Wildfire exposure and academic performance in Brazil: A causal inference approach for spatiotemporal data

Sean McGrath; Rajarshi Mukherjee; Weeberb J Réquia; Wan-Chen Lee

doi:10.1016/j.scitotenv.2023.167625

Wildfire exposure and academic performance in Brazil: A causal inference approach for spatiotemporal data

Sci Total Environ. 2023 Dec 20:905:167625. doi: 10.1016/j.scitotenv.2023.167625. Epub 2023 Oct 5.

Authors

Sean McGrath¹, Rajarshi Mukherjee¹, Weeberb J Réquia², Wan-Chen Lee³

Affiliations

¹ Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, USA.
² Center for Environment and Public Health Studies, School of Public Policy and Government, Fundação Getúlio Vargas, Brasília, Brazil.
³ Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, Taipei, Taiwan. Electronic address: wanchenlee@ntu.edu.tw.

PMID: 37804967
DOI: 10.1016/j.scitotenv.2023.167625

Abstract

As the frequency and intensity of wildfires are projected to globally amplify due to climate change, there is a growing need to quantify the impact of exposure to wildfires in vulnerable populations such as adolescents. In our study, we applied rigorous causal inference methods to estimate the effect of wildfire exposure on the academic performance of high school students in Brazil between 2009 and 2015. Using longitudinal data from 8,183 high schools across 1,571 municipalities in Brazil, we estimated that the average performance in most academic subjects decreases under interventions that increase wildfire exposure, e.g., a decrease of 1.8 % (p = 0.01) in the natural sciences when increasing the wildfire density from 0.0035 wildfires/km² (first quantile in the sample) to 0.0222 wildfires/km² (third quartile). Furthermore, these effects considerably worsened over time. Our findings highlight the adverse impact of wildfires on educational outcomes.

Keywords: Academic performance; Adolescents; Causal inference; Spatiotemporal data; Wildfire.