Urban Evacuation to Rural Areas - Planning for Population Surge Michael Meit, M.A., M.P.H NORC at the University of Chicago

2 Project Overview – Partners NORC is a subcontractor for the Western New York Public Health Alliance (WNYPHA), which is funded by an Advance Practice Centers grant from NACCHO and CDC NORC has partnered with the Penn State University Center for Environmental Informatics to develop a map-based online modeling tool

3 Co-Authors From NORC: Thomas Briggs, Alene Kennedy, and Hiroaki Minato, M.A. Ph.D. Cand. From PSU: Stephen Crawford and Douglas Miller, Ph.D.

4 Walsh Center for Rural Health Analysis Evacuation Project Funded by HRSA, Office of Rural Health Policy –Key informant interviews –National survey of urban residents to assess evacuation intentions –Findings to inform development of the modeling and spatial analysis tool

5 Background To date, rural preparedness risk assessments have tended to focus on issues within the rural community and have not examined the implications of population surge resulting from evacuating residents from neighboring urban areas. In many areas, rural public health infrastructure is likely to be stretched thin or possibly overwhelmed in such a scenario.To date, rural preparedness risk assessments have tended to focus on issues within the rural community and have not examined the implications of population surge resulting from evacuating residents from neighboring urban areas. In many areas, rural public health infrastructure is likely to be stretched thin or possibly overwhelmed in such a scenario. At the same time, evacuation planning research has focused primarily on the successful exodus of urban citizens following a disaster situation, with little focus on likely destinations or secondary impacts.At the same time, evacuation planning research has focused primarily on the successful exodus of urban citizens following a disaster situation, with little focus on likely destinations or secondary impacts.

6 Purpose The objective of this project is to develop a map- based tool to predict rural population surge following potential urban disasters. We envision the final product being used as a planning tool for rural preparedness planners, and as an educational tool to inform policy makers about the issue of urban to rural evacuation.The objective of this project is to develop a map- based tool to predict rural population surge following potential urban disasters. We envision the final product being used as a planning tool for rural preparedness planners, and as an educational tool to inform policy makers about the issue of urban to rural evacuation. The tool includes information on the number of likely evacuees, evacuee demographic information (such as presence of children, disability status, etc.), and local planning information.The tool includes information on the number of likely evacuees, evacuee demographic information (such as presence of children, disability status, etc.), and local planning information.

7 Methods –Identified variables predictive of urban to rural evacuation based upon historical evidence and key informant interviews with preparedness experts at in rural and urban communities and national authorities –Developed modeling algorithms using identified variables based upon availability of nationwide data sets containing county-level information –Worked with Penn State University’s Center for Environmental Informatics to develop a web-based interface that provides access to evacuation information in a user-friendly manner.

8 How the tool works – 3 types of variables Scenario Specific Variables: Based on the nature of the precipitating event – how much “push” does it have, and how many urban citizens are likely to evacuate as a result?Based on the nature of the precipitating event – how much “push” does it have, and how many urban citizens are likely to evacuate as a result? Current scenarios: dirty bomb, pandemic flu, industrial/chemicalCurrent scenarios: dirty bomb, pandemic flu, industrial/chemical Population Demographics: Based on the demographics of the urban area, who is more or less likely to evacuate? For example, people with children are more likely to evacuate; people with disabilities are less likely to evacuate, etc.Based on the demographics of the urban area, who is more or less likely to evacuate? For example, people with children are more likely to evacuate; people with disabilities are less likely to evacuate, etc. Pull Variables: Based on known information about counties surrounding the urban area, which will be more or less attractive to evacuees? Features that make a county more attractive include things such as road networks into the county, number of hotel rooms and second homes, family networks, etc.Based on known information about counties surrounding the urban area, which will be more or less attractive to evacuees? Features that make a county more attractive include things such as road networks into the county, number of hotel rooms and second homes, family networks, etc.

9 Population Demographics and Pull Variables Setting variables: Historical studies (e.g. TMI, hurricanes)Historical studies (e.g. TMI, hurricanes) Survey researchSurvey research Expert opinionExpert opinion Data sources: U.S. Census BureauU.S. Census Bureau U.S. Bureau of Labor StatisticsU.S. Bureau of Labor Statistics Smith Travel ResearchSmith Travel Research

10 By clicking on the circle, the user can select the city and region of interest. In this iteration of the tool, we see Buffalo.

11 The model zooms into the selected city and surrounding counties.

12 By checking the boxes, the user can see more detailed information about the region of interest, such as hospital locations and data.

13 The user can select the scenario of interest from a drop-down menu. The user also may select to view one wave of an evacuation or more.

14 By left-clicking on the county, the user can access detailed information about the destination county’s resources and the arriving evacuees.

15 Next steps National Expansion The tool will be expanded nationally, to include at least the 100 largest urban centers in the U.S. and surrounding counties within at least a 150-mile radius.The tool will be expanded nationally, to include at least the 100 largest urban centers in the U.S. and surrounding counties within at least a 150-mile radius. Refining Algorithms and Variables We will continue to refine algorithms and identify variables for enhanced precision of estimates.We will continue to refine algorithms and identify variables for enhanced precision of estimates. User Testing We will conduct web-based user testing to refine the user interface and produce optimal outputs to stimulate rural preparedness planning.We will conduct web-based user testing to refine the user interface and produce optimal outputs to stimulate rural preparedness planning.

For more information: Michael Meit, MA, MPH Senior Research Scientist NORC at the University of Chicago 7500 Old Georgetown Road, Ste 620 Bethesda, MD PH: