activity
20192023
most citedThe Zoltar forecast archive: a tool to facilitate standardization and storage of interdisciplinary prediction research

1 citations · 2 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CY2023

Infectious disease surveillance needs for the United States: lessons from COVID-19

Marc Lipsitch, Mary T. Bassett, John S. Brownstein +27

The COVID-19 pandemic has highlighted the need to upgrade systems for infectious disease surveillance and forecasting and modeling of the spread of infection, both of which inform…

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.AP20201 cited

The Zoltar forecast archive: a tool to facilitate standardization and storage of interdisciplinary prediction research

Nicholas G Reich, Matthew Cornell, Evan L Ray +2

Forecasting has emerged as an important component of informed, data-driven decision-making in a wide array of fields. We introduce a new data model for probabilistic predictions th…

stat.AP2020

Infectious Disease Forecasting for Public Health

Stephen A Lauer, Alexandria C Brown, Nicholas G Reich

Forecasting transmission of infectious diseases, especially for vector-borne diseases, poses unique challenges for researchers. Behaviors of and interactions between viruses, vecto…

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.ME2019

The covariate-adjusted residual estimator and its use in both randomized trials and observational settings

Stephen A. Lauer, Nicholas G. Reich, Laura B. Balzer

We often seek to estimate the causal effect of an exposure on a particular outcome in both randomized and observational settings. One such estimation method is the covariate-adjust…