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. 2024 Dec 31;9(1):e362.
doi: 10.1097/EE9.0000000000000362. eCollection 2025 Feb.

Applying a two-stage generalized synthetic control approach to quantify the heterogeneous health effects of extreme weather events: A 2018 large wildfire in California event as a case study

Noemie Letellier  1   2 , Maren Hale  1 , Kasem U Salim  3 , Yiqun Ma  1 , Francois Rerolle  1 , Lara Schwarz  1   4 , Tarik Benmarhnia  1   2
Affiliations

Applying a two-stage generalized synthetic control approach to quantify the heterogeneous health effects of extreme weather events: A 2018 large wildfire in California event as a case study

Noemie Letellier et al. Environ Epidemiol. .

Abstract

Extreme weather events, including wildfires, are becoming more intense, frequent, and expansive due to climate change, thus increasing negative health outcomes. However, such effects can vary across space, time, and population subgroups, requiring methods that can handle multiple exposed units, account for time-varying confounding, and capture heterogeneous treatment effects. In this article, we proposed an approach based on staggered generalized synthetic control methods to study heterogeneous health effects, using the 2018 California wildfire season as a case study. This study aimed to estimate the effects of the November 2018 California wildfires, one of the state's deadliest and most destructive wildfire seasons, on respiratory and circulatory health, document heterogeneity in health impacts, and investigate drivers of this heterogeneity. We applied a two-stage generalized synthetic control method to compare health outcomes in exposed (from 8 November to 5 December 2018) versus unexposed counties and used random-effects meta-regression to evaluate the effect modification of county-level socioeconomic variables on the observed health effects of the November 2018 wildfires. We observed an increase in respiratory hospitalizations for most exposed counties when compared with unexposed counties, with significant increases in Fresno, San Francisco, San Joaquin, San Mateo, and Santa Clara counties. No effect on circulatory hospitalizations was observed. County-level sociodemographic characteristics seem to not modulate the effects of wildfire smoke on respiratory hospitalizations. This novel two-stage framework can be applied in broader settings to understand spatially and temporally compounded health impacts of climate hazards. We provide codes in R for reproducibility and replication purposes.

Keywords: Air pollution; Climate hazards; Environmental justice; Heterogeneous effect; Quasi-experimental method.

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Conflict of interest statement

The authors declare that they have no conflicts of interest with regard to the content of this report.

Figures

Figure 1.
Figure 1.
Mean smoke exposure for California zip codes during 2018 wildfires, 8 November–5 December 2018.
Figure 2.
Figure 2.
California counties considered exposed to wildfire smoke during the November 2018 wildfires.
Figure 3.
Figure 3.
Results of synthetic control analysis of the effect of November 2018 wildfires on respiratory hospitalizations in California for counties exposed to wildfire smoke.
Figure 4.
Figure 4.
ATT and 95% CI by county for the effect of 2018 wildfires on respiratory hospitalizations.
Figure 5.
Figure 5.
Results of meta-regression of change in effects of wildfire smoke on respiratory hospitalizations for standardized increase in county-level sociodemographic variables during November 2018 wildfires in California.
See this image and copyright information in PMC

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