Publications – Center for Communicable Disease Dynamics

Gastroenteritis Forecasting Assessing the Use of Web and Electronic Health Record Data With a Linear and a Nonlinear Approach: Comparison Study.

Author(s): Poirier C, Bouzillé G, Bertaud V, Cuggia M, Santillana M, Lavenu AJournal: JMIR Public Health SurveillPMID: 36719726 January 2023

Disease surveillance systems capable of producing accurate real-time and short-term forecasts can help public health officials design timely public health…

Using digital traces to build prospective and real-time county-level early warning systems to anticipate COVID-19 outbreaks in the United States.

Author(s): Stolerman LM, Clemente L, Poirier C, Parag KV, Majumder A, Masyn S, Resch B, Santillana MJournal: Sci AdvPMID: 36652520 January 2023

Coronavirus disease 2019 (COVID-19) continues to affect the world, and the design of strategies to curb disease outbreaks requires close…

A nowcasting framework for correcting for reporting delays in malaria surveillance.

Author(s): Menkir TF, Cox H, Poirier C, Saul M, Jones-Weekes S, Clementson C, M de Salazar P, Santillana M, Buckee COJournal: PLoS Comput BiolPMID: 34784353 November 2021

Time lags in reporting to national surveillance systems represent a major barrier for the control of infectious diseases, preventing timely…

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 MJournal: PLoS OnePMID: 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 MJournal: Sci RepPMID: 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 MJournal: J Med Internet ResPMID: 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 MJournal: ArXivPMID: 32550248 April 2020

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