IntroductionLimited transportation options contribute to poor societal outcomes even absent any hazard (Syed et al. 2013). Transportation is critical for accessing medical care and other life-sustaining resources, and vulnerable populations may depend on public transit resources to evacuate. Transportation issues are addressed using an all-hazards approach that coordinates with federal, state, and local authorities to ensure provision of services for evacuation (FEMA 2018). Resources need to be deployed to areas vulnerable to an emergency in advance of a hazard impact. Moreover, residents of the at-risk area must prepare for the logistics of evacuation in advance, especially if they have family members with disabilities or other specific needs. For example, vulnerable populations relying on public transportation need to know ahead of time the location of the nearest pick-up point (Bian and Wilmot 2018). Additional planning items include identifying the best time to leave, determining if multiple vehicles are needed, compiling trusted or reliable sources of information regarding evacuation, and estimating how much evacuation will cost (Lindell et al. 2019; Watts et al. 2019).The transportation sector has a significant community outreach role during emergencies. After Hurricane Katrina, evacuation approaches where individuals or households were reliant on their own vehicles were overhauled and use of public transportation emphasized to accommodate populations without cars (Deka and Carnegie 2010). Contributors to household evacuation and resource-sharing decision making include source of information, risk perception, social connections, location, employment requirements, past experience, nature of evacuation order, pets, and other indicators of vulnerability (Hasan et al. 2011; Bowser and Cutter 2015; Huang et al. 2016; Sadri et al. 2017; Collins et al. 2018; Ahmed et al. 2020; Lindell et al. 2020). However, unprecedented factors, such as fears during a concurrent pandemic, make actual evacuation logistics difficult to model. Various hazard assessment and emergency response manuals (e.g., FEMA 2018) include information regarding safety but need to be adapted to consider issues related to long-term and compound hazards, especially where underlying medical conditions increase risk (Clark et al. 2020).A pandemic, such as the COVID-19 pandemic, alters supply chains, changes the density of vehicles on roadways, and limits the number of seats available on public transit (Pei et al. 2020; Cowling and Aiello 2020; Fong et al. 2020; Parr et al. 2020). It also increases the burden on public-facing transportation workers to provide safe options (Capano et al. 2020; Chu et al. 2020; Cai et al. 2020). The performance of the transportation sector during an emergency has significant public health and economic implications, especially during a compound hazard such as a hurricane-pandemic. Local operations during a pandemic and hydrometeorological hazard may strain resources including budgets for transportation and emergency management departments alike (Andrews 2020). For hydrometeorological hazards, such as hurricanes and floods, planned evacuation routes may need to be used and traffic flow changed. A study of shared resources from Hurricane Irma showed ample resource capacity for ride-sharing that could be leveraged to supplement strained public transportation options under the right controls for pricing, communication, and allocation systems (Wong et al. 2020). Coastal communities must quickly adapt evacuation logistics to the pandemic. The role of technology in tracking resource capacity in conjunction with and in addition to existing data and modeling software remains unclear.This study uses a two-pronged participatory process to propose practical adaptations and set an agenda for continued assessment of the demand for and capacity to provide evacuation transportation services during a compound hazard (hurricane-pandemic) event. Three research questions are addressed: 1.How has COVID-19 impacted availability of and demand for evacuation transportation assets?2.What protocols and additional resources may be necessary to maintain and enforce infection control measures for disease surveillance, safety, and security?3.What data and analytical approaches (models, simulations, or decision trees) are needed to support planning for evacuation transportation under COVID-19?First, data from a series of six national workshops held in May and June 2020 highlight key issues associated with planning transportation logistics for hurricane evacuation during the COVID-19 pandemic. Second, data from two focus groups held in September 2020 featuring participatory mapping exercises based on a case-study of Hampton Roads, Virginia, identify multijurisdictional transportation and evacuation planning changes at local and national levels to determine an adaptation timeline for the transportation sector and analytical gaps that still need to be filled.BackgroundEmergency managers and planners anticipate actions while using evacuation planning as a tool to proactively determine critical aspects of evacuating residents at different time thresholds, priorities, and sequences. Common understanding of hurricane evacuation behavior includes who leaves versus who stays and factors considered in the decision-making calculus (Baker 1991; Huang et al. 2016, 2017; Lindell et al. 2020). It is established that the coordination to support evacuation is complex and requires substantial intergovernmental interactions within diverse governmental levels and bodies and with regional industry to support evacuation endeavors (Kapucu et al. 2010). Planning involves decisions related to the timing and type of evacuation orders (voluntary and mandatory), and travel routing and transportation options. From a humanitarian supply-chain perspective, the supply side involves the regional capacity to evacuate and shelter residents. The demand side considers the potential behavior of the displaced population, such as their propensity to evacuate or shelter in place and the factors that influence these decisions (Lindell et al. 2020).Transportation timing and messaging of the evacuation are fundamental decisions that shape the results of evacuation orders. Transportation decisions during an evacuation involve the routing from affected areas to shelters and areas away from danger as well as the duration of the evacuation. Estimates of the number of evacuees are used to determine vehicle allocation, concentration points, and messaging to mobilize endangered populations. The latter includes determining how far in advance evacuation notices should be made, which, thanks to technology, can allow longer lead times for residents to engage in positive evacuation behavior (Sorensen et al. 2020; Yi et al. 2017). It also includes the content, aim, and intersectionality of the message (Borowski and Stathopoulos 2020; Sorensen et al. 2020). A number of techniques have been examined to analyze the problem of evacuation transportation planning during simultaneous hazards (Doan and Shaw 2019; Yang et al. 2019). Techniques to determine optimal evacuation routes when limited information is known about both the evacuation demand and road capacities have also been proposed (Ng and Waller 2010; Ng and Lin 2015). Further, Dulebenets et al. (2019, 2020) proposed mathematical programming models that assign individuals and vulnerable population groups to emergency shelters through evacuation routes.Household evacuation decisions are complex (Dash and Gladwin 2007) because they incorporate many direct factors, such as evacuation impediments, and indirect factors, such as personal household characteristics (Huang et al. 2017; Smith and McCarty 2009). Smith and McCarty (2009) found that the strength of the hurricane and the vulnerability of the housing unit has the most significant impact on evacuation. They also found that some demographic variables have substantial effects on the likelihood of evacuating and the selection of lodging with family/friends or in public shelters, hotels, or motels. For example, medically fragile and carless populations require additional public accommodation considerations (Karaye et al. 2019; Renne 2018; Wong et al. 2020). An increased number of residents may be at heightened risk if they choose not to follow evacuation orders during a pandemic because of contradictions in protective measures to prevent virus transmission versus evacuate from a hurricane (Shultz et al. 2020).MethodsThis study used multiple approaches and data sources to address the three research questions. First, foundational knowledge was developed about expected transportation challenges during the 2020 hurricane season. A series of six workshops were convened to identify common issues and challenges faced by professionals in local, state, and federal agencies across the US, including their counterparts in profit and nonprofit organizations. From this broad national landscape, Hampton Roads was used as a case study to develop understanding of how hurricane evacuation and logistics have and should continue to change as the COVID-19 pandemic progresses.Second, two additional focus groups were convened to engage emergency management, public health, and transportation officials as well as other key stakeholders in a participatory research process using geospatial technology to address the altered demands and resource requirements for evacuation under a compound hazard. Triangulation was conducted across qualitative and geospatial data sets to develop a practical timeline and agenda to promote logistical resilience using the example of a hurricane-pandemic threat.Hurricane-Pandemic National WorkshopsTransportation challenges were assessed from the workshops organized by the CONVERGE COVID-19 Working Group on Planning for Evacuation and Sheltering of Vulnerable and Medically Fragile Populations during a Compound Hurricane-Pandemic Threat. The purpose of the workshops was to engage experts in identifying gaps in knowledge, planning and resource needs, and concerns related to hurricane evacuation and sheltering during the COVID-19 pandemic, particularly with respect to vulnerable populations. In May and June 2020, a team of researchers from Old Dominion University (ODU) and the University of South Florida convened six online workshops from a convenience snowball sample of professionals from federal, state, and local agencies; nonprofit and volunteer organizations; and businesses, representing areas of expertise in emergency management, public health, human services, transportation, and many others. Participants were recruited through a variety of means, including personal contacts of the researchers, referral by these personal contacts, and through state and national networks of emergency managers. Workshop participants also included researchers from multiple academic disciplines and institutions. In total, 265 professionals and researchers participated from 20 states, mostly from the Atlantic and Gulf Coasts. The workshops received a not human research designation by ODU’s Internal Review Board (Project No. 1606408-1).Participation in individual workshops was voluntary and ranged between 74 and 198 participants. Workshops were structured into concurrent breakout groups that each had between 12 and 18 participants. Each breakout group session was led by a moderator through the same semistructured questionnaire, recorded, and transcribed. Transcripts were analyzed qualitatively. Identifying information was removed prior to analysis. Responses were manually coded based on themes and relationships between them, which were identified in the After Action Reports. Descriptive quotes were included to further explore participants’ concerns.Hampton Roads Case-Study AreaCoastal Virginia has experienced severe weather events, such as tropical storms and hurricanes, necessitating evacuation inland (Liu et al. 2016). Studies of evacuation behavior within Hampton Roads in response to Hurricanes Irene in 2011 indicate that economically depressed and medically fragile populations have lower propensity to evacuate (Ng et al. 2014, 2015). Variation in risk perceptions, access to transportation, and resources to support basic needs once outside the region have been cited as explanations for staying instead of evacuating (Ng et al. 2016). For these medically fragile populations, the propensity to either evacuate or shelter in a congregate venue may be less under a pandemic-type public health crisis (Behr and Diaz 2013, 2014). With this premise in mind and as the 2020 hurricane season progressed in the midst of a pandemic, emergency planners had to revisit planning assumptions and adjust plans to account for the compound threat of a hurricane-pandemic. This advanced planning provided an opportunity to alter transportation practices to effectively reduce risk and thus encourage evacuation by hesitant populations.The Hampton Roads region of coastal Virginia, in particular, is home to the leading port on the east coast, based on tonnage, and with the deepest channel. In 2020, the region was home to more than 1.7 million people living in approximately1,360 sq km (525 sq mi) (GHR Connects 2020a). More than one in three households qualified as asset-limited, income constrained employed households (income above the Federal Poverty Level but below the basic cost-of-living threshold), indicating the presence of socially and economically vulnerable populations in the region (GHR Connects 2020b).Evacuation orders must balance the safety of residents with broader social and economic concerns such as access to workplaces and the workforce. Evacuation plans are a high priority throughout the region (HRPDC 2017). In addition to tropical cyclones and nor’easters, heavy rains and tides contribute to flooding in Hampton Roads (Allen and Allen 