The research team, led by Wei Wang and Boyuan Lu of the University of Wisconsin-Madison and Peking University, together with colleagues at the University of Maryland and Peking University’s Department of Sociology, exploited a natural experiment embedded in the timing of the December 2015 alerts. Beijing’s red haze alerts, the most severe tier in the city’s emergency response system, were triggered by forecasts of sustained heavy pollution and came bundled with dramatic countermeasures, including restrictions on vehicle use, suspension of industrial production, and closures of schools and construction sites. Because the alerts arrived suddenly and applied citywide, the researchers could compare the pollution estimates of people surveyed before the alerts with those of people surveyed after, treating the intervention much like a randomized treatment in a laboratory setting.

The study combined two sources of data. The first was official air-quality monitoring information from the Beijing Municipal Ecological and Environmental Monitoring Center, which provided objective benchmarks for fine particulate matter concentrations, known as PM2.5, and for the frequency of yellow-level haze days, a milder pollution category. The second was a survey experiment involving 947 university students who were randomly assigned to report their perceptions of pollution conditions either before or after the red alerts. By asking participants to estimate pollution levels and then comparing those estimates against monitored values, the researchers could quantify the estimation gap with unusual precision for a social science study of environmental perception.

The headline result is striking. Among students who reported being aware of the red alert, mean overestimation of PM2.5 concentrations fell from 49.90 percent above monitored values to 30.53 percent. The correction was even more dramatic for yellow-level haze days, a category that most residents would find harder to judge from memory: overestimation collapsed from 178.89 percent to 87.43 percent. In other words, before the alerts, students believed mild haze days were nearly three times more common than the monitoring record showed; afterward, their estimates were less than twice the true figure. Multivariate statistical models that controlled for individual characteristics confirmed these reductions, estimating that the red alert cut PM2.5 overestimation by 19 to 27 percent and yellow-level haze-day overestimation by 92 to 147 percent.

These numbers speak to a well-documented puzzle in the literature on environmental risk perception. Decades of research, stretching back to foundational work on judgment under uncertainty by Amos Tversky and Daniel Kahneman, have shown that people rely on heuristics and salient memories rather than statistical records when assessing hazards. Air pollution is a particularly tricky case because its severity varies across space and time, is often invisible at low concentrations, and is filtered through media coverage, personal symptoms, and social conversations. Previous studies in China and elsewhere have found that self-reported pollution levels routinely diverge from station data, sometimes wildly, and that these mismatches can distort protective behavior, undermine trust in government statistics, and complicate emergency management. The Beijing study suggests that a single, highly salient official alarm can serve as an anchoring event that resets the reference point people use when making subsequent judgments.

The mechanism the authors propose is consistent with salience theory in behavioral economics. A red alert is not just information; it is a dramatic, citywide signal that makes pollution cognitively available and provides a concrete benchmark against which past and present conditions can be evaluated. Once residents know that a red alert corresponds to a specific, severe pollution state, they apparently recalibrate their internal scale, becoming more accurate not only about extreme episodes but also about milder yellow-level conditions. This spillover from high-severity signals to lower-severity judgments is one of the study’s most interesting technical contributions, because it implies that extreme warnings do more than communicate the immediate emergency; they teach the public where the whole pollution distribution sits.

Yet the alert’s effects were strikingly selective when it came to evaluations of government mitigation efforts. The researchers examined whether the red alerts changed how students assessed specific policy responses, including vehicle restrictions, factory shutdowns, urban greening programs, and restaurant regulations. Only the vehicle restriction policy showed a significant increase in recognition and evaluation. The authors attribute this asymmetry to measure visibility: odd-even license plate rules remove half the cars from the streets, an effect that any commuter can directly observe, whereas factory closures, tree planting, and restaurant oversight happen largely out of public view. Assessments of those less visible measures did not shift at all in response to the alert. For policymakers, this is a sobering result, because the measures that are hardest for citizens to see are precisely the ones whose public support may depend on deliberate communication rather than ambient visibility.

The study also probed whether the alerts changed self-reported protective behavior, such as wearing masks or limiting outdoor activity, and whether gender shaped the accuracy of pollution estimates. On both fronts the results were more muted. Changes in protective behavior were modest and statistically insignificant, and gender had no significant effect on overestimation, a finding that runs counter to some earlier literature reporting systematic gender differences in environmental risk perception and pro-environmental behavior. The authors are careful not to overclaim here; a survey of university students, however well designed, captures a specific population at a specific moment, and self-reported behavior is vulnerable to recall and social desirability biases that the study’s own framing acknowledges.

Those limitations are worth taking seriously, but they do not erase the central contribution. By pairing a randomized survey design with objective monitoring data and a genuine policy shock, the study moves the field beyond the correlational snapshots that have dominated perception research. It demonstrates causally, not just associatively, that high-severity environmental alarms function as reference signals that narrow the perception gap. It also identifies the boundary conditions of that effect: the correction applies to pollution estimates but not automatically to policy evaluations, and it operates through visibility, meaning that invisible mitigation work remains invisible even during a crisis. The practical implication is that warnings and transparency must travel together. An alert can teach the public what severe pollution looks like, but only visible, well-communicated policy action can convert that heightened attention into durable trust in the institutions managing the air.

As cities worldwide grapple with wildfire smoke, dust storms, and industrial smog in a warming climate, the Beijing red alert experiment offers a template for evidence-based risk communication. Emergency warnings are often evaluated solely by whether they prompt immediate protective action, a metric on which this study found only weak effects. But the research suggests a second, subtler function that has been largely overlooked: alarms as calibration devices that align public perception with scientific measurement. If subsequent studies replicate these findings in other cities and populations, environmental agencies may come to see their most severe alert tiers not just as sirens but as teaching moments, brief windows in which the public is unusually receptive to learning what the numbers on the monitor actually mean for the air in their lungs.

Subject of Research: The effect of high-severity air pollution alerts on public perception accuracy and policy evaluation during Beijing's 2015 red haze alerts

Article Title: High-severity environmental alarms as reