Addiction is one of the most stigmatized public health issues, which serves to silence individuals who need help. Despite emerging global interest in workplace mental health and addiction, scholarship examining addiction among university faculty members (FMs) is lacking, particularly in a Canadian context. Using a Communication Privacy Management (CPM) framework and semi-structured interviews with key informants , this qualitative study aimed to answer the following research questions: (1) What is the experience of key informants who encounter FM addiction? (2) How may addiction stigma affect FM disclosure and help-seeking? and (3) What may help reduce addiction stigma for FMs? Thematic analysis was used to identify three main themes: (1) Disclosure was rare, and most often involved alcohol; (2) Addiction stigma and non-disclosure were reported to be affected by university alcohol and productivity cultures, faculty type, and gender; (3) Reducing addiction stigma may involve peer support, vulnerable leadership , and non-discriminatory protective policies. This study offers novel insights into how addiction stigma may operate for FMs in relation to university-specific norms , and outlines some recommendations for creating more recovery-friendly campuses. This exploratory qualitative study is inspired by my (first author) complicated experience disclosing an addiction-recovery identity in an academic context. Specifically, in a recent article , I exposBoth as a sober PhD student and junior faculty member (FM), academia was one of the last places where I felt safe disclosing. Warned by more senior academics that disclosure may negatively affect my reputation and job prospects, for the first five years of my recovery, I told very few people. As an addiction researcher and social work educator, the constant “calculus of disclosure”  (p. 688)On the one hand, the invisibility he reported was not surprising given the extent of public and self-stigma associated with addiction, and its shame-fueled silencing effect . On the In recognizing that research focusing on FMs direct experience of disclosing addiction is sorely needed ,9, as a Definitional clarification: This study is centering on addiction, and not substance use in general. Addiction is defined as the “problematic use of a substance, with harms ranging from mild  to severe ”  (n.p.). The relationship between problematic substance use and lost productivity is well documented in the workplace literature . While nWorkplace stress and norms  are associated with a higher incidence of problematic substance use . FurtherDespite high rates of addiction, a minority of people struggling with addiction seek help, often because of stigma . For insAccording to Goffman , stigma Avery and Avery  (p. 2) dResearch has found that addiction is more heavily stigmatized than other mental health issues  ,28. For When prejudices are internalized, people with addiction experience self-stigma, which is characterized by negative feelings and perceptions of self . FurtherThe concept of disclosure is inextricably tied to stigma, as it implies a need for concealment or a secret life . DisclosCommunication Privacy Management (CPM) Theory  is a useCPM has been a useful framework to examine how individuals with varied stigmatized identities manage disclosure and privacy. For example, Yep  exploredWhat is the experience of deans and CMHPs who encounter FM addiction?How may addiction stigma affect FM disclosure and help-seeking?What may help reduce addiction stigma for FMs?Overall, while research has focused on disclosure dialectics from the perspective of individuals with stigmatized identities, including non-drinkers in university and workplace contexts, scant research has focused on disclosure encounters with FMs with addiction. Redressing this gap in the literature, using a CPM framework and semi-structured interviews with key informants , this exploratory qualitative study aimed to answer the following research questions:By capturing key informants’ perspectives, this study offers novel insights into how addiction stigma may operate in academia and outlines some recommendations and next steps that may help reduce addiction stigma for FMs.An exploratory qualitative design was used, where the aim is not to generalize but to provide a rich, nuanced understanding of a particular human experience or phenomenon ,44. QualRecruitment: Sixteen faculty deans and eight CMHPs from one Western Canadian university were purposefully sampled through existing community connections or the university website. All identified key informants were sent a detailed letter of invitation via email. If the individual agreed to participate in the study, an interview was scheduled at a mutually convenient time and place. All were required to be in their role for at least one year. Six of the deans and two CMHPs declined the invitation to be interviewed, the most common reason being that they felt they would not be able to properly address the topic.Sixteen in-depth interviews were conducted privately with 10 deans and 6 CMHPs . Interviews lasted from 30 to 60 min, averaging 40 min in length. A semi-structured approach was used to guide the discussion (included below). The interviews were conducted by one of the three authors. All interviews were done in person, except for one via telephone. The interview guide covered three main discussion areas: (1) understanding encounters with FM addiction; (2) perceptions of the risk of FM disclosure and help-seeking; and (3) recommendations for additional supports see .Ethics approval was obtained from the University Institutional Review Board, and written informed consent was provided by all key informants. The consent form outlined the process for ensuring confidentiality and protecting the right of informants to withdraw at any time during the study. Transcripts were carefully reviewed and de-identified to protect anonymity. No monetary compensation was provided to study participants.All interviews were audio-recorded, then transcribed verbatim by a research assistant using a word processor. Braun and Clarke’s  5-Phase Phase 1 of Braun and Clark’s method of analysis begins with data familiarization. The first author and the research assistant listened to the audio recordings and read all the transcripts (transcribed into a Microsoft Word file). For Phase 2 , excerpts from transcripts were cut-and-pasted, using a Microsoft Excel spreadsheet, into broad preliminary descriptive categories that matched the areas probed in the interview guide: (1) types of drugs used ; (2) negative consequences descriptors ; (3) mentions of university-specific culture affecting stigma , as well as words or phrases describing “vulnerability” . (4) demographics identified as affecting addiction stigma and (non) disclosure ; and (5) recommendations to reduce addiction stigma . In Phase 3, patterns were identified by the three authors, who discussed variations in the data, moving back and forth within and between cases. Of note, some of the patterns became evident based on frequency , while others came directly from codes . This approach is consistent with thematic analysis, as outliers can be significant and become a theme, when they provide further insight into the research questions at hand . In Phase 4, the three authors discussed and resolved discrepancies in how the codes would be organized into specific themes . Finally, in Phase 5 (reviewing themes), three main themes were identified: (1) Disclosure was rare, and most often involved alcohol; (2) Addiction stigma and non-disclosure were reinforced by university-based alcohol and productivity cultures, faculty type, and gender; (3) Reducing addiction stigma may involve peer support, vulnerable leadership, and non-discriminatory protective policies.The following section describes the three themes with illustrative quotes drawn from the transcripts and labeled with the identification number. The deans represented 10 faculties ranging in size from approximately 30 to 400 faculty members. Most had more than 20 years of academic service . The CMHPs included staff wellness, counsellor, and human resources roles. Of the 16 key informants, five identified as women and the remainder identified as men. The majority were white. The team limited the demographic information collected, as the participants were recruited from a small pool of eligible interviewees, and we wanted to ensure their identities were protected as much as possible. Theme 1.Addiction disclosure was rare, and most often involved alcohol.Although all the key informants expressed openness to being approached by FMs with a substance use problem, only two deans and one CMHP reported experiencing a direct disclosure and all three involved alcohol. As one dean expressed, this was surprising, given his length of time in service combined with awareness of the prevalence of addiction in broader society:I’ve had one conversation with an FM here at the university. That’s mind-boggling to me, and it suggests that we have a huge issue with stigma and a fear, perhaps, of going to others and having an open conversation about these issues and how to get support. For me that’s particularly troubling, because when we look at our broader community, we know that these are massive issues, and it would be naïve to think that they do not happen with the same intensity and rate that we see elsewhere in the community.(Dean 5)The majority of the deans became aware of FM problematic substance use through a second party or other indirect means, including concerns expressed by students/colleagues, disruptions in work performance, erratic behavior, and legal consequences , as the following two quotes illustrate: The person was becoming more disconnected within the department, and there were concerns from colleagues and the department head with respect to literally finding the person at the pub, in the afternoons, and not showing as much care around things like personal grooming.(Dean 2)He was a very smart person, uh … you know … [a] person of integrity and good work habits. However, then for periods he would just go—this isn’t a very precise term—but go off-kilter. His attendance would be spotty, sloppiness would be apparent in his work.(Dean 4)Despite few FMs disclosing to their deans directly, when reflecting on their past experiences, several deans noticed signs of addiction, as this quote highlights:In retrospect, I’m just hypothesizing, but knowing about the alcohol issues that this individual had, it makes sense as to why he was never able to make morning meetings, was always late, and didn’t answer e-mail. He wasn’t just the absent-minded professor, there was actually something going on there.(Dean 7)Another dean reported being aware of one FM who had a history of alcohol addiction but did not see it as an issue because the FM was performing and meeting targets: There was a prof who was an alcoholic. I only knew him professionally, but some of his colleagues were complaining that they could smell booze on him. Then I noticed his erratic behavior, and then he behaved very badly with some students,so I was mad at him. He ended up dying shortly after. But before the outburst with the students, he was doing his job, he handled a lot of teaching and students and generally was—for most of the time I’ve known him (which was at least 25 years)—I guess, he was a pretty high performing FM.(Dean 10)In contrast, almost all the deans had direct encounters with FMs disclosing physical or mental health issues . Several reported that the non-disclosure may be associated with the assumption that addiction is a personal failing and/or choice, and a weakness as the following three quotes highlight:My gut feeling is that [most people think] depression or anxiety-related disorders are not the fault of the individual. And they might assume, they could assume, that an addiction could be personality-related or just [someone] lacking self-control. Right? And so, I would say the risk of disclosing a substance abuse issue is probably higher than some of the medical, the well-known medical conditions that you might disclose from a mental health perspective.(Dean 3)There’s a stigma of shame with addiction because it’s perceived as negative coping, as opposed to something like a bipolar diagnosis, or anxiety. I think, by and large, they’re seen differently, even though we know it’s a chronic issue like any other chronic disease, but there’s the social stigma and shame attached. It doesn’t typically come up until there’s a negative consequence, right? I think that the attached or collateral shame around the negative consequence also contributes to it. I mean, so for instance if you had a diabetic who had a significant drop in their blood sugar and lost consciousness in the hallway, you know there’s not going to be the same perception of shame, as opposed to someone binge drinking and passing out in the classroom.(Dean 9)I think that there is more sympathy and understanding for physical impediments and conditions and ailments, things that you can see. For things that you can’t see, I think people tend to blame the victim, or blame the patient. People expect you to just “get over it.” If you can’t, you are viewed as weak.(Dean 6)Theme 2.Addiction stigma and non-disclosure were reported to be affected by university alcohol and productivity cultures, faculty type, and gender.Some of the key informants spoke to the pervasiveness of alcohol culture on campus. They described how drinking was not only normalized but encouraged among students, and also prevalent at faculty events . Although some key informants mentioned that alcohol culture has shifted away from the days of “boozy faculty lounges,” alcohol-centric activities such as “pub Fridays” are still common, as one dean suggested:There, there is a culture of alcohol in our faculty, it really isn’t nearly as prevalent as it was 20 or 30 years ago but there’s a few groups that I am aware of who head to the pub together on a Friday afternoon.(Dean 2)Other key informants mentioned that alcohol culture could reinforce stigma, thus preventing disclosure, as the following quotes highlight:I think there are high stakes of disclosing a substance use disorder amongst faculty. That said, we live also in a culture where we make jokes about wine to help us at the end of the day, and you know, there’s certain parts of the culture I think that allow for it like, “Oh, let’s go get a drink!”, there’s a certain glam in the culture, where drinking socially is good and then we don’t kind of talk about the other stuff.(CMHP 5)Several key informants perceived that the high level of non-disclosure related the high-pressure, competitive nature of academia, where any sign of vulnerability or weakness is strongly discouraged, as the following three quotes highlight: FMs are afraid to come out because of the fear of how it would be perceived. That an adult, somebody with a PhD, cannot handle day-to-day stress, that they would be considered weak, which may prevent [them from] getting a career opportunity.(Dean 1)I think that’s a big part of non-disclosure; it’s recognition, it’s competitiveness, its reputation.(Dean 7)FMs may not want to disclose addiction because [doing so] is voluntarily disclosing a potential weakness that, in a competitive world, could be a disadvantage. And it starts to color how people see your performance.(Dean 6)Along similar lines, a CMHP pointed out that the culture of academia and specifically the emphasis on productivity and high achievement tends to mask potential issues related to addiction: I haven’t encountered a single FM with an addiction. Even though it’s 1 in 10 people, right? You know it’s because FMs are fairly high functioning. If you can get your papers out there and get grants then, you know, people don’t really care about the rest.(CMHP 5)Further, some of the CMHPs identified that staff tend to reach out for help for mental health issues more often than FMs because they do not have the added pressures associated with status and reputation, as the following quote illustrates: I am aware of an FM with a substance issue but have not been approached by the person. It’s because of academic reputation. I hear more about people in supporting staff, but I don’t hear about FMs.(CMHP 3)Disclosure risks were also identified as being affected by the faculty the FM belonged to . For instance, in the professional faculties , disclosing could lead to an FM being deemed unfit for practice and potentially losing his or her professional license. However, one dean described how being “fit to practice” in academia is not as clear as it is in a clinical setting where there is a duty to report problematic substance use:How intrusive can you be without being overly intrusive? If you try to intervene, they [the FM] might say, “Well it’s none of your business, and you’re harassing or bullying me,” or when you’re really coming out of a place of concern, and again [worry about the FM’s] fitness to practice, it’s more opaque in an academic institution than when you’re in [clinical] practice.(Dean 7)Some of the deans reported specific risks associated with the nature of their work, such as risk factors associated with intoxication and being in a laboratory setting as Dean 7 pointed out: There’s another piece, though, that is really important to think about: there are a lot of things that university professors do that could kill you. Right? And so, when we compare it to, you know, if you’re human resources staff, if you come into work drunk, [at least] you’re not going to blow up the lab. One of the key informants reported that it was riskier for women to experience addiction and seek help than it was for their male colleagues, especially if they are pre-tenure, as the following quote highlights: There are different ways we describe male substance abuse versus female substance abuse. For women, everything is a strike against them when it comes to tenure, so they are ultra-careful and have to be more perfect than the men.(Dean 7)Theme 3.Reducing stigma through peer support, vulnerable leadership, and non-discriminatory protective policies.All key informants highlighted the major gap in services for FMs, commenting that most target students. For instance, some of the key informants pointed out that there is a harm reduction support advisor specific for students, there used to be a student-led Alcoholics Anonymous (AA) group, and additional student peer-support groups led by the campus faith and spirituality center. Several key informants suggested that a promising way forward would be to offer university-based peer-support that is exclusive to academics as the following three quotes highlight: Peer support is certainly something on the student side that we’re keeping an eye on. I’ve talked about it for staff and faculty, but it’s not quite got that same sort of accessibility, I think, for staff in faculty, but it is something in terms of the Campus Mental Health Strategy that we’re starting to have conversations about.(CMHP 5)What’s missing is a peer model where somebody who’s been through addiction themselves offers their time, like a spiritual director would. People go to therapy, counselling, psychology, psychiatry, or they go to an addiction treatment center. I think peer counselling is what’s missing.(CMHP 4)I think it would be interesting if there were a recovery meeting, a 12-step program with a cohort of other academics. It would be doubly supportive because you’re working through your addiction, but you also have this shared knowledge of what the academic context is.(Dean 9)A number of key informants suggested that addiction stigma could be reduced if a conversation about addiction amongst FM and staff started. Supporting this view, CMHP5 stated, “faculty need to start getting real about what is really going on, they need to start taking off the mask, and talking about addiction.” As some CMHPs alluded to, the conversation has to start “from the top” through what several referred to as “vulnerable leadership.” The prestige associated with being an FM was reported to affect non-disclosure, because as one CMHP expressed, it “doesn’t leave much room to make mistakes and be human.” Some pointed out that if FMs are going to feel safe disclosing, they need to make sure they are going to be met with compassion, and “not lose their job,” as another key informant suggested. The community becomes safer when those in more of an authoritative space lead with vulnerability.(CMHP 2)Finally, to reduce addiction stigma for FMs, several key informants suggested normalizing addiction-recovery by having more campus community members  share openly about their personal experiences, as has been done with other mental illnesses, as CMHP 1 suggests:People have conceptions of what mental illness is, and that conception doesn’t necessarily include addictions. I think we have to be a little more explicit on that. Maybe it’s bringing in people to talk about their experiences with alcohol or other substances. We had one FM speak openly about her anxiety and how she’s dealt with it—that got a lot of uptake, right? The video was viewed by thousands of our community members.Several key informants suggested having policies and procedures in place so that FMs could safely discuss substance use concerns without consequences  and get adequate help. For instance, one of the CMHPs explained that not being reassured about their job security might serve as a major obstacle for FMs in disclosing and seeking help:FMs are known for what they do, but are we providing the resources to allow them to come forward without consequence?(CMHP 4)Several also reported that if they did encounter an FM with a substance use problem, they would recommend the FM to employee assistance programs (EAP). However, they also elaborated that EAP is often inadequate to address addiction issues:I have my doubts about referrals to EAP for people who are seeking support for addictions. When a person reaches out for help and doesn’t get it, the person goes 15 steps backward in terms of ever asking for help again. We tell people we have an EAP program and give them a pamphlet that I find so simplistic and patronizing, like how (will this help?) It’s about facilitating that (request for support), not just about “here’s a card, here’s a card, here’s a card.”