Xavier Basagaña

Xavier Basagaña is an Associate Research Professor at the Barcelona Institute for Global Health (ISGlobal), specializing in environmental epidemiology and biostatistics. He holds a Diploma (1999) and Licenciatura in Statistics (2002) from Universitat Politécnica de Catalunya and a PhD in Biostatistics from Harvard University (2007). Previously, he served as Assistant Research Professor at the Centre for Research in Environmental Epidemiology (CREAL).

His educational background includes:

• Diploma in Statistics, Universitat Politécnica de Catalunya (1999)
• Licenciatura in Statistics, Universitat Politécnica de Catalunya (2002)
• PhD in Biostatistics, Harvard University (2007)

Dr. Basagaña's research centers on statistical methodologies for observational studies, extreme temperature-health relationships, and air pollution health impacts. He leads the European citizen science project CitieS-Health (urban environment and health) and the ATENC!Ó project investigating air pollution effects on students' attention. His work extends to heat exposure, exposome research, and respiratory health, employing advanced epidemiological designs to address critical environmental health questions.

His recent publications (2015-2019) reveal consistent focus on environmental health epidemiology, with key contributions in temperature-mortality relationships, air pollution neurodevelopmental effects, and methodological innovations for multicentre studies. His research predominantly utilizes longitudinal and time-series designs with Spanish population data, directly informing public health interventions like Heat Health Prevention Plans.

Dr. Basagaña leads major research initiatives including the European CitieS-Health project and ATENC!Ó, while collaborating on multiple studies spanning air pollution, heat exposure, exposome, and respiratory health domains.

He operates within ISGlobal's environmental epidemiology research framework, contributing to institutional expertise in environmental health risk assessment through rigorous statistical approaches and community-engaged science.