Ibraheem M Karaye1, Courtney Thompson2, Jennifer A Horney1. 1. Program in Epidemiology, University of Delaware, Newark, DE, USA. 2. Department of Geography, Texas A&M University, College Station, TX, USA.
Abstract
BACKGROUND: Socially vulnerable residents of US Gulf Coast counties have higher exposure to physical hazards and disaster-associated risks. Evacuation is one way to mitigate the consequences of disaster exposure among socially vulnerable populations. However, it is unknown whether existing evacuation shelter capacity and locations in designated hurricane evacuation zones of Texas are adequate to accommodate persons with housing and transportation needs. This study estimated the evacuation shelter deficit arising from demand from socially vulnerable residents of the Houston-Galveston area. METHODS: Spatial statistical methods including Global Moran's I and Getis-Ord (Gi*) were used to measure spatial autocorrelation and identify census tracts in the study area with high (hot spots) and low (cold spots) social vulnerability in both housing and transportation domains. The shelter deficit in each county within the study area was estimated as well as for the entire Houston-Galveston Metropolitan Statistical Area. RESULTS: Designated evacuation zones in the Houston-Galveston area have an overall shelter deficit of 163 317 persons. Shelters in the area can only accommodate 36% of evacuees with significant housing and transportation needs, while 3 of 4 counties had county-specific evacuation shelter deficits. The highest deficits were in Harris County, where Houston is located, and the lowest were in Matagorda County, a rural county southwest of Harris County. CONCLUSION: Emergency managers and other authorities should consider data related to demand from socially vulnerable residents for public shelters during disasters and increase shelter capacity in certain locations to address evacuation shelter shortage for vulnerable persons in designated evacuation zones of Texas.
BACKGROUND: Socially vulnerable residents of US Gulf Coast counties have higher exposure to physical hazards and disaster-associated risks. Evacuation is one way to mitigate the consequences of disaster exposure among socially vulnerable populations. However, it is unknown whether existing evacuation shelter capacity and locations in designated hurricane evacuation zones of Texas are adequate to accommodate persons with housing and transportation needs. This study estimated the evacuation shelter deficit arising from demand from socially vulnerable residents of the Houston-Galveston area. METHODS: Spatial statistical methods including Global Moran's I and Getis-Ord (Gi*) were used to measure spatial autocorrelation and identify census tracts in the study area with high (hot spots) and low (cold spots) social vulnerability in both housing and transportation domains. The shelter deficit in each county within the study area was estimated as well as for the entire Houston-Galveston Metropolitan Statistical Area. RESULTS: Designated evacuation zones in the Houston-Galveston area have an overall shelter deficit of 163 317 persons. Shelters in the area can only accommodate 36% of evacuees with significant housing and transportation needs, while 3 of 4 counties had county-specific evacuation shelter deficits. The highest deficits were in Harris County, where Houston is located, and the lowest were in Matagorda County, a rural county southwest of Harris County. CONCLUSION: Emergency managers and other authorities should consider data related to demand from socially vulnerable residents for public shelters during disasters and increase shelter capacity in certain locations to address evacuation shelter shortage for vulnerable persons in designated evacuation zones of Texas.
