Facing involuntary immobility: Prioritizing the marginalized in climate and disaster risk policy

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Some exposed populations have the ability to move to safer places; others are unable to get out of harm’s way. The climate risks facing these involuntary immobile populations are not often addressed by local and national authorities, despite increasing recognition by international development agencies and humanitarian actors. Here we discuss when and how climate and extreme weather events lead to involuntary immobility by considering the influence of political, socioeconomic, and environmental factors. Addressing barriers in policy and disaster planning, early warning systems and anticipatory action could be tailored to support involuntarily immobile communities. While policy and planning should be data-informed, lack of appropriate data quality should not limit governments and institutions from taking action. Immobility needs to be aligned with the broader sustainable development objectives which entail climate justice and orderly migration. Climate Analysis and Modeling Environmental Policy climate change migration heat immobility health Figures Figure 1 Introduction There is increasing recognition in academia and policy circles that the real risk of climate change to the world’s most vulnerable populations is less likely to be mass migration, but rather involuntary immobility - whereby people who would like to move cannot do so because of constraints imposed both by climate stressors and extreme poverty. 1 , 2 From urban slums and refugee camps to prisons and conflict zones, millions of people worldwide face immense challenges to relocate when impacted by natural hazards. 3 , 4 For these potentially immobile populations, impacts from climate change not only exacerbate pre-existing environmental and habitability challenges, but also amplify the structural socioeconomic, cultural, and political challenges they face. While socioeconomically, culturally, and politically marginalized populations worldwide are generally at elevated risk to natural hazards compared to the broader population, immobile populations are underrepresented and understudied in the context of policy and research concerned with evolving and worsening climate change impacts. 5 – 7 To date, most human mobility research focuses on migration, displacement, and refugee flows, excluding those populations unable or unwilling to move when faced with extreme weather or declining habitability. This omission is tied to factors relating to the lack of political representation and/or marginalization of populations in situations of immobility. Furthermore, unlike migration or displacement, inherent difficulty arises from observing cases that are essentially characterized by a lack of distinct empirical manifestations, data and surveys, enabling the identification of involuntary immobile populations. However, involuntary immobility is much more than a data concern or a gap in the literature. It is also a lens through which action toward climate resilience can and must be structured and leveraged. 8 , 9 In this work, we recapitulate the scientific logic behind involuntary immobility, focusing on the challenges induced by extreme weather and climate change that involuntary immobile populations face today. We highlight barriers that must be overcome for climate action to reach the most vulnerable populations. To do so, we showcase the diverse drivers of climate immobilities through a set of case studies. We conclude with policy implications in view of implementing pragmatic solutions to alleviate vulnerabilities to natural hazards faced by involuntarily immobile populations. Leveraging climate action through an involuntary immobility lens requires an understanding of the multi-scale political, socioeconomic, and environmental contextual structures constraining the ability of individuals and households to move out of areas at immediate risk of disasters or that are experiencing inexorable declines in habitability. 10 – 12 Immobile populations are at risk of suffering severe damage resulting from individual extreme weather events, and compound, and complex disasters. 13 , 14 Given these complexities, incorrect or incomplete framing can exacerbate the maladaptive conditions that such efforts seek to address. 15 Outlining involuntary human immobility as a framework for climate action is therefore crucial. Understanding involuntary immobility is not merely an academic exercise but a key lens through which the efficacy of climate adaptation initiatives can be evaluated and improved. By integrating the concept of involuntary immobility into our analysis, we contribute to a more nuanced understanding of how climate change disproportionately affects the most vulnerable populations. This understanding is essential for recognizing the barriers to mobility, leading to involuntary immobility, faced by certain populations. 12 It further illuminates the gaps in current climate adaptation strategies, highlighting the need for appropriately designed policies that address these unique challenges. Consequently, our focus on involuntary immobility aims to bridge these gaps, advocating for a holistic approach to climate action that prioritizes the protection and empowerment of all individuals, particularly those who are most at risk. By doing so, we seek to align our research with worldwide efforts to address climate and environmental related risks, underscoring the imperative for policies that are both scientifically sound and socially just. Immobility as a scientific concept Mobility outcomes can be structured along the two dimensions of the aspirations-capabilities framework 16 , where aspirations refer to a person’s desire to move from their current location, and capabilities capture whether they are indeed able to undertake a move. Those who wish to and can move are usually able to realize their move (voluntary mobility), whereas those who want to, but cannot move can be characterized as trapped (involuntary immobility). Among those who do not want to move, a conceptual distinction is possible between those who could move but don’t (voluntary immobility) and those who do not have the capability to move (acquiescent immobility). Distinguishing the latter two categories is empirically challenging. 17 For the purpose of this piece, involuntary immobility pertains to situations in which individuals, households, or communities face risks to their physical, psychological, and economic well-being due to exposure to natural hazards. They are either unable to leave their residence despite a desire to do so, or perceive that any such attempt would be unsuccessful or ineffective. 18 , 19 Immobility occurs across a spectrum ranging from complete immobility on one end to unconstrained mobility on the other, rather than as a sharp delineation between mobile and immobile populations. 20 , 21 A person’s or population’s position on this spectrum can fluctuate over time. The ability to anticipate such changes increases the likelihood of developing policies and services to support potentially immobile populations and mitigate the conditions driving such a shift. Climate change impacts are changing many dimensions of involuntary immobility. In this context, involuntary immobility is characterized by the inability of individuals or populations to relocate in response to considerable threats from extreme weather events, environmental degradation, or other climate-related impacts. 22 This immobility is not a voluntary condition but is instead the result of a variety of intersecting factors. 23 These include, but are not limited to, economic, political, legal, social, and cultural obstacles, which collectively inhibit their movement and ability to find shelter in perceived safer areas. At the same time, we recognize that involuntary immobility in the face of a natural hazard is a complex phenomenon, susceptible to substantial variation across contexts. Indeed, involuntary immobility can occur at different time scales, when facing an immediate threat of extreme weather, in the aftermath of a disaster, and over a longer time horizon. 15 , 24 A person’s ability to move across long distances may be substantially curtailed, though she might remain locally mobile and able to find immediate, but not durable, shelter in their villages/communities. Early uses of the notion of involuntary immobility in the literature primarily referred to economic and social barriers of migration. 25 , 26 Climatic and environmental factors were not explicitly investigated until the past two decades. 27 , 28 A growing body of literature and data has quantified aspects of who is most likely to be mobile and identified, by extension, who is potentially immobile for a given natural hazard. 6 , 29 Even so, populations at risk of involuntary immobility in the face of climate change impacts – as a result of economic, social and political constraints – remain structurally hidden from vulnerability assessments. 30 This is particularly true for populations facing physical constraints to their mobility, such as prisoners or undocumented migrants. Outlook and policy challenges for developing effective systems While a more nuanced representation of involuntary immobility has led to more appropriate governance discourse 64 , gaps remain in the development of policy and services tailored specifically for immobile populations. For policy and services intending to address climate-related risk, the outputs will be incomplete at best, and detrimental at worst, if the needs of populations facing immobility are not central. On the one hand, political will is required to enhance the development of climate services and support for disaster risk reduction activities - and adaptation programming more broadly. On the other hand, such support requires conducting a systematic review of affected communities and their ability to mitigate the impact of natural hazards and climate change, adapt to these in situ or relocate, with specific attention to those communities that may be invisible or otherwise marginalized. Therefore, policies need to be grounded in the local contexts and involve a participatory process, allowing multiple communities and societal actors to co-produce usable knowledge for decision-making. 