2019). Further, historic land-use decisions have removed some of the natural vegetation that reduce flooding, and complex geology is causing land subsidence. The rate of sea level rise has also been twice the global average rate for the last 80  years (Eggleston and Pope 2013). The role of these factors in flood frequency is of concern to emergency planners because access to flood-free roadways is critical to evacuation (Kirchmeier-Young and Zhang 2020). The lessons learned in Hampton Roads and best practices identified are applicable to other coastal communities that are similarly at risk.In 2017, cities within the region set goals to reduce roadway flooding. Transportation to evacuate to areas outside of a locality or around flooded streets or hazardous materials was expected to increase transportation costs and durations. Nonetheless, Hampton Roads planners worked with North Carolina officials regarding evacuation routes from the North Carolina Outer Banks that traverse the region. Neighborhoods with reduced access to social or broadcast media are of particular concern for communicating evacuation orders and transportation route changes (HRPDC 2017). Existing spatial data can be used to identify communication-limited populations, traffic flows across state lines, and other influential factors for evacuation planning, but data presented in unified, user-friendly formats require continued cooperation among local, state, and federal officials.The hurricane evacuation zones in Virginia were originally designated in 2017 through a joint effort between Atkins (a private company), the Virginia Department of Emergency Management (VDEM), and the US Army Corps of Engineers. Zones were established by combining information from the National Oceanic and Atmospheric Administration’s Sea, Lake, and Overland Surges from Hurricane (SLOSH) models of potential storm surge with information on land use, socioeconomic data, and other factors (VDEM 2020). Information supporting evacuation and sheltering is maintained and current, including: population estimates, shelter capacities, transportation projects, traffic flow changes, and wind and storm surge models. Dynamic transportation simulations addressing the impact of traffic incidents (including accidents) in Hampton Roads upon the evacuation procedures in the Virginia Hurricane Emergency Response Plan are available (Robinson et al. 2009). Although some of the data are static, other data can be used dynamically in online platforms, such as HURREVAC.Further, in compliance with Title VI of the Civil Rights Act of 1964, the Hampton Roads 2045 Long-Range Transportation Plan accounts for the access and mobility needs of vulnerable populations, such as carless, female-headed, low-income, disabled, and minority households, when assessing potential projects and assigns each a score and outreach strategy based on the populations present (HRTPO 2020a). Regional population and employment projections for the next 20  years have also been integrated with statewide travel demand models to forecast the impacts of local transportation projects (HRTPO 2020b). These efforts reduce congestion and increase safety and connectivity for transit needs. Short-term assessments to account for potential impacts of the COVID-19 pandemic require additional staff and tools.COVID-19 Transportation Webapp Development to Support Participatory ResearchA participatory research approach was used for the Transportation, Vulnerability, and COVID-19 Focus Groups conducted following the national workshops to identify changes, policies, and resources needed to adapt the transportation system to address changing demand for evacuation and sheltering options during the COVID-19 pandemic. The COVID-19 Transportation Webapp was developed as a participatory mapping aid to these focus groups. The objective of this application was to allow users to draw shapes and use bookmarks to identify areas of concern along roadways and transit changes needed to accommodate shifting resources and behaviors. During the virtual focus groups, participants were introduced to the platform and given a brief demonstration on the user interface. Participants were then asked to contribute feedback by using the tool to place points, lines, and polygons on the map to designate important locations on the topics being discussed. The application used Esri’s Web AppBuilder application programming interface (API) as its platform. Twenty-nine data layers were used to highlight topics related to vulnerability, behavior, and infrastructure at the national, state, regional, and local scales through the Layer List menu. Table S1 shows the data dictionary of layers.Twenty-one of the 29 layers were pulled in through the Esri ArcGIS Online interface via web feature services from authoritative data sources. One data layer was developed from private proprietary data provided through VDEM showing distributions of vulnerability according to factors specific to the Commonwealth.Two feature layers were developed from the Life in Hampton Roads (LIHR) survey data collected by the ODU Social Science Research Center to show intended behavior in the case of a storm with similar characteristics and path to Hurricane Florence (2018) occurring during the 2020 hurricane season. The LIHR online survey conducted in summer 2020 included 1,105 participants. The recruitment pool included two panels of residents from seven cities in Hampton Roads generated using Qualtrics and LIHR participants from previous years (2014–2019). The data were weighted to account for discrepancies between the demographic characteristics of the respondents and the census data of each city. SPSS version 27 was used to analyze two questions that became two separate data layers: 1.If a major hurricane was forecast to hit Hampton Roads during this hurricane season with the current public health crisis, would you consider evacuating?2.If a hurricane was forecast to hit Hampton Roads during this hurricane season with the current public health crisis, would you consider sheltering in a public shelter?Two feature layers were developed from the Hurricane Florence survey data collected by the ODU Social Science Research Center to show past behavior from the last evacuation order issued in 2018. The Hurricane Florence phone survey conducted in 2018 included 1,210 participants from a random stratified sampling of telephone numbers from seven cities within Hampton Roads with oversampling of residents in evacuation Zone A, where evacuation was mandatory. Two survey questions were analyzed via SPSS to create two data layers: 1.For Hurricane Florence in September, did your household stay somewhere in Hampton Roads or leave completely out of Hampton Roads, even for a short while?2.At any time during Hurricane Florence, did you shelter somewhere other than your primary home?The coded data for both surveys were added to the attribution of newly created spatial data using Esri’s ArcGIS Pro version 2.7 software to produce four feature layers that could then be used in ArcGIS Online to develop choropleth maps for the online web maps. These choropleth maps were used to show focus group participants preliminary results regarding actual (Hurricane Florence) and intended evacuation behavior for the local context. Reported rates of past and intended evacuation and sheltering shown via these layers were lower than average when compared with national empirical analysis of actual and intended behavior, such as those of Lindell et al. (2019) and Huang et al. (2016). However, the layers were consistent with data specific to the Hampton Roads region of Virginia, where accounting for intraregional and interregional evacuees as two separate types is particularly influential (Ng et al. 2016).The three remaining data layers were added following the two focus groups. These data layers were developed by focus group participants who identified roadway and transit changes needed or resources available to help accommodate shifting vulnerabilities as well as evacuation and sheltering behaviors. Focus group participants were provided basic tool functionality such as being able to zoom in and out on the map, searching for a particular location, accessing the legend that shows data symbology, and the ability to turn on and off the various data layers using the layer list provided. Additional functionality included a bookmark tool that provided users the ability to create and save different map views and extents, a measure tool that calculated linear distances and areas as well as location coordinates (i.e., latitude and longitude), and an edit tool allowing users to make contributions to the map by creating new features (points, lines, and polygons).Transportation, Vulnerability, and COVID-19 Focus GroupsIn September 2020, researchers at ODU convened two online Transportation, Vulnerability, and COVID-19 focus groups. One group focused on the transportation, vulnerability, and COVID-19 issues at the national level and another focused on the local Hampton Roads context. The focus groups utilized a targeted snowball sample of emergency management, transportation, and public health professionals from the coastal US. Participants were recruited from registration lists for the workshops convened by the CONVERGE COVID-19 Working Group on Planning for Evacuation and Sheltering of Vulnerable and Medically Fragile Populations during a Compound Hurricane-Pandemic Threat, which included a total of 332 people. Invitations were sent via email with a request to forward to additional relevant contacts. The research was designated exempt by ODU’s Arts and Letters Human Subjects Committee (Project No. 1636840-1). Thirty-seven participants registered for the national focus group and 43 participants registered for the local focus group. Of these registrants, 23 and 27 participated in the focus groups, respectively. Participation was voluntary, and all registrants received focus group materials via email.Focus group participants viewed a presentation of the data from Hampton Roads and a demonstration of the COVID-19 Transportation Webapp before discussing a predetermined set of questions about the utility of the shared data, including maps, and shifting resource and policy needs. Participants in the local focus group were randomly assigned to breakout groups of about equal size, whereas participants in the national focus group remained in one room for discussion.Discussions were recorded and qualitatively analyzed. Responses were manually coded based on evacuation procedures from the literature as well as resource needs and operating options that emerged from the responses to generate themes and identify relationships between them. Descriptive quotes were identified and extracted to further explore participants’ concerns.Results and DiscussionConcerns and proposed solutions perceived to be relevant to hurricane evacuation operations during the COVID-19 pandemic were generated from workshop and focus group participants. Findings are first presented chronologically from when lockdowns ended and national workshops were convened to the peak of hurricane season when the two focus groups were conducted. This temporal analysis is used to explore the first two research questions about (1) the impact of COVID-19 upon availability of and demand for transportation assets, and (2) additional protocol and resource needs for disease surveillance, safety, and security. Then, in light of the changes suggested by answering the first two questions, the third question is addressed by analyzing focus group responses regarding the utility of data and analytical approaches as planning and realignment support tools for future hurricane seasons. Connections to the literature and implications for transportation workers and evacuees are noted throughout.Vulnerability and Transportation as Lockdowns Ended: Local–National PerspectivesThe CONVERGE Workshops revealed that for communities across the Gulf and Atlantic coasts, COVID-19 poses challenges to typical planning and operation for evacuation. One participant stated We have our plans that are in place already, but right now, we’re working on expanding those […] we’re looking at a lot of different options, trying to look at a lot of unconventional things that maybe we haven’t done before in the past, and then how that can apply with current federal law and current policies that are in place, and then what policies we can change, which ones we can’t change, to better serve the populations.Participants sought ways to be more strategic, to triage, and to work within resource limitations.Participants noted that government budget constraints and furloughs, layoffs, and hiring freezes reduced the availability of transportation staff. However, evacuation during a pandemic requires expanded public transit services to maintain physical distancing and allow for additional space to quarantine or isolate (National Academies of Sciences 2021). Additional staff with specialized skill sets for screening and management of symptomatic populations, additional equipment, and training for new cleaning protocols were identified as necessary. To expand the traditional workforce, participants suggested use of transportation resources and staff from other regions and states to assist in evacuation procedures, in addition to volunteers such as from the Civil Air Patrol. However, these volunteers and nontraditional workers, like staff, may be burnt-out, and mental health resources need to be provided. One participant stated In terms of emergency management, […] all the same cast of characters are pretty much maxed out right now working 60, 70, 80-hour weeks managing and responding to the pandemic, and then as hurricane season now holds out, how do you divide and conquer and make sure you’re still taking care of business on all fronts?Not only additional buses, staff, and