Entities:
Keywords:
evacuation; hurricane; shelter capacity; social vulnerability; spatial statistics
Exposure to geophysical natural hazards, such as fault lines and flood plains, does not
always result in disaster impacts. Disasters are not the “inevitable outcome of a hazards’ impact”[1] but occur when proximity to natural hazards coincides with preexisting social vulnerabilities.[2,3] This interaction occurs frequently in a number of areas located along the US Gulf
Coast, where high-risk, hazard-susceptible areas have high proportions of socially
vulnerable residents.[4] In US Gulf Coast counties, higher social vulnerability has been positively associated
with the amount of disaster damage, measured in total dollars per capita.[5] For example, in New Orleans, Louisiana, flooding associated with Hurricane Katrina
and subsequent levee failures had the largest impacts on socially vulnerable residents who
were more likely to live in poverty, be renters rather than homeowners, African American,
female, and have poorer physical health.[6] While a larger total share of damage may have been borne by wealthier residents, the
relative impacts of disasters such as Hurricane Katrina on residents with lower incomes mean
that they are more likely to face challenges with response and also lack the resources
necessary for recovery.[7]After Hurricane Katrina, more than 70 000 socially vulnerable residents of New Orleans were
stranded in flooded neighborhoods for days, unable to access evacuation shelter facilities
and other response and recovery resources.[8] Inability to evacuate an impending storm has been shown to result in excess deaths
from both direct causes, including drowning, trauma, and carbon monoxide poisoning, and
indirectly through complications associated with exacerbation of chronic conditions such as
diabetes or cardiovascular disease.[9-11] The health impacts of disasters on socially vulnerable populations are often greater
in part due to their higher disaster-associated risks and expanded care needs. Poverty may
leave socially vulnerable residents of hazard-prone areas unable to finance the costs
associated with an evacuation.[12] Lack of access to a personal vehicle may prevent them from driving to shelters or
higher ground,[13] while highly publicized traffic jams from prior storms, some leading to injury and
death during evacuations, may further deter evacuation.[14-16] Disabilities and poor physical or mental health may limit socially vulnerable
residents’ ability to comply with evacuation orders or access shelters due to concerns about
disruptions to routine medical care or access to durable medical equipment.[17,18]In high hazard exposure states located along the US Gulf Coast, like Texas, other factors
that could potentially magnify the impact of a disaster on socially vulnerable groups
include poor adaptive capacity and resilience at the state, county, and community levels. In
a study conducted by Ross[19] on the administrative perspective of disaster resilience, Texas was the least
equipped for natural disasters, with coastal counties in the state having lower adaptive
capacities for disaster resilience than coastal counties in Louisiana, Alabama, Mississippi,
and Florida. According to the Baseline Resilience Indicators for Communities, measures of
social, economic, housing, and infrastructure resilience in south Texas counties were among
the lowest in the United States.[20] Similarly, research by Reams et al[21] on county-level adaptive capacity for resilience found that the most resilient
counties in the US Gulf Coast were those that invested more in education, had higher per
capita incomes, and more women in the workforce—4 of the 5 least resilient counties using
this metric were located along the Texas Gulf Coast.[21]Synergies between high social vulnerability and poor adaptive capacity like those present
in coastal Texas can compound disaster-associated risks for residents. One potential way to
minimize disaster impacts from tropical storms and hurricanes for socially vulnerable
residents of this region is to ensure that hurricane evacuation shelters have adequate
capacity and are accessible to socially vulnerable populations. For example, based on data
related to hurricane evacuation behavior in Florida, officials have eliminated shelter
deficits, ensuring accessibility to a shelter with adequate space in evacuees home counties,
since in the event of a storm, residents are more likely to evacuate to shelters near their homes.[22] However, no study has been conducted to quantify the potential shelter deficit for
socially vulnerable residents of designated hurricane evacuation zones in the highly
vulnerable Houston-Galveston area of Texas. Using a “county-boundary sheltering” model
similar to the State of Florida’s, this study estimated the shelter deficit for socially
vulnerable residents of this area. In the context of this study, socially vulnerable
populations refer to residents of hurricane evacuation zip-zones of Texas who have
significantly high housing and transportation needs. To our knowledge, this is the first
study to quantify shelter deficit for socially vulnerable populations in Texas. Findings
could inform emergency management and other public health preparedness and response
officials about potential approaches to eliminate shelter shortages, especially for socially
vulnerable residents living in highly physically vulnerable locations.
Methods
Study Area and Population
The Houston-Galveston Area Council has designated 4 hurricane evacuation zip-zones in the
Houston-Galveston Metropolitan Statistical Area (MSA); zip-zone Coastal, zip-zone A,
zip-zone B, and zip-zone B[23,24] (Figure 1). The zip-zones
include zip codes in 6 coastal Texas counties: Matagorda, Chambers, Brazoria, Galveston,
Harris, and Liberty. The total population of the 4 evacuation zip-zones is 1.78 million.[25] Although other areas of the MSA are also highly vulnerable to the impacts of
tropical storms and hurricanes, including inland flooding, we assume for this study that
evacuation shelter demand would arise only from the population living in the designated
zip-zones, since residents who live outside the zip-zones are considered to be at low risk
of storm-surge associated flooding. For this reason, this study was only restricted to the
population that reside in the evacuation zip-zones.
Figure 1.
Hurricane evacuation zip-zones in the Houston-Galveston Metropolitan Statistical Area
(MSA).
Hurricane evacuation zip-zones in the Houston-Galveston Metropolitan Statistical Area
(MSA).