65 Factors that incentivize people to stay in their place of residence can include hard-to-quantify connections and networks - such as solidarity and support systems. Similar to property loss, these incentives are often lost if relocated. 66 Losses and damages from climate change can make it difficult to re-establish life and community, particularly without community support. Increasingly, studies are acknowledging a broader perspective related to the choice to stay 67 , 68 or the choice to leave, leading to more appropriate policy responses. 69 While explicitly including immobile populations within pre-disaster, early warning, and anticipatory action programming remains challenging, lack of data itself continues to be a major challenge in including immobile population in policy and risk planning. 70 We argue that a lack of detailed population data on marginalized populations should not limit governments and institutions from providing support and striving for policy and disaster planning that include immobile populations. Moreover, the availability and accessibility of appropriate and sufficient data does not imply that it can be integrated within policy and services without close attention to the translation processes. There is also the risk that inclusion of such data could lead to prioritization of some populations over others. 71 , 72 Much of the existing literature on vulnerability draws on variables from census data to identify marginalized populations and other communities at risk of immobility in the face of climate change and disasters. However, key immobile groups, such as inmates or unhoused populations, are likely missed by census data. 18 , 73 In addition, disagreement across some population datasets could create differences in policy implementation, including but not limited to prioritization of resources for climate change adaptation and activation of early warning systems. 74 Ethical considerations need to involve an assessment of data quality to ensure that the most vulnerable people are not left out of policy responses and that action prioritizes those most in need. Furthermore, high resolution data are needed in order for community needs, justice, and equity to be met. 75 , 76 Investing in data-collection processes that are co-produced with people facing an immobility risk together with decision makers is a key step to outlining and addressing these data challenges. Then, the integration, translation and decision-making steps need to reflect both the data from the co-production process, as well as other lessons learned from this process. 77 In our view, centering and including the populations facing involuntary immobility in climate and disaster risk analysis is the only way to ensure that appropriate attention, resources and action are devoted to support them. While more research is needed to understand the natural hazard elements, further analysis of risk perception, governance schemes, communication is also critical to ensure that the experiences of populations are integrated within research - to in turn increase the likelihood that the research outcomes are actionable. Ultimately, we call for closer attention to involuntarily immobility across research, policy and practice. This requires urgent action to develop a collaborative effort to that aim, as without doing so, the call to support the involuntary immobile would be incomplete at best and might lead to unanticipated consequences at worst. Drivers and processes of involuntary immobility For both short and long-term immobility, a multicausality conceptual framework approach has been applied. 2 However, further attention to spatiotemporal scales is needed to account for current direct and indirect drivers and those likely to be at play in the immediate-term future. As an initial step in crafting a new appropriately detailed framework, a set of key mobility barriers are described here. Economic and physical barriers : The classical perspective on migration has long documented that economic considerations are important constraints to migration. 31 , 32 The upfront costs a migrant must pay to cover travel expenses exert a significant constraint on the ability to travel, particularly over long-distances and through regions with complex geographic and socioeconomic deterrents. 33 , 34 Financial barriers limit the ability of lower-income households to pursue migration, also across shorter distances. 35 , 36 These barriers are likely to be particularly important when would-be migrants are forced to travel along irregular migration routes, due to a lack of access to visas or other authorizations, often relying on costly human smugglers. 37 In addition, current economic conditions and perceptions of what future economic conditions will be, can influence long-term mobility options and how populations perceive immobility. 29 Increasingly, heat exposure (see also Fig. 1 ) plays a role in limiting mobility in the short-term. For example, economically deprived districts are harbingers of immobility when faced with heat stress during the growing season in Zambia. 31 Under future sea level change (SLC) scenarios, occurrences and experiences of flooding and associated damages from SLC are found to contribute to increases in migration toward coastal areas in Bangladesh by the end of the century. Coastal populations’ ability to move is constrained by access to cash and the relative affordability of alternative options and livelihoods to migration. 38 Financial constraints to migration can also be understood in the context of livelihood choices for individuals and households. Livelihood choices of smallholder farmers in Nepal show how international migration can play out as a higher-cost, higher-reward strategy as compared to other, in situ options. Reduced agricultural income limits the ability of households with lower access to capital to choose migration as a livelihood strategy by mid-century. 29 Physical infrastructure barriers to mobility have manifested in the effects of extreme weather events on telecommunications and transportation, particularly in areas with already relatively isolated or remote communities such as those in island states and in countries with complex topography. As an example of the latter, recurrent flooding in Tajikistan’s Bartang Valley has impacted infrastructural connectivity and human mobility. Road closures and repairs add to the mix of physical barriers to immobility. High car operating costs impede the local population’s mobility. Telecommunication can mitigate situations of physical immobility. Phone calls provide an opportunity for immobile populations to stay connected with their social network, thereby limiting feelings of isolation and depression. Yet, the instability of the telecommunication network substantially constrains the ability of residents of the valley to move around. 39 , 40 While populations of small-island states can seek shelter in other areas of the island they inhabit, movement is constrained to a degree as islands present unique geographic challenges. In addition, many small-island states have limited and expensive transportation to travel off island, especially given economic barriers. As island roads are often constrained by topography, and thus are positioned close to flatter areas along coastline or other water bodies, there is an increased likelihood of evacuations being hampered by issues related to inundation, landslides, and other disruptions of infrastructure that affect road access. 41 , 42 In the ‘large-island’ case of the Japanese Tohoku earthquake, tsunami, and nuclear accident at Fukushima, evacuation was made difficult or impossible at scale in the short-term due to damage to physical infrastructure. 43 Political, legal, and bureaucratic barriers: International borders and restrictions on internal mobility can impose long-term immobility in the face of a natural hazard. In the face of increasing natural hazards and risks from SLC with additional warming, island populations lack legal mechanisms enabling mobility leaving them unable to move. 42 Similarly, refugees living in host countries with restrictive asylum policies may be physically confined to a camp or specific areas of a country with little ability to migrate post-hazard. These policy restrictions to mobility compound the extreme poverty and resource deprivation faced by many refugees and the dwindling availability of humanitarian aid, the delivery of which is itself subject to political and climate disruptions. Forced to flee Myanmar after a campaign of persecution, the Rohingya refugee population in Bangladesh have faced significant political and legal barriers to mobility within the country. 44 In addition, Bangladesh has periodically resorted to forced relocation to keep refugees in specific areas of the country, generally along the border with Myanmar. 45 Most refugees in the country reside in the Cox’s Bazar district where refugee settlements are among the most densely populated areas in the world (e.g. 40,000 refugees per square kilometer in the Kutupalong Refugee Camp). 46 Many camps face high levels of landslide exposure, while others face high risk of coastal and inland flooding. 47 , 48 Climate change impacts could even further diminish migration opportunities, while making the consequences of immobility even more catastrophic. Refugees are not the only group that face barriers to movements due to restrictions on entry. Many migrants find themselves stuck in transit countries and forced to survive on marginal lands with evidence from North Africa and Mexico indicating that stranded migrants are particularly vulnerable to flooding. 28 , 49 , 50 Because of language and cultural barriers, as well as limited access to humanitarian assistance, these populations face particularly high exposure to natural hazards. By way of example, the Covid-19 pandemic substantially worsened the situation for many transit migrants in Mexico, with many left stranded after the enactment of US Title 42 ostensibly in view of limiting the spread of the disease. These migrants faced significant natural hazard in the place of transit. 51 – 53 Even under optimistic climate projections, climate change impacts will continue to significantly harm involuntary immobile populations if substantial shifts in policy discourse and targeted investment in adaptation are not enacted. As an illustration, nearly all refugee camps will face an unprecedented rise in hazardous heat stress (Fig. 1 ). By 2050, the hottest fifteen camps may experience nearly 200 or more days per year of hazardous heat stress under middle-of-the-road climate projections (SSP 245). Should these locations continue to house refugees with little investment in adaptations like air conditioning, such heat stress is likely to drastically harm health and well-being among refugees, with recent evidence suggesting a precipitous rise in mortality. 54 Heat stress is just one of the multitude of natural hazards projected to worsen for involuntary immobile groups worldwide. 55 Social and cultural barriers : Indigenous communities, as well as residents in informal or deprived areas of cities are systematically predisposed to experience a lack of services and financial opportunities, in addition to social and cultural barriers. 57 These dynamics exist both in high-income countries and in lower- and middle-income countries. Spatial patterns are documented in the environmental and climate justice literature in which marginalized populations are located in risky places, even in the most developed countries. 58 Pacific island communities are faced with displacement that breaks community connections, including losses and disconnection from culture, language, and religious ties. The ability to migrate can be limited by bureaucratic barriers, as well as attachment to their lands. 59 , 60 In Aotearoa (New Zealand), indigenous Māori communities face potential relocation of coastal marae , communal meetings grounds of cultural and religious significance (that can include a meeting hall, place of prayer, dinner facilities, as well as preschool and other communal building) due to risks stemming from recurrent flooding, soil erosion and SLC. Yet, the lack of land availability and land ownership restrictions resulting from colonial legacies, contribute to hurdles in relocating marae to safer places; without endangering the survival of local indigenous communities by severing its symbolic connection to a place. 61 Unhoused populations (UPs) face exposure to natural hazards without sufficiently reliable options to avoid risk. While some UPs, such as those living in shelters, may be able to move about a defined area, the extent to which they are able to find effective refuge from threats remains limited in many situations. UPs in New York City face economic, political, legal, physical or mental barriers that limit their ability to find shelter when facing floods, storms and heat waves. Heat-related mortality among UPs is projected to double, while a paucity of data exists for similar analyses for other natural hazards. 62 As a consequence, UPs are likely to disproportionately suffer from the impact of a natural hazard, relative to populations having access to housing, and without their specific needs accounted for. UPs in New York City face higher levels of respiratory conditions and temperature exposure due to lack of filtration and air conditioning as a result of living on the streets. 62 While there may be poor air quality and extreme temperature warnings, UPs are often incapable of relocating to safer locations despite underlying conditions that make them more susceptible. 63 Methods Participatory action data collection The participatory action data collection combined 3 primary phases: (i) a World Cafe session, (ii) a group deliberation and (iii) the development of a synthesis manuscript co-authored by session participants. World Cafe structure We used a World Cafe approach as a participatory action research technique to guide qualitative data collection. The World Cafe method has been applied to leverage knowledge on complex topics and is a well-vetted technique from the field of applied decision science. 78 , 79 The World Cafe event was held in June 2023 with 53 participants during the 2023 Managed Retreat Conference (Columbia University). This World Cafe aimed to highlight immobility in the context of environmental, political and social elements and uncover underlying themes of involuntary immobility. The World Cafe session consisted of three discussion rounds on (i) driver and impacts, (ii) challenges and obstacles, (iii) policy implications and guardrails. Each table consisted of 8–9 participants with one facilitator at each table, serving a dual role: guiding the discussion and taking notes. After each round, participants were encouraged to change tables. The second stage of the participatory action data collection was a group deliberation. The deliberation combined a participatory summary of the World Cafe session through facilitators and a discussion around unique learnings ( What surprised you most about today’s discussions? ) as well as points not raised during the World Cafe ( What was missing from the discussions today? ). On the basis of notes of the World Cafe session and the group deliberation, anonymous transcripts were prepared with points raised and then summarized. The summarized transcripts from the World Cafe rounds were analyzed by L.T., A.K. and F.C. through qualitative content analysis with support from C.H. and C.T. All co-authors contributed to the writing of this paper. Refugee Heat Stress Observations and Projections Refugee camp locational data are based on publicly available “People of Concern” data from UNHCR 80 accessed on 21 February 2024. We filtered the UNHCR dataset to 1344 refugee population locations across spontaneous locations (931), planned settlements (384), unplanned settlements (5), and dispersed locations (24). We exclude refugee population locations in Lebanon, which are recorded differently than other countries, and exclude locations of asylum-seeking populations, internally displaced persons (IDPs), returnees, stateless populations, and those classified as unknown. We use the Climate Hazards Center Coupled Model Intercomparison Project Phase 6 climate projection dataset (CHC-CMIP6) to estimate historical (2007–2016) and future (2050) average annual heat stress at the location of all refugee camps worldwide. Available at 5-km globally, CHC-CMIP6 is among the highest resolution climate projections specifically designed to estimate future heat stress in data sparse refugee-hosting regions, like the African Sahel. 81 A highly accurate 5-km blended satellite and station derived daily maximum air temperature record – CHIRTS-daily 82 – and down-scaled relative humidity estimates from ERA5 climate reanalysis form the foundation of the CHC-CMIP6 daily shaded daily maximum wet bulb globe temperature (WBGTmax) observational record. Next, coarse-grained (100–250 km) CMIP6 ensembles for 245 and SSP 585 scenarios are used to develop high resolution (0.05°) 2030 and 2050 “delta” fields, which is the difference between CMIP6 multi-model ensemble-based changes between 1983–2016 and 2025–2035 and 2045–2055. The delta fields are then used to perturb the WBGTmax observational record to derive the CHC-CMIP6 SSP245 and SSP 585 2030 and 2050 projections. We use the SSP245 projections for 2050, derived from the CHC-CMIP6 dataset because of its high spatial resolution that better captures local climate heterogeneity compared to the coarse-grained CMIP6 projections. For a full description of CHC-CMIP6. 81 To measure heat stress at refugee camp locations, we first estimate the average annual number of days per year WBGTmax exceeded 30°C from 2007–2016 using the CHC-CMIP6 observational record. We then estimate future heat stress as the average annual number of days per year WBGTmax exceeded 30°C from 2007–2016 under a 2050 climate following SSP 245. While we fully recognize that a plethora of heat stress metrics exist (Baldwin et al 2023), we estimate heat stress as the number of days where WBGTmax exceeded 30°C because it is the International Organization for Standardization (ISO) criteria for occupational risk to heat stress for acclimated people under moderate metabolic rates (65–130 Wm − 2 ). This ISO criteria is well-established and commonly used in the heat-health literature. 54 , 73 , 83 For context, monthly average WBGT of 30°C has been associated with increased mortality rates among vulnerable populations. 54 Declarations Acknowledgments The authors wish to thank participants of the 2023 Columbia University Managed Retreat Conference World Cafe on Climate Change Implications for Conflict Zones, Displaced Persons, Refugees, Slums Residents, and Other Involuntary Immobile Populations. We also thank Elizabeth Fussell for comments on an earlier version of this manuscript. C.T. was supported by the Air Force Office of Scientific Research grant no. FA9550-23-1-0684. J.V.D.H. was supported by the NASA Land Cover/Land Use Change Program grant no. 80NSSC23K0528. Data Availability Statement Refugee camp locations are available in the “UNHCR People of Concern” dataset https://data.unhcr.org/en/geoservices/ . 