323 citations · 505 across the 12 of their papers we have counts for
12 papers
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…
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…
Comparing trained and untrained probabilistic ensemble forecasts of COVID-19 cases and deaths in the United States
Evan L. Ray, Logan C. Brooks, Jacob Bien +12
The U.S. COVID-19 Forecast Hub aggregates forecasts of the short-term burden of COVID-19 in the United States from many contributing teams. We study methods for building an ensembl…
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…
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…
Evaluating epidemic forecasts in an interval format
Johannes Bracher, Evan L. Ray, Tilmann Gneiting +1
For practical reasons, many forecasts of case, hospitalization and death counts in the context of the current COVID-19 pandemic are issued in the form of central predictive interva…
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…
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…
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…
Prediction of infectious disease epidemics via weighted density ensembles
Evan L. Ray, Nicholas G. Reich
Accurate and reliable predictions of infectious disease dynamics can be valuable to public health organizations that plan interventions to decrease or prevent disease transmission.…
Enriching students' conceptual understanding of confidence intervals: An interactive trivia-based classroom activity
Xiaofei Wang, Nicholas G. Reich, Nicholas J. Horton
Confidence intervals provide a way to determine plausible values for a population parameter. They are omnipresent in research articles involving statistical analyses. Appropriately…
Infrastructure and methods for real-time predictions of the 2014 dengue fever season in Thailand
Nicholas G. Reich, Stephen A. Lauer, Krzysztof Sakrejda +8
Epidemics of communicable diseases place a huge burden on public health infrastructures across the world. Producing accurate and actionable forecasts of infectious disease incidenc…