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Mauricio Santillana

Bio

Mauricio Santillana, PhD, MSc is the director of the Machine Intelligence Group for the betterment of Health and the Environment (MIGHTE) at the Network Science Institute at Northeastern University. He is a Professor at both the Physics and Electrical and Computer Engineering Departments at Northeastern University, and an Adjunct Professor at the Department of Epidemiology, at the Harvard T.H. Chan School of Public Health. ​ Dr. Santillana’s research areas include the modeling of geographic patterns of population growth, modeling fluid flow to inform coastal floods simulations and atmospheric global pollution transport models, and most recently, the design and implementation of disease outbreaks prediction platforms and mathematical solutions to healthcare. His research has shown that machine learning techniques can be used to effectively monitor and predict the dynamics of disease outbreaks using novel data sources not designed for these purposes such as: Internet search activity, social media posts, clinician’s searches, human mobility, weather, etc. His original research and perspectives have appeared in journals such as Nature, Science, Proceedings of the National Academy of Science, Science Advances, Nature Communications, and Nature Climate Change, among others. His work has been funded by the National Institute of General Medical Sciences (National Institutes of Health, NIH), the U.S. Centers for Disease Control and Prevention, and multiple foundations such as: the Bill and Melinda Gates Foundation, the Johnson and Johnson Foundation, Ending Pandemics Fund, Skoll Global Threats Fund. Dr. Santillana has advised the US CDC, Africa CDC, and the White House on the development of population-wide disease forecasting tools. His original research and perspectives have been featured in a diverse array of national and international news outlets such as The New York Times, The Washington Post, The Atlantic, The Wall Street Journal, Vox.com, Politico, National Public Radio, CNN, CNN Espanol, Fox, BBC, among others. ​Mauricio received a B.S. in Physics with highest honors from Universidad Nacional Autónoma de México in Mexico City, and a Master’s and PhD in Computational and Applied Mathematics from the University of Texas at Austin. Mauricio was a Postdoctoral fellow at the Harvard Center for the Environment and later became a lecturer in applied mathematics at the Harvard School of Engineering and Applied Sciences, receiving two awards for excellence in teaching. He became a tenure-track faculty member at Boston Children's Hospital, Harvard Medical School, and the Harvard T.H. Chan School of Public Health. He recently joined the faculty at Northeastern University.

Education

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Personal Academic Website

Topics of Interest/Expertise
 

Countries of Work/Collaboration

United States

Projects

Understanding and controlling antibiotic resistance

National Institutes of Health, National Institute of General Medical Sciences
People: Laura White, Ted Cohen, William Hanage, Ben Cowling, Tyler Brown, Joseph Wu, Joseph Lewnard, Aimee Taylor, Pablo Martinez de Salazar, Lerato Magosi, Mauricio Santillana, Christine Tedijanto, Tigist Menkir, Sze Man Leung, Hsiao-Han Chang, Caroline Buckee, Pamela Martinez, Marc Lipsitch
2009 – 2021 Continue Reading Understanding and controlling antibiotic resistance

Papers

Teo K, Arnold N, Hone A, Coulon M, Ireland M, Santillana M, Kiss IZ. (2026). Unveiling individual and collective temporal patterns in the tanker shipping network. Nature communications

Perlis RH, Ramachandiran AK, Verhaak PF, Santillana M, Baum MA, Druckman JN, Ognyanova K, Lazer D. (2026). Antidepressant use among American adults in a 50-state survey. BMJ mental health, 29(1)

Dewey G, Meyer AG, Garcia RG, Santillana M. (2026). Uncovering the post-pandemic timing of influenza, RSV, and COVID-19 driving seasonal influenza-like illness in the United States: a retrospective ecological study. Lancet regional health. Americas, (55)

Garrido-Garcia R, Clemente L, Meyer AG, Dewey G, Yang S, Santillana M. (2026). A real-time early warning system to anticipate respiratory disease outbreaks using transfer learning. Nature communications, 17(1)

Parag KV, Santillana M, Cori A, Obolski U. (2026). The R = 1 threshold can misclassify epidemic stability. Communications physics, 9(1)

Perlis RH, Gunning FM, Uslu A, Santillana M, Baum MA, Druckman JN, Ognyanova K, Lazer D. (2026). Emulated trial of artificial intelligence use and subsequent depressive outcomes in a survey of US adults. BMJ mental health, 29(1)

Meyer AG, Blasick S, Yang S, Santillana M. (2026). An Introduction to Machine Learning for the Pediatric Hospitalist. Hospital pediatrics

Meyer AG, Dewey G, Blasick S, Hovland C, Santillana M. (2026). Quantifying the Protection Gap: Respiratory Syncytial Virus Activity Outside the Recommended Prophylaxis Administration Window. Journal of the Pediatric Infectious Diseases Society, 15(5)

Pant B, Levine ME, Nande A, Garcia RG, Dewey G, Link NB, Santillana M. (2026). Resolving parameter uncertainty in SIR models through population-level serological surveillance: A synthetic study. Infectious Disease Modelling, 11(4)

Ramachandiran AK, Gunning F, Santillana M, Baum MA, Verhaak PF, Druckman JN, Ognyanova K, Lazer D, Perlis RH. (2026). Sociodemographic disparities, healthcare system trust, and social support in mental health treatment among U.S. adults with depressive or anxiety symptoms. Journal of mood and anxiety disorders, (13)

Perlis RH, Gunning FM, Usla A, Santillana M, Baum MA, Druckman JN, Ognyanova K, Lazer D. (2026). Generative AI Use and Depressive Symptoms Among US Adults. JAMA network open, 9(1)

Arifi D, Resch B, Santillana M, Guan WW, Knoblauch S, Lautenbach S, Jaenisch T, Morales I, Havas C. (2025). Geosocial Media's Early Warning Capabilities Across US County-Level Political Clusters: Observational Study. JMIR infodemiology, (5)

Perlis RH, Uslu A, Barroilhet SA, Vohringer PA, Ramachandiran AK, Santillana M, Baum MA, Druckman JN, Ognyanova K, Lazer D. (2025). Conspiratorial thinking in a 50-state survey of American adults. Journal of affective disorders

Wu S, Meyer AG, Clemente L, Stolerman LM, Lu F, Majumder A, Verbeeck R, Masyn S, Santillana M. (2025). Ensemble approaches for short-term dengue fever forecasts: A global evaluation study. Proceedings of the National Academy of Sciences of the United States of America, 122(33)

Song TH, Clemente L, Pan X, Jang J, Santillana M, Lee K. (2025). Fine-grained forecasting of COVID-19 trends at the county level in the United States. NPJ digital medicine, 8(1)

Urmi T, Pant B, Dewey G, Quintana-Mathe A, Lang I, Druckman J, Ognyanova K, Baum M, Perlis R, Riedl C, Lazer D, Santillana M. (2025). Characterizing population-level changes in human behavior during the COVID-19 pandemic in the United States. Proceedings of the National Academy of Sciences of the United States of America, 122(37)

Meyer AG, Lu F, Clemente L, Santillana M. (2025). A prospective real-time transfer learning approach to estimate influenza hospitalizations with limited data. Epidemics, (50)

Perlis RH, Uslu A, Schulman J, Gunning FM, Santillana M, Baum MA, Druckman JN, Ognyanova K, Lazer D. (2025). Irritability and Social Media Use in US Adults. JAMA network open, 8(1)

Arifi D, Resch B, Santillana M, Knoblauch S, Lautenbach S, Jaenisch T, Morales I. (2025). How politics affect pandemic forecasting: spatio-temporal early warning capabilities of different geo-social media topics in the context of state-level political leaning. Frontiers in public health, (13)

Perlis RH, Gunning FM, Santillana M, Baum MA, Druckman JN, Ognyanova K, Lazer D. (2025). Derivation of a 3-Item Patient Health Questionnaire as a Shortened Survey to Capture Depressive Symptoms. JAMA network open, 8(7)

Mathis SM, Webber AE, León TM, Murray EL, Sun M, White LA, Brooks LC, Green A, Hu AJ, Rosenfeld R, Shemetov D, Tibshirani RJ, McDonald DJ, Kandula S, Pei S, Yaari R, Yamana TK, Shaman J, Agarwal P, Balusu S, Gururajan G, Kamarthi H, Prakash BA, Raman R, Zhao Z, Rodríguez A, Meiyappan A, Omar S, Baccam P, Gurung HL, Suchoski BT, Stage SA, Ajelli M, Kummer AG, Litvinova M, Ventura PC, Wadsworth S, Niemi J, Carcelen E, Hill AL, Loo SL, McKee CD, Sato K, Smith C, Truelove S, Jung SM, Lemaitre JC, Lessler J, McAndrew T, Ye W, Bosse N, Hlavacek WS, Lin YT, Mallela A, Gibson GC, Chen Y, Lamm SM, Lee J, Posner RG, Perofsky AC, Viboud C, Clemente L, Lu F, Meyer AG, Santillana M, Chinazzi M, Davis JT, Mu K, Pastore Y Piontti A, Vespignani A, Xiong X, Ben-Nun M, Riley P, Turtle J, Hulme-Lowe C, Jessa S, Nagraj VP, Turner SD, Williams D, Basu A, Drake JM, Fox SJ, Suez E, Cojocaru MG, Thommes EW, Cramer EY, Gerding A, Stark A, Ray EL, Reich NG, Shandross L, Wattanachit N, Wang Y, Zorn MW, Aawar MA, Srivastava A, Meyers LA, Adiga A, Hurt B, Kaur G, Lewis BL, Marathe M, Venkatramanan S, Butler P, Farabow A, Ramakrishnan N, Muralidhar N, Reed C, Biggerstaff M, Borchering RK. (2024). Title evaluation of FluSight influenza forecasting in the 2021-22 and 2022-23 seasons with a new target laboratory-confirmed influenza hospitalizations. Nature communications, 15(1)

Oliveira Roster K, Martinelli T, Connaughton C, Santillana M, Rodrigues FA. (2024). Impact of the COVID-19 pandemic on dengue in Brazil: Interrupted time series analysis of changes in surveillance and transmission. PLoS neglected tropical diseases, 18(12)

Perlis RH, Uslu A, Schulman J, Himelfarb A, Gunning FM, Solomonov N, Santillana M, Baum MA, Druckman JN, Ognyanova K, Lazer D. (2024). Prevalence and correlates of irritability among U.S. adults. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology

Pant B, Safdar S, Santillana M, Gumel AB. (2024). Mathematical Assessment of the Role of Human Behavior Changes on SARS-CoV-2 Transmission Dynamics in the United States. Bulletin of mathematical biology, 86(8)

Menkir TF, Citarella BW, Sigfrid L, Doshi Y, Reyes LF, Calvache JA, Kildal AB, Nygaard AB, Holter JC, Panda PK, Jassat W, Merson L, Donnelly CA, Santillana M, Buckee C, Verguet S, Hejazi NS. (2024). Modeling the relative influence of socio-demographic variables on post-acute COVID-19 quality of life. medRxiv : the preprint server for health sciences

Jaywant A, Gunning FM, Oberlin LE, Santillana M, Ognyanova K, Druckman JN, Baum MA, Lazer D, Perlis RH. (2024). Cognitive Symptoms of Post-COVID-19 Condition and Daily Functioning. JAMA network open, 7(2)

Santillana M, Uslu AA, Urmi T, Quintana-Mathe A, Druckman JN, Ognyanova K, Baum M, Perlis RH, Lazer D. (2024). Tracking COVID-19 Infections Using Survey Data on Rapid At-Home Tests. JAMA network open, 7(9)

Perlis RH, Ognyanova K, Uslu A, Lunz Trujillo K, Santillana M, Druckman JN, Baum MA, Lazer D. (2024). Trust in Physicians and Hospitals During the COVID-19 Pandemic in a 50-State Survey of US Adults. JAMA network open, 7(7)

Poirier C, Bouzillé G, Bertaud V, Cuggia M, Santillana M, Lavenu A. (2023). Gastroenteritis Forecasting Assessing the Use of Web and Electronic Health Record Data With a Linear and a Nonlinear Approach: Comparison Study. JMIR public health and surveillance, (9)

Solomonov N, Green J, Quintana A, Lin J, Ognyanova K, Santillana M, Druckman JN, Baum MA, Lazer D, Gunning FM, Perlis RH. (2023). A 50-state survey study of thoughts of suicide and social isolation among older adults in the United States. Journal of affective disorders, (334)

Stolerman LM, Clemente L, Poirier C, Parag KV, Majumder A, Masyn S, Resch B, Santillana M. (2023). Using digital traces to build prospective and real-time county-level early warning systems to anticipate COVID-19 outbreaks in the United States. Science advances, 9(3)

Mathis SM, Webber AE, León TM, Murray EL, Sun M, White LA, Brooks LC, Green A, Hu AJ, McDonald DJ, Rosenfeld R, Shemetov D, Tibshirani RJ, Kandula S, Pei S, Shaman J, Yaari R, Yamana TK, Agarwal P, Balusu S, Gururajan G, Kamarthi H, Prakash BA, Raman R, Rodríguez A, Zhao Z, Meiyappan A, Omar S, Baccam P, Gurung HL, Stage SA, Suchoski BT, Ajelli M, Kummer AG, Litvinova M, Ventura PC, Wadsworth S, Niemi J, Carcelen E, Hill AL, Jung SM, Lemaitre JC, Lessler J, Loo SL, McKee CD, Sato K, Smith C, Truelove S, McAndrew T, Ye W, Bosse N, Hlavacek WS, Lin YT, Mallela A, Chen Y, Lamm SM, Lee J, Posner RG, Perofsky AC, Viboud C, Clemente L, Lu F, Meyer AG, Santillana M, Chinazzi M, Davis JT, Mu K, Piontti APY, Vespignani A, Xiong X, Ben-Nun M, Riley P, Turtle J, Hulme-Lowe C, Jessa S, Nagraj VP, Turner SD, Williams D, Basu A, Drake JM, Fox SJ, Gibson GC, Suez E, Thommes EW, Cojocaru MG, Cramer EY, Gerding A, Stark A, Ray EL, Reich NG, Shandross L, Wattanachit N, Wang Y, Zorn MW, Al Aawar M, Srivastava A, Meyers LA, Adiga A, Hurt B, Kaur G, Lewis BL, Marathe M, Venkatramanan S, Butler P, Farabow A, Muralidhar N, Ramakrishnan N, Reed C, Biggerstaff M, Borchering RK. (2023). Evaluation of FluSight influenza forecasting in the 2021-22 and 2022-23 seasons with a new target laboratory-confirmed influenza hospitalizations. medRxiv : the preprint server for health sciences

Sperotto F, Emani S, Zhu L, Delgado M, Santillana M, Kheir JN. (2023). Predicting favorable response to intravenous morphine in pediatric critically ill cardiac patients. Pharmacotherapy, 43(7)

Perlis RH, Santillana M, Ognyanova K, Lazer D. (2023). Correlates of symptomatic remission among individuals with post-COVID-19 condition. medRxiv : the preprint server for health sciences

De Salazar PM, Lu F, Hay JA, Gómez-Barroso D, Fernández-Navarro P, Martínez EV, Astray-Mochales J, Amillategui R, García-Fulgueiras A, Chirlaque MD, Sánchez-Migallón A, Larrauri A, Sierra MJ, Lipsitch M, Simón F, Santillana M, Hernán MA. (2022). Near real-time surveillance of the SARS-CoV-2 epidemic with incomplete data. PLoS computational biology, 18(3)

Reichert E, Schaeffer B, Gantt S, Rumpler E, Govender N, Welch R, Shonhiwa AM, Iwu CD, Lamola TM, Moema-Matiea I, Muganhiri D, Hanage W, Santillana M, Jassat W, Cohen C, Swerdlow D. (2022). Methods for early characterisation of the severity and dynamics of SARS-CoV-2 variants: a population-based time series analysis in South Africa. The Lancet. Microbe

Koplewitz G, Lu F, Clemente L, Buckee C, Santillana M. (2022). Predicting dengue incidence leveraging internet-based data sources. A case study in 20 cities in Brazil. PLoS neglected tropical diseases, 16(1)

Liu D, Shin WY, Sprecher E, Conroy K, Santiago O, Wachtel G, Santillana M. (2022). Machine learning approaches to predicting no-shows in pediatric medical appointment. NPJ digital medicine, 5(1)

Kaashoek J, Testa C, Chen JT, Stolerman LM, Krieger N, Hanage WP, Santillana M. (2022). The evolving roles of US political partisanship and social vulnerability in the COVID-19 pandemic from February 2020-February 2021. PLOS global public health, 2(12)

Kogan NE, Gantt S, Swerdlow D, Viboud C, Semakula M, Lipsitch M, Santillana M. (2022). Leveraging Serosurveillance and Postmortem Surveillance to Quantify the Impact of COVID-19 in Africa. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America

Perlis RH, Ognyanova K, Santillana M, Lin J, Druckman J, Lazer D, Green J, Simonson M, Baum MA, Della Volpe J. (2022). Association of Major Depressive Symptoms With Endorsement of COVID-19 Vaccine Misinformation Among US Adults. JAMA network open, 5(1)

