Srinivasan Venkatramanan

TL;DR: A coarse taxonomy of models is discussed and the context and significance of the Imperial College and other models in contributing to the analysis of COVID-19 are explored.

TL;DR: This paper describes one such agent-based model framework developed for forecasting the 2014-2015 Ebola epidemic in Liberia, and subsequently used during the Ebola forecasting challenge, and concludes by highlighting how such a data-driven approach can be refined and adapted for future epidemics.

TL;DR: This article reviews some of the important mathematical models used to support the ongoing planning and response efforts in the COVID-19 pandemic and discusses their use, their mathematical form and their scope.

TL;DR: In this paper, the authors used a multiple-model approach comprising six models to assess the potential course of COVID-19 in the United States across four scenarios with different vaccination coverage rates and effectiveness estimates and strength and implementation of nonpharmaceutical interventions (NPIs) (such as physical distancing and masking) over a 6-month period (April-September 2021) using data available through March 27, 2021 (4).

TL;DR: This paper presents an evaluation framework which allows for combining different features, error measures, and ranking schema to evaluate forecasts, and demonstrates the utility of the framework by evaluating six forecasting methods for predicting influenza in the United States.