publications

2024

1. Evaluating infectious disease forecasts with allocation scoring rules

   Aaron Gerding, Nicholas G Reich, Benjamin Rogers, and Evan L Ray

   Journal of the Royal Statistical Society Series A: Statistics in Society, Dec 2024

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   Recent years have seen increasing efforts to forecast infectious disease burdens, with a primary goal being to help public health workers make informed policy decisions. However, there has been only limited discussion of how predominant forecast evaluation metrics might indicate the success of policies based in part on those forecasts. We explore one possible tether between forecasts and policy: the allocation of limited medical resources so as to minimize unmet need. We use probabilistic forecasts of disease burden in each of several regions to determine optimal resource allocations, and then we score forecasts according to how much unmet need their associated allocations would have allowed. We illustrate with forecasts of COVID-19 hospitalizations in the U.S., and we find that the forecast skill ranking given by this allocation scoring rule can vary substantially from the ranking given by the weighted interval score. We see this as evidence that the allocation scoring rule detects forecast value that is missed by traditional accuracy measures and that the general strategy of designing scoring rules that are directly linked to policy performance is a promising direction for epidemic forecast evaluation.

2023

1. 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, Matthew Biggerstaff, Nikos I. Bosse, Johannes Bracher, Estee Y. Cramer, Sebastian Funk, Aaron Gerding, Michael A. Johansson, Aaron Rumack, Yijin Wang, Martha Zorn, Ryan J. Tibshirani, and Nicholas G. Reich

   International Journal of Forecasting, Dec 2023

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2022

1. Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

   Estee Y Cramer, Evan L Ray, Velma K Lopez, Johannes Bracher, Andrea Brennen, Alvaro J Castro Rivadeneira, Aaron Gerding, Tilmann Gneiting, Katie H House, Yuxin Huang, and  others

   Proceedings of the National Academy of Sciences, Dec 2022

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2. The United States COVID-19 forecast hub dataset

   Estee Y Cramer, Yuxin Huang, Yijin Wang, Evan L Ray, Matthew Cornell, Johannes Bracher, Andrea Brennen, Alvaro J Castro Rivadeneira, Aaron Gerding, Katie House, and  others

   Scientific Data, Dec 2022

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2021

1. Challenges in training ensembles to forecast COVID-19 cases and deaths in the United States

   Evan L Ray, LC Brooks, J Bien, J Bracher, A Gerding, A Rumack, M Biggerstaff, MA Johansson, RJ Tibshirani, and NG Reich

   International Institute of Forecasters, Dec 2021

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2011

1. Constant mean curvature surfaces: an integrable systems perspective

   A. Gerding, F. Pedit, and N. Schmitt

   In Harmonic maps and differential geometry. A harmonic map fest in honour of John C. Wood’s 60th birthday, Cagliari, Italy, September 7–10, 2009, Dec 2011

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2. Spectral methods for higher genus constant mean curvature surfaces

   Aaron Gerding

   Dec 2011

   Thesis (Ph.D.)–University of Massachusetts Amherst

2009

1. Global aspects of integrable surface geometry

   A Gerding, S Heller, F Pedit, and N Schmitt

   In Systèmes intégrables et théorie des champs quantiques. Travaux en cours No. 75, Dec 2009

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