The Lyme Forecast

1. early every state, cases are reported based on the county of residence, not necessarily the county
The Lyme Forecast

2. early every state, cases are reported based on the county of residence, not necessarily the county
The Lyme Forecast
Using climate to predict
the prevalence of
Lyme disease
through time

3. early every state, cases are reported based on the county of residence, not necessarily the county
Lyme data

4. early every state, cases are reported based on the county of residence, not necessarily the county
Lyme data
Barnstable County, MA

5. early every state, cases are reported based on the county of residence, not necessarily the county
Lyme data
Barnstable County, MA
What to expect from coming years?

6. early every state, cases are reported based on the county of residence, not necessarily the county
Lyme data
Barnstable County, MA
What to expect from coming years?
CDC slow to confirm/update

7. early every state, cases are reported based on the county of residence, not necessarily the county
Lyme data
Barnstable County, MA
What to expect from coming years?
CDC slow to confirm/update
Must rely on outdated info

8. early every state, cases are reported based on the county of residence, not necessarily the county
Lyme data
Barnstable County, MA
What to expect from coming years?
CDC slow to confirm/update
Must rely on outdated info
Build a Lyme model

9. early every state, cases are reported based on the county of residence, not necessarily the county
Lyme data
Barnstable County, MA
What to expect from coming years?
CDC slow to confirm/update
Must rely on outdated info
Build a Lyme model
Fresher data, faster turnaround

10. early every state, cases are reported based on the county of residence, not necessarily the county
Climate
Barnstable County, MA

11. early every state, cases are reported based on the county of residence, not necessarily the county
Climate
Barnstable County, MA
Climate

12. early every state, cases are reported based on the county of residence, not necessarily the county
Climate
Barnstable County, MA
Climate
Temperature, Precipitation

13. early every state, cases are reported based on the county of residence, not necessarily the county
Climate
Barnstable County, MA
Climate
Temperature, Precipitation
Canonical set of 19 features

14. early every state, cases are reported based on the county of residence, not necessarily the county
Climate
Barnstable County, MA
Climate
Temperature, Precipitation
Canonical set of 19 features
(ex: temp. in hottest month,
precip. in wettest month, etc.)

15. early every state, cases are reported based on the county of residence, not necessarily the county
Climate
Barnstable County, MA
Climate
Temperature, Precipitation
Canonical set of 19 features
(ex: temp. in hottest month,
precip. in wettest month, etc.)
Population count/density

16. early every state, cases are reported based on the county of residence, not necessarily the county
Data

17. early every state, cases are reported based on the county of residence, not necessarily the county
Data
9 states, 248 counties, 15 years

18. early every state, cases are reported based on the county of residence, not necessarily the county
Data
9 states, 248 counties, 15 years
551 tables to manage/query!

19. early every state, cases are reported based on the county of residence, not necessarily the county
Data
9 states, 248 counties, 15 years
551 tables to manage/query!
3720 samples, 24 features

20. early every state, cases are reported based on the county of residence, not necessarily the county
Algorithm
9 states, 248 counties, 15 years
551 tables to manage/query!
3720 samples, 24 features

21. early every state, cases are reported based on the county of residence, not necessarily the county
Algorithm
Predicting a quantity (Lyme cases)
9 states, 248 counties, 15 years
551 tables to manage/query!
3720 samples, 24 features

22. early every state, cases are reported based on the county of residence, not necessarily the county
Algorithm
Predicting a quantity (Lyme cases)
Random Forest Regressor
9 states, 248 counties, 15 years
551 tables to manage/query!
3720 samples, 24 features

23. early every state, cases are reported based on the county of residence, not necessarily the county
Algorithm
Predicting a quantity (Lyme cases)
Random Forest Regressor
Split dataset into training/validation sets
9 states, 248 counties, 15 years
551 tables to manage/query!
3720 samples, 24 features

24. Lyme disease
sqrt(Actual)
sqrt(Predicted)

25. Lyme disease
sqrt(Actual)
sqrt(Predicted)
R2
on
validation set:
0.78

26. early every state, cases are reported based on the county of residence, not necessarily the county
Demo!

27. Roger Shaw

28. Roger Shaw
Ph.D. University of Texas at Austin

29. Roger Shaw
Ph.D. University of Texas at Austin
Ecology, Evolution, and Behavior

30. Roger Shaw
Ph.D. University of Texas at Austin
Ecology, Evolution, and Behavior

31. Roger Shaw
Ph.D. University of Texas at Austin
Ecology, Evolution, and Behavior

32. Bioclim
• Annual Mean Temperature
• Mean Diurnal Range
• Isothermality
• Temperature Seasonality
• Max Temperature of Warmest Month
• Min Temperature of Coldest Month
• Temperature Annual Range
• Mean Temperature of Wettest Quarter
• Mean Temperature of Driest Quarter
• Mean Temperature of Warmest Quarter
• Mean Temperature of Coldest Quarter
• Annual Precipitation
• Precipitation of Wettest Month
• Precipitation of Driest Month
• Precipitation Seasonality
• Precipitation of Wettest Quarter
• Precipitation of Driest Quarter
• Precipitation of Warmest Quarter
• Precipitation of Coldest Quarter

33. Lyme disease