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Nat Hazards Res 2:230–248 He Y, Thies S, Avner P, Rentschler J (2021) Flood impacts on urban transit and accessibility—A case study of Kinshasa. Transp Res Part D: Transp Environ 96:102889 Frank-Vitale A (2020) Stuck in Motion: Inhabiting the Space of Transit in Central American Migration. J Latin Am Caribb Anthropol 25:67–83 Blue SA et al (2021) Im/mobility at the US–Mexico border during the COVID-19 pandemic. Social Sci 10:47 Vega LAA, de los Santos EC (2020) Immobile and vulnerable: Migrants at Mexico’s southern border at the outset of Covid-19. Baker Inst Rep 8 Casillas R (2008) The routes of central americans through Mexico: characterization, principal agents y complexities. Migración y Desarrollo 10:157–174 Pradhan B et al (2019) Heat stress impacts on cardiac mortality in Nepali migrant workers in Qatar. Cardiology 143:37–48 Fransen S, Werntges A, Hunns A, Sirenko M, Comes T (2024) Refugee settlements are highly exposed to extreme weather conditions. Proceedings of the National Academy of Sciences 121, e2206189120 Parsons K (2006) Heat stress standard ISO 7243 and its global application. Ind Health 44:368–379 Subbaraman R et al (2014) The psychological toll of slum living in Mumbai, India: a mixed methods study. Soc Sci Med 119:155–169 Maantay J, Maroko A (2009) Mapping urban risk: Flood hazards, race, & environmental justice in New York. Appl Geogr 29:111–124 Noy I (2017) To Leave or Not to Leave? Climate Change, Exit, and Voice on a Pacific Island. CESifo Economic Stud 63:403–420 McMichael C, Farbotko C, Piggott-McKellar A, Powell T, Kitara M (2021) Rising seas, immobilities, and translocality in small island states: case studies from Fiji and Tuvalu. Popul Environ 43:82–107 Bailey-Winiata A, Gallop SL, Hikoura D, White I (2022) The role of coastal marae in natural hazard response and climate change adaptation Ramin B, Svoboda T (2009) Health of the Homeless and Climate Change. J Urban Health 86:654–664 Alfonseca K (2023) Homeless populations vulnerable amid poor air quality and smoke: Advocates. ABC News https://abcnews.go.com/US/homeless-populations-vulnerable-amid-poor-air-quality-smoke/story?id=99937365 Thornton F, Serraglio DA, Thornton A (2023) Trapped or staying put: Governing immobility in the context of climate change. Front Clim 5:1092264 Mach KJ et al (2020) Actionable knowledge and the art of engagement. Curr Opin Environ Sustain 42:30–37 Bower ER, Badamikar A, Wong-Parodi G, Field CB (2023) Enabling pathways for sustainable livelihoods in planned relocation. Nat Clim Chang 13:919–926 Zickgraf C (2021) Climate change, slow onset events and human mobility: reviewing the evidence. Curr Opin Environ Sustain 50:21–30 Iyer M, Schewel K (2024) Articulating and Claiming the Right to Stay in the Context of Climate Change. Georgetown Immigration Law Journal, Forthcoming Farbotko C, Dun O, Thornton F, McNamara KE, McMichael C (2020) Relocation planning must address voluntary immobility. Nat Clim Chang 10:702–704 Jaime C, de Perez EC, van Aalst M, Easton-Calabria E (2024) Beyond the forecast: knowledge gaps to anticipate disasters in armed conflict areas with high forced displacement. Environ Res Lett 19:023001 Jagannathan K et al (2023) A research agenda for the science of actionable knowledge: Drawing from a review of the most misguided to the most enlightened claims in the science-policy interface literature. Environ Sci Policy 144:174–186 Enenkel M, Kruczkiewicz A (2022) The humanitarian sector needs clear job profiles for climate science translators now more than ever. Bull Am Meteorol Soc 103:E1088–E1097 Tuholske C et al (2021) Global urban population exposure to extreme heat. Proceedings of the National Academy of Sciences 118, e2024792118 Kruczkiewicz A et al (2021) Opinion: Compound risks and complex emergencies require new approaches to preparedness. PNAS 118 Unger E-M, Lemmen C, Bennett R (2023) Women’s access to land and the Land Administration Domain Model (LADM): Requirements, modelling and assessment. Land use policy 126:106538 Morales J, Lemmen C, de By RA, Dávila AEO, Molendijk M (2021) Designing all-inclusive land administration systems: A case study from Colombia. Land use policy 109:105617 Vincent K, Daly M, Scannell C, Leathes B (2018) What can climate services learn from theory and practice of co-production? Clim Serv 12:48–58 Lorenzetti LA, Azulai A, Walsh CA (2016) Addressing Power in Conversation: Enhancing the Transformative Learning Capacities of the World Café. J Transformative Educ 14:200–219 Silva S, Guenther E (2018) Setting the research agenda for measuring sustainability performance – systematic application of the world café method. Sustain Acc Manage Policy J 9:455–469 UNHCR. UNHCR Core GIS Data (2024) Williams E, Funk C, Peterson P, Tuholske C (2024) High resolution climate change observations and projections for the evaluation of heat-related extremes. Sci Data 11:261 Verdin A et al (2020) Development and validation of the CHIRTS-daily quasi-global high-resolution daily temperature data set. Sci Data 7:303 Cheung SS, Lee JK, Oksa J (2016) Thermal stress, human performance, and physical employment standards. Appl Physiol Nutr Metab 41:S148–S164 Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5839757","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":402867230,"identity":"0c46b5f9-1719-442b-a6ce-6195f9d18df9","order_by":0,"name":"Lisa Thalheimer","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYDACCQbGwyCSgYH5wIEEYnTwABVDtbAlIGnBoxmqBcw0QBLHo8VeuvnB4YIKi2h+6TMfDzyoqZNnYD/8gOHnDzy2yBwzODzjjETuzL7cDQcSjh02bOBJM2DsweuwBIPDvG0SuRvO8AK1sB1gbGDIAQrj1ZL+4TDvP4nc/Wd4HhxI+Fdn38D/hoHxD14tOUBbGoC28PAwHEhsY05skMhhYMZry42cgsM8xyRyZ5xhMziQ2Hc4uU3imcFhmTTcWthnpG98zFNTl9vfw/z4449vdbb9/MkPH76xwa0FE7AB8QFSNIyCUTAKRsEowAQAn5VS4uYK7yAAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-3737-3586","institution":"International Institute for Applied Systems Analysis, Laxenburg, Austria","correspondingAuthor":true,"prefix":"","firstName":"Lisa","middleName":"","lastName":"Thalheimer","suffix":""},{"id":402867231,"identity":"6a6ccf45-d3c7-4f04-a265-6d8b132f11e2","order_by":1,"name":"Fabien Cottier","email":"","orcid":"","institution":"Center for International Earth Science Information Network, Columbia Climate School, Columbia University, USA","correspondingAuthor":false,"prefix":"","firstName":"Fabien","middleName":"","lastName":"Cottier","suffix":""},{"id":402867232,"identity":"eb3f0ced-4c98-41ad-b20c-c26c6c980f32","order_by":2,"name":"Andrew Kruczkiewicz","email":"","orcid":"","institution":"International Research Institute for Climate and Society, Columbia Climate School, Columbia University, New York, USA","correspondingAuthor":false,"prefix":"","firstName":"Andrew","middleName":"","lastName":"Kruczkiewicz","suffix":""},{"id":402867233,"identity":"3c4ce23c-e186-4443-83f2-5341505bf575","order_by":3,"name":"Carolynne Hultquist","email":"","orcid":"","institution":"School of Earth and Environment, University of Canterbury, New Zealand","correspondingAuthor":false,"prefix":"","firstName":"Carolynne","middleName":"","lastName":"Hultquist","suffix":""},{"id":402867234,"identity":"d20250da-a1fc-43c2-ab4f-9010857927f1","order_by":4,"name":"Cascade Tuholske","email":"","orcid":"","institution":"Department of Earth Sciences, Montana State University, USA","correspondingAuthor":false,"prefix":"","firstName":"Cascade","middleName":"","lastName":"Tuholske","suffix":""},{"id":402867732,"identity":"2357888a-2105-423b-9d1a-9c82dcb7e5e1","order_by":5,"name":"Hélène Benveniste","email":"","orcid":"","institution":"Doerr School of Sustainability, Stanford University, USA","correspondingAuthor":false,"prefix":"","firstName":"Hélène","middleName":"","lastName":"Benveniste","suffix":""},{"id":402867733,"identity":"35145e6b-28d4-4494-abe5-f056fe8e3b56","order_by":6,"name":"Jan Freihardt","email":"","orcid":"","institution":"Department of Mechanical and Process Engineering, ETH Zürich, Switzerland","correspondingAuthor":false,"prefix":"","firstName":"Jan","middleName":"","lastName":"Freihardt","suffix":""},{"id":402867734,"identity":"07f4ec79-557b-4797-8d01-f1a95d4f98e1","order_by":7,"name":"Mona Hemmati","email":"","orcid":"","institution":"Lamont-Doherty Earth Observatory, Columbia Climate School, Columbia University, USA","correspondingAuthor":false,"prefix":"","firstName":"Mona","middleName":"","lastName":"Hemmati","suffix":""},{"id":402867735,"identity":"0fa51f4d-f23e-4f0b-8682-242987818deb","order_by":8,"name":"Pui Man Kam","email":"","orcid":"","institution":"Department of Environmental Systems Science, ETH Zürich, Switzerland","correspondingAuthor":false,"prefix":"","firstName":"Pui","middleName":"Man","lastName":"Kam","suffix":""},{"id":402867736,"identity":"d2228d24-db88-480d-b906-0c3b7ac87d14","order_by":9,"name":"Narcisa G. Pricope","email":"","orcid":"","institution":"Department of Geosciences, Mississippi State University, USA","correspondingAuthor":false,"prefix":"","firstName":"Narcisa","middleName":"G.","lastName":"Pricope","suffix":""},{"id":402867737,"identity":"62ef3c7d-f3d4-4b04-a9d9-36830994eada","order_by":10,"name":"Jamon Van Den Hoek","email":"","orcid":"","institution":"College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, Oregon, USA","correspondingAuthor":false,"prefix":"","firstName":"Jamon","middleName":"Van Den","lastName":"Hoek","suffix":""},{"id":402867738,"identity":"88302542-841d-4a86-b384-f63244a2ddf8","order_by":11,"name":"Andrew Zimmer","email":"","orcid":"","institution":"Department of Earth Sciences, Montana State University, USA","correspondingAuthor":false,"prefix":"","firstName":"Andrew","middleName":"","lastName":"Zimmer","suffix":""},{"id":402867739,"identity":"595d6a47-47ed-49ff-a7cf-da24856ddfe9","order_by":12,"name":"Radley