15 citations · 22 across the 4 of their papers we have counts for
4 papers
Time Series Methods and Ensemble Models to Nowcast Dengue at the State Level in Brazil
Katherine Kempfert, Kaitlyn Martinez, Amir Siraj +8
Predicting an infectious disease can help reduce its impact by advising public health interventions and personal preventive measures. Novel data streams, such as Internet and socia…
Nowcasting Influenza Incidence with CDC Web Traffic Data: A Demonstration Using a Novel Data Set
Wendy K. Caldwell, Geoffrey Fairchild, Sara Y. Del Valle
Influenza epidemics result in a public health and economic burden around the globe. Traditional surveillance techniques, which rely on doctor visits, provide data with a delay of 1…
Dynamic Bayesian Influenza Forecasting in the United States with Hierarchical Discrepancy
Dave Osthus, James Gattiker, Reid Priedhorsky +1
Timely and accurate forecasts of seasonal influenza would assist public health decision-makers in planning intervention strategies, efficiently allocating resources, and possibly s…
Quantifying Uncertainty in Stochastic Models with Parametric Variability
Kyle S. Hickmann, James M. Hyman, Sara Y. Del Valle
We present a method to quantify uncertainty in the predictions made by simulations of mathematical models that can be applied to a broad class of stochastic, discrete, and differen…