partnerships, but also health and safety protocols were of interest to maintain critical services and accommodate populations at increased risk for contracting and experiencing a severe case of COVID-19, including staff. Participants determined that individuals with underlying health conditions required additional precautions due to COVID-19. Populations of usual additional concern for evacuation, such as families with pets, those with disabilities, caretakers, and those in nursing homes or similar group housing facilities, remained of additional concern due to the changing protocols to prevent COVID-19 transmission. Participants also questioned how the financial impact of lockdowns might change the number of people requiring public transportation to evacuate. These demographic factors traditionally show only indirect effects on evacuation behavior (Lindell et al. 2020; Huang et al. 2016) but may be amplified by the additional supplies required for operations during a pandemic.Revised guidance for what supplies are needed and who should evacuate based on COVID-19 risk was sought to reduce transmission and fear. Shadow evacuations, in particular, are not desirable. One participant shared a new strategy being considered, “outside storm surge zones, we are promoting ‘Know your home’—if built to code and in a safe space, maybe stay home.” Evacuating to a nearby family or friend’s residence outside of the official evacuation zone was preferred by officials to long-distance evacuations outside the region. Seeking shelter in a friend or family member’s home is the most common form of evacuation for hurricanes, but usually these homes are far from the area under evacuation orders (Lindell et al. 2019). Following guidance to stay with friends or family nearby might produce minimal changes in traditional evacuation behavior because evacuees typically do try to stay with the nearest peers that are outside the risk area. In any event, such guidance would challenge households without strong networks in safe areas near their residences.The potential for registration and self-reporting of symptoms prior to using transit for evacuation was proposed to ensure supply can safely meet demand. Alternative transportation strategies were thought to be needed for positive or symptomatic individuals and potentially their families. The ability of emergency management and transportation staff to communicate health and safety protocols to the public is critical in individual and household decision making and compliance but requires training and protection, the availability of which participants questioned.Participants expressed an urgent need for personal protective equipment (PPE) and sanitization supplies for “when it comes to hand sanitizer […] we’ve also broken those thresholds […] we are looking at everything from masks and hand sanitizers, soap, everything […] a challenge is we don’t know what is going to be available.” PPE would be required on buses, but there was concern regarding how operators might enforce this requirement safely. Physical barriers on buses and air filtration systems were also being considered to limit virus spread. Participants were also concerned that timelines for evacuation could be extended beyond the traditional window because buses would be expected to sanitize between rotations, make multiple trips to transport evacuees with physical distancing, and potentially make drop-offs at alternative shelter locations.Participants stated that existing contracts for emergency transportation and supplies should be reassessed to ensure that they are operational and logistically sound under the new guidelines and account for private companies going out of business due to financial strain. New and expanded partnerships were also suggested to meet demand and account for expected failure of staff to report for shifts. Uber, Lyft, and other ride-share services were under consideration to speed evacuation and provide noncongregate options. Ride sharing has been a method of evacuation in past hurricanes. Wong et al. (2020) identified that capacity exceeded demand for shared resources including ride shares and rooms during Hurricane Irma, but the capacity to integrate this with public evacuation efforts requires additional exploration. Thinking of the future, participants also suggested infrastructural changes including alternative public transit pick-up points, retrofitting buses, and identification of shelters of last resort.Vulnerability and Transportation Postlockdown/Prevaccine: Local–National PerspectivesPolicies and procedures to adapt evacuation needs to COVID-19 gained traction by the peak of the 2020 hurricane season through consistent messaging and outsourcing. Focus group participants recommended local evacuations. One participant provided the following example: “if an evacuee from Hampton Roads lives in Zone A, they should evacuate tens of miles to Zone B, C, or D rather than hundreds of miles to another city or state.” Although evacuees have logical reasons for going to the destinations they choose (Lindell et al. 2019), emphasizing local evacuation in emergency messaging could geographically limit virus outbreaks (Pei et al. 2020).Focus group participants were still concerned about timing and registration for evacuation. Receiving information about the number of individuals evacuating with a group, their COVID-19 status, and desired destination in advance of pick-up was desirable to help deploy transport. Participants noted that most states have a shelter registration system, at least for medically fragile individuals and those with pets, which could be expanded. Who would enter that information and where it would be collected remained unclear. As stated by one participant, “We need folks that don’t necessarily have clinical backgrounds but have logistics backgrounds.”Registration and other COVID-19 measures were expected to take additional time. One participant provided an example from Hampton Roads: “evacuation 48 hours prior to an event is customary, but 72 hours or more will be necessary under the current pandemic.” Experiences with timing of evacuation orders during the 2020 hurricane season varied. A participant shared that in advance of Hurricane Isaias, some local governments waited until the last minute to call for evacuations in hopes that the hurricane would not strike their jurisdiction because there was a limited ability to mobilize state resources. Inconsistent timing of orders across jurisdictions is not uncommon, although localities are historically likely to issue an order less than a day after a National Hurricane Center issues a Hurricane Watch or Hurricane Warning (Sorensen et al. 2020).Participants were also concerned that individuals may wait longer than usual to make their decision because of the pandemic, thereby inundating roadways with vehicles. Delays in complying with evacuation orders at the household level are not unique