---
id: "aiethics:lecture/data-science-against-covid"
type: "AI Ethics course lecture"
title: "Data Science against COVID-19: The Valencian Experience"
url: "https://aiethicscourse.org/lectures/data-science-against-covid"
authors: ["Nuria Oliver"]
summary: "In this module, we explore the ELLIS Alicante Foundation’s Data-Science for COVID-19 team’s work in the Valencian region of Spain."
source: "AI Ethics: Global Perspectives (aiethicscourse.org)"
licence: "Creative Commons Attribution-ShareAlike 4.0 International (http://creativecommons.org/licenses/by-sa/4.0/)"
---

# Data Science against COVID-19: The Valencian Experience

A lecture of the course [AI Ethics: Global Perspectives](https://aiethicscourse.org/).

## Lecturer

- Nuria Oliver, Scientific Director and Co-Founder, ELLIS Alicante Foundation

## About this lecture

In this module, we explore the ELLIS Alicante Foundation’s Data-Science for COVID-19 team’s work in the Valencian region of Spain. The team was founded in response to the pandemic in March 2020 to assist policymakers in making informed, evidence-based decisions. The team tackles four different work areas: modeling human mobility, building computational epidemiological models, predictive models on the prevalence of the disease, and operating one of the largest online citizen surveys related to COVID-19 in the world. This lecture explains the four work streams and shares lessons learned from their work at the intersection between data, AI, and the pandemic.

## Video and transcript

- Video: [https://www.youtube.com/watch?v=k7AHusmFCF0](https://www.youtube.com/watch?v=k7AHusmFCF0)
- Transcript (PDF): [https://aiethicscourse.org/img/72ebd62e-34d9-4987-99aa-1d4db948413f.pdf](https://aiethicscourse.org/img/72ebd62e-34d9-4987-99aa-1d4db948413f.pdf)

## Read, watch, and listen

- COVID-19 Impact Survey
- [Covid-19 Impact Survey Results](https://ellisalicante.org/en/covid19impactsurvey)
- [Open Data Science to Fight COVID-19: Winning the 500k XPRIZE Pandemic Response Challenge](https://doi.org/10.1007/978-3-030-86514-6_24), Lozano, M.A. et al. (2021). "Open Data Science to Fight COVID-19: Winning the 500k XPRIZE Pandemic Response Challenge". In: Dong, Y., Kourtellis, N., Hammer, B., Lozano, J.A. (eds) Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track. ECML PKDD 2021. Lecture Notes in Computer Science, vol 12978. Springer, Cham. https://doi.org/10.1007/978-3-030-86514-6_24
- [The impact of control and mitigation strategies during the second wave of coronavirus infections in Spain and Italy](https://doi.org/10.1038/s41598-022-05041-0), De Nadai, M., Roomp, K., Lepri, B. et al. "The impact of control and mitigation strategies during the second wave of coronavirus infections in Spain and Italy". Sci Rep 12, 1073 (2022). https://doi.org/10.1038/s41598-022-05041-0
- [Using Data to Fight COVID-19 and Build Back Better](https://datapopalliance.org/publications/policy-paper-using-data-to-fight-covid-19-and-build-back-better/), Letouzé, E., Oliver, N., Bravo, M.A., and Shoup, N.. "Using Data to Fight COVID-19 and Build Back Better.", Data Pop Alliance Paper Series No. 2, October 2020.
- [Key factors affecting people’s unwillingness to be confined during the COVID-19 pandemic in Spain: a large-scale population study](https://doi.org/10.1038/s41598-021-97645-1), Martinez-Garcia, M., Rabasa, A., Barber, X. et al. "Key factors affecting people’s unwillingness to be confined during the COVID-19 pandemic in Spain: a large-scale population study". Sci Rep 11, 18626 (2021). https://doi.org/10.1038/s41598-021-97645-1