Tackling Pandemic and Heart Disease with Predictive Tool
Predictive Models
Click below to try our models by changing model parameters!
XGBoost models were developed (performance plots shown on right) to predict case counts for COVID-19, Heart Stroke, and Coronary Heart based on individual county's # of people uninsured, people who responded 'never use mask', people who responded 'always use mask', poverty population, unemployed population, and median income. Click below to try our models by changing the model parameters!
1-minute guide on how to use the model
A quick way to predict the disease count in your area
1. Click the below button to start the model.
2.Type in the disease name
3. Type in the state's full name
4. Type in the county's full name
5. Type in % (with integer only) change for uninsured . (10 would result in 10% more in uninsured population and -10 would result in 10% less in uninsured population)
6. Type in % (with integer only)Â change for people never using mask
7. Type in % (with integer only) change for people always using maskÂ
8. Type in %Â (with integer only) change for poverty population
9. Type in %Â (with integer only) change for unemployed population
10. Type in %Â (with integer only) change for median income
11. Click Submit!
