ABOUT THE RESEARCHER

OVERVIEW

Using social media, Internet searches, and electronic health records to predict incidence of flu and dengue in multiple locations worldwide. Using electronic health records to predict outcomes in pediatric intensive care units.

BACKGROUND

Mauricio Santillana is an Assistant Professor at Harvard Medical School, a faculty member in the Computational Health Informatics Program at Boston Children’s Hospital, and an associate at the Harvard Institute for Applied and Computational Sciences. Mauricio enjoys working with clinicians in the design of decision-making support tools.

Mauricio is a physicist and applied mathematician with expertise in mathematical modeling and scientific computing. He has worked in multiple research areas frequently analyzing big data sets to understand and predict the behavior of complex systems. His research modeling population growth patterns has informed policy makers in Mexico and Texas. His research in numerical analysis and computational fluid dynamics has been used to improve models of coastal floods due to hurricanes, and to improve the performance of global atmospheric chemistry models. In recent years, his main interest has been to develop mathematical models to improve healthcare. Specifically, he has leveraged information from big data sets from Internet-based services (such as Google, Twitter, Flu Near You, Weather) and electronic health records (EHR) to predict disease incidence in multiple locations worldwide and to predict outcomes in hospitalized patients. Dr. Santillana has advised the CDC and the White House on the development of population-wide disease forecasting tools.

Mauricio received a B.S. in physics with highest honors from the Universidad Nacional Autonoma de Mexico in Mexico City, and a master’s and PhD in computational and applied mathematics from the University of Texas at Austin. Mauricio first joined Harvard as a postdoctoral fellow at the Harvard Center for the Environment and has been a lecturer in applied mathematics at the Harvard SEAS, receiving two awards for excellence in teaching.

