Dataset Information

Social inequalities in climate change-attributed impacts of Hurricane Harvey.

ABSTRACT: Climate change is already increasing the severity of extreme weather events such as with rainfall during hurricanes. But little research to date investigates if, and to what extent, there are social inequalities in climate change-attributed extreme weather event impacts. Here, we use climate change attribution science paired with hydrological flood models to estimate climate change-attributed flood depths and damages during Hurricane Harvey in Harris County, Texas. Using detailed land-parcel and census tract socio-economic data, we then describe the socio-spatial characteristics associated with these climate change-induced impacts. We show that 30 to 50% of the flooded properties would not have flooded without climate change. Climate change-attributed impacts were particularly felt in Latina/x/o neighborhoods, and especially so in Latina/x/o neighborhoods that were low-income and among those located outside of FEMA's 100-year floodplain. Our focus is thus on climate justice challenges that not only concern future climate change-induced risks, but are already affecting vulnerable populations disproportionately now.

SUBMITTER: Smiley KT

PROVIDER: S-EPMC9411551 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Social inequalities in climate change-attributed impacts of Hurricane Harvey.

Smiley Kevin T KT Noy Ilan I Wehner Michael F MF Frame Dave D Sampson Christopher C CC Wing Oliver E J OEJ

Nature communications 20220825 1

Climate change is already increasing the severity of extreme weather events such as with rainfall during hurricanes. But little research to date investigates if, and to what extent, there are social inequalities in climate change-attributed extreme weather event impacts. Here, we use climate change attribution science paired with hydrological flood models to estimate climate change-attributed flood depths and damages during Hurricane Harvey in Harris County, Texas. Using detailed land-parcel and ...[more]

PMID: 36008390

Similar Datasets

Project description:Extreme weather events can temporarily alter the structure of coastal systems and generate floodwaters that are contaminated with fecal indicator bacteria (FIB); however, every coastal system is unique, so identification of trends and commonalities in these episodic events is challenging. To improve our understanding of the resilience of coastal systems to the disturbance of extreme weather events, we monitored water quality, FIB at three stations within Clear Lake, an estuary between Houston and Galveston, and three stations in bayous that feed into the estuary. Water samples were collected immediately before and after Hurricane Harvey (HH) and then throughout the fall of 2017. FIB levels were monitored by culturing E. coli and Enterococci. Microbial community structure was profiled by high throughput sequencing of PCR-amplified 16S rRNA gene fragments. Water quality and FIB data were also compared to historical data for these water body segments. Before HH, salinity within Clear Lake ranged from 9 to 11 practical salinity units (PSU). Immediately after the storm, salinity dropped to < 1 PSU and then gradually increased to historical levels over 2 months. Dissolved inorganic nutrient levels were also relatively low immediately after HH and returned, within a couple of months, to historical levels. FIB levels were elevated immediately after the storm; however, after 1 week, E. coli levels had decreased to what would be acceptable levels for freshwater. Enterococci levels collected several weeks after the storm were within the range of historical levels. Microbial community structure shifted from a system dominated by Cyanobacteria sp. before HH to a system dominated by Proteobacteria and Bacteroidetes immediately after. Several sequences observed only in floodwater showed similarity to sequences previously reported for samples collected following Hurricane Irene. These changes in beta diversity corresponded to salinity and nitrate/nitrite concentrations. Differential abundance analysis of metabolic pathways, predicted from 16S sequences, suggested that pathways associated with virulence and antibiotic resistance were elevated in floodwater. Overall, these results suggest that floodwater generated from these extreme events may have high levels of fecal contamination, antibiotic resistant bacteria and bacteria rarely observed in other systems.

Project description:OBJECTIVE:To evaluate the association between Hurricane Harvey landfall with maternal and neonatal morbidity. METHODS:Using an institutional perinatal database from two hospitals in Houston, Texas, women with nonanomalous singletons delivering after 24 weeks of gestation between August 2011 and June 2018 were included. To evaluate the possible association of hurricane landfall with pregnancy outcomes, gravid women delivering within 280 days (40 weeks of gestation) on or after August 25, 2017 (the day of hurricane landfall) were categorized as exposed, and women who delivered before August 25, 2017, were the reference group. Composite maternal morbidity included any of the following: hypertensive disorders of pregnancy, chorioamnionitis, endometritis, blood transfusion, peripartum hysterectomy, maternal critical care admission, pulmonary edema, or maternal death. Composite neonatal morbidity included any of the following: 5-minute Apgar score 3 or less, respiratory distress syndrome, use of ventilator or continuous positive airway pressure, suspected newborn sepsis, seizure, stillbirth, or neonatal death. Adjusted odds ratios (aORs) were calculated after correcting for possible confounders identified on univariate analysis. Disruption in outcome trends were measured in time series analyses. RESULTS:Of 40,502 deliveries in our database, 29,179 (72%) met the inclusion criteria, with 3,842 (13.2%) delivering within 280 days of Hurricane Harvey landfall. Women delivering after Hurricane Harvey were on average less likely to be obese and more likely to be older, Caucasian, married, have a household income higher than $75,000, a high school education, and private insurance. However, compared with the cohort of gravid patients who delivered before Hurricane Harvey, composite maternal morbidity increased by 27% (11.5% vs 14.7%, aOR 1.27, 95% CI 1.14-1.42) after the storm. Composite neonatal morbidity increased by 50% (7.8% vs 11.9%, aOR 1.52, 95% CI 1.34-1.71). In time series analyses, we observed a significant shift in composite maternal morbidity specific to women of low socioeconomic status (estimate 2.87, P=.028). CONCLUSION:Despite having fewer at-risk baseline characteristics, gravid patients delivering after landfall by Hurricane Harvey had a significantly higher likelihood of adverse outcomes as did their neonates.

Dataset Information

Social inequalities in climate change-attributed impacts of Hurricane Harvey.

Publications

Social inequalities in climate change-attributed impacts of Hurricane Harvey.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets