Influenza Forecaster
Contribute weekly state-level influenza hospitalization forecasts to the CDC FluSight project (Fall 2026–Spring 2027).
Forecasting
tom mcandrew
Principal Investigator; applied math, stats, human judgment, forecasting, infectious diseases
Chimeric Forecasting: An experiment to leverage human judgment to improve forecasts of infectious disease using simulated surveillance data
We presented 3000 humans with simulated surveillance data about the number of incident hospitalizations from a current and two past seasons, and asked that they predict the peak time and intensity of the underlying epidemic
A Cluster-Aggregate-Pool (CAP) Ensemble Algorithm for Improved Forecast Performance of influenza-like illness
We propose a novel Cluster-Aggregate-Pool or `CAP’ ensemble algorithm that first clusters together individual forecasts, aggregates individual models that belong to the same cluster into a single forecast (called a cluster forecast), and then pools together cluster forecasts via a linear pool.
Australia’s having an intense flu season, and it could be a signal of what’s to come in the US
CNN — Infectious disease forecasting opinions
Early human judgment forecasts of human monkeypox, May 2022
These results suggest that a human judgment forecasting platform can quickly generate probabilistic predictions for targets of public health importance
Aggregating Human Judgment Probabilistic Predictions of Coronavirus Disease 2019 Transmission, Burden, and Preventive Measures
Our work shows that aggregated human judgment forecasts for infectious agents are timely, accurate, and adaptable, and can be used as a tool to aid public health decision making during outbreaks.
Adaptively stacking ensembles for influenza forecasting with incomplete data
Needing no data at the beginning of an epidemic, an adaptive ensemble can quickly train and forecast an outbreak, providing a practical tool to public health officials looking for a forecast to conform to unique features of a specific season.
Public-Health Prognosticators: Forecasting Public Health Events
Lehigh News — Aggregating computational and human judgment forecasts
An expert judgment model to predict early stages of the COVID-19 outbreak in the United States
This work highlights the importance that an expert linear pool could play in flexibly assessing a wide array of risks early in future emerging outbreaks, especially in settings where available data cannot yet support data-driven computational modeling.