PUBLICATIONS

Publications powered by Harvard Catalyst Profiles

  1. Comparison of post-COVID depression and major depressive disorder. medRxiv. 2021 Apr 04. View abstract
  2. Avoidable Serum Potassium Testing in the Cardiac ICU: Development and Testing of a Machine-Learning Model. Pediatr Crit Care Med. 2021 04 01; 22(4):392-400. View abstract
  3. Persistence of symptoms up to 10 months following acute COVID-19 illness. medRxiv. 2021 Mar 08. View abstract
  4. An early warning approach to monitor COVID-19 activity with multiple digital traces in near real time. Sci Adv. 2021 03; 7(10). View abstract
  5. Association of Acute Symptoms of COVID-19 and Symptoms of Depression in Adults. JAMA Netw Open. 2021 03 01; 4(3):e213223. View abstract
  6. Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile. medRxiv. 2021 Jan 15. View abstract
  7. Incorporating human mobility data improves forecasts of Dengue fever in Thailand. Sci Rep. 2021 Jan 13; 11(1):923. View abstract
  8. COVID-19: US federal accountability for entry, spread, and inequities-lessons for the future. Eur J Epidemiol. 2020 Nov; 35(11):995-1006. View abstract
  9. Rates of increase of antibiotic resistance and ambient temperature in Europe: a cross-national analysis of 28 countries between 2000 and 2016. Euro Surveill. 2020 11; 25(45). View abstract
  10. The role of environmental factors on transmission rates of the COVID-19 outbreak: an initial assessment in two spatial scales. Sci Rep. 2020 10 12; 10(1):17002. View abstract
  11. Correction: Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models. J Med Internet Res. 2020 Sep 22; 22(9):e23996. View abstract
  12. Adding Continuous Vital Sign Information to Static Clinical Data Improves the Prediction of Length of Stay After Intubation: A Data-Driven Machine Learning Approach. Respir Care. 2020 Sep; 65(9):1367-1377. View abstract
  13. Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models. J Med Internet Res. 2020 08 17; 22(8):e20285. View abstract
  14. Real-time estimation of disease activity in emerging outbreaks using internet search information. PLoS Comput Biol. 2020 08; 16(8):e1008117. View abstract
  15. An Early Warning Approach to Monitor COVID-19 Activity with Multiple Digital Traces in Near Real-Time. ArXiv. 2020 Jul 01. View abstract
  16. Communicating Benefits from Vaccines Beyond Preventing Infectious Diseases. Infect Dis Ther. 2020 Sep; 9(3):467-480. View abstract
  17. SARS-CoV-2 titers in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases. medRxiv. 2020 Jun 23. View abstract
  18. Estimating the Early Outbreak Cumulative Incidence of COVID-19 in the United States: Three Complementary Approaches. medRxiv. 2020 Jun 18. View abstract
  19. Effect of non-pharmaceutical interventions to contain COVID-19 in China. Nature. 2020 09; 585(7825):410-413. View abstract
  20. Patients with Cancer Appear More Vulnerable to SARS-CoV-2: A Multicenter Study during the COVID-19 Outbreak. Cancer Discov. 2020 06; 10(6):783-791. View abstract
  21. 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. 2020 Apr 08. View abstract
  22. Aggregated mobility data could help fight COVID-19. Science. 2020 04 10; 368(6487):145-146. View abstract
  23. The Role of Environmental Factors on Transmission Rates of the COVID-19 Outbreak: An Initial Assessment in Two Spatial Scales. SSRN. 2020 Mar 12; 3552677. View abstract
  24. Effect of non-pharmaceutical interventions for containing the COVID-19 outbreak in China. medRxiv. 2020 Mar 06. View abstract
  25. Fitbit-informed influenza forecasts. Lancet Digit Health. 2020 02; 2(2):e54-e55. View abstract
  26. Internet search query data improve forecasts of daily emergency department volume. J Am Med Inform Assoc. 2019 12 01; 26(12):1574-1583. View abstract
  27. Noninvasive Ventilation Is Interrupted Frequently and Mostly Used at Night in the Pediatric Intensive Care Unit. Respir Care. 2020 Mar; 65(3):341-346. View abstract
  28. Differences in Regional Patterns of Influenza Activity Across Surveillance Systems in the United States: Comparative Evaluation. JMIR Public Health Surveill. 2019 Sep 14; 5(4):e13403. View abstract
  29. Improved Real-Time Influenza Surveillance: Using Internet Search Data in Eight Latin American Countries. JMIR Public Health Surveill. 2019 Apr 04; 5(2):e12214. View abstract
  30. Genomic, epidemiological and digital surveillance of Chikungunya virus in the Brazilian Amazon. PLoS Negl Trop Dis. 2019 03; 13(3):e0007065. View abstract
  31. Improved state-level influenza nowcasting in the United States leveraging Internet-based data and network approaches. Nat Commun. 2019 01 11; 10(1):147. View abstract
  32. Enhancing Situational Awareness to Prevent Infectious Disease Outbreaks from Becoming Catastrophic. Curr Top Microbiol Immunol. 2019; 424:59-74. View abstract
  33. Estimation of Pneumonic Plague Transmission in Madagascar, August-November 2017. PLoS Curr. 2018 Nov 01; 10. View abstract
  34. Comparison of crowd-sourced, electronic health records based, and traditional health-care based influenza-tracking systems at multiple spatial resolutions in the United States of America. BMC Infect Dis. 2018 08 15; 18(1):403. View abstract
  35. Relatedness of the Incidence Decay with Exponential Adjustment (IDEA) Model," Farr's Law" and SIR Compartmental Difference Equation Models. Infectious Disease Modelling. 2018; 3(1):1-12. View abstract