Perlis RH, Simonson MD, Green J, Lin J, Safarpour A, Lunz Trujillo K, Quintana A, Chwe H, Della Volpe J, Ognyanova K, Santillana M, Druckman J, Lazer D, Baum MA. (2022). Prevalence of Firearm Ownership Among Individuals With Major Depressive Symptoms. JAMA network open, 5(3)

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. (2021). Using heterogeneous data to identify signatures of dengue outbreaks at fine spatio-temporal scales across Brazil. PLoS neglected tropical diseases, 15(5)

Lu FS, Nguyen AT, Link NB, Molina M, Davis JT, Chinazzi M, Xiong X, Vespignani A, Lipsitch M, Santillana M. (2021). Estimating the cumulative incidence of COVID-19 in the United States using influenza surveillance, virologic testing, and mortality data: Four complementary approaches. PLoS computational biology, 17(6)

Menkir TF, Cox H, Poirier C, Saul M, Jones-Weekes S, Clementson C, M de Salazar P, Santillana M, Buckee CO. (2021). A nowcasting framework for correcting for reporting delays in malaria surveillance. PLoS computational biology, 17(11)

Perlis RH, Ognyanova K, Quintana A, Green J, Santillana M, Lin J, Druckman J, Lazer D, Simonson MD, Baum MA, Chwe H. (2021). Gender-specificity of resilience in major depressive disorder. Depression and anxiety, 38(10)

Wu F, Xiao A, Zhang J, Moniz K, Endo N, Armas F, Bonneau R, Brown MA, Bushman M, Chai PR, Duvallet C, Erickson TB, Foppe K, Ghaeli N, Gu X, Hanage WP, Huang KH, Lee WL, Matus M, McElroy KA, Nagler J, Rhode SF, Santillana M, Tucker JA, Wuertz S, Zhao S, Thompson J, Alm EJ. (2021). SARS-CoV-2 RNA concentrations in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases. The Science of the total environment, (805)

Aiken EL, Nguyen AT, Viboud C, Santillana M. (2021). Toward the use of neural networks for influenza prediction at multiple spatial resolutions. Science advances, 7(25)

Perlis RH, Santillana M, Ognyanova K, Green J, Druckman J, Lazer D, Baum MA. (2021). Factors Associated With Self-reported Symptoms of Depression Among Adults With and Without a Previous COVID-19 Diagnosis. JAMA network open, 4(6)

Perlis RH, Green J, Simonson M, Ognyanova K, Santillana M, Lin J, Quintana A, Chwe H, Druckman J, Lazer D, Baum MA, Della Volpe J. (2021). Association Between Social Media Use and Self-reported Symptoms of Depression in US Adults. JAMA network open, 4(11)

Kogan NE, Clemente L, Liautaud P, Kaashoek J, Link NB, Nguyen AT, Lu FS, Huybers P, Resch B, Havas C, Petutschnig A, Davis J, Chinazzi M, Mustafa B, Hanage WP, Vespignani A, Santillana M. (2021). An early warning approach to monitor COVID-19 activity with multiple digital traces in near real time. Science advances, 7(10)

McGough SF, Clemente L, Kutz JN, Santillana M. (2021). A dynamic, ensemble learning approach to forecast dengue fever epidemic years in Brazil using weather and population susceptibility cycles. Journal of the Royal Society, Interface, 18(179)

Liu D, Clemente L, Poirier C, Ding X, Chinazzi M, Davis J, Vespignani A, Santillana M. (2020). Real-time forecasting of the COVID-19 outbreak in Chinese provinces: Machine learning approach using novel digital data and estimates from mechanistic models. Journal of medical Internet research, 22(8)

McGough SF, MacFadden DR, Hattab MW, Mølbak K, Santillana M. (2020). Rates of increase of antibiotic resistance and ambient temperature in Europe: a cross-national analysis of 28 countries between 2000 and 2016. Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin, 25(45)

Castiñeira D, Schlosser KR, Geva A, Rahmani AR, Fiore G, Walsh BK, Smallwood CD, Arnold JH, Santillana M. (2020). Adding Continuous Vital Sign Information to Static Clinical Data Improves the Prediction of Length of Stay After Intubation: A Data-Driven Machine Learning Approach. Respiratory care, 65(9)