Data Sources and Software
Data to calculate the Social Vulnerability Index (SVI) were obtained from the Center for
Disease Control and Prevention (CDC).[26] Shapefiles for evacuation shelters in the Houston-Galveston MSA were obtained from
Federal Emergency Management Agency (FEMA) and Homeland Infrastructure Foundation-Level Data.[27] Regional boundary data on counties and zip codes were downloaded from the
Houston-Galveston Area Council.[28] ArcMap 10.4.2 (Redlands, California) was used for the analysis.
Social Vulnerability Index
The SVI was developed by the Agency for Toxic Substances and Disease Registry (ATSDR) and
CDC to enable public health officials and other relevant authorities to spatially identify
populations that would likely need support before, during, and after disasters of all types.[29] The SVI is calculated by ranking census tracts on 15 variables in 4 domains
including socioeconomic status, household composition and disability, minority status and
language, and housing and transportation.[29] Although information on the 4 themes were available in the comprehensive data set,
for this study, we focused on the index for housing and transportation (HTI), which is
made up of housing structure, crowding, and vehicle access variables. The HTI was
estimated for census tracts located in the hurricane evacuation zip-zones of the
Houston-Galveston MSA. Additional details on the methods for estimation of SVI is
available elsewhere.[29]
Spatial Analysis
Moran’s I statistic
Moran’s I statistic is a global measure of spatial dependence used to estimate spatial
correlation based on feature locations and attribute values and determine if the feature
locations are clustered, dispersed, or random.[30] The null hypothesis assumes that no spatial dependence exists in the study area,
meaning that feature locations are random. Moran’s I statistic ranges from −1 to +1 with
statistically significantly negative values indicating dispersion, positive values
indicating clustering, and a zero value indicating complete spatial randomness (no
autocorrelation).
Hot spot analysis
The Getis-Ord statistic (Gi*) was used to identify HTI hotspots. A high value of the
Gi* statistic denotes a cluster of high-index values (ie, hot spots), while a low value
of the statistic represents a cluster of low-index values (ie, cold spots). The
statistical significance of the hotspots was determined based on 90%, 95%, and 99%
confidence intervals.
Estimation of evacuation shelter space deficit
The “Select by Location” tool was used to restrict the analysis to the HTI hotspots
contained in the hurricane evacuation zip-zones. For each county, the population of
vulnerable persons was determined by estimating the total hotspot population within the
county boundary. Because previous studies have estimated potential shelter demand at 25%
of the total population,[31,32] a similar threshold was used to estimate potential shelter demand in this study.
Shelter supply was calculated as the total number of shelter spaces in a county. Using a
supply and demand relationship, shelter deficit was then estimated. Absolute county
deficit was obtained by calculating the difference between shelter capacity and shelter
demand in a county, while relative county shelter capacity was obtained by computing a
ratio between the 2 variables. The aggregate absolute deficit for the Houston-Galveston
MSA was estimated by computing the difference between the total shelter spaces in the
13-county MSA (N = 91 600) and the total shelter demand for vulnerable persons living in
evacuation zip-zones. Similarly, the aggregate relative capacity was estimated by
computing the ratio between the 2 variables.
Results
The Moran’s I index was 0.17 with an Z score of 62.49 and an P value of
.00. Therefore, there was a significant spatial dependence of housing and transportation
vulnerability in the study area. Figure
2 illustrates census tracts with statically significant housing and transportation
vulnerability in the study area (hot spots = red; cold spots = blue).
Figure 2.
Housing and transportation vulnerability hot spots.
Housing and transportation vulnerability hot spots.Four of the 6 counties in the hurricane evacuation zip-zones have populations with
significantly high vulnerability for housing and transportation. The total population of
vulnerable persons in these counties was 1 019 667. No housing and transportation hot spots
were identified in Liberty or Chambers Counties. The Houston-Galveston MSA (including
counties outside of the evacuation zip-zones) has a total shelter capacity of 91 600 persons
(Table 1).
Table 1.
Evacuation Shelter Deficit in the Evacuation Zip-Zones of Texas.
County
Total Population (est. 2017)
Vulnerable Population
Shelter Demand (0.25*Vul. Pop.)
Shelter Capacity
Absolute Shelter Space Deficit
Relative Shelter Capacity
Brazoria
362 457
214 086
53 522
6450
47 072a
0.12
Galveston
335 036
9976
2494
4530
2036
1.82
Harris
4 652 980
787 229
196 807
35 303
161 504a
0.18
Matagorda
36 840
8376
2094
518
1576a
0.25
Houston-Galveston MSA
7 064 712
1 019 667
254 917
91 600
163 317a
0.36
Abbreviation: MSA, Metropolitan Statistical Area.
adenotes evacuation shelter space deficit.
Evacuation Shelter Deficit in the Evacuation Zip-Zones of Texas.Abbreviation: MSA, Metropolitan Statistical Area.adenotes evacuation shelter space deficit.Three of the 4 counties with the highest social vulnerability in HTI—Brazoria, Harris, and
Matagorda—were deficient in evacuation shelter space (Table 1). Harris County had the highest absolute
shelter deficit (161 504) while Matagorda had the lowest (1 576). In addition, Harris County
can only meet 18% (35 303 of 196 807) of the shelter demand arising from highly vulnerable
populations, and additional shelter space for 161 504 persons would be required to eliminate
the deficit in Harris County. Overall, the hurricane evacuation zip-zones have a shelter
deficit for 163 317 persons and only 36% (91 600 of 254 917) of the highly vulnerable
housing and transportation population in these zones could be sheltered in the facilities
within the entire Houston-Galveston MSA (Table 1).
Discussion
The Houston-Galveston region’s hurricane evacuation zip-zones have relatively large shelter
deficits for populations with high transportation and housing vulnerability as defined by
the SVI. In the advent of a severe tropical storm or hurricane with significant storm surge,
more than 160 000 vulnerable persons in evacuation zip-zones may be left stranded without
shelter space in the entire 13-county MSA. Because these residents also have housing and
transportation needs, they are likely unable to travel longer distances beyond their county
of residence to access evacuation shelters in other counties or regions of Texas.After Hurricane Katrina, a survey of residents who did not evacuate reported that 55%
attributed their nonevacuation to not owning a car or having access to another means of transportation.[33] In addition, most evacuation decisions in Hurricane Katrina were shaped by social
vulnerabilities like poverty, preexisting medical conditions, and minority status.[6] If a similar storm were to make landfall along the Texas Gulf Coast, the shelter
shortage in the hurricane evacuation zip-zones may expose disaster-susceptible residents not
only to the immediate impacts of the storm, such as surge and flooding, but also to acute
and longer term consequences such as physical and mental health morbidity and mortality.[6] For example, drowning was the leading cause of death due to Hurricane Katrina,[9] while a majority of the 117 deaths that occurred following Hurricane Sandy were
attributed to drowning of nonevacuees in their homes.[9] Nonevacuees are also more likely to die of trauma, carbon monoxide poisoning, and
other illnesses such as heart failure.[10,11]Although counties predominantly located in evacuation zip-zones would be expected to have
nonsufficient shelter space because of their geographic locations, alternative ways exist by
which shelter deficit could still be eliminated in these areas. These include (but are not
limited to) the retrofitting of existing shelters, mandating district schools to serve a
dual-purpose function, creating new shelter spaces that conform to American Red Cross (ARC)
guidelines, and transporting vulnerable persons to shelters in other counties (inland). For
example, Texas could follow the model applied by the State of Florida[22] in addressing shelter deficit, having attained the milestone of eliminating shelter
deficits through 2023. In 1995, Florida conducted an appraisal of existing evacuation
shelters and enacted a statute that mandated district schools in the state to serve a
dual-purpose role. Existing shelters were retrofitted with school-based shelters overhauled
to meet ARC shelter design guidelines. By 2006, Florida estimated a statewide shelter
deficit of 386 379 persons for category 5 hurricanes, and by 2018 the state has eliminated
its aggregate shelter deficit for the general population, with shelter spaces projected to
be sufficient (based on population growth estimates) through 2023.[22] Regardless of the method chosen by authorities in Texas to eliminate shelter deficit,
the findings in this study would assist in estimating the burden of shelter support that is
required for the vulnerable population. This study has several important limitations. Based
on a long-standing evidence from both disaster research and data collected by first responders,[31,32,22] shelter demand was estimated to be 25% for the socially vulnerable population
residing in the hurricane evacuation zip-zones. In other words, it was assumed that 25% of
socially vulnerable population living in high-hazard areas would use public shelters in the
case of an evacuation. The use of 25% for shelter demand in this study assumes that shelter
needs are similar in both general and vulnerable populations. However, actual shelter demand
would likely be higher for the socially vulnerable, and our result may be an underestimate.