(CMHP 3)This qualitative study explored 10 dean and 6 CMHPs encounters with FM addiction, how addiction stigma may have affected FM (non) disclosure, and recommendations that may help reduce addiction stigma for FMs.Using a CPM framework, this study makes a unique contribution to the literature as it provides insights into how alcohol culture, productivity culture, faculty type and gender may amplify disclosure risks/impermeable boundaries , therebyThe interviews revealed that addiction disclosure was rare and most often involved alcohol. This finding is consistent with organizational literature suggesting that alcohol is the most frequently used drug by employed people . AlcoholWhile research has yet to focus on FMs direct experiences disclosing addiction or recovery, several studies have shown that college drinking culture leads non-drinkers to view abstinence as deviant and stigmatized, which affects their decisions to disclose ,21,42. AStudy findings also revealed that key informants were being made aware of problematic drinking through negative consequences . This finding leads us to question the extent to which FMs were seeking help for addiction elsewhere. Having an impermeable privacy boundary  may reinTherefore, in order to assist help-seeking and/or the maintenance of recovery for FMs who find themselves along the alcohol addiction-recovery continuum, efforts to change university drinking culture may be promising may forward to reduce addiction stigma. For instance, ensuring more ethical and responsible alcohol advertising on campuses , servingSeveral study participants reported that the highly competitive nature of academia created an additional barrier to disclosing, as “any sign of weakness” could negatively affect their reputations and careers. Supporting this view, it has been suggested that “research-intensive universities create cultures that demand high performance while promoting excellence and achievement, and also carry the risk of stress, stigma, and challenges to mental health”  (p. 1). Numerous participants identified that having more “vulnerable leadership” could help reduce addiction stigma thus help to promote FM disclosure and help-seeking. Several linked the concept of vulnerable leadership to encouraging the university community to share more openly about their addiction-recovery journeys. This finding aligns with other research suggesting that having access to sober role models, is an effective way to combat stigma and ultimately promote and sustain recovery . It alsoWhile the small sample of this study did not permit a thorough exploration of identity markers, one key informant pointed to the additional risks that disclosing an addiction identity would hold for female FMs. This finding is consistent with previous literature, suggesting that addiction is more heavily stigmatized for women than it is for men, which affects women’s ability to seek help . QualitaFaculty type was also identified as affecting disclosure risk. Some research has emphasized that there may be more understanding in helping disciplines, such as social work, because of the emphasis on the use of self and social justice . Other rDespite the risks of FM addiction disclosure, an emerging body of literature highlights some of the unique opportunities connected to academics disclosing an addiction identity. For instance, two recent articles have argued that having professors disclose in undergraduate classrooms may be an effective way to combat stigma while also paving the way for students to seek help ,9. The bWhether FMs decide to disclose an addiction and/or recovery identity is a deeply personal decision. Despite the call for more vulnerability, disclosure risks in the workplace are significant  and reinUltimately, it took me five years of negotiating my privacy boundaries  to reachKey informants overwhelmingly recommended implementing dedicated addiction peer-support groups for FMs. Peer support involves individuals with lived experience of addiction and exists on a continuum: from informal volunteer mutual aid support systems, such as the 12-step model of AA, to formalized and employed paraprofessionals who require training and certification . LivingsPeer support is a cornerstone of Collegiate Recovery Programs (CRPs), which have been implemented in 138 universities and colleges across the USA (two recently in Canada), and have shown to be effective in promoting recovery for students . A CRP iTraditional workplace responses to addiction focus largely on identifying and treating the “problem” of a limited number of people, which can reinforce stigma . There hEven though addiction is a protected disability , this protection is often disputed because people with addiction are viewed as being morally defective and thus less deserving of protection . LegislaTaken together, inspired by the findings of this study, the intervening literature, and consultations with CRPs and RFW leaders, I (first author) am leading an initiative working toward promoting recovery from addiction, building community, and combatting addiction stigma at my university. Relatedly, I started an Instagram page called @recoveringacademics, a community collective for academics in recovery and allies who are committed to addiction/recovery research and social justice. The page is profiling academics in recovery, with the aim to build community and reduce addiction stigma by celebrating recovery identities, as Dr. Wendy Dossett  expressed:Academia exerts powerful and toxic identity orthodoxies which make addressing stigma within universities particularly challenging. I commend the @recoveringacademics initiative for legitimizing and celebrating a recovery identity, my identity, in what can sometimes be an inhospitable environment. Let’s make our universities recovery-friendly!This qualitative study explored 10 dean and 6 CMHPs encounters with FM addiction, how addiction stigma may affect FM (non) disclosure, and recommendations that may help reduce addiction stigma for FMs. Using a CPM framework, this study makes a unique contribution to the literature as it provides insights into how psychosocial factors including university norms , and identity markers  may affect addiction stigma and disclosure for FMs. Ultimately, there is a need to look beyond individual vulnerabilities and start examining organizational culture, policies, and procedures that help and/or hinder disclosure and help-seeking behaviors. Bolstering existing services available to FMs , challenging productivity culture and alcohol culture, sharing addiction-recovery narratives, and ensuring policy safeguards are in place, are promising ways forward to support addiction-recovery for FMs and the campus community at large.While this study provided a glimpse into how deans and CMHPs experienced FM addiction disclosure, the findings need to be interpreted in view of their limitations. First, FMs themselves were not directly consulted about their addiction and disclosure experiences. Additional qualitative studies focusing on the direct experiences of FMs are needed, with a particular focus on the disclosure decision-making process. Additional quantitative research is also needed to evaluate future addiction anti-stigma interventions and determine the help-seeking behaviors for addiction and their prevalence among FMs in a larger sample across university settings.Second, in recognizing an aim of qualitative research is transferability, not generalizability ,61, and Despite these limitations, exploring key informants’ encounters with FM addiction provides an enriched understanding of how university culture may affect addiction stigma and FM disclosure, while providing several practical recommendations and useful jumping off points for future research.


The magnitude of a disaster’s severity cannot be easily assessed because there is no global method that provides real magnitudes of natural disaster severity levels. Therefore, a new universal severity classification scheme for natural disasters is developed and is supported by data. This universal system looks at the severity of disasters based on the most influential impact factor and gives a rating from zero to ten: Zero indicates no impact and ten is a worldwide devastation. This universal system is for all types of natural disasters, from lightning strikes to super-volcanic eruptions and everything in between, that occur anywhere in the world at any time. This novel universal severity classification system measures, describes, compares, rates, ranks, and categorizes impacts of disasters quantitatively and qualitatively. The severity index is useful to diverse stakeholder groups, including policy makers, governments, responders, and civilians, by providing clear definitions that help convey the severity levels or severity potential of a disaster. Therefore, this universal system is expected to avoid inconsistencies and to connect severity metrics to generate a clear perception of the degree of an emergency; the system is also expected to improve mutual communication among stakeholder groups. Consequently, the proposed universal system will generate a common communication platform and improve understanding of disaster risk, which aligns with the priority of the Sendai Framework for Disaster Risk Reduction 2015–2030. This research was completed prior to COVID-19, but the pandemic is briefly addressed in the discussion section. One or more natural disasters occur on most days somewhere in the world causing immense hardship to living beings and major damage and losses. Natural disasters can be land based , water based , atmospheric , biological , extraterrestrial based , or any combination of these . Although these disasters are different, their impacts on humans and habitats are similar. All natural disasters can cause loss of life and damage to humans and their possessions, and they disturb people’s daily lives. However, it is difficult to express the level of severity caused by different types of natural disasters, in different countries, and in different time periods because there is no agreed upon terminology, no global standard communication platform, and no single common measurement for all types of natural disasters for all stakeholders that can estimate the total impact of an event and understand the full scope of severity. Further, there is no system that can be used for communication purposes without confusion and for educating the public regarding the disaster continuum.Disasters do not respect national boundaries. Therefore, an international standard communication platform for severity is vital to have agreement among countries. The impact of a disaster in a region, if not managed properly, can produce political and social instability and affect international security and relations  are used for different purposes, by different stakeholder groups, and for all types of natural disasters (or particular types of disasters). Among the various scales with different measurement systems, a few common classifications for all types of natural disasters for all stakeholders exist, but they also have several deficiencies. For example, Disaster Scope, introduced by Gad-el-Hak , uses caAlthough there are many scales, clearly expressing the level of severity is difficult for two main reasons: first, there is no globally accepted standard to communicate the level of severity of a natural disaster  is not feasible. However, the confusion can be minimized when there is an adequate number of levels to distinguish between different categories of seriousness and when a consistent/standard number of levels exists.When describing a disaster, we not only use words, but also accompanying numbers. Natural events are often described using many objective factors of severity, e.g., deaths, injuries, and property damage. By comparing damage and fatalities, some disasters are labeled as the most expensive  Brink  and someHowever, a statistical comparison of disaster impacts is a complex task because various factors present different insights into the level of severity of an event. For example, comparing the number of fatalities and the total cost of damage gives contrasting ideas as to the level of severity of the 2004 tsunami that struck Sri Lanka versus the 2013 flood that struck Southern Alberta, Canada. The 2013 Southern Alberta flood resulted in $5.7 billion in damage, 4 fatalities, and affected 100,000 people (but no injuries nor did it leave anyone homeless) (Centre 2013), while the 2004 tsunami caused $1.32 billion in damage, but it caused more than 35,000 fatalities and affected more than 1 million people  (Centre 2013). If one considers only fatalities, then the Sri Lankan tsunami appears more severe, and if one considers cost of damages, the Alberta flood appears more severe. There are many factors that can be considered when addressing the severity of an event. No current scale identifies the relationships between impact factors nor uses these relationships to estimate the overall severity of a disaster Caldera .Therefore, comparing levels of impact for different types of disasters is challenging. Nevertheless, comparing key impact factors , as shown in the comparison of the Sri Lanka tsunami and Southern Alberta flood, provides a more complete comparative picture between two disasters and a more comprehensive idea of the extent of damage, rather than merely comparing one or two factors, such as fatalities and/or damage costs. This more complete picture helps disaster and insurance managers to estimate the true magnitude of a disaster's severity  