Publications

Influenza forecasting for French regions combining EHR, web and climatic data sources with a machine learning ensemble approach.

Author(s): Poirier C, Hswen Y, Bouzillé G, Cuggia M, Lavenu A, Brownstein JS, Brewer T, Santillana M|Journal: PLoS One|PMID: 34010293| May 2021

Effective and timely disease surveillance systems have the potential to help public health officials design interventions to mitigate the effects…

The role of environmental factors on transmission rates of the COVID-19 outbreak: an initial assessment in two spatial scales.

Author(s): Poirier C, Luo W, Majumder MS, Liu D, Mandl KD, Mooring TA, Santillana M|Journal: Sci Rep|PMID: 33046802| October 2020

First identified in Wuhan, China, in December 2019, a novel coronavirus (SARS-CoV-2) has affected over 16,800,000 people worldwide as of…

Real-time forecasting of the COVID-19 outbreak in Chinese provinces: Machine learning approach using novel digital data and estimates from mechanistic models.

Author(s): Poirier C, Liu D, Clemente L, Ding X, Chinazzi M, Vespignani A, Santillana M|Journal: J Med Internet Res|PMID: 32730217| July 2020

The inherent difficulty to identify and monitor emerging outbreaks caused by novel pathogens can lead to their rapid spread; and…

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.

Author(s): Liu D, Clemente L, Poirier C, Ding X, Chinazzi M, Vespignani A, Santillana M|Journal: ArXiv|PMID: 32550248| April 2020

We present a timely and novel methodology that combines disease estimates from mechanistic models with digital traces, via interpretable machine-learning…