Assistant Professor

Mauricio Santillana

Assistant Professor in the Department of Epidemiology

Epidemiology

Mauricio.SantillanaGuzman@childrens.harvard.edu

Other Positions

Assistant Professor of Pediatrics

Pediatrics

Boston Children's Hospital

Associate in Computer Science (IACS)

SEAS

Harvard University

Links

Mauricio Santillana Catalyst Profile

Overview

My current research utilizes mathematical concepts of machine learning for:
(a) the design and implementation of novel ways to track epidemic outbreaks around the Globe in real-time, using data from: Google searches, Twitter microblogs, Electronic Health Records, and news reports, and
(b) to improve patient outcomes and reduce hospital costs in Critical Care Medicine.

Bibliography

Estimating the cumulative incidence of COVID-19 in the United States using influenza surveillance, virologic testing, and mortality data: Four complementary approaches.

Lu FS, Nguyen AT, Link NB, Molina M, Davis JT, Chinazzi M, Xiong X, Vespignani A, Lipsitch M, Santillana M.

PLoS Comput Biol. 2021 06. 17(6):e1008994. PMID: 34138845

A dynamic, ensemble learning approach to forecast dengue fever epidemic years in Brazil using weather and population susceptibility cycles.

McGough SF, Clemente L, Kutz JN, Santillana M.

J R Soc Interface. 2021 06. 18(179):20201006. PMID: 34129785

Toward the use of neural networks for influenza prediction at multiple spatial resolutions.

Aiken EL, Nguyen AT, Viboud C, Santillana M.

Sci Adv. 2021 Jun. 7(25). PMID: 34134985

Factors Associated With Self-reported Symptoms of Depression Among Adults With and Without a Previous COVID-19 Diagnosis.

Perlis RH, Santillana M, Ognyanova K, Green J, Druckman J, Lazer D, Baum MA.

JAMA Netw Open. 2021 06 01. 4(6):e2116612. PMID: 34115130

Using heterogeneous data to identify signatures of dengue outbreaks at fine spatio-temporal scales across Brazil.

Castro LA, Generous N, Luo W, Pastore Y Piontti A, Martinez K, Gomes MFC, Osthus D, Fairchild G, Ziemann A, Vespignani A, Santillana M, Manore CA, Del Valle SY.

PLoS Negl Trop Dis. 2021 May. 15(5):e0009392. PMID: 34019536

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

Poirier C, Hswen Y, Bouzillé G, Cuggia M, Lavenu A, Brownstein JS, Brewer T, Santillana M.

PLoS One. 2021. 16(5):e0250890. PMID: 34010293

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