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)
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)
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)
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)
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
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)
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)
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)
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)
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