to operations during a hurricane-pandemic. Lindell et al. (2020) showed that evacuation facilitators are a primary contributor to household evacuation preparation time along with perceived storm impacts. The capacity to assess how COVID-19 specifically affected government or household decision-making timelines is beyond the scope of this study; however, the capacity to communicate how officials planned to prevent virus transmission may have influenced behavior because it adds another hazard to the decision-making equation. Study participants expressed confidence in existing infrastructure to communicate evacuation recommendations and accommodations, but consistent messaging and protocol between jurisdictions was desired for those who might still evacuate across local or state boundaries.Some participants established new or expanded transportation options in their respective areas. One participant shared that current state plans included two noncongregate options: (1) sending voucher codes for individuals and households to book their own Lyft, Uber, or other contracted ride-sharing provider, or (2) booking the ride for the individual or household in the ride-share portal. Rides could either go to a friend or relative’s home or a public shelter. Participants in multiple states had explored government contracts with hotels as noncongregate evacuation destinations. However, one participant noted that a statewide survey of hotels found a low percentage willing to provide public shelter despite protection under the Good Samaritan law. Noncongregate accommodation options were further limited by flood zones, and low density in rural areas required the inclusion of distant bed and breakfasts, Airbnbs, and campgrounds. These noncongregate public shelter options may extend evacuation transportation timelines.Although a shift to noncongregate transportation would reduce the need and exposure for bus operators by redistributing it to ride-share drivers, concerns with transportation worker fatigue remained because physical distancing requirements would still increase the number of trips required for public transportation. Further, shifting to noncongregate ride-share and shelter options increases the number of personal vehicle drivers and accommodation providers potentially exposed to COVID-19, which is a public health concern that requires additional consideration beyond reducing the burden on city and county staff.Participants expressed that individuals with COVID-19 symptoms, disabilities, and pets still require public transportation options for evacuation because ride-shares may not be accessible to or refuse them. Once the demand is established, composition of vehicles must be assessed, and routes modified to ensure efficiency and determine congregate pick-up locations. A participant shared the results of trying to include public school buses for congregate transportation while schools are virtual; however, schools hesitated to allow access due to virus transmission concerns.It was widely accepted that masks are needed to protect staff and volunteers. A participant stated that police could be available to enforce mask wearing in shelters. However, some participants expressed concerns that the potential interactions with law enforcement may deter migrant workers and minorities from utilizing public emergency services. Staff training resources regarding protocol enforcement remained unclear beyond document circulation. Responsibility for enforcement on buses was still ambiguous.Several supply chain and enforcement issues had been resolved by the peak of the hurricane season. Participants reported that PPE stockpiles were available or being collected in spite of ongoing strain—sharing arrangements were of interest. Negotiations were also underway with hotels regarding meal provisions. Some areas made the evacuee responsible for bringing meals and PPE to the evacuation destination, congregate or noncongregate. However, the capacity of low-income individuals and families to afford or source supplies concerned some participants.Participants noted that difficult decisions to activate resources based on the information available were expected and that lessons should be learned from those who have already implemented evacuations during the pandemic. One participant suggested a Disaster Czar to make final decisions in a timely manner “when life safety exceeds exposure risk.” In part, this was thought to be necessary because COVID-19 precautions, such as lockdowns, have become political, administrations change, resources are limited, and there is disagreement amongst jurisdictions regarding requirements. Another participant reflected that emergency management was already engaging in preparations for COVID-19 vaccine distribution, and clear decision-making channels for protocols and resource distribution would be especially important when one is available.Leveraging Technology to Adapt Evacuation Logistics: Webapp InputThe concerns with household decision making reflect those common among public officials for predicting and accommodating evacuation behavior for decades, such as messaging in the area at risk and capacity of resources, residences, and facilities to withstand flood (Baker 1991). However, workshop participants expressed interest in connecting decision-making concerns with perceived redistributions of vulnerabilities and assets associated with the COVID-19 pandemic. The COVID-19 Transportation Webapp developed in response to these interests allowed focus group participants to identify locations in need of additional evacuation planning attention. Low-response census tracts, public housing units, pick-up points, parking garages used to temporarily park vehicles above flood waters, and areas with frequent flooding were selected (Fig. 1). The issues of concern were extensions of ongoing planning gaps that received added attention given the need to re-envision evacuation transportation to reduce congregate settings. The need to separate out behavioral responses and intentions in evacuation zones from the shadow evacuations occurring in the overall city was noted.Participants also stated that HURREVAC remained useful during the pandemic to predict timelines and resource mobilizations based on the unique storm characteristics, but modeling options as a whole could be improved by integrating information about roads that flood prior to a storm and additional real-time information about contraflow measures, closures, traffic, weather forecasts, supplies, staffing, and ride-share availability. A participant noted staff limitations to do “real-time data analysis for things like 25 and 50 year flood events” and stated that “Lidar of infrastructure, models of floods, and transportation elevation data are needed” to complement travel demand models. Another participant was conflicted, stating that these features would help reroute around problem areas but could also be seen as negative branding in frequently flooded areas. An alternative use was proposed: resource redeployment once limitations and problem areas are identified. No matter the use, participants cautioned that these applications would need to be available in advance, stay current, and be easily manipulated.Some participants wanted to develop applications similar to the COVID-19 Transportation Webapp for their locations or an expanded version including a broader area to account for interjurisdictional traffic flow. Some suggested inclusion of considerations used in individual evacuation decision making, such as crime and COVID-19 infection rates. Others were engaged in collaborations to inventory and geolocate nonacute services, such as mental health services, food banks, and childcare. Despite the interest of cities and counties to conduct evacuation and behavior studies, the capacity to do so is often limited (Lindell et al. 2019). Getting current and reliable behavioral, infrastructural, and vulnerability data to city and county evacuation planners and households under evacuation orders could be the most efficient use of resources.Conclusions and RecommendationsEmergency management, public health, and transportation officials identified that COVID-19 impacted availability of and demand for evacuation transportation assets in the following ways: service capacity, staffing, resource acquisition, and public messaging. Increases in demand for public services were anticipated because of financial losses during lockdowns. The potential to outsource transportation was explored to ensure continuity. Evacuation recommendations favoring sheltering at home or with friends or relatives in the event the home was not safe were preferred. Communication about health and safety requirements in shelters was added to traditional evacuation messaging. A period of a few months was needed to negotiate the contracts to modify evacuation options to preferred local noncongregate ones. Additional considerations regarding willingness to participate and accommodate certain populations were identified. Public resources were adjusted to accommodate those still in need of congregate options. Vaccine availability and administration changes to support distribution were anticipated to be the next planning hurdles.Additional protocols and resources needed to maintain and enforce infection control measures including physical distancing, PPE, sanitization, and symptom reporting needed to be developed. Preregistration was desirable. Stockpiles and sharing agreements were identified for health and safety supplies. The decision to rely on individuals to self-report symptoms and provide their own PPE, sanitization, and meals was made, although not consistently. Special considerations for individuals with underlying conditions associated with increased COVID-19 risk were identified. The potential to develop pandemic protocol training, provide mental health services, renegotiate partnerships, and contract noncongregate options was proposed. Safety protocols for public transit were largely agreed upon, despite continued concerns about enforcement. Routes and destinations were being revised.The following opportunities were identified from an assessment of existing data and modeling approaches to address remaining struggles with placing evacuation pick-up and drop-off points and timing evacuation orders: •Allowing additional time for deploying strained resources despite local hesitation to order evacuations early in the hopes of avoiding evacuation bottlenecks;•Modeling to identify route and pick-up point changes in the case of a local mobilization for a specific storm severity and path;•Coordinating real-time weather, resource, staffing, and traffic information and local knowledge with interjurisdictional data; and•Local behavior data acquisition and web application development to include additional health and social services.Cities and counties should prioritize the efficient transfer of similar and expanded spatially referenced data on behavioral expectations, vulnerability, and infrastructure to planners and negotiate sharing agreements to facilitate planning by creating integrated web applications for evacuation transportation during pandemics. Real-time data and dynamic data platforms should be coordinated in advance to facilitate natural, pandemic, and compound hazard planning.Findings complement existing collaborations among transportation departments, emergency managers, and FEMA regarding evacuation expectations and pandemic-related modification options. Beyond emergency management applications, this study provides practical methods that can be used immediately to make transportation systems more tailored to populations at increased risk of complications from pandemic-related changes in demand. Sharing agreements for supplies, outsourced noncongregate evacuation options, and expanded drop-off and pick-up locations could improve operations of and access to public services throughout a pandemic. This study can also be applied to a variety of hazards that may require evacuation during a pandemic, such as floods.References Ahmed, M. A., A. M. Sadri, and M. Hadi. 2020. “Modeling social network influence on hurricane evacuation decision consistency and sharing capacity.” Transp. Res. Interdiscip. Perspect 7 (Sep): 100180. Allen, M. J., and T. R. Allen. 2019. “Precipitation trends across the Commonwealth of Virginia (1947–2016).” Virginia J. Sci. 70 (1): 4. Andrews, R. G. 2020. “What happens if a ‘big one’ strikes during the pandemic?” The Atlantic, May 9, 2020. Baker, E. J. 1991. “Hurricane evacuation behavior.” Int. J. Mass Emergencies Disasters 9 (2): 287–310. Behr, J. G., and R. Diaz. 2013. “Disparate health implications stemming from the propensity of elderly and medically fragile populations to shelter in place during severe storm events.” Supplement, J. Public Health Manage. Pract. 19 (2): 55–62. Behr, J. G., and R. Diaz. 2014. “Hurricane preparedness: Community vulnerability and medically fragile populations.” Virginian Newslett. 90 (2): 1–10. Bian, R., and C. G. Wilmot. 2018. “An analysis on transit pick-up points for vulnerable people during hurricane evacuation: A case study of New Orleans.” Int. J. Disaster Risk Reduct. 31 (Oct): 1143–1151. Borowski, E., and A. Stathopoulos. 2020. “On-demand ridesourcing for urban emergency evacuation events: An exploration of message content, emotionality, and intersectionality.” Int. J. Disaster Risk Reduct. 44 (Apr): 101406. Cai, H., B. Tu, J. Ma, L. Chen, L. Fu, Y. Jiang, and Q. Zhuang. 2020. “Psychological impact and coping strategies of frontline medical staff in Hunan between January and March 2020 during the outbreak of Coronavirus Disease 2019 (COVID-19) in Hubei, China.” Med. Sci. Monit. 26: e924171. Capano, G., M. Howlett, D. S. L. Jarvis, M. Ramesh, and N. Goyal. 