M. Horton","email":"","orcid":"","institution":"Columbia Climate School, Columbia University, USA","correspondingAuthor":false,"prefix":"","firstName":"Radley","middleName":"M.","lastName":"Horton","suffix":""},{"id":402867740,"identity":"51af8e39-2517-457a-8bb5-2dabe3d8a6d4","order_by":13,"name":"Alex de Sherbinin","email":"","orcid":"","institution":"Center for International Earth Science Information Network, Columbia Climate School, Columbia University, USA","correspondingAuthor":false,"prefix":"","firstName":"Alex","middleName":"","lastName":"de Sherbinin","suffix":""}],"badges":[],"createdAt":"2025-01-16 07:54:09","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5839757/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5839757/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":74098314,"identity":"efe7db77-7b39-4097-b951-93a1505619c6","added_by":"auto","created_at":"2025-01-17 17:47:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":600560,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of refugee camps where (A) the average number of days per year shaded daily maximum wet bulb globe temperature (WBGTmax) exceeded 30°C for 2007-2016. (B) is the average number of days WBGTmax exceeded 30°C for 2007-2016, but under a 2050 climate following SSP245 (middle of the road) radiative forcing. (C) lists the top 15 hottest refugee camps in 2050 under SSP 245, with the count days in 2050 vs. the 2007-2016 baseline. The yellow boxes in (A) and (B) are the approximate locations of the camps identified in (C). WBGTmax \u0026gt; 30°C the ISO standard\u003ca href=\"https://www.zotero.org/google-docs/?Fv8YjE\"\u003e\u003csup\u003e56\u003c/sup\u003e\u003c/a\u003e for risk to occupational heat stress for acclimated people under moderate metabolic rates (65-130 Wm\u003csup\u003e-2\u003c/sup\u003e). For context, monthly average WBGT of 30°C has been associated with increased mortality rates among vulnerable populations.\u003ca href=\"https://www.zotero.org/google-docs/?1oQ7P4\"\u003e\u003csup\u003e54\u003c/sup\u003e\u003c/a\u003e See Supplementary Materials for the full description of the methodology.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5839757/v1/0611c4357f6ced4a1bffb8c7.png"},{"id":74100135,"identity":"626a80b9-17fb-46d0-8db6-2b623f176040","added_by":"auto","created_at":"2025-01-17 18:11:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1063431,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5839757/v1/a100f8eb-e42f-474d-b55c-f94e19e1c597.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eFacing involuntary immobility: Prioritizing the marginalized in climate and disaster risk policy\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThere is increasing recognition in academia and policy circles that the real risk of climate change to the world\u0026rsquo;s most vulnerable populations is less likely to be mass migration, but rather involuntary immobility - whereby people who would like to move cannot do so because of constraints imposed both by climate stressors and extreme poverty.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e From urban slums and refugee camps to prisons and conflict zones, millions of people worldwide face immense challenges to relocate when impacted by natural hazards.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e For these potentially immobile populations, impacts from climate change not only exacerbate pre-existing environmental and habitability challenges, but also amplify the structural socioeconomic, cultural, and political challenges they face. While socioeconomically, culturally, and politically marginalized populations worldwide are generally at elevated risk to natural hazards compared to the broader population, immobile populations are underrepresented and understudied in the context of policy and research concerned with evolving and worsening climate change impacts.\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTo date, most human mobility research focuses on migration, displacement, and refugee flows, excluding those populations unable or unwilling to move when faced with extreme weather or declining habitability. This omission is tied to factors relating to the lack of political representation and/or marginalization of populations in situations of immobility. Furthermore, unlike migration or displacement, inherent difficulty arises from observing cases that are essentially characterized by a lack of distinct empirical manifestations, data and surveys, enabling the identification of involuntary immobile populations. However, involuntary immobility is much more than a data concern or a gap in the literature. It is also a lens through which action toward climate resilience can and must be structured and leveraged.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn this work, we recapitulate the scientific logic behind involuntary immobility, focusing on the challenges induced by extreme weather and climate change that involuntary immobile populations face today. We highlight barriers that must be overcome for climate action to reach the most vulnerable populations. To do so, we showcase the diverse drivers of climate immobilities through a set of case studies. We conclude with policy implications in view of implementing pragmatic solutions to alleviate vulnerabilities to natural hazards faced by involuntarily immobile populations.\u003c/p\u003e \u003cp\u003eLeveraging climate action through an involuntary immobility lens requires an understanding of the multi-scale political, socioeconomic, and environmental contextual structures constraining the ability of individuals and households to move out of areas at immediate risk of disasters or that are experiencing inexorable declines in habitability.\u003csup\u003e\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Immobile populations are at risk of suffering severe damage resulting from individual extreme weather events, and compound, and complex disasters.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Given these complexities, incorrect or incomplete framing can exacerbate the maladaptive conditions that such efforts seek to address.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Outlining involuntary human immobility as a framework for climate action is therefore crucial.\u003c/p\u003e \u003cp\u003eUnderstanding involuntary immobility is not merely an academic exercise but a key lens through which the efficacy of climate adaptation initiatives can be evaluated and improved. By integrating the concept of involuntary immobility into our analysis, we contribute to a more nuanced understanding of how climate change disproportionately affects the most vulnerable populations. This understanding is essential for recognizing the barriers to mobility, leading to involuntary immobility, faced by certain populations.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e It further illuminates the gaps in current climate adaptation strategies, highlighting the need for appropriately designed policies that address these unique challenges. Consequently, our focus on involuntary immobility aims to bridge these gaps, advocating for a holistic approach to climate action that prioritizes the protection and empowerment of all individuals, particularly those who are most at risk. By doing so, we seek to align our research with worldwide efforts to address climate and environmental related risks, underscoring the imperative for policies that are both scientifically sound and socially just.\u003c/p\u003e"},{"header":"Immobility as a scientific concept","content":"\u003cp\u003eMobility outcomes can be structured along the two dimensions of the aspirations-capabilities framework\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, where aspirations refer to a person’s desire to move from their current location, and capabilities capture whether they are indeed able to undertake a move. Those who wish to and can move are usually able to realize their move (voluntary mobility), whereas those who want to, but cannot move can be characterized as trapped (involuntary immobility). Among those who do \u003cem\u003enot\u003c/em\u003e want to move, a conceptual distinction is possible between those who could move but don’t (voluntary immobility) and those who do not have the capability to move (acquiescent immobility). Distinguishing the latter two categories is empirically challenging.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFor the purpose of this piece, involuntary immobility pertains to situations in which individuals, households, or communities face risks to their physical, psychological, and economic well-being due to exposure to natural hazards. They are either unable to leave their residence despite a desire to do so, or perceive that any such attempt would be unsuccessful or ineffective.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e Immobility occurs across a spectrum ranging from complete immobility on one end to unconstrained mobility on the other, rather than as a sharp delineation between mobile and immobile populations.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e A person’s or population’s position on this spectrum can fluctuate over time. The ability to anticipate such changes increases the likelihood of developing policies and services to support potentially immobile populations and mitigate the conditions driving such a shift.\u003c/p\u003e \u003cp\u003eClimate change impacts are changing many dimensions of involuntary immobility. In this context, involuntary immobility is characterized by the inability of individuals or populations to relocate in response to considerable threats from extreme weather events, environmental degradation, or other climate-related impacts.