102 citations · 111 across the 4 of their papers we have counts for
5 papers
Using digital traces to build prospective and real-time county-level early warning systems to anticipate COVID-19 outbreaks in the United States
Lucas M. Stolerman, Leonardo Clemente, Canelle Poirier +5
The ongoing COVID-19 pandemic continues to affect communities around the world. To date, almost 6 million people have died as a consequence of COVID-19, and more than one-quarter o…
Fever and mobility data indicate social distancing has reduced incidence of communicable disease in the United States
Parker Liautaud, Peter Huybers, Mauricio Santillana
In March of 2020, many U.S. state governments encouraged or mandated restrictions on social interactions to slow the spread of COVID-19, the disease caused by the novel coronavirus…
A machine learning methodology for real-time forecasting of the 2019-2020 COVID-19 outbreak using Internet searches, news alerts, and estimates from mechanistic models
Dianbo Liu, Leonardo Clemente, Canelle Poirier +5
We present a timely and novel methodology that combines disease estimates from mechanistic models with digital traces, via interpretable machine-learning methodologies, to reliably…
Towards the Use of Neural Networks for Influenza Prediction at Multiple Spatial Resolutions
Emily L. Aiken, Andre T. Nguyen, Mauricio Santillana
We introduce the use of a Gated Recurrent Unit (GRU) for influenza prediction at the state- and city-level in the US, and experiment with the inclusion of real-time flu-related Int…
Relatedness of the Incidence Decay with Exponential Adjustment (IDEA) Model, "Farr's Law" and Compartmental Difference Equation SIR Models
Mauricio Santillana, Ashleigh Tuite, Tahmina Nasserie +5
Mathematical models are often regarded as recent innovations in the description and analysis of infectious disease outbreaks and epidemics, but simple models have been in use for p…