Shelter deficit was also estimated in both absolute and relative terms—the former to enable
emergency managers and county officials to quantify the shelters required to eliminate
shortage, and the latter to permit comparison between shelter capacity and shelter demand
for each county. County-shelter deficits were estimated assuming that socially vulnerable
residents would evacuate to shelters in the same county as their residence, and aggregate
deficit was estimated assuming that vulnerable residents would evacuate to shelters in other
counties within the MSA. If authorities are able to provide transportation to shelters in
other counties or regions across the state respectively, then our deficit estimates would
overestimate the true demand. We used county-level analysis because it was employed in
previous studies conducted by Florida and New England states.[22,34] County governments are also known to play significant roles in emergency management
activities and often serve as intermediaries between municipalities and state governments.[35-37]Shelter demand was estimated based on the US Center for Disease Control and Prevention’s
SVI. The hierarchical model of CDC’s SVI has been shown to have a lower precision and weaker
internal validity compared to deductive and inductive models,[38,39] and the precision of the model has been found to be sensitive to the weighting scheme chosen.[39] However, some studies have shown that CDC’s SVI has a higher accuracy than other
models and compares well to other indices of social vulnerability.[39,40] The CDC SVI was also chosen for this study because it is publicly available and has
been cited more than 180 times in the literature (see https://www.researchgate.net/publication/274439003_A_Social_Vulnerability_Index_for_Disaster_Management).
Finally, the data source for evacuation shelters used in the study is synchronized with FEMA
and ARC databases in real time and therefore subjected to frequent updates. While such
updates may provide the most currently relevant information, they may also impact the
ability of readers to replicate the study results. The findings obtained from this study
were based on data collected on April 8, 2019.This study also has several important strengths. To our knowledge, it is the first to
estimate shelter deficits specifically for socially vulnerable residents of designated
hurricane evacuation zip-zones in Texas. Second, it employed spatial statistical methods to
identify highly vulnerable groups and corresponding shelter capacity. Finally, it relied on
publically available data from the US Census and FEMA, as well as a validated measure of
social vulnerability developed by ATSDR and CDC.
Conclusion
This study employed spatial statistical methods to estimate shelter deficits for socially
vulnerable residents of designated hurricane evacuation zones in Texas. In addition to
social vulnerability, this region is frequently exposed to physical hazards, including major
hurricane landfalls every 6 years on average.[41] This study focused on vulnerability related to housing and transportation, which are
likely to be related to both the decision and the ability to evacuate when ordered by local
officials in the event of a disaster. While Hurricane Harvey was primarily an inland
flooding event in the Houston-Galveston area, the next major tropical storm or hurricane
will likely include more severe storm surge and coastal flooding, which may be exacerbated
by sea-level rise,[42] subsidence,[43] and rapid population growth and development in the region.[44] In the event of a major tropical storm or hurricane, more than 160 000 socially
vulnerable residents of Harris, Brazoria, and Matagorda counties could be left without
needed space in an evacuation shelter. To protect the public’s health and safety, emergency
management and other local authorities should consider approaches to eliminating the shelter
deficit (like creating new shelters, retrofitting existing shelters, or providing
transportation to shelters in other counties), particularly for socially vulnerable
residents.
Authors: David P Eisenman; Kristina M Cordasco; Steve Asch; Joya F Golden; Deborah Glik Journal: Am J Public Health Date: 2007-04-05 Impact factor: 9.308
Authors: Keith Elder; Sudha Xirasagar; Nancy Miller; Shelly Ann Bowen; Saundra Glover; Crystal Piper Journal: Am J Public Health Date: 2007-04-05 Impact factor: 9.308
Authors: David F Zane; Tesfaye M Bayleyegn; John Hellsten; Ryan Beal; Crystal Beasley; Tracy Haywood; Dana Wiltz-Beckham; Amy F Wolkin Journal: Disaster Med Public Health Prep Date: 2011-03 Impact factor: 1.385
Authors: Ibraheem M Karaye; Jennifer A Horney; David P Retchless; Ashley D Ross Journal: Int J Environ Res Public Health Date: 2019-11-03 Impact factor: 3.390