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Hurricane evacuation is one of the strategies employed by emergency management and other agencies to reduce morbidity and mortality associated with hurricanes. However, factors associated with residents’ evacuation decision-making have been inconsistent. In this study, we conducted a statistical meta-analysis to identify factors associated with hurricane evacuation as well as moderators of the evacuation decision.
A systematic literature search identified 36 studies published between 1999 and 2018. Pooled estimates were calculated using random-effects models, and heterogeneity across studies was checked using both Q and I2 statistics. Meta-regression methods were used to identify moderators. Publication bias was assessed using both visual (funnel plots) and statistical methods.
Mobile home residence, perception of risk, female sex, and Hispanic ethnicity were statistically associated with hurricane evacuation, while geographic region modified the relationship between Hispanic race and evacuation.
Agencies responsible for preparedness may utilize these findings to identify specific population sub-groups for hurricane evacuation communication and other interventions. Future studies should consider statistical interactions and explore opportunities for research translation to emergency officials.
In response to increasing caseloads of foodborne illnesses and high consequence infectious disease investigations, the Texas Department of State Health Services (DSHS) requested funding from the Texas Legislature in 2013 and 2015 for a new state-funded epidemiologist (SFE) program.
Primary cross-sectional survey data were collected from 32 of 40 local health departments (LHDs) via an online instrument and analyzed to quantify roles, responsibilities, and training of epidemiologists in Texas in 2017 and compared to similar state health department assessments.
Sixty-six percent of SFEs had epidemiology-specific training (eg, master’s in public health) compared to 45% in state health department estimates. For LHDs included in this study, the mean number of epidemiologists per 100 000 was 0.73 in medium LHDs and 0.46 in large LHDs. SFE positions make up approximately 40% of the LHD epidemiology workforce of all sizes and 56% of medium-sized LHD epidemiology staff in Texas specifically.
Through this program, DSHS increased epidemiology capacity almost twofold from 0.28 to 0.47 epidemiologists per 100 000 people. These findings suggest that capacity funding programs like this improve epidemiology capacity in local jurisdictions and should be considered in other regions to improve general public health preparedness and epidemiology capacity.
Hurricane Harvey (2017) forced the closure of hemodialysis centers across Harris County, Texas (USA) disrupting the provision of dialysis services. This study aims to estimate the percentage of hemodialysis clinics flooded after Harvey, to identify the proportion of such clinics located in high-risk flood zones, and to assess the sensitivity of the Federal Emergency Management Agency (FEMA) Flood Insurance Rate Maps (FIRMs) for estimation of flood risk.
Data on 124 hemodialysis clinics in Harris County were extracted from Medicare.gov and geocoded using ArcGIS Online. The FIRMs were overlaid to identify the flood zone designation of each hemodialysis clinic.
Twenty-one percent (26 of 124) of hemodialysis clinics in Harris County flooded after Harvey. Of the flooded clinics, 57.7% were in a high-risk flood zone, 30.8% were within 1km of a high-risk flood zone, and 11.5% were not in or near a high-risk flood zone. The FIRMs had a sensitivity of 58%, misidentifying 42% (11 of 26) of the clinics flooded.
Hurricanes are associated with severe disruptions of medical services, including hemodialysis. With one-quarter of Harris County in the 100-year floodplain, projected increases in the frequency and severity of disasters, and inadequate updates of flood zone designation maps, the implementation of new regulations that address the development of hemodialysis facilities in high-risk flood areas should be considered.
Rural Long-term Care (LTC) providers face unique challenges when planning, preparing for, and responding to disasters. We sought to better understand challenges and identify best practices for LTC in rural areas.
Case studies including key informant interviews and site visits were conducted with LTC staff and emergency planning, preparedness, and response partners in three rural communities. Themes were identified across sites using inductive coding.
Communication across disaster phases continues to be a challenge for LTC providers in rural communities for all disaster types. Communication challenges limit LTC providers’ ability to address patient needs during emergencies and limit the resilience of providers and patients to future disasters. Limited coordination among local leadership and LTC providers prevents dissemination of information, resources, and services, and slows response and recovery time. Including LTC providers as stakeholders in planning and exercises may improve communication and coordination.
More than two decades into efforts to increase preparedness of health care systems to all hazards, rural LTC facilities still face challenges related to communication and coordination. Agencies at the federal, state, and local level should include input from rural LTC stakeholders to address gaps in communication and coordination and increase their disaster resilience.
In the United States, tornadoes are the third leading cause of fatalities from natural disasters1. To aid prevention and mitigation of tornado-related morbidity and mortality, improvement in standardizing tornado specific threat analysis terminology was assessed. The largest number of tornado-related fatalities has occurred in the state of Texas for over a hundred years. The occurrence of tornadic clusters or “outbreaks” has not been formally standardized. The concept of “tornado outbreaks” is better defined and its role in fatality mitigation is addressed in this Institutional Review Board (IRB) approved study.
To understand the role of “tornado outbreaks” related clusters in Texas in relationship to morbidity and mortality.
This IRB approved (IRB2017- 0507) research study utilized GIS tools and statistical analysis of historical data to examine the relationship between tornado severity (based on the Fujita Scale), the number of tornadoes, and the trends in morbidity and mortality. This study was funded in part from The National Science Foundation grant (NSF Grant #1560106) in support of the CyberHealthGIS Research Experience for Undergraduates (REU).
A statistically significant difference was demonstrated between the severity of a tornado and related morbidity and mortality during “tornado outbreaks” in Texas during a defined 30-year period.
Understanding the role and discerning the impacts of “tornado outbreaks” as related to tornado severity has critical implications to disaster preparedness. Applications of this conclusion may improve shelter planning/preparation, timely warning, and educating the at-risk public. Subsequently, examining the likelihood and improved descriptions of “tornado outbreaks” may aid in reducing the number of tornado-related injuries and fatalities nationally.
The use of the Community Assessment for Public Health Emergency Response (CASPER) method in disaster and non-disaster settings continues to grow. While CASPERs flexibility has been well demonstrated, the documentation of specific actions that have resulted from the utilization of CASPER data has been limited. We attempted to document changes in emergency preparedness planning and policy based on CASPER data.
Written reports from 19 CASPERs conducted in Texas between 2001 and 2015 were collected. Key informant interviews were conducted with 9 public health staff knowledgeable about the CASPERs. Written reports and interview transcripts were coded and analyzed for themes.
Few specific outcomes could be documented beyond a single successful grant application. Respondents felt CASPER data was not duplicative and was useful for improving existing plans. CASPER is seen as an effective way to enhance relationships with communities and partnerships with agencies including Emergency Management.
As the use of CASPER grows, it is increasingly important to document any specific and measurable benefits, actions, and changes to planning or policy taken as the result of data collected using the CASPER method. Without measurable outputs and outcomes, support for the use of CASPER from decision-makers may begin to wane. (Disaster Med Public Health Preparedness. 2018;12:680-684)
Prenatal hurricane exposure may be an increasingly important contributor to poor reproductive health outcomes. In the current literature, mixed associations have been suggested between hurricane exposure and reproductive health outcomes. This may be due, in part, to residual confounding. We assessed the association between hurricane exposure and reproductive health outcomes by using a difference-in-difference analysis technique to control for confounding in a cohort of Florida pregnancies.
We implemented a difference-in-difference analysis to evaluate hurricane weather and reproductive health outcomes including low birth weight, fetal death, and birth rate. The study population for analysis included all Florida pregnancies conceived before or during the 2003 and 2004 hurricane season. Reproductive health data were extracted from vital statistics records from the Florida Department of Health. In 2004, 4 hurricanes (Charley, Frances, Ivan, and Jeanne) made landfall in rapid succession; whereas in 2003, no hurricanes made landfall in Florida.
