Impact

Awards

The article Nowcasting Temporal Trends Using Indirect Surveys received the Honorary Mention (2nd Best Paper) Award at the Social Impact Track of AAAI 2024, Vancouver, Canada. March 2024

CoronaSurveys was among the five finalists for the COVID-19 Symptom Data Challenge. Over 150 researchers and 50 organizations participated in the call for proposals entitled the COVID-19 Symptom Data Challenge, sponsored by Facebook Data for Good, with the participation of Delphi Group-Carnegie Mellon University (CMU), the Joint Program on Survey Methodology-University of Maryland (UMD), the Duke Margolis Center for Health Policy, and Resolve to Save Lives, an initiative by Vital Strategies. Read more.

CoronaSurveys has received honorable mention in the Pandemic Response Challenge. The project was among the top ten of the challenge launched by XPrize in partnership with Cognizant. Read more.

Our team member, Ananth Venkatesh, from San Ramon Valley High School, USA, finished in third place in the 2022 Congressional App Challenge for the 11th district of California for his app COVID-19 Notebook. Read more.

Reports & Publications

  1. Gontzal Sagastabeitia, Josu Doncel, José Aguilar, Antonio Fernández Anta, Juan Marcos Ramírez, COVID-19 seroprevalence estimation and forecasting in the USA from ensemble machine learning models using a stacking strategy, Expert Systems with Applications, Volume 258, 2024, 124930, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2024.124930.
  2. Baccega, Daniele, Paolo Castagno, Antonio Fernandez Anta, and Matteo Sereno. Enhancing COVID-19 Forecasting Precision through the Integration of Compartmental Models, Machine Learning and Variants. Sci Rep 14, 19220 (2024). https://doi.org/10.1038/s41598-024-69660-5
    • Initial version: medRxiv (2024): 2024-03.
    • Revised version presented at epiDAMIK 2024: The 7th International workshop on Epidemiology meets Data Mining and Knowledge discovery, held in conjunction with ACM SIGKDD 2024, Barcelona, Spain, August 26, 2024.
  3. Srivastava, Ajitesh, Juan Marcos Ramirez, Sergio Díaz-Aranda, Jose Aguilar, Antonio Fernández Anta, Antonio Ortega, and Rosa Elvira Lillo. Nowcasting Temporal Trends Using Indirect Surveys. In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, no. 20, pp. 22359-22367. 2024.
  4. Fernández-Anta, Antonio, Jose Aguilar, Juan M. Ramírez, Rosa Elvira Lillo, and Sergio Díaz-Aranda. Coronasurveys: encuestas indirectas en línea para monitorizar la evolución del COVID-19. Revista Espanola de Comunicacion en Salud (2024): 15-23.
  5. Jesus Rufino, Juan Marcos Ramirez, Jose Aguilar, Carlos Baquero, Jaya Champati, Davide Frey, Rosa Elvira Lillo, Antonio Fernandez Anta. Consistent comparison of symptom-based methods for COVID-19 infection detection, International Journal of Medical Informatics, Volume 177, September 2023, 105133. https://doi.org/10.1016/j.ijmedinf.2023.105133
  6. Jesus Rufino, Juan Marcos Ramirez, Jose Aguilar, Carlos Baquero, Jaya Champati, Davide Frey, Rosa Elvira Lillo, Antonio Fernandez Anta. Performance and explainability of feature selection-boosted tree-based classifiers for COVID-19 detection. Heliyon, vol 10, issue 1, E23219, Jan 15, 2024. https://doi.org/10.1016/j.heliyon.2023.e23219.
  7. Juan M. Ramírez, Sergio Díaz-Aranda, Jose Aguilar, Oluwasegun Ojo, Rosa Elvira Lillo,  Antonio Fernández Anta. A Snapshot of COVID-19 Incidence, Hospitalizations, and Mortality from Indirect Survey Data in China in January 2023, MedRxiv, Jan 2023. doi: https://doi.org/10.1101/2023.02.22.23286167.
  8. Jesús Rufino et al. Using survey data to estimate the impact of the omicron variant on vaccine efficacy against COVID-19 infection, Scientific Reports volume 13, Article number: 900 (2023). DOI: 10.1038/s41598-023-27951-3.
  9. Javier Álvarez et al. Estimating Active Cases of COVID-19, arXiv:2108.03284 [physics.soc-ph], August 2021. Presented at the 2nd KDD Workshop on Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resiliency Planning, August 15, 2021. Updated version in MedRxiv, December 2021.
  10. Carlos Baquero et al. The CoronaSurveys System for COVID-19 Incidence Data Collection and Processing, Front. Comput. Sci., 08 June 2021. doi: 10.3389/fcomp.2021.641237
  11. Augusto Garcia-Agundez, Oluwasegun Ojo, Harold Hernandez, Carlos Baquero, Davide Frey, Chryssis Georgiou, Mathieu Goessens, Rosa Lillo, Raquel Menezes, Nicolas Nicolaou, Antonio Ortega, Efstathios Stavrakis, Antonio Fernandez Anta. Estimating the COVID-19 Prevalence in Spain with Indirect Reporting via Open Surveys, Front. Public Health, 09 April 2021. doi: 10.3389/fpubh.2021.658544
  12. INESC TEC. Estimating active cases of COVID-19: The unknown matters, Medium.com, July 16th, 2020.
  13. Oluwasegun Ojo et al. CoronaSurveys: Using Surveys with Indirect Reporting to Estimate the Incidence and Evolution of Epidemics, arXiv:2005.12783 v2 [cs.DC], June 2020. Presented at The KDD Workshop on Humanitarian Mapping, San Diego, California USA, August 24, 2020.
  14. Carlos Baquero, Paolo Casari, Antonio Fernandez Anta, Davide Frey, Augusto Garcia-Agundez, Chryssis Georgiou, Raquel Menezes, Nicolas Nicolaou, Oluwasegun Ojo, Paul Patras. Measuring Icebergs: Using Different Methods to Estimate the Number of COVID-19 Cases in Portugal and Spain, medRxiv, April 2020. doi: https://doi.org/10.1101/2020.04.20.20073056

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