activity
20192022
most citedChimeric forecasting: combining probabilistic predictions from computational models and human judgment

2 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

stat.AP20221 cited

Comparison of Combination Methods to Create Calibrated Ensemble Forecasts for Seasonal Influenza in the U.S

Nutcha Wattanachit, Evan L. Ray, Thomas C. McAndrew +1

The characteristics of influenza seasons varies substantially from year to year, posing challenges for public health preparation and response. Influenza forecasting is used to info…

stat.AP20222 cited

Chimeric forecasting: combining probabilistic predictions from computational models and human judgment

Thomas McAndrew, Allison Codi, Juan Cambeiro +5

Forecasts of the trajectory of an infectious agent can help guide public health decision making. A traditional approach to forecasting fits a computational model to structured data…

q-bio.QM2020

The sleep loss insult of Spring Daylight Savings in the US is absorbed by Twitter users within 48 hours

Kelsey Linnell, Thayer Alshaabi, Thomas McAndrew +3

Sleep loss has been linked to heart disease, diabetes, cancer, and an increase in accidents, all of which are among the leading causes of death in the United States. Population-sca…

stat.AP2019

Aggregating predictions from experts: a scoping review of statistical methods, experiments, and applications

Thomas McAndrew, Nutcha Wattanachit, G. Casey Gibson +1

Forecasts support decision making in a variety of applications. Statistical models can produce accurate forecasts given abundant training data, but when data is sparse, rapidly cha…

stat.AP2019

Adaptively stacking ensembles for influenza forecasting with incomplete data

Thomas McAndrew, Nicholas G. Reich

Seasonal influenza infects between 10 and 50 million people in the United States every year, overburdening hospitals during weeks of peak incidence. Named by the CDC as an importan…