases Kaggle competition! This competition is designed to challenge and inspire you to apply data science techniques in uncovering the underlying connections between air toxicity, specifically lead concentration, and the incidence of chronic respiratory diseases in the elderly population across the US. The dataset we provide for this competition combines data from the Global Burden of Disease (GBD) Results tool and the United States Environmental Protection Agency (EPA), giving you a unique opportunity to explore the multifaceted dynamics of health and environment. 

## About The Task

Your task is to develop a predictive model that can accurately predict the incidence of chronic respiratory diseases based on the given air toxicity parameters and other relevant variables. The 'Incidence' rate is the number of new cases divided by the population at the middle of the year for that age group and state.

Use the `train.csv` file to train your models, and make predictions on the `test.csv` dataset. The data has been split into training and testing sets to ensure fair evaluation of your model. Please make sure you understand the dataset structure, variables, and supplementary data provided.

## How to Contribute to the Scientific Knowledge

The way to contribute to the scientific knowledge is to share the notebooks with the EDA and prediction models. Thus, epidemiologists can find your notebooks and use your data analysis and model in their research. Participants are encouraged to use external data on air pollution. However, external public health data should be avoided so that the model has environmental data as input and public health data as output.