2020. “Mobilizing policy (in)capacity to fight COVID-19: Understanding variations in state responses.” Policy Soc. 39 (3): 285–308. Chu, D. K., E. A. Akl, S. Duda, K. Solo, S. Yaacoub, and H. J. Schünemann. 2020. “Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: A systematic review and meta-analysis.” Lancet 395 (10242): 1973–1987. Clark, A. M., et al. 2020. “Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: A modelling study.” Lancet Global Health 8 (8): E1003–E1017. Collins, J., R. Ersing, A. Polen, M. Saunders, and J. Senkbeil. 2018. “The effects of social connections on evacuation decision making during Hurricane Irma.” Weather Clim. Soc. 10 (3): 459–469. Cowling, B. J., and A. E. Aiello. 2020. “Public health measures to slow community spread of coronavirus disease 2019.” J. Infect. Dis. 221 (11): 1749–1751. Deka, D., and J. Carnegie. 2010. “Analyzing evacuation behavior of transportation-disadvantaged populations in northern New Jersey.” In Proc., Transportation Research Board, No. 10-1584. Washington, DC: Transportation Research Board. Dulebenets, M. A., J. Pasha, O. F. Abioye, M. Kavoosi, E. E. Ozguven, R. Moses, W. R. Boot, and T. Sando. 2019. “Exact and heuristic solution algorithms for efficient emergency evacuation in areas with vulnerable populations.” Int. J. Disaster Risk Reduct. 39 (Oct): 101114. Dulebenets, M. A., J. Pasha, M. Kavoosi, O. F. Abioye, E. E. Ozguven, R. Moses, W. R. Boot, and T. Sando. 2020. “Multiobjective optimization model for emergency evacuation planning in geographical locations with vulnerable population groups.” J. Manage. Eng. 36 (2): 04019043. Eggleston, J., and J. Pope. 2013. “Land subsidence and relative sea-level rise in the southern Chesapeake Bay region. Reston, VA: US Department of the Interior, USGS. Fong, M. W., H. Gao, J. Y. Wong, J. Xiao, E. Y. Shiu, S. Ryu, and B. J. Cowling. 2020. “Nonpharmaceutical measures for pandemic influenza in nonhealthcare settings—Social distancing measures.” Emerging Infect. Dis. 26 (5): 976. HRPDC (Hampton Roads Planning District Commission). 2017. Hampton Roads hazard mitigation plan. Chesapeake, VA: HRPDC. HRTPO (Hampton Roads Transportation Planning Organization). 2020c. Hampton Roads 2045 long-range transportation plan: Title VI/Environmental justice candidate project evaluation. Chesapeake, VA: HRPDC. HRTPO (Hampton Roads Transportation Planning Organization). 2020d. Hampton Roads 2045 long-range transportation plan: Regional needs. Chesapeake, VA: HRPDC. Huang, S.-K., M. K. Lindell, and C. S. Prater. 2016. “Who leaves and who stays? A review and statistical meta-analysis of hurricane evacuation studies.” Environ. Behav. 48 (8): 991–1029. Kapucu, N., T. Arslan, and M. L. Collins. 2010. “Examining intergovernmental and interorganizational response to catastrophic disasters: Toward a network-centered approach.” Administration Soc. 42 (2): 222–247. Karaye, I. M., C. Thompson, and J. A. Horney. 2019. “Evacuation shelter deficits for socially vulnerable Texas residents during Hurricane Harvey.” Health Serv. Res. Manage. Epidemiol. 6: 233339281984888. Kirchmeier-Young, M. C., and X. Zhang. 2020. “Human influence has intensified extreme precipitation in North America.” Proc. Natl. Acad. Sci. 117 (24): 13308. Lindell, M. K., P. Murray-Tuite, B. Wolshon, and E. J. Baker. 2019. Large-scale evacuation: The analysis, modeling, and management of emergency relocation from hazardous areas. New York: Routledge. Lindell, M. K., J. H. Sorensen, E. J. Baker, and W. P. Lehman. 2020. “Community response to hurricane threat: Estimates of household evacuation preparation time distributions.” Transp. Res. Part D Transp. Environ. 85 (Aug): 102457. Liu, H., J. Behr, and R. Diaz. 2016. “Population vulnerability to storm surge flooding in coastal Virginia, USA.” Integr. Environ. Assess. Manage. 12 (3): 500–509. National Academies of Sciences, Engineering, and Medicine. 2021. Emergency evacuation and sheltering during the COVID-19 Pandemic. Washington, DC: National Academies Press. Ng, M., J. Behr, and R. Diaz. 2014. “Unraveling the evacuation behavior of the medically fragile population: Findings from Hurricane Irene.” Transp. Res. Part A Policy Pract. 64 (Jun): 122–134. Ng, M., R. Diaz, and J. Behr. 2015. “Departure time choice behavior for hurricane evacuation planning: The case of the understudied medically fragile population.” Transp. Res. Part E Logist. Transp. Rev. 77 (May): 215–226. Ng, M., and D. Y. Lin. 2015. “Sharp probability inequalities for reliable evacuation planning.” Trans. Res. Pt. C: Emer. Technol. 60 (1): 161–168. Ng, M., and S. T. Waller. 2010. “Reliable evacuation planning via demand inflation and supply deflation.” Trans. Res. Pt. E: Logistics Trans. Rev. 46 (6): 1086–1094. Parr, S., B. Wolshon, J. Renne, P. Murray-Tuite, and K. Kim. 2020. “Traffic impacts of the COVID-19 pandemic: Statewide analysis of social separation and activity restriction.” Nat. Hazards Rev. 21 (3): 04020025. Pei, S., K. A. Dahl, T. K. Yamana, R. Licker, and J. Shaman. 2020. “Compound risks of hurricane evacuation amid the COVID-19 pandemic in the United States.” Geohealth 4 (12): e2020GH000319. Renne, J. L. 2018. “Emergency evacuation planning policy for carless and vulnerable populations in the United States and United Kingdom.” Int. J. Disaster Risk Reduct. 31 (Oct): 1254–1261. Robinson, R. M., A. J. Khattak, J. A. Sokolowski, P. Foytik, and X. Wang. 2009. “Role of traffic incidents in hampton roads hurricane evacuations.” In Proc., Transportation Research Board 88th Annual Meeting. Washington, DC: Transportation Research Board. Shultz, J. M., C. Fugate, and S. Galea. 2020. “Cascading risks of COVID-19 resurgence during an active 2020 Atlantic hurricane season.” JAMA 324 (10): 935–936. Smith, S. K., and C. McCarty. 2009. “Fleeing the storm(s): An examination of evacuation behavior during Florida’s 2004 hurricane season.” Demography 46 (1): 127–145. Sorensen, J. H., M. K. Lindell, E. J. Baker, and W. P. Lehman. 2020. “Community response to hurricane threat: Estimates of warning issuance time distributions.” Weather Clim. Soc. 12 (4): 837–846. Syed, S. T., B. S. Gerber, and L. K. Sharp. 2013. “Traveling towards disease: Transportation barriers to health care access.” J. Community Health 38 (5): 976–993. Watts, J., R. E. Morss, C. M. Barton, and J. L. Demuth. 2019. “Conceptualizing and implementing an agent-based model of information flow and decision making during hurricane threats.” Environ. Modell. Software 122 (Dec): 104524. Yang, K., R. A. Davidson, H. Vergara, R. L. Kolar, K. M. Dresback, B. A. Colle, B. Blanton, T. Wachtendorf, J. Trivedi, and L. K. Nozick. 2019. “Incorporating inland flooding into hurricane evacuation decision support modeling.” Nat. Hazards 96 (2): 857–878. Yi, W., L. Nozick, R. Davidson, B. Blanton, and B. Colle. 2017. “Optimization of the issuance of evacuation orders under evolving hurricane conditions.” Transp. Res. Part B Methodol. 95 (Jan): 285–304.

Source link

Leave a Reply

Your email address will not be published. Required fields are marked *