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e This immobility is not a voluntary condition but is instead the result of a variety of intersecting factors.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e These include, but are not limited to, economic, political, legal, social, and cultural obstacles, which collectively inhibit their movement and ability to find shelter in perceived safer areas. At the same time, we recognize that involuntary immobility in the face of a natural hazard is a complex phenomenon, susceptible to substantial variation across contexts. Indeed, involuntary immobility can occur at different time scales, when facing an immediate threat of extreme weather, in the aftermath of a disaster, and over a longer time horizon.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e A person’s ability to move across long distances may be substantially curtailed, though she might remain locally mobile and able to find immediate, but not durable, shelter in their villages/communities.\u003c/p\u003e \u003cp\u003eEarly uses of the notion of involuntary immobility in the literature primarily referred to economic and social barriers of migration.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e Climatic and environmental factors were not explicitly investigated until the past two decades.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e A growing body of literature and data has quantified aspects of who is most likely to be mobile and identified, by extension, who is potentially immobile for a given natural hazard.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Even so, populations at risk of involuntary immobility in the face of climate change impacts – as a result of economic, social and political constraints – remain structurally hidden from vulnerability assessments.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e This is particularly true for populations facing physical constraints to their mobility, such as prisoners or undocumented migrants.\u003c/p\u003e \n\n \n\n "},{"header":"Outlook and policy challenges for developing effective systems","content":"\u003cp\u003eWhile a more nuanced representation of involuntary immobility has led to more appropriate governance discourse\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e, gaps remain in the development of policy and services tailored specifically for immobile populations. For policy and services intending to address climate-related risk, the outputs will be incomplete at best, and detrimental at worst, if the needs of populations facing immobility are not central. On the one hand, political will is required to enhance the development of climate services and support for disaster risk reduction activities - and adaptation programming more broadly. On the other hand, such support requires conducting a systematic review of affected communities and their ability to mitigate the impact of natural hazards and climate change, adapt to these in situ or relocate, with specific attention to those communities that may be invisible or otherwise marginalized. Therefore, policies need to be grounded in the local contexts and involve a participatory process, allowing multiple communities and societal actors to co-produce usable knowledge for decision-making.\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eFactors that incentivize people to stay in their place of residence can include hard-to-quantify connections and networks - such as solidarity and support systems. Similar to property loss, these incentives are often lost if relocated.\u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e Losses and damages from climate change can make it difficult to re-establish life and community, particularly without community support. Increasingly, studies are acknowledging a broader perspective related to the choice to stay\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e,\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e or the choice to leave, leading to more appropriate policy responses.\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eWhile explicitly including immobile populations within pre-disaster, early warning, and anticipatory action programming remains challenging, lack of data itself continues to be a major challenge in including immobile population in policy and risk planning.\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e We argue that a lack of detailed population data on marginalized populations should not limit governments and institutions from providing support and striving for policy and disaster planning that include immobile populations. Moreover, the availability and accessibility of appropriate and sufficient data does not imply that it can be integrated within policy and services without close attention to the translation processes. There is also the risk that inclusion of such data could lead to prioritization of some populations over others.\u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e,\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eMuch of the existing literature on vulnerability draws on variables from census data to identify marginalized populations and other communities at risk of immobility in the face of climate change and disasters. However, key immobile groups, such as inmates or unhoused populations, are likely missed by census data.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e In addition, disagreement across some population datasets could create differences in policy implementation, including but not limited to prioritization of resources for climate change adaptation and activation of early warning systems.\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e Ethical considerations need to involve an assessment of data quality to ensure that the most vulnerable people are not left out of policy responses and that action prioritizes those most in need. Furthermore, high resolution data are needed in order for community needs, justice, and equity to be met.\u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e,\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e Investing in data-collection processes that are co-produced with people facing an immobility risk together with decision makers is a key step to outlining and addressing these data challenges. Then, the integration, translation and decision-making steps need to reflect both the data from the co-production process, as well as other lessons learned from this process.\u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eIn our view, centering and including the populations facing involuntary immobility in climate and disaster risk analysis is the only way to ensure that appropriate attention, resources and action are devoted to support them. While more research is needed to understand the natural hazard elements, further analysis of risk perception, governance schemes, communication is also critical to ensure that the experiences of populations are integrated within research - to in turn increase the likelihood that the research outcomes are actionable. Ultimately, we call for closer attention to involuntarily immobility across research, policy and practice. This requires urgent action to develop a collaborative effort to that aim, as without doing so, the call to support the involuntary immobile would be incomplete at best and might lead to unanticipated consequences at worst.\u003c/p\u003e"},{"header":"Drivers and processes of involuntary immobility","content":"\u003cp\u003eFor both short and long-term immobility, a multicausality conceptual framework approach has been applied.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e However, further attention to spatiotemporal scales is needed to account for current direct and indirect drivers and those likely to be at play in the immediate-term future. As an initial step in crafting a new appropriately detailed framework, a set of key mobility barriers are described here.\u003c/p\u003e\u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eEconomic and physical barriers\u003c/span\u003e: The classical perspective on migration has long documented that economic considerations are important constraints to migration.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e The upfront costs a migrant must pay to cover travel expenses exert a significant constraint on the ability to travel, particularly over long-distances and through regions with complex geographic and socioeconomic deterrents.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e Financial barriers limit the ability of lower-income households to pursue migration, also across shorter distances.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e These barriers are likely to be particularly important when would-be migrants are forced to travel along irregular migration routes, due to a lack of access to visas or other authorizations, often relying on costly human smugglers.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e In addition, current economic conditions and perceptions of what future economic conditions will be, can influence long-term mobility options and how populations perceive immobility.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eIncreasingly, heat exposure (see also Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) plays a role in limiting mobility in the short-term. For example, economically deprived districts are harbingers of immobility when faced with heat stress during the growing season in Zambia.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e Under future sea level change (SLC) scenarios, occurrences and experiences of flooding and associated damages from SLC are found to contribute to increases in migration toward coastal areas in Bangladesh by the end of the century. Coastal populations’ ability to move is constrained by access to cash and the relative affordability of alternative options and livelihoods to migration.\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eFinancial constraints to migration can also be understood in the context of livelihood choices for individuals and households. Livelihood choices of smallholder farmers in Nepal show how international migration can play out as a higher-cost, higher-reward strategy as compared to other, in situ options. Reduced agricultural income limits the ability of households with lower access to capital to choose migration as a livelihood strategy by mid-century.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003ePhysical infrastructure barriers to mobility have manifested in the effects of extreme weather events on telecommunications and transportation, particularly in areas with already relatively isolated or remote communities such as those in island states and in countries with complex topography. As an example of the latter, recurrent flooding in Tajikistan’s Bartang Valley has impacted infrastructural connectivity and human mobility. Road closures and repairs add to the mix of physical barriers to immobility. High car operating costs impede the local population’s mobility. Telecommunication can mitigate situations of physical immobility. Phone calls provide an opportunity for immobile populations to stay connected with their social network, thereby limiting feelings of isolation and depression. Yet, the instability of the telecommunication network substantially constrains the ability of residents of the valley to move around.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eWhile populations of small-island states can seek shelter in other areas of the island they inhabit, movement is constrained to a degree as islands present unique geographic challenges. In addition, many small-island states have limited and expensive transportation to travel off island, especially given economic barriers. As island roads are often constrained by topography, and thus are positioned close to flatter areas along coastline or other water bodies, there is an increased likelihood of evacuations being hampered by issues related to inundation, landslides, and other disruptions of infrastructure that affect road access.\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e In the ‘large-island’ case of the Japanese Tohoku earthquake, tsunami, and nuclear accident at Fukushima, evacuation was made difficult or impossible at scale in the short-term due to damage to physical infrastructure.\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003ch3\u003ePolitical, legal, and bureaucratic barriers:\u003c/h3\u003e\u003cp\u003eInternational borders and restrictions on internal mobility can impose long-term immobility in the face of a natural hazard. In the face of increasing natural hazards and risks from SLC with additional warming, island populations lack legal mechanisms enabling mobility leaving them unable to move.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e Similarly, refugees living in host countries with restrictive asylum policies may be physically confined to a camp or specific areas of a country with little ability to migrate post-hazard. These policy restrictions to mobility compound the extreme poverty and resource deprivation faced by many refugees and the dwindling availability of humanitarian aid, the delivery of which is itself subject to political and climate disruptions.\u003c/p\u003e\u003cp\u003eForced to flee Myanmar after a campaign of persecution, the Rohingya refugee population in Bangladesh have faced significant political and legal barriers to mobility within the country.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e In addition, Bangladesh has periodically resorted to forced relocation to keep refugees in specific areas of the country, generally along the border with Myanmar.\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e Most refugees in the country reside in the Cox’s Bazar district where refugee settlements are among the most densely populated areas in the world (e.g. 40,000 refugees per square kilometer in the Kutupalong Refugee Camp).\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e Many camps face high levels of landslide exposure, while others face high risk of coastal and inland flooding.\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e Climate change impacts could even further diminish migration opportunities, while making the consequences of immobility even more catastrophic.\u003c/p\u003e\u003cp\u003eRefugees are not the only group that face barriers to movements due to restrictions on entry. Many migrants find themselves stuck in transit countries and forced to survive on marginal lands with evidence from North Africa and Mexico indicating that stranded migrants are particularly vulnerable to flooding.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e Because of language and cultural barriers, as well as limited access to humanitarian assistance, these populations face particularly high exposure to natural hazards. By way of example, the Covid-19 pandemic substantially worsened the situation for many transit migrants in Mexico, with many left stranded after the enactment of US Title 42 ostensibly in view of limiting the spread of the disease. These migrants faced significant natural hazard in the place of transit.\u003csup\u003e\u003cspan additionalcitationids=\"CR52\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e–\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eEven under optimistic climate projections, climate change impacts will continue to significantly harm involuntary immobile populations if substantial shifts in policy discourse and targeted investment in adaptation are not enacted. As an illustration, nearly all refugee camps will face an unprecedented rise in hazardous heat stress (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). By 2050, the hottest fifteen camps may experience nearly 200 or more days per year of hazardous heat stress under middle-of-the-road climate projections (SSP 245). Should these locations continue to house refugees with little investment in adaptations like air conditioning, such heat stress is likely to drastically harm health and well-being among refugees, with recent evidence suggesting a precipitous rise in mortality.\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e Heat stress is just one of the multitude of natural hazards projected to worsen for involuntary immobile groups worldwide.\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eSocial and cultural barriers\u003c/span\u003e: Indigenous communities, as well as residents in informal or deprived areas of cities are systematically predisposed to experience a lack of services and financial opportunities, in addition to social and cultural barriers.\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e These dynamics exist both in high-income countries and in lower- and middle-income countries. Spatial patterns are documented in the environmental and climate justice literature in which marginalized populations are located in risky places, even in the most developed countries.\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003ePacific island communities are faced with displacement that breaks community connections, including losses and disconnection from culture, language, and religious ties. The ability to migrate can be limited by bureaucratic barriers, as well as attachment to their lands.\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e,\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e In Aotearoa (New Zealand), indigenous Māori communities face potential relocation of coastal \u003cem\u003emarae\u003c/em\u003e, communal meetings grounds of cultural and religious significance (that can include a meeting hall, place of prayer, dinner facilities, as well as preschool and other communal building) due to risks stemming from recurrent flooding, soil erosion and SLC. Yet, the lack of land availability and land ownership restrictions resulting from colonial legacies, contribute to hurdles in relocating \u003cem\u003emarae\u003c/em\u003e to safer places; without endangering the survival of local indigenous communities by severing its symbolic connection to a place.\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eUnhoused populations (UPs) face exposure to natural hazards without sufficiently reliable options to avoid risk. While some UPs, such as those living in shelters, may be able to move about a defined area, the extent to which they are able to find effective refuge from threats remains limited in many situations. UPs in New York City face economic, political, legal, physical or mental barriers that limit their ability to find shelter when facing floods, storms and heat waves. Heat-related mortality among UPs is projected to double, while a paucity of data exists for similar analyses for other natural hazards.\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e As a consequence, UPs are likely to disproportionately suffer from the impact of a natural hazard, relative to populations having access to housing, and without their specific needs accounted for. UPs in New York City face higher levels of respiratory conditions and temperature exposure due to lack of filtration and air conditioning as a result of living on the streets.\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e While there may be poor air quality and extreme temperature warnings, UPs are often incapable of relocating to safer locations despite underlying conditions that make them more susceptible.