A county-month panel linked reconstructed tropical cyclone wind exposure to all-cause mortality across Texas counties between 1968 and 2018. Counties ranked high on the Social Vulnerability Index showed raised mortality in the years following exposure, with no clear effect in the rest. Repeating the model with storms that struck only later produced no such effect.
Why it is interesting: The same storm exposure produces different long-run mortality depending on which counties it crosses.
Abstract — the authors' own words, CC BY
Abstract Tropical cyclones can affect health long after landfall, but the persistence and magnitude of these effects may differ across communities. This study examines whether social vulnerability modifies the long-run mortality response to tropical cyclone exposure in Texas. We combine county-month all-cause mortality, population, and temperature data for 1968--2018 with reconstructed tropical cyclone wind exposure beginning in 1953 and county vulnerability classifications based on the Social Vulnerability Index. A reduced-form county-month panel model aggregates current and lagged wind exposure using a normalized long-run response profile and estimates separate effects for high- and lower-vulnerability counties. The specification accounts for county-specific seasonality, common month-year shocks, county trends, evolving seasonal patterns, and county-specific temperature effects. The estimated mortality response is positive and statistically significant among high-vulnerability counties, whereas the estimate for lower-vulnerability counties is smaller and statistically indistinguishable from zero. Future-exposure placebos and exposure-randomization tests support the interpretation that the high-vulnerability estimate is not generated mechanically by the model or exposure distribution. Translating the estimates into event-level and spatial burdens shows that long-run tropical-cyclone mortality is concentrated where repeated physical exposure overlaps with high social vulnerability. These findings indicate that disaster-mortality assessment and resilience planning should consider both hazard intensity and communities' capacity to absorb and recover from shocks.
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