but not the impact . As shown in Table Currently, different stakeholder groups have their own scales with different measurement systems to assess a disaster according to their requirements. For example, disaster managers and emergency responders use incident management teams (IMTs)—typing United , databasWhen a disaster strikes, these disconnected systems make it even more difficult for stakeholders to communicate about the severity of the disaster. Therefore, confusion and misunderstanding can occur. For example, most of the North American emergency management agencies use IMTs’ as a way to classify all hazards and to assign a type number to the incident, in order to address response and recovery activities and the command and control infrastructure that is required to manage the logistical, fiscal, planning, operational, safety, and community issues related to local/regional/national emergencies, natural disasters, and public events Alberta . IMTs arIn addition, when a disaster is first identified, emergency responders often do not know the full scope of the disaster. An event can quickly escalate from a routine emergency to a disaster, and then to a bigger disaster. The management challenges associated with response and recovery also increase as impacts escalate. During events when emergency responders communicate with other stakeholders, such as national/regional/local governments, relief agencies, non-governmental organizations (NGOs), and the media, they have no common classification system that provides a unified understanding of the level of severity of the event. Consequently, officials who are trying to understand the full impact of a disaster do not have a consistent scale that can provide a clear understanding of the potential hazard, and so they cannot alert other stakeholders, such as the general public, about the degree of severity.Moreover, the type is assigned by internal personnel and can be subjective due to the level of experience and internal processes used. Decisions made can delay the adoption of appropriate actions needed to mitigate a disaster; in other words, assistance from international governments, NGO’s, relief agencies, and volunteer communities can be delayed. The consequences of failing to identify a potential hazard and failing to manage a disaster adequately can be significant. For example, regarding Hurricane Katrina, Tierney  explaineFurthermore, nation’s ability to manage disasters is more effective when there is mutual understanding between countries and different emergency management systems at all levels: international, continental, regional, national, provincial, and local. The ability of countries to manage extreme events can be dependent on the system that they use. However, since countries use different systems to manage extreme events, either a universal understanding of the systems used by other countries or a global standard is required to better prepare and manage global disasters that affect more than one country. For instance, if there had been a universal system in 2004 when the Indian Ocean tsunami struck 12 countries in Asia and Africa, it may have saved thousands of lives. Thus, a new approach is needed to mobilize resources properly, make adjustments as necessary, and more correctly gauge the need for regional, national, or international assistance. Therefore, there is a mandate for a new system that integrates both measurement systems: management and severity.A consistent scale is needed to understand the disaster continuum and to develop a platform for a reliable and transparent data management process that facilitates comparisons between different disasters  is necessary to solve the previously mentioned problems. This new universal system is expected to integrate all current measurement systems: impacts, management, and size. The UDSCS will connect the current measurement systems and provide a common communication platform that can be used to compare, quantitatively and qualitatively, and measure, describe, and categorize the impact of disasters for the general public and emergency responders. Therefore, the UDSCS is expected to avoid inconsistencies and, most importantly, to connect the severity metrics to generate a clear understanding of the degree of an emergency and potential hazard.Identify the most influential factors related to disaster severity.Develop the foundation of the UDSCS in terms of (i) the number of levels and (ii) associated color coding.Develop qualitative measures by clearly defining words that describe disasters.Develop quantitative measures that are based on data and statistically robust.Develop the UDSCS.The 5 key steps to develop a UDSCS are addressed by the following two questions: How many levels are required to clearly differentiate the impact of natural disasters? How are these levels used to clearly distinguish the various degrees of natural disasters, both quantitatively and qualitatively?What makes a disaster “large scale” is the number of people affected by it and/or the extent of the damaged infrastructure and geographical area involved , etc.Strength-measuring factors that reflect the power and intensity of an event: magnitude, duration, speed, location, distance from disaster site to affected populated area(s), etc.Preparedness factors that reflect a region’s preparedness: available technology, resources, whether the area(s) could be evacuated before being affected, mitigation methods, response rate, etc.The severity of natural disasters increases as the impact to humans and their possessions increases and the power and intensity of an event increases. In contrast, severity decreases the more a region is prepared for a disaster. Therefore, severity relates to all factors that can be grouped as follows:More details about the above groups can be found in Analysis and classification of natural disasters Caldera .A scale representing all factors is complex. However, no matter how prepared people are, where the disaster occurred, or how intense/powerful the disaster is, if people lose their belongings or loved ones in a natural disaster, their disutility mainly depends on what they have lost and not how they prepared for the disaster, the intense/powerful the disaster, nor where the disaster occurred. Therefore, the severity of an event directly relates to socioeconomic factors and indirectly relates to strength-measuring and preparedness factors. Hence, the severity of an event can be evaluated by measuring the negative impact of a disaster on people and infrastructure  and damage factors . A 0–10 level system is proposed because very large ranges of almost all socioeconomic factors can be expressed within 11 levels using the log scale. The 11 levels of human factors (H), which range from 0 to 7.674 billion people  represent higher severity levels. White is also added to indicate nondestructive events. The color codes that correspond to the 11 severity levels are shown in Table As a qualitative measure of the UDSCS, the linguistic method, which is the most commonly used and oldest method of describing natural disasters of various magnitudes, is used. For example, the words such as calamity, cataclysm, catastrophe, disaster, and emergency are used in this analysis to categorize the different levels of disaster impacts. Still, only words that describe the magnitude of the natural phenomena are considered. Therefore, words, such as “Armageddon,” which describe “a usually vast decisive conflict or confrontation” or “a terrible war that could destroy the world” Oxford  are not However, the sense of the real magnitude of a disaster’s severity cannot be comprehended using the current linguistic method because it has several deficiencies described in the following subsection. Therefore, an order of seriousness and clear definitions for the considered terms are also proposed to describe the severity spectrum.Apocalypse: an event involving destruction or damage on a catastrophic scale.Calamity: an event causing great and often sudden damage or distress; a disaster.Cataclysm: a large-scale and violent event in the natural world.Catastrophe: an event causing great and usually sudden damage or suffering; a disaster.Disaster: a sudden accident or a natural catastrophe that causes great damage or loss of life.Emergency: a serious, unexpected, and often dangerous situation requiring immediate action.First, there are no consistent definitions, methods, or clear sense of scale to differentiate these terms (used to describe disasters) from each other. For example, the Oxford dictionary defines common terms used to describe disasters as follows Oxford :Apocalyp“Catastrophe” is used to define “disaster,” and “disaster” is used to describe both “catastrophe” and “calamity” in the Oxford dictionary Oxford , and theApocalypse: uncover, disclose, reveal (late fourteenth century)Calamity: damage, loss, failure, misfortune, adversity (early fifteenth century)Cataclysm: to wash down  (1630 s)Catastrophe: overturning, sudden turn (a sudden end) (1530 s)Disaster: ill-started event (the stars are against you) (1560 s)Emergency: to rise out or up (unforeseen occurrence requiring immediate attention) (1630 s)Second, vocabulary, context, and interpretation of each term is not fixed Kelman ; therefoThird, the order of seriousness implied by these terms has also changed over time because the meaning of these terms have changed. According to the word origins , we use “event,” “disturbance,” and “upheaval,” which are modified by the adjectival forms “sudden,” “major,” “large-scale,” “very large-scale,” “extremely large-scale,” and “world-scale.”To describe impact (purple colored text), we use “damage,” “destruction,” and “devastation,” which are modified by the adjectival forms “significant,” “severe,” “widespread continental,” “global,” and “universal.”To describe injuries (green colored text), we use “many serious,” “major,” “massive,” and “uncountable.”To describe fatalities (red colored text), we use “some,” “many,” “great,” “extensive,” “unimaginable,” and “partial or full extinction.”The definitions for the terms are proposed in Table Unlike the existing definitions, the proposed definitions provide a consistent method of differentiating as these definitions clearly articulate the real magnitude of different severity levels  and the foundation of the UDSCS . The first destructive level of the UDSCS, UDSCS 1, is “Emergency” to indicate the impact of the disturbance on inhabited areas. The term “Partial or Full extinction” represents the last level of the UDSCS, UDSCS 10, and indicates total or partial destruction of the Earth. The levels in between are equally distributed among the remaining 4 words; each term has been subdivided into Types 1 and 2 of “Disaster,” “Calamity,” “Catastrophe,” and “Cataclysm,” as shown in Column 2 in Table Identifying relationships between factors that reflect the severity of an event aids in deciding what factors should be included in the multidimensional scale. Then, the most influential factors of severity are selected to develop the scale. Different methods can be used to identify the direct relationship between the factors. Statistical correlation can be used to identify the degree of linear relationship, and regression analysis can be used to identify the specific relationship. Different types of regression analyses and correlation methods are employed according to the type of variables used in the following analysis.The most influential impact factors that can be considered for a multidimensional scale are from the socioeconomic factors listed in Step 1. Therefore, the impact of disasters on people, facilities, and the economy should be studied in detail to understand the severity of a natural disaster. Due to the lack of a complete recording system, the only socioeconomic factors considered in this correlation analysis are fatalities, injuries, missing persons, houses damaged/destroyed, and cost of damage in USD, as given in the NOAA database National , 2013b. Impact factors for tornado effects show a strong linear dependency as ρ is greater than 0.75, which normally means that, when one factor increases, the other factor is expected to increase. For example, an increase in the number of fatalities predicts an increased number of injuries and damage. However, when there are advanced warnings and mitigation measures, the number of fatalities and injuries can be minimized even if property damage increases. For the considered dataset, a natural linear relationship between these factors is investigated using multiple regression analysis and shown in Eq. . Table 1The model that describes the relationships between fatalities, injuries, and damage fits 71% of the human impacts in data on tornadoes because the adjusted R-squared value is 0.71, which indicates a strong linear relationship. This R-squared value indicates that 71% of the variance in fatalities can be predicted from injuries and damage. Therefore, analyzing one factor can determine another using their linear dependency. For tornadoes, according to Eq. ρ ≥ 0.5) with each other, two approaches can be applied: measure the severity using one of these factors or develop a complex disutility function that includes several factors. Initially, the simplest approach of using one factor is selected to measure severity. The complex disutility function approach can be used to develop a multidimensional UDSCS. Therefore, 1 of the 5 factors  is selected for the initial scale.Given that the impact factors are correlated , regional disasters  floods, heat waves, tornadoes, and viral infectious diseases), and local disasters  are included in this analysis with the frequency distribution shown in Table This analysis consists of 5 out of 6 main groups of natural disasters, and the frequency distributions of these 37 different categories of disasters are shown in Table It is essential to determine the statistical characteristics of fatalities and the best probability distribution fit that are able to describe fatalities. There are 10,805 records of fatalities out of 10,807 records from 1977 to 2013 logged in the EM-DAT database, with minimum 0 and maximum 300,000. The mean of fatalities is 258.04, and the standard deviation is 5491.18 with 38.65 skewness and 1,686.98 kurtosis, which means the parent probability distribution of fatalities has more extreme events at longer fatality numbers, i.e., a long right tail.Determining the distribution that historical data follow is necessary to estimate the probability of future events for a given number of fatalities. To better fit the distribution, fatalities are transformed into natural logarithms after eliminating zeros (3287 records) and no records of fatality (2 records) from the 10,807 records Caldera . The logth order statistic, and peak over threshold, to identify the extreme events . The EPDFs are limiting distributions and essential to evaluate the probability of extreme disasters. There are three models available, block maxima, Rn in Eq.   ranging from small-scale to large-scale disasters. Extremes in the Rth order statistical model are distributed as a generalized extreme value distribution (GED). GED can be further explained by either Gumbel (GE0), Frechet (GE1), or Weibull (GE2) distributions . To reflect a reasonable number of data points in each block, first, the different types of disasters are grouped according to their secondary sub-type, sub-type, or main type if there are not enough events in the category to represent the Rth order; then, fatalities are ordered from highest to lowest for each category. Subsequently, the first R number of fatalities in each block is selected. Therefore, the following categories are combined:“Parasitic infectious diseases” and “Other epidemics” are combined into “Other epidemics”;“Cold wave” and “Extreme winter conditions” are combined into “Cold wave or Extreme winter conditions”;“Scrub/Grassland fire,” “Bush/Brush fire,” and “Other wildfires” are combined into “Other wildfires”;“Tsunami,” “Other seismic activity,” “Mass movement dry landslide,” “Other mass movement dry,” “Debris flow,” “Sudden subsidence,” “Mudslide,” “Snow avalanche,” “Rock fall,” and “Avalanche” are combined into “Other geophysical events”; and“Other Local/Convectional storm,” “Snowstorm/Blizzard,” “Blizzard,” “Blizzard/Tornado,” “Blizzard/Dust storm,” “Dust storm,” “Sandstorm/Dust storm,” “Sandstorm,” “Snowstorm,” “Sandstorm,” “Extratropical cyclone (winter storm),” and “Severe storm/ Hailstorm” are combined into “Other local/Convectional storm.”To apply the extreme value theory to the random variable , each type of natural disaster represents one block in the extreme value analysis. Although there are 59 different secondary sub-types of disasters recorded in the EM-DAT database from 1977 to 2013, the same categorizations (blocks) cannot be used to extract the extreme values as some secondary sub-types have none or only one, two, or less than 10 recorded events . In these cases, there are not enough extreme values to represent the highest Rth order, 10th order, 15th order, …, up to 70th order statistics  are analyzed. The sample sizes of these 14 extreme datasets of Rth order statistics increase by multiples of 27 according to Eq. . The first derivative of these fitted trend lines measures the rate of change of the mean, while the second derivative measures whether this rate of change is increasing or decreasing. The mean value stabilizes when Rth order increases because the rate of change is decreasing when Rth order increases. Therefore, the mean slowly decreases and converges to its full sample value  when Rth order increases.The distribution of the mean (and its trend line) of these 14 extreme datasets are shown in Fig. th order statistic is considered as the best minimum Rth order statistic to estimate the probabilities of severity levels of fatalities , Weibull (GE2), and generalized extreme value distribution (GED).The estimated probabilities and the sample probabilities of severity levels 0 to 10 according to the foundation of UDSCS from Step 2 are shown in Table th order sample  although the 70th order sample has 0.42% representation for UDSCS 6 or higher events. In contrast, GE1 yields significantly higher probabilities compared to GE2 and GED for the estimated probabilities of levels 7 to 10. For example, 2 out of 10,000 severe natural disasters can be considered as severity level 10 events  according to the fitted GE1, which is a higher probability for partial or full extinction. However, compared to the estimated probabilities of GE1 and GE2, the estimated probabilities of GED are closer (and more reliable) to the 70th order sample probabilities for higher severity levels. Table th order statistic is suitable to calculate the approximate probability values of natural disaster severity levels  and qualitative measures to differentiate each level as shown in Table Almost everything in this table is novel. For the first time, a 0–10 level ranking is proposed, which make sense because it is a log scale that can cover wide ranges in terms of socioeconomic factors. Although each severity level increases by a power of 10, the probability of events that fall within the higher ranges of the scale is small. The probability of a very high classification is low for severe natural disasters as these events are rare. Furthermore, the base 10 measurement is easy to remember and meaningful because it clearly differentiates one severity level from another.th order statistic GED  because there are no historical records for UDSCS 7 or higher disasters in the considered dataset; however, there is geographical evidence of natural disasters that have occurred in the past. Therefore, the estimated probabilities for last four levels (UDSCS 7 to 10) are very low, and these probabilities are indicative of their severity range.The estimated probabilities of these levels are calculated using the approximate best-fitted 70th order GED, it is expected that 5 in 1 million severe events are Catastrophe Type 2 or higher disasters. The severity levels of the 2 worst extreme natural disasters that have occurred in history, and for which data are available, are the Black death pandemic that occurred between 1346 and 1353 where more than 50 million fatalities were recorded, and the Spanish Flu pandemic that occurred between 1918 and 1920 where more than 40 million fatalities were recorded . However, according to the fitted 70Disasters, such as meteoroid impacts, have the potential to vary from “Emergency” (UDSCS 1) to “Partial or Full Extinction” (UDSCS 10). Although there are no recorded fatalities caused by a meteoroid impact, the falling of meteoroids gained attention after the Russian meteor strike in 2013 that injured more than 1,000 people. Also, there are many studies about extinction risks, such as super-volcanic eruptions or major asteroid impacts. The studies estimated the number of deaths that might occur, but the probability of these events occurring is very low. According to the Planetary Society, an asteroid larger than 1 km across is big enough to threaten global destruction, and astronomers estimate such objects have a 1 in 50,000 chance of hitting Earth every 100 years Kettley . These kth order GED, 19 out of 100 extreme natural disasters are less than UDSCS 1. They can be disasters that are not recorded in the database  or zero fatality events, such as insect infestations and lightning strikes, according to the historical events recorded. Four out of 100 severe natural disasters can be considered as UDSCS 1 events that have 1 to 10 fatalities. An example of a UDSCS 1 is icing, which is any deposit or coating of ice on an object that can seriously hamper its function and is considered an extreme temperature condition grouped under climatological disasters. Note that the EM-DAT database records events that have less than 10 fatalities, if 100 or more people are reported as affected or there has been a call for international assistance/declaration of a state of emergency. Thus, the estimated probabilities of UDSCS 0 and 1 are also conditional to the above data entering criteria.Predictions from the model need to consider possibilities outside the estimated probabilities and must be used with caution because decision makers may believe them to be absolute. According to the estimated probabilities of 70Severe natural disasters fall under Disaster Type 2 (UDSCS 3) according to the analysis; 39 out of 100 severe disasters will have 100 to 1,000 fatalities. According to historical events, bush and forest fires, cold waves, avalanches, snow avalanches, rock falls, storm surges/coastal floods, sudden subsidence, debris flows, mudslides, tornadoes, and storms  can be classified as UDSCS 3. The second most likely severity level that severe natural disasters can fall under is Disaster Type 1 (UDSCS 2); 29 out of 100 severe events will have 10 to 100 fatalities. According to the data, freezing rains, scrub/grassland fires, other wildfires, other seismic activity, and storms  can be classified as UDSCS 2. Thus, 68% of severe natural disasters will have 10 to 1000 fatalities and fall under either Disaster Type 1 or Type 2 (UDSCS 2 or 3).The next major natural disaster will have a 7.75% chance of causing between 1000 and 10,000 deaths. In other words, 775 out of 10,000 extreme disasters can be classified as UDSCS 4, Calamity Type 1. Most biological events, such as epidemics , extreme winter conditions, floods , landslides, and other storms fall under this category.Extreme disasters, such as volcanoes, flash floods, and heat waves can be classified as UDSCS 5, which means 72 out of 10,000 severe natural disasters can be considered as Calamity Type 2 events that have 10,000 to 0.1 million fatalities. Earthquakes, tsunamis, tropical cyclones, and droughts have the ability to reach UDSCS 6, and 6 out of 10,000 severe disasters can be classified as Catastrophe Type 1 events.This universal classification system compares the severity of different types of disasters and presents an overall picture of severity levels Caldera . AccordiHowever, it should be noted that the extreme fatality analysis used historical events from 1977 to 2013 recorded in the EM-DAT database, and none of these records included events that had fatalities exceeding 300,000 (Catastrophe Type 1). In addition, as mentioned previously, the database records depend on the country . Moreover, there are events before 1977  that this analysis does not cover, and there is the possibility that future events exceed 300,000 fatalities.In addition, simultaneous disaster events  are not considered in this analysis. These events can cause the classification level to increase by one or more levels.Additionally, infrastructure failure can be added to an event or simultaneous events, for example, the nuclear plant failure subsequent to the Great North East Japan Earthquake and Tsunami. A meteoroid impact on land close to population centers or in the ocean (causing massive tsunamis) could cause millions of fatalities.Although the analysis is subject to many limitations, it provides a good foundation to develop an advanced multidimensional scale to classify disaster occurrences worldwide based on a combination of several independent factors. This analysis also provides an overall picture of the severity of each type of disaster. This kind of scale makes it easy to recognize an event occurrence and enter it into a database.Table Moreover, the disaster classification of geophysical disasters is validated using this table. The maximum fatality record (China in 1556) for earthquakes in the NOAA database from 2000 B.C.E. to 2015 C.E. is 830,000 .Enhanced databases Improved information management and processing .Precise disaster terminology .However, these requirements do not stand alone but are interconnected with each other. Hence, consistent interpretation, a proper scale, good understanding of each disaster, and an expanded recording system are required to accomplish this goal. Therefore, a global disaster classification system is an important contribution to improving the quality and reliability of international disaster databases  that are validated via firsthand reports and changing requirements. Therefore, this new universal severity classification system is expected to provide benefits to several groups:Disaster managers and emergency respondent personnel can gain a clear sense of scale of the severity of each type of disaster by considering the expected probabilities according to historical disasters. Also, they can have an overall picture of a disaster because UDSCS provides relative comparisons among disasters of various degrees and ranks natural disasters using a set of criteria. This knowledge can be used to deploy resources as needed when disaster strikes, and it can be used for pre-planning , and separate disasters can be recorded as subdivisions of the records, where possible (if the impact of primary and secondary disasters can be separated clearly). As a result, complications, misunderstandings, misclassifications, and missing records can be minimized as much as possible. Additionally, decision capabilities of disaster information management processing can be improved as this universal system classifies disasters according to severity.The UDSCS has an academic value in addition to practical applications. For example, if we have an accurate disaster database, more research can be conducted on disaster mitigation to improve disaster preparedness technologies. It may take many years to obtain quality reports. However, even relatively short records can be used to develop relationships among variables in the records in databases Brooks , which iThe UDSCS will serve as a bridge between qualitative and quantitative techniques used in emergency management systems. Qualitative and quantitative techniques are integrated in the UDSCS to produce management and size measurement systems, respectively. Therefore, the UDSCS is expected to avoid inconsistencies and, most importantly, connect severity metrics to generate a clear understanding of the degree of an emergency and the potential impacts, thereby improving mutual understanding between the emergency management systems of countries at all levels: international, continental, regional, national, provincial, and local.As UDSCS is used post-event, the classification of the severity of the event may change as reports on the number of fatalities are updated. Therefore, the degree of severity changes with time and with updated reporting on the disaster. For example, an earthquake, which occurs in seconds, could be categorized as a “disaster” in terms of severity within the first few hours depending on the reported impacts and causalities. However, the impact and causalities can increase days or weeks after the event. Accordingly, the severity of the earthquake could be reclassified as a “calamity” a day or two after the event, and it could potentially be considered a catastrophic event within weeks. Although frequent updates improve the accuracy of the severity, it is vital to estimate the severity shortly after an event strikes to provide information to first responders and for public reporting and planning. The potential impact of a disaster can be estimated with a certain degree of accuracy, which is beneficial because the size of a first-responder contingency depends on the magnitude of the disaster impact. Therefore, predicting the severity can accelerate the recovery process.The information in the initial UDSCS, listed in Table In addition, the UDSCS has a reasonable and standard number of levels to articulate the full range of disaster severity, and it has a clear order of seriousness for the severity levels. The increasing level of seriousness from 0 to 10 is defined using quantitative boundaries and clearly defined descriptive terms, which avoids confusion as to whether UDSCS 0 or UDSCS 10 is the most critical. Because the UDSCS has a reasonable number of levels, events that have different levels of severity will not be in the same category. Therefore, because this universal measurement system clearly conveys the size of the impact of a disaster, it avoids confusion and improves mutual understanding among stakeholder groups.Moreover, the UDSCS can be adapted to any language, country, or culture. The UDSCS clearly defines the levels of the disaster continuum by (1) redefining the existing terms without using one term to define another, (2) outlining the impact factors, damage, injuries, and fatalities, and (3) using better descriptive words to reflect the order of seriousness of a disaster.The number of fatalities is chosen as the most influential factor because it is correlated with several factors that affect humans. Fatalities is highly correlated with injuries and missing persons and moderately correlated with houses damaged and cost of damage. However, one factor alone is not sufficient to measure the severity of disasters because a single factor does not address all aspects of severe events. For example, a disaster, such as a wildfire in an uninhabited forest, may affect only a geographical area and not have any direct and immediate impact on humans, but the wildfire may have long-term adverse effects on the local and global ecosystems. Real-world examples include the 2016 Fort McMurray fire, which had no fatalities, and the 2013 Alberta flood, which had 4 fatalities, but both disasters were the costliest Canadian disasters in history; consequently, neither event is properly represented using a scale that only considers fatalities. Therefore, a more advanced multidimensional quantitative scale that combines all impact factors, such as fatalities, injuries, homeless, affected population, area affected, and cost of damage, is needed to properly address the full range of a disaster impact.Even using one impact factor, this simple universal system that incorporates all types of natural disasters  is more informative and consistent for assessing severity. The boundaries of the levels are clearly defined. Therefore, an overall picture of the disaster continuum is available using the UDSCS. In addition, the UDSCS links the disaster severity matrices because it serves as a bridge between quantitative and qualitative techniques.This research was completed mostly prior to coronavirus pandemic in 2019–2020 (COVID-19); therefore, COVID-19 is not discussed in detail in this paper except in this paragraph. COVID-19 is an acute respiratory infectious disease that affects humans and some animals, and it is caused by the 2019 novel coronavirus (2019-nCoV); the first patient to be infected is unknown  is developed to assess the impact of any uncontrollable forces of nature regardless of disaster type, place, or time. This universal severity classification system is applicable to all stakeholders, such as civilians, emergency responders, disaster managers, relief agencies, all levels of government, NGOs, insurance managers/estimators, reporters, media, database/information managers, academics, researchers, and policy makers. Therefore, it is expected to create a universal standard severity measurement system, and most importantly, generate a common communication platform to describe the impact of disasters, ensuring mutual understanding across the globe. A nation’s ability to prepare and manage extreme global disasters that affect more than one country will improve if there is mutual understanding among different countries’ emergency management systems at all levels.By selecting the appropriate terms for the levels and naming the categories using plain language to describe the magnitude of a disaster, the UDSCS is expected to allow for easier management at all levels. Moreover, combining these terms with quantitative techniques gives clear boundaries and guidelines, and combining these terms with the color coding scheme enables easy adaption to any language, country, or culture. The color coding system is helpful to some people working or involved in disaster recovery who are not literate or cannot understand the local language or dialect (if working in foreign regions). Therefore, the definitions and colors together ensure broader communication between people and organizations.The UDSCS explains the disaster continuum. Using this universal system, the impact of a broad range of natural disasters that occur anywhere in the world at any time can be described, measured, compared, assessed, and ranked both quantitatively and qualitatively. The UDSCS uses a color coding scheme and disaster terminology to describe disasters qualitatively, and it uses severity levels and impact factor boundaries to assess disasters quantitatively using the rating scale 0–10 to rank disasters. Further, it uses the probability of occurrence of extreme disasters to predict the impact of any natural disaster. Most importantly, the UDSCS is a single common measurement for all types of natural disasters because it integrates colors, words, impact factors, and severity level rank.The proposed severity scheme will improve communication and understanding of disaster risks, which aligns with the priority of the Sendai Framework for Disaster Risk Reduction 2015–2030. Additionally, the UDSCS is a simple scientific instrument. The selected descriptive terms, impact factors to measure severity, and proposed ranges are based on data and statistically robust. Furthermore, the UDSCS will avoid inconsistencies and, more importantly, will connect severity metrics to generate a clear understanding of the degree of an emergency and the potential impacts. Lastly, qualitative and quantitative techniques are integrated to produce management and size measurement systems, respectively.This is an ongoing research project to develop a multidimensional UDSCS to understand the disaster continuum. The scope of this paper is to introduce an initial UDSCS that can be used to compare the impact of any type of natural disaster both qualitatively and quantitatively. When developing quantitative measures (in Step 4), we considered only one impact factor, fatalities, to develop the initial UDSCS. However, using the initial scale with one factor does not capture all aspects of an impact, as noted previously. Therefore, an advanced multidimensional scale that combines all impact factors using a disutility function needs to be developed.


Managing older people in the emergency department remains a challenge. We aimed to identify the factors influencing the care quality of older patients in the emergency department, to fine-tune future interventions for older people, considering the naturalistic context of the ED.This is a qualitative study of some 450 h of observations performed in three emergency departments selected for their diverse contexts. We performed seventy observations of older patient trajectories admitted to the emergency department. Themes were extracted from the material using an inductive reasoning approach, to highlight factors positively or negatively influencing management of patient’s trajectories, in particular those presenting with typically geriatric syndromes.Four themes were developed: no geriatric flow routine; risk of discontinuity of care; unmet basic needs and patient-centered care; complex older patients are unwelcome in EDs.The overall process of care was based on an organ- and flow-centered paradigm, which ignored older people’s specific needs and exposed them to discontinuity of care. Their basic needs were neglected and, when their management slowed the emergency department flow, older people were perceived as unwelcome. Findings of our study can inform the development of interventions about the influence of context and organizational factors. Older people (OP) account for 12–24% of emergency department (ED) admissions . They arManagement of OP in EDs is, thus, a qualitative and quantitative challenge, which means that emergency professionals have to deal with an increasing number of OP, more often suffering from multiples chronic pathologies and atypical presentations of acute diseases , 6. InteOur study aims firstly to describe procedures for managing older patients in EDs, especially those presenting with typically geriatric issues; secondly, to explore factors that positively or negatively influence care quality in the naturalistic context of the ED.16. The investigation included observations of OP trajectories, in order to describe and analyze the specific process of care for OP in EDs.We used a qualitative design suitable to the study of processes and the exploration of mechanisms affecting care qualityThe study was conducted in three Belgian sites selected for their diverse contexts. Two were in teaching hospitals in an urban area. The third was in a medium-sized hospital in a region peripheral to this previous urban situation. Each had a geriatric department, making collaboration theoretically possible. We included 3 sites to enrich the observations and not for comparison purposes.The field researcher (IDB), a geriatrician, conducted observations for 1 month per site on weekdays in the daytime, starting with the first morning shift. Observations focused on management of OP admitted to EDs, involving ED staff, patients, and relatives. They mainly began at the front desk and ended at patient discharge from EDs. The investigator then followed the next older patients admitted at the front desk. When several arrived simultaneously, the researcher chose those with a main complaint not yet observed or a typically geriatric feature.Field notes were taken, including details of trajectory, geographical details, and care process, as well as personal notes. Ad hoc field interviews supplemented the observation data .Field notes were fully transcribed and analyzed by the researcher who did the observations. She regularly met a senior qualitative researcher (IA) and a geriatric medicine expert (PC) for critical review of the analysis; data were pseudonymized to these experts. Results were then discussed with a panel of experts in emergency care, qualitative analysis, and public health medicine.All notes were repeatedly read carefully to ensure appropriate content and general understanding. Analysis was then performed in two phases, combining framework and inductive coding. The first phase aimed to identify elderly patients with typical geriatric problems, while the second phase aimed to explore inductively the factors that influence the quality of care for these identified patients.We based our analysis on Donabedian’s conceptual framework for evaluation of care quality, with a main focus on organizational (as part of structure) and care process, including interaction within and between practitioners and patients . AnalysiFalls, delirium, and functional decline were analyzed more deeply, as they are frequent reasons for ED admission, are often atypical symptoms of a hidden acute disease, and are likely to predict adverse outcomes in OP , 17, 18.The second phase of analysis was carried out on the material collected from the patient trajectories identified in the first phase. To develop themes relating to factors that positively or negatively influence the management of these geriatric presentations, we used an inductive reasoning approach –21.At the beginning of the process, some particularly challenging trajectories were coded independently by IDB and IA who met several times to discuss the issues until consensus was reached. The four analytical themes developed were: no geriatric flow routine; risk of discontinuity of care; unmet basic needs and patient-centered care; complex older patients are unwelcome in EDs.All methods were performed in accordance with the relevant guidelines and regulations. The study, its qualitative method and the written informed consent process with the emergency department Head was approved by the IRB Biomedical Ethics Commission Hospital-Faculty of UCLouvain (2010/25jui/81). The ethical officials of the three anonymized hospitals in which the observations were conducted gave their written approval to the study.The study used naturalistic observations conducted in collectivities, i.e. emergency departments. This implies adaptation of ethical consent –24.First, an informed consent form has been submitted to the relevant institutional officials following recommendations for naturalistic observation of a process. Written informed consent was obtained from the ED head, as representative of the emergency department staff, after a presentation of the study to the staff of the departments, as a group.Second, the researcher (IDB), a geriatrician, was an overt non-participant. Professionals, patients, and/or relatives were informed about the researcher’s role; a written research summary, including contact information, was available on request. Verbal consent was systematically and directly requested by IDB from all those present during the study, including ED staff, patients, and their family/carers, prior to observation. Contact information and prolonged immersion in the wards allowed to create the conditions to exercise free informed consent at any time. This respects the key principle of human autonomy. Moreover, potential harms arising from participation in the research were considered as no greater than those arising under usual practice.primum non-nocere).Specifically, and although they were not direct subjects of the research, the patients were an important concern throughout the observation process. We supported a not strictly normative ethical attitude, which sought to preserve the principle of autonomy and non-maleficence towards patients. IDB therefore systematically informed patients about her presence, the aim and modalities of the study, answered any questions, asked for verbal consent, and made her contact details available. When patients suffered from overt cognitive impairment, this process was performed with a relative, present on site. If this could not be achieved, the observations were directed towards the professionals rather than the patients themselves, aiming to respect their intimacy, while not soliciting them for the research , high risk of delirium , and functional decline   patients, while 63 (90%) presented with at least one of the three typical geriatric presentations, i.e. falls .“I always skip it [screening]; it is in the wrong place and should be part of triage, and I forget it. Whereas charging, we’ve been drilled, we don’t forget it.” ; “there are more urgent things; I forget items; it’s not difficult, but going through it every time, ugh!” . This highlights the low priority given to geriatric “triage” compared to other, purely technical and financial tasks. In particular, systematic screening for delirium and subsequent prevention measures were not part of standard procedures. However, repeated screening of elderly people for delirium, starting at triage, is of paramount importance, as it is a frequent and serious geriatric syndrome: precipitating factors must be rapidly assessed, and specific care and monitoring put in place to limit the consequences. Patients with a geriatric profile require a specific management, because of its inherent risk of adverse outcome following ED consultation and acute admission.ED caregivers generally had no triage routine to screen for a geriatric profile, including functional status, and identify older patients at risk of complications. One hospital had incorporated such a process, using a screening tool, into the nurse’s triage but implementation was almost never done: “to save time because we know what the doctors want” . Prioritization and categorization at the triage stage were of paramount importance for subsequent management. For example, a patient (H1–10) admitted by ambulance was not triaged by an ED nurse but sent directly to trauma for a fall, delaying treatment of an underlying heart problem. Moreover, when falls were the main reason for admission (n = 17), they were systematically labelled as traumatic issues. Preoperative assessment in 6 of these cases ruled out any urgent underlying somatic cause. However, minor trauma, particularly uncomplicated wounds, did not automatically lead to such assessments: management focused on the primary motivating category, e.g. “wound requiring suturing”. However, falls are also an important geriatric concern, as they are often an atypical presentation of an underlying medical problem to exclude. Being triaged and labelled as a “simple wound to repair” expose patients to incomplete evaluation and possible inadequate primary care and/or geriatric follow-up.Management followed two guiding principles, prioritization and categorization, to label the problem presented. Prioritization assigned an acuteness level; categorization specified the nature of the priority. This was to exclude organic health conditions requiring rapid treatment, e.g. hip fractures, and to maintain patient flow. In some cases, procedures requiring a prescription were initiated by a nurse, “So Dr J. phoned the lung specialist. The doctor she spoke to wanted an echocardiogram. I was surprised and asked Dr J why. She said she didn’t know why but she was doing it because she might lose out on a bed. She dressed the patient’s story up for the ultrasonographer, who agreed to conduct the examination.” (H1–8 observation and interview notes).Categorization also allowed implementation of a treatment plan, in particular to facilitate “negotiation for a bed” with a consultant, where necessary. A bed then became the priority. One of the hospitals allocated one nurse to this. Consultants contacted during the care pathway were mainly organ specialists, corresponding to the categorization. However, categorization in a specific specialty was often a challenge for multimorbid patients. Additional technical examinations were regularly used to facilitate negotiation for a bed. Consultants often set “technical” conditions for