Dai M, Liu D, Liu M, Zhou F, Li G, Chen Z, Zhang Z, You H, Wu M, Zheng Q, Xiong Y, Xiong H, Wang C, Chen C, Xiong F, Zhang Y, Peng Y, Ge S, Zhen B, Yu T, Wang L, Wang H, Liu Y, Chen Y, Mei J, Gao X, Li Z, Gan L, He C, Li Z, Shi Y, Qi Y, Yang J, Tenen DG, Chai L, Mucci LA, Santillana M, Cai H. (2020). Patients with cancer appear more vulnerable to SARS-COV-2: a multi-center study during the COVID-19 outbreak. Cancer discovery

Chevalier-Cottin EP, Ashbaugh H, Brooke N, Gavazzi G, Santillana M, Burlet N, Tin Tin Htar M. (2020). Communicating Benefits from Vaccines Beyond Preventing Infectious Diseases. Infectious diseases and therapy

Wu F, Xiao A, Zhang J, Moniz K, Endo N, Armas F, Bonneau R, Brown MA, Bushman M, Chai PR, Duvallet C, Erickson TB, Foppe K, Ghaeli N, Gu X, Hanage WP, Huang KH, Lee WL, Matus M, McElroy KA, Nagler J, Rhode SF, Santillana M, Tucker JA, Wuertz S, Zhao S, Thompson J, Alm EJ. (2020). SARS-CoV-2 titers in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases. medRxiv : the preprint server for health sciences

Buckee CO, Balsari S, Chan J, Crosas M, Dominici F, Gasser U, Grad YH, Grenfell B, Halloran ME, Kraemer MUG, Lipsitch M, Metcalf CJE, Meyers LA, Perkins TA, Santillana M, Scarpino SV, Viboud C, Wesolowski A, Schroeder A. (2020). Aggregated mobility data could help fight COVID-19. Science (New York, N.Y.)

Liu D, Clemente L, Poirier C, Ding X, Chinazzi M, Davis J, Vespignani A, Santillana M. (2020). Correction: Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models. Journal of medical Internet research, 22(9)

Lu FS, Nguyen AT, Link NB, Davis JT, Chinazzi M, Xiong X, Vespignani A, Lipsitch M, Santillana M. (2020). Estimating the Early Outbreak Cumulative Incidence of COVID-19 in the United States: Three Complementary Approaches. medRxiv : the preprint server for health sciences

Aiken EL, McGough SF, Majumder MS, Wachtel G, Nguyen AT, Viboud C, Santillana M. (2020). Real-time estimation of disease activity in emerging outbreaks using internet search information. PLoS computational biology, 16(8)

Poirier C, Luo W, Majumder MS, Liu D, Mandl KD, Mooring TA, Santillana M. (2020). The role of environmental factors on transmission rates of the COVID-19 outbreak: an initial assessment in two spatial scales. Scientific reports, 10(1)

Liu D, Clemente L, Poirier C, Ding X, Chinazzi M, Davis JT, Vespignani A, Santillana M. (2020). 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. ArXiv

Lai S, Ruktanonchai NW, Zhou L, Prosper O, Luo W, Floyd JR, Wesolowski A, Santillana M, Zhang C, Du X, Yu H, Tatem AJ. (2020). Effect of non-pharmaceutical interventions for containing the COVID-19 outbreak in China. medRxiv : the preprint server for health sciences

Lai S, Ruktanonchai NW, Zhou L, Prosper O, Luo W, Floyd JR, Wesolowski A, Santillana M, Zhang C, Du X, Yu H, Tatem AJ. (2020). Effect of non-pharmaceutical interventions to contain COVID-19 in China. Nature

Naveca FG, Claro I, Giovanetti M, de Jesus JG, Xavier J, Iani FCM, do Nascimento VA, de Souza VC, Silveira PP, Lourenço J, Santillana M, Kraemer MUG, Quick J, Hill SC, Thézé J, Carvalho RDO, Azevedo V, Salles FCDS, Nunes MRT, Lemos PDS, Candido DDS, Pereira GC, Oliveira MAA, Meneses CAR, Maito RM, Cunha CRSB, Campos DPS, Castilho MDC, Siqueira TCDS, Terra TM, de Albuquerque CFC, da Cruz LN, Abreu AL, Martins DV, Simoes DSMV, Aguiar RS, Luz SLB, Loman N, Pybus OG, Sabino EC, Okumoto O, Alcantara LCJ, Faria NR. (2019). Genomic, epidemiological and digital surveillance of Chikungunya virus in the Brazilian Amazon. PLoS neglected tropical diseases, 13(3)