Overall models using the difference-in-difference analysis showed no association between exposure to hurricane weather and reproductive health.
The inconsistency of the literature on hurricane exposure and reproductive health may be in part due to biases inherent in pre-post or regression-based county-level comparisons. We found no associations between hurricane exposure and reproductive health. (Disaster Med Public Health Preparedness. 2017;11:407–411)
Karachi, Pakistan was affected by a heat wave in June 2015 during the Muslim holy month of Ramadan. Many media reports attributed the excess deaths in part to the practice of daylight fasting during Ramadan. As much of the published research reports on heat-related mortality in Europe and the United States, an exploration of the effects of extreme heat on residents of a South Asian mega-city address a gap in current disaster research.
This report investigated potential risk factors for excess mortality associated with the June 2015 heat wave in Karachi, Pakistan.
Data were obtained through manual review of death certificates at public hospitals and private clinics in Karachi, Pakistan, conducted from July 1 through July 31, 2015 by a trained physician. Demographic data for any deaths with a primary cause of death of heat-related illness were recorded in Microsoft Excel (Microsoft Corp.; Redmond, Washington USA). EpiSheet (2012; Rothman. Modern Epidemiology. Lippincott Williams & Wilkins; Philadelphia, Pennsylvania USA) was used to calculate risk differences (RD), rate ratios (RR), and 95% confidence intervals (95% CI).
Overall, residents of Karachi were approximately 17 times as likely to die of a heat-related cause of death during June 2015 (RR=17.68; 95% CI, 13.87-22.53) when compared with the reference period of June 2014. Residents with a monthly income lower than 20,000 Pakistani Rupees (US $196; RD=0.03; 95% CI, 0.01-0.05) and those with less than a fifth grade education (RD=0.03; 95% CI, 0.00-0.05) were at significantly higher risk of death during the 2015 heat wave compared to the reference period.
Fasting during Ramadan was not a significant risk factor for mortality from heat-related causes during the Karachi heat wave of June 2015. A large number of excess deaths were reported across all demographic groups, which due to the burden of record keeping in an under-resourced health system during a public health emergency, are almost certainly an underestimate.
GhummanU, HorneyJ. Characterizing the Impact of Extreme Heat on Mortality, Karachi, Pakistan, June 2015. Prehosp Disaster Med. 2016;31(3):263–266.
Community Assessment for Public Health Emergency Response (CASPER) is a group of tools and methods designed by the US Centers for Disease Control and Prevention (CDC) to provide rapid, reliable, and accurate population-based public health information. Since 2003, North Carolina public health professionals have used CASPERs to facilitate public health emergency responses and gather information on other topics including routine community health assessments.
To date, there has been no evaluation of CASPER use by public health agencies at the state or local level in the US.
Local health departments of North Carolina reported when and how CASPERs were used during the period 2003 to 2010 via an online survey. Data on barriers and future plans for using CASPERs also were collected.
Fifty-two of North Carolina's 85 local health departments (61%) completed the survey. Twenty-eight departments reported 46 instances of CASPER use during 2003 to 2010. The majority of CASPERs were performed for community health assessments (n = 20, 43%) or exercises (n = 11, 24%). Fifty-six percent of respondents indicated they were “likely” or “very likely” to use CASPERs in the future; those who had prior experience with CASPERs were significantly more likely (P = .02) to report planned future use of CASPERs compared to those without prior experience with the tool. Lack of training, equipment, and time were the most frequently reported barriers to using CASPERs.
Local public health agencies with clear objectives and goals can effectively use CASPERs in both routine public health practice and disaster settings.
HorneyJ, DavisMK, DavisSEH, FleischauerA. An Evaluation of Community Assessment for Public Health Emergency Response (CASPER) in North Carolina, 2003-2010. Prehosp Disaster Med. 2013;28(2):1–5.
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