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Aggregating Statistical Models and Human Judgment to forecast COVID-19
Forecasting the trajectory of the US COVID-19 pandemic can support public health officials who make decisions with partial knowledge of how the virus will evolve over time. Computational models are capable of processing large, structured datasets.
Jun 2, 2021 12:00 AM
Zoom
Slides
Metaforecasting the US COVID-19 outbreak
Feb 10, 2021 12:00 AM
Zoom
Slides
A consensus of probabilistic predictions by experts and trained forecasters of the timing and efficacy of a SARS-CoV-2 vaccine
A safe, effective vaccine is a key component to slowing the spread of SARS- CoV- 2. But a recent poll suggests less than 50% of the US public would volunteer for inoculation, highlighting uncertainty surrounding the safety and efficacy of a vaccine.
Nov 2, 2020 12:00 AM
Zoom
Slides
Consensus probabilistic predictions of the timing, efficacy, and safety of a SARS-CoV-2 vaccine by experts and trained forecasters
In the first of our new Speaker Series exploring the science of forecasting, biostatistician @tomcm39 will present new research on Consensus Forecasting Models for COVID-19 Vaccines and Treatments, supporting policy makers and the public.
Oct 23, 2020 12:00 AM
Zoom
Slides
Aggregating Expert Opinion on COVID-19
Community-wide transmission of SARS-CoV-2 was reported in the US on February 26th. Since the virus was declared a pandemic by the WHO on March 11th, it has spread rapidly throughout the US and has caused more than 1.
Aug 3, 2020 12:00 AM
Zoom
Slides
Aggregating Expert Opinion on COVID-19
Community-wide transmission of SARS-CoV-2 was reported in the US on February 26th. Since the virus was declared a pandemic by the WHO on March 11th, it has spread rapidly throughout the US and has caused more than 1.
May 29, 2020 12:00 AM
Zoom
Slides
FluSight Network Ensemble
We present three combination forecasting techniques. The FluSight Network (FSN) ensemble model is a multimodel ensemble; a convex combination of component predictive densities. The adaptive ensemble is a multimodel ensemble, but unlike the FSN ensemble, recomputes component model weights every week.
Aug 20, 2019 12:00 AM
Atlanta, Georgia
Slides
Adaptively stacked ensembles for influenza forecasting with incomplete data
Seasonal Influenza infects an average 30 million people in the United States every year, overburdening hospitals during weeks of peak incidence.Named by the CDC as an important tool to fight the damaging effects of these epidemics, accurate forecasts of influenza and influenza like illness (ILI) forewarn public health officials about when, and where, seasonal influenza outbreaks will hit hardest.
May 31, 2019 12:00 AM
Bellevue, Washington
Slides
Adaptively stacked ensembles for influenza forecasting with incomplete data
Influenza prediction can better prepare public health officials for seasonal outbreaks. We propose an adaptive multi-model ensemble forecast method that changes model weights week-by-week throughout the flu season. Without historical training data or when models do not have a track-record, an adaptive model can enhance the public health impact of ensemble forecasts.
May 20, 2019 12:00 AM
Bethesda, Maryland
Slides
Adaptively stacked ensembles for influenza forecasting with incomplete data
Seasonal Influenza infects an average 30 million people in the United States every year, overburdening hospitals during weeks of peak incidence.Named by the CDC as an important tool to fight the damaging effects of these epidemics, accurate forecasts of influenza and influenza like illness (ILI) forewarn public health officials about when, and where, seasonal influenza outbreaks will hit hardest.
May 16, 2019 12:00 AM
Hartford, CT
Slides
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