Author Profile

Jennifer Horney

Institution: Texas A&M School of Public Health

Department: Epidemiology and Biostatistics

City: College Station

State: TX

Jennifer Horney is an associate professor of Epidemiology and Biostatistics at the Texas A&M University Health Science Center School of Public Health and a faculty fellow of the Hazard Reduction and Recovery Center at the Texas A&M College of Architecture. At Texas A&M, Dr. Horney’s research focuses on measuring the health impacts of disasters, as well as the linkages between disaster planning and household actions related to preparedness, response, and recovery. Dr. Horney received her PhD and MPH from the University of North Carolina at Chapel Hill, where her research focused on the role of social factors in decision making during disasters. She serves as a member of the Center for Disease Control and Prevention’s Disaster Epidemiology Community of Practice and was a member of a team of public health practitioners who responded to Hurricanes Isabel, Charley, Katrina, Wilma, and Irene, where she conducted rapid assessments of disaster impact on the public health of individuals and communities. She has also provided technical assistance to public health agencies globally around disasters, infectious disease outbreaks and pandemic influenza planning and response.

Recent Posts

Validating Indicators of Disaster Recovery with Qualitative Research

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Introduction: Recovery from disasters is a critical function of federal, state, and local governments, yet measurable, validated indicators of community recovery remain unidentified. A list of potential recovery indicators was developed by the authors through a literature review, recovery plan review, and case study of two disaster impacted communities.

Methods: To validate the indicators, qualitative data was collected from experts on disaster recovery. Twenty-one key informant interviews and two focus groups were conducted between January and April of 2014 to solicit feedback from disaster recovery practitioners and academics.

Results: Five major themes emerged from the qualitative data. These included: the flexibility of the indicators to serve multiple purposes for communities and individuals both pre- and post- disaster; the focus areas are comprehensive, but content and organization can be improved; the importance of seeing the indicators as a self-assessment, rather than a tool for comparing communities; the potential challenges of collecting data for some indicators; and the identification of potential measurement issues with the indicators.

Discussion: The proposed recovery indicators can be utilized by both practitioners and researchers to effectively track post-disaster recovery. They capture many of the complexities of community disaster recovery and provide potential opportunities for linkages to the development of disaster recovery plans and other activities that could increase community resilience in the future.

Social Factors as Modifiers of Hurricane Irene Evacuation Behavior in Beaufort County, NC

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Encouraging residents in high-risk areas to evacuate before a hurricane makes landfall is one of the few ways to reduce hurricane-related morbidity and mortality. However, demographic factors associated with evacuation in at-risk groups have not been consistent across studies. To determine if social factors (social control, social cohesion, and social capital) modified the relationship between demographic groups and failure to evacuate from Hurricane Irene, the authors conducted a cross-sectional stratified two-stage cluster sample among residents of Beaufort County, NC. Of 226 attempted rapid response interviews, 205 were completed (response rate = 90.7%). Data were analyzed using generalized linear modeling, which produced crude risk differences to estimate the association between failure to evacuate from Hurricane Irene and a number of demographic and social factors; effect measure modification (EMM) was assessed on the additive scale through stratified analyses of key social factors. There were no significant associations between demographic or social factors and evacuation in the bivariate analysis. However, EMM was present for households with high social capital or social cohesion among special needs residents, those over age 65, males, and non-whites. In Beaufort County, NC, future hazard mitigation plans should include evacuation messages tailored for households with high social capital or social cohesion.