Baltrusaitis K, Vespignani A, Rosenfeld R, Gray J, Raymond D, Santillana M. (2019). Differences in Regional Patterns of Influenza Activity Across Surveillance Systems in the United States: Comparative Evaluation. JMIR public health and surveillance, 5(4)

Lipsitch M, Santillana M. (2019). Enhancing Situational Awareness to Prevent Infectious Disease Outbreaks from Becoming Catastrophic. Current topics in microbiology and immunology

Clemente L, Lu F, Santillana M. (2019). Improved Real-Time Influenza Surveillance: Using Internet Search Data in Eight Latin American Countries. JMIR public health and surveillance, 5(2)

MacFadden DR, McGough SF, Fisman D, Santillana M, Brownstein JS. (2018). Antibiotic Resistance Increases with Local Temperature. Nature climate change, 8(6)

Lu FS, Hou S, Baltrusaitis K, Shah M, Leskovec J, Sosic R, Hawkins J, Brownstein J, Conidi G, Gunn J, Gray J, Zink A, Santillana M. (2018). Accurate Influenza Monitoring and Forecasting Using Novel Internet Data Streams: A Case Study in the Boston Metropolis. JMIR public health and surveillance, 4(1)

Majumder MS, Cohn EL, Santillana M, Brownstein JS. (2018). Estimation of Pneumonic Plague Transmission in Madagascar, August-November 2017. PLoS currents, (10)

Brownstein JS, Chu S, Marathe A, Marathe MV, Nguyen AT, Paolotti D, Perra N, Perrotta D, Santillana M, Swarup S, Tizzoni M, Vespignani A, Vullikanti AKS, Wilson ML, Zhang Q. (2017). Combining Participatory Influenza Surveillance with Modeling and Forecasting: Three Alternative Approaches. JMIR public health and surveillance, 3(4)

Yang S, Kou SC, Lu F, Brownstein JS, Brooke N, Santillana M. (2017). Advances in using Internet searches to track dengue. PLoS computational biology, 13(7)

Kluberg SA, McGinnis DP, Hswen Y, Majumder MS, Santillana M, Brownstein JS. (2017). County-level assessment of United States kindergarten vaccination rates for measles mumps rubella (MMR) for the 2014-2015 school year. Vaccine, 35(47)

Baltrusaitis K, Santillana M, Crawley AW, Chunara R, Smolinski M, Brownstein JS. (2017). Determinants of Participants' Follow-Up and Characterization of Representativeness in Flu Near You, A Participatory Disease Surveillance System. JMIR public health and surveillance, 3(2)

Majumder MS, Santillana M, Mekaru SR, McGinnis DP, Khan K, Brownstein JS. (2016). Utilizing Nontraditional Data Sources for Near Real-Time Estimation of Transmission Dynamics During the 2015-2016 Colombian Zika Virus Disease Outbreak. JMIR public health and surveillance, 2(1)

Johansson MA, Reich NG, Hota A, Brownstein JS, Santillana M. (2016). Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico. Scientific reports, (6)

Santillana M, Nguyen AT, Dredze M, Paul MJ, Nsoesie EO, Brownstein JS. (2015). Combining Search, Social Media, and Traditional Data Sources to Improve Influenza Surveillance. PLoS computational biology, 11(10)

Majumder MS, Kluberg S, Santillana M, Mekaru S, Brownstein JS. (2015). 2014 ebola outbreak: media events track changes in observed reproductive number. PLoS currents, (7)

Smolinski MS, Crawley AW, Baltrusaitis K, Chunara R, Olsen JM, Wójcik O, Santillana M, Nguyen A, Brownstein JS. (2015). Flu Near You: Crowdsourced Symptom Reporting Spanning 2 Influenza Seasons. American journal of public health, 105(10)

Yang S, Santillana M, Kou SC. (2015). Accurate estimation of influenza epidemics using Google search data via ARGO. Proceedings of the National Academy of Sciences of the United States of America, 112(47)

Gluskin RT, Johansson MA, Santillana M, Brownstein JS. (2014). Evaluation of Internet-based dengue query data: Google Dengue Trends. PLoS neglected tropical diseases, 8(2)

Nagar R, Yuan Q, Freifeld CC, Santillana M, Nojima A, Chunara R, Brownstein JS. (2014). A case study of the New York City 2012-2013 influenza season with daily geocoded Twitter data from temporal and spatiotemporal perspectives. Journal of medical Internet research, 16(10)

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