admission; this sometimes prolonged ED consultations, slowing down the flow and efficiency, with little added value for patients as explained by Dr. J.: “There is definitely no bed in the geriatric department. By the way, there’s never any bed in the geriatric department! Many people are not treated in the right department.” (H3–47 nurse’s interview).A geriatrician was called in for 12 of the 63 patients presenting with one of the three geriatric issues (19%), mainly to obtain admission to the geriatric ward, not for a specific advice for the management of these issues within the ED. Four of these patients already had a link with that department; six others had psychosocial issues and presented with deterioration in general status. The lack of beds in geriatrics was often mentioned, which could be one reason why a geriatrician’s advice was not sought: An average of five caregivers intervened per patient, including ED team members and others from other specialties. ED caregivers, moreover, changed during shift handovers and each was often responsible for several patients with different problems, priorities, and, possibly, very different timeliness. A high number of caregivers and care recipients could expose to discontinuity of care and loss of information. The case of Mr. F., aged 81, admitted from a rehabilitation center for a fall with a complicated wound (H3–55), illustrated the risks of this division of work for both care quality and ED flow. A 27-h stay, intervention by at least 12 professionals, and unclear leadership illustrated the difficulties of passing on the information needed to bring the pathway to an end. In some cases, the observer was approached by ED caregivers, mainly with regard to continuity of information. Observation of a self-appointed case-manager illustrated the importance of coordination of the care process in EDs: a woman aged 81 (H1–12) arrived with a cardiac rhythm problem at a busy time. Her grandson, an emergency nurse assigned to triage, acted as case-manager until she returned home, while complying with the established prioritization rules. He ensured that information was passed on within the team and to the patient, identified the additional examinations needed, and the responsible physician. Eight professionals were involved in this pathway, even though she only stayed for about 3.5 h.“I would like to put her in a bed because she’s in such pain ( …), but I still have two infusions to set up.” (nurses’ observation notes H1–6).Functional status rarely figured in the medical history or ED assessment. It was addressed in 9 of the 63 cases by an ED caregiver, including one social worker and one ambulance doctor, and spontaneously declared by the patient or a relative in two. Medico-technical care was the priority, often at the expense of traditional bedside and patient-centered care. Some ED caregivers managed to reconcile technical care with a more global approach. Nevertheless, these kinds of care were in competition, given the irregular flow of patients, which hindered efforts to meet basic needs such as comfort, pain relief, food, or hydration: “I like the [observation unit] and reception. I pamper my patients. Most here have flashing lights on their heads!”  (H1–6 observation notes and spontaneous nurse’s declaration).Two ED caregivers were particularly attuned to these basic needs. They had experience with a different care paradigm. A social worker provided in-home coordination that took account of the patient’s functional status and preferences . One nurse – who had worked on a pediatric ward – was particularly attuned to patients’ basic needs (H1–6): she was quite respectful and took the time to explain the steps. She put a cover over her, ensured she was comfortable, and tried to reassure her. She talked about her previous experience, which wasn’t typical for an emergency nurse … Furthermore, management was carried out without consulting older people and considering their priorities, which led to unexpressed and therefore missed needs. They were deemed to have agreed to the process, without consulting them for approval about management. Although rarely involved in decisions, they seldom complained about this. But they sometimes addressed information requests and basic care concerns to the observer. A relative can be a precious resource, mainly as companionship for the patient, for communicating basic needs and transmitting information. For patients with cognitive disorders, conclusions and treatment plans were entrusted to a relative. In one case, daughters adopted a more proactive attitude, disagreeing with the doctor’s conclusion that “the assessment had turned up nothing unusual” and with “the decision to send the patient back [to the nursing home] without any explanation [of the symptoms] …. They requested a second opinion …! Dr. Y … contacted the geriatric department. He was not convinced that hospitalization was justified, even if he sympathized with the daughters. , highlighting an emotional dimension of the evaluation.During certain observations, the issue of caring for elderly patients was raised with ED professionals.“They have often called the family doctor [unlike younger patients]. If they come to the hospital to be admitted [to a hospital care unit], it is often at the request of the family, who want to get rid of the parents.”  “Some people call an ambulance to jump the queue – young people, not older people. Older people seem ‘stronger’.”  Moreover, prioritization seemed to be easier for older people “because either they [older people] arrive by ambulance and are by definition priority or they are accompanied.” .Its legitimacy was almost never questioned at the front desk or at the triage step, or at least the elderly patient was not blamed. They were often legitimized by their general practitioner’s referrals and stereotyped in such a way that if they present at ED, it is because they could not do otherwise, that they do not abuse the system: “We don’t have much time, but they take up a lot of time even though there are so many people [in the waiting room]” . “They block up the emergency department” . “I don’t like geriatrics … [in the ED] you have to work quickly and nothing is simple with elderly patients.” .However, during subsequent stages, old age was often associated with complexity of care – one caregiver even referred to troublesome cases (H3–55 observation notes) – and/or slowness, things that do not fit the current emergency department care model (H2–43 interview Dr. M). “if one weeps and cannot cope” .The feeling that older patients are a burden was indirectly illustrated by overestimations of their proportion in EDs . One caregiver described his/her distress when admitting older patients in the ED observation unit, saying [he/she] was incapable of taking care of them...and needed help “understand why this patient has been sent in [before the weekend], especially since she has come from a nursing home” ; the second observed: “when elderly people come in at night, it really is serious … or it’s a nursing home that sends them in because they can no longer cope.” .Although the legitimacy of presenting at the department was rarely questioned directly, two doctors criticized the failure of care in nursing homes. One described a case as “prophylactic” and could not These attitudes may be associated with stereotypes about elderly patients, which may explain, e.g., a caregiver mainly addressing a daughter before realizing that the patient was cognitively sound (observation notes H2–45). One professional ignored the patient and seemed uninterested in treating the elderly (observation notes H2–40). This recalls ED caregivers’ problems with consultants reluctant to admit elderly patients, as they want patients to fit their specialty’s parameters .For many years now, several projects have sought to meet the challenge of treating the elderly in emergency wards. The findings of this empirical study describe processes that may put OP at risk and factors that influence care quality in EDs. This knowledge is important to fine-tuning ED procedures for OP, considering the naturalistic context of the ED.Our results raise important concerns: while nine out of ten patients had at least one typical geriatric issue, the technical and highly specialized management process in the emergency department did not meet their specific needs, even the most basic ones, highlighting some thorny issues, particularly that of neglect.The four themes discerned in their management were similar in the three hospitals: no geriatric flow routine, risk of discontinuity of care, unmet basic needs patient care needs and, finally, complex older patients are unwelcome in EDs.First, although almost all patients would have benefited from screening for psycho-cognitive and functional status, procedures were not adapted to their assessment. Emergency caregivers adopted a sort of batch processing, performing multiple tasks for which they followed set categories and priorities, based on biomedical considerations. They aimed to exclude organic conditions that could be treated quickly and to maintain patient flow, including finding beds for some. As older patients were often hospitalized, the lack of beds was possibly one factor in the limited contact with geriatric departments. Triage was of particular importance, as it determined subsequent management. At the start of triage, the biomedical care process applied was inadequate to ensuring quality of care for older patients, particularly those presenting with geriatric issues: falls were not systematically recognized as possible consequences of underlying medical problems and delirium was not screened. Failure to recognize these syndromes could mean unmet needs and further adverse outcomes, a matter of concern in the literature –4. More Second, a great many caregivers intervened during older patients’ care pathways; specialized skills and expertise imply a division of labor. Our results showed that lack of coordination exposed OP to care fragmentation and information loss. As care fragmentation is a well-known source of medical errors and negative experiences of emergency department care , 31, ourThird, the priority given to medico-technical care was often at the expense of patient-centered and bedside care, a conflict already described by some authors , 33. FaiFourth, the burden of treating older patients who don’t fit the usual ED care process was often raised; they were described as bed-blockers and unwelcome patients by some caregivers. OP legitimacy is the subject of previous studies, in light of the tension between flow management and clinical, organizational, and social categorization , 26, 28.Limitations are discussed following Lincoln and Guba’s criteria . The obsOur observations provide a unique empirical insight into management of OP in EDs, including the different actors intervening, while bearing in mind the difficulties of the ED environment. Awareness of the specific presentations of OP, early in the triage stage, would make it possible to better categorize the problems in question. Furthermore, it would make it possible to anticipate and set in motion specific “geriatric” processes and procedures to meet both the needs of elderly people and the requirements of patient flow. Reducing inappropriate ED admissions by early identification of frail patients and care planning in view of their needs and preferences could be an option, but would be insufficient and would risk discrimination against OP. The acute care process should be adapted to this population, at greater risk of admission than others. Particular attention should be paid to care for OP, to prevent negative images and inappropriate attitudes in EDs. Acknowledging that ED organization is unsuited to OP needs and the introduction of specialized caregivers may improve the overall process. Such changes go beyond the emergency setting, however, and should extend to the entire care network and policy for OP.