  36. Antibiotic Resistance Increases with Local Temperature. Nature Climate Change. 2018; (8):510-514. View abstract
  37. Antibiotic Resistance Increases with Local Temperature. Nat Clim Chang. 2018 Jun; 8(6):510-514. View abstract
  38. Relatedness of the incidence decay with exponential adjustment (IDEA) model, "Farr's law" and SIR compartmental difference equation models. Infect Dis Model. 2018; 3:1-12. View abstract
  39. Accurate Influenza Monitoring and Forecasting Using Novel Internet Data Streams: A Case Study in the Boston Metropolis. JMIR Public Health Surveill. 2018 Jan 09; 4(1):e4. View abstract
  40. Combining Participatory Influenza Surveillance with Modeling and Forecasting: Three Alternative Approaches. JMIR Public Health Surveill. 2017 Nov 01; 3(4):e83. View abstract
  41. County-level assessment of United States kindergarten vaccination rates for measles mumps rubella (MMR) for the 2014-2015 school year. Vaccine. 2017 11 07; 35(47):6444-6450. View abstract
  42. Advances in using Internet searches to track dengue. PLoS Comput Biol. 2017 Jul; 13(7):e1005607. View abstract
  43. Using electronic health records and Internet search information for accurate influenza forecasting. BMC Infect Dis. 2017 05 08; 17(1):332. View abstract
  44. Determinants of Participants' Follow-Up and Characterization of Representativeness in Flu Near You, A Participatory Disease Surveillance System. JMIR Public Health Surveill. 2017 Apr 07; 3(2):e18. View abstract
  45. Forecasting Zika Incidence in the 2016 Latin America Outbreak Combining Traditional Disease Surveillance with Search, Social Media, and News Report Data. PLoS Negl Trop Dis. 2017 01; 11(1):e0005295. View abstract
  46. 1015: IDENTIFICATION OF PEDIATRIC VENTILATOR-ASSOCIATED CONDITIONS USING CONTINUOUS VENTILATOR DATA. Crit Care Med. 2016 Dec; 44(12 Suppl 1):330. View abstract
  47. 955: A MACHINE-LEARNING ALGORITHM FOR OXYGENATION RESPONSE PREDICTION IN MECHANICALLY VENTILATED CHILDREN. Crit Care Med. 2016 Dec; 44(12 Suppl 1):315. View abstract
  48. 949: DEVELOPMENT OF HEART, RESPIRATORY RATE, AND OXYGEN SATURATION PERCENTILE CURVES IN CHILDREN. Crit Care Med. 2016 Dec; 44(12 Suppl 1):313. View abstract
  49. Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico. Sci Rep. 2016 Sep 26; 6:33707. View abstract
  50. Editorial Commentary: Perspectives on the Future of Internet Search Engines and Biosurveillance Systems. Clin Infect Dis. 2017 01 01; 64(1):42-43. View abstract
  51. Utilizing Nontraditional Data Sources for Near Real-Time Estimation of Transmission Dynamics During the 2015-2016 Colombian Zika Virus Disease Outbreak. JMIR Public Health Surveill. 2016 Jun 01; 2(1):e30. View abstract
  52. Cloud-based Electronic Health Records for Real-time, Region-specific Influenza Surveillance. Sci Rep. 2016 05 11; 6:25732. View abstract
  53. Accurate estimation of influenza epidemics using Google search data via ARGO. Proc Natl Acad Sci U S A. 2015 Nov 24; 112(47):14473-8. View abstract
  54. Combining Search, Social Media, and Traditional Data Sources to Improve Influenza Surveillance. PLoS Comput Biol. 2015 Oct; 11(10):e1004513. View abstract
  55. Flu Near You: Crowdsourced Symptom Reporting Spanning 2 Influenza Seasons. Am J Public Health. 2015 Oct; 105(10):2124-30. View abstract
  56. 2014 ebola outbreak: media events track changes in observed reproductive number. PLoS Curr. 2015 Apr 28; 7. View abstract
  57. A case study of the New York City 2012-2013 influenza season with daily geocoded Twitter data from temporal and spatiotemporal perspectives. J Med Internet Res. 2014 Oct 20; 16(10):e236. View abstract
  58. Using clinicians' search query data to monitor influenza epidemics. Clin Infect Dis. 2014 Nov 15; 59(10):1446-50. View abstract
  59. What can digital disease detection learn from (an external revision to) Google Flu Trends? Am J Prev Med. 2014 Sep; 47(3):341-7. View abstract
  60. Evaluation of Internet-based dengue query data: Google Dengue Trends. PLoS Negl Trop Dis. 2014 Feb; 8(2):e2713. View abstract
  61. Gradient-based estimation of Manning’s friction coefficient from noisy data. Journal of Computational and Applied Mathematics. 2013; (238):1–13. View abstract
  62. Quantifying the loss of information in source attribution problems using the adjoint method in global models of atmospheric chemical transport. arXiv preprint arXiv:1311.6315. 2013. View abstract
  63. A numerical approach to study the properties of solutions of the diffusive wave approximation of the shallow water equations. Computational Geosciences. 2010; 1(14):31-53. View abstract
  64. A local discontinuous Galerkin method for a doubly nonlinear diffusion equation arising in shallow water modeling. Computer Methods in Applied Mechanics and Engineering. 2010; 23(199):1424–1436.. View abstract
  65. Estimating small-area population growth using geographic-knowledge-guided cellular automata. International Journal of Remote Sensing. 2010; 21(31):5689–5707. View abstract
  66. An adaptive reduction algorithm for efficient chemical calculations in global atmospheric chemistry models. Atmospheric Environment. 2010; 35(44):4426–4431. View abstract
  67. On the diffusive wave approximation of the shallow water equations. European Journal of Applied Mathematics. 2008; 05(19):575–606. View abstract