\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eParticipatory action data collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe participatory action data collection combined 3 primary phases: (i) a World Cafe session, (ii) a group deliberation and (iii) the development of a synthesis manuscript co-authored by session participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWorld Cafe structure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe used a World Cafe approach as a participatory action research technique to guide qualitative data collection. The World Cafe method has been applied to leverage knowledge on complex topics and is a well-vetted technique from the field of applied decision science.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e78\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e The World Cafe event was held in June 2023 with 53 participants during the 2023 Managed Retreat Conference (Columbia University). This World Cafe aimed to highlight immobility in the context of environmental, political and social elements and uncover underlying themes of involuntary immobility.\u003c/p\u003e\n\u003cp\u003eThe World Cafe session consisted of three discussion rounds on (i) driver and impacts, (ii) challenges and obstacles, (iii) policy implications and guardrails. Each table consisted of 8\u0026ndash;9 participants with one facilitator at each table, serving a dual role: guiding the discussion and taking notes. After each round, participants were encouraged to change tables.\u003c/p\u003e\n\u003cp\u003eThe second stage of the participatory action data collection was a group deliberation. The deliberation combined a participatory summary of the World Cafe session through facilitators and a discussion around unique learnings (\u003cem\u003eWhat surprised you most about today\u0026rsquo;s discussions?\u003c/em\u003e) as well as points not raised during the World Cafe (\u003cem\u003eWhat was missing from the discussions today?\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eOn the basis of notes of the World Cafe session and the group deliberation, anonymous transcripts were prepared with points raised and then summarized. The summarized transcripts from the World Cafe rounds were analyzed by L.T., A.K. and F.C. through qualitative content analysis with support from C.H. and C.T. All co-authors contributed to the writing of this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRefugee Heat Stress Observations and Projections\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRefugee camp locational data are based on publicly available \u0026ldquo;People of Concern\u0026rdquo; data from UNHCR\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e accessed on 21 February 2024. We filtered the UNHCR dataset to 1344 refugee population locations across spontaneous locations (931), planned settlements (384), unplanned settlements (5), and dispersed locations (24). We exclude refugee population locations in Lebanon, which are recorded differently than other countries, and exclude locations of asylum-seeking populations, internally displaced persons (IDPs), returnees, stateless populations, and those classified as unknown.\u003c/p\u003e\n\u003cp\u003eWe use the Climate Hazards Center Coupled Model Intercomparison Project Phase 6 climate projection dataset (CHC-CMIP6) to estimate historical (2007\u0026ndash;2016) and future (2050) average annual heat stress at the location of all refugee camps worldwide. Available at 5-km globally, CHC-CMIP6 is among the highest resolution climate projections specifically designed to estimate future heat stress in data sparse refugee-hosting regions, like the African Sahel.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eA highly accurate 5-km blended satellite and station derived daily maximum air temperature record \u0026ndash; CHIRTS-daily\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e \u0026ndash; and down-scaled relative humidity estimates from ERA5 climate reanalysis form the foundation of the CHC-CMIP6 daily shaded daily maximum wet bulb globe temperature (WBGTmax) observational record. Next, coarse-grained (100\u0026ndash;250 km) CMIP6 ensembles for 245 and SSP 585 scenarios are used to develop high resolution (0.05\u0026deg;) 2030 and 2050 \u0026ldquo;delta\u0026rdquo; fields, which is the difference between CMIP6 multi-model ensemble-based changes between 1983\u0026ndash;2016 and 2025\u0026ndash;2035 and 2045\u0026ndash;2055. The delta fields are then used to perturb the WBGTmax observational record to derive the CHC-CMIP6 SSP245 and SSP 585 2030 and 2050 projections. We use the SSP245 projections for 2050, derived from the CHC-CMIP6 dataset because of its high spatial resolution that better captures local climate heterogeneity compared to the coarse-grained CMIP6 projections. For a full description of CHC-CMIP6.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eTo measure heat stress at refugee camp locations, we first estimate the average annual number of days per year WBGTmax exceeded 30\u0026deg;C from 2007\u0026ndash;2016 using the CHC-CMIP6 observational record. We then estimate future heat stress as the average annual number of days per year WBGTmax exceeded 30\u0026deg;C from 2007\u0026ndash;2016 under a 2050 climate following SSP 245. While we fully recognize that a plethora of heat stress metrics exist (Baldwin \u003cem\u003eet al\u003c/em\u003e 2023), we estimate heat stress as the number of days where WBGTmax exceeded 30\u0026deg;C because it is the International Organization for Standardization (ISO) criteria for occupational risk to heat stress for acclimated people under moderate metabolic rates (65\u0026ndash;130 Wm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e). This ISO criteria is well-established and commonly used in the heat-health literature.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e73\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e83\u003c/span\u003e\u003c/sup\u003e For context, monthly average WBGT of 30\u0026deg;C has been associated with increased mortality rates among vulnerable populations.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003e The authors wish to thank participants of the 2023 Columbia University Managed Retreat Conference World Cafe on Climate Change Implications for Conflict Zones, Displaced Persons, Refugees, Slums Residents, and Other Involuntary Immobile Populations. We also thank Elizabeth Fussell for comments on an earlier version of this manuscript. C.T. was supported by the Air Force Office of Scientific Research grant no. FA9550-23-1-0684. J.V.D.H. was supported by the NASA Land Cover/Land Use Change Program grant no. 80NSSC23K0528.\u003c/p\u003e\u003ch2\u003eData Availability Statement\u003c/h2\u003e \u003cp\u003eRefugee camp locations are available in the \u0026ldquo;UNHCR People of Concern\u0026rdquo; dataset \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://data.unhcr.org/en/geoservices/\u003c/span\u003e\u003cspan address=\"https://data.unhcr.org/en/geoservices/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. The Climate Hazards Center Coupled Model Intercomparison Project Phase 6 climate projection dataset (CHC-CMIP6) is available \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.21424/R47H0M\u003c/span\u003e\u003cspan address=\"10.21424/R47H0M\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Code to reproduce Fig.\u0026nbsp;1 is publicly available on GitHub [URL provided upon publication].\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCundill G et al (2021) Toward a climate mobilities research agenda: Intersectionality, immobility, and policy responses. Glob Environ Change 69:102315\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlack R et al (2011) The effect of environmental change on human migration. 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Appl Physiol Nutr Metab 41:S148\u0026ndash;S164\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"climate change, migration, heat, immobility, health","lastPublishedDoi":"10.21203/rs.3.rs-5839757/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5839757/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGlobally, populations are increasingly located in areas at high risk of frequent, extreme weather events. Some exposed populations have the ability to move to safer places; others are unable to get out of harm\u0026rsquo;s way. The climate risks facing these involuntary immobile populations are not often addressed by local and national authorities, despite increasing recognition by international development agencies and humanitarian actors. Here we discuss when and how climate and extreme weather events lead to involuntary immobility by considering the influence of political, socioeconomic, and environmental factors. Addressing barriers in policy and disaster planning, early warning systems and anticipatory action could be tailored to support involuntarily immobile communities. While policy and planning should be data-informed, lack of appropriate data quality should not limit governments and institutions from taking action. Immobility needs to be aligned with the broader sustainable development objectives which entail climate justice and orderly migration.\u003c/p\u003e","manuscriptTitle":"Facing involuntary immobility: Prioritizing the marginalized in climate and disaster risk policy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-17 17:47:18","doi":"10.21203/rs.3.rs-5839757/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f68171a5-3c75-470f-9050-26b68a9db21a","owner":[],"postedDate":"January 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":42947011,"name":"Climate Analysis and Modeling"},{"id":42947012,"name":"Environmental Policy"}],"tags":[],"updatedAt":"2025-01-17T17:47:18+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-17 17:47:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5839757","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5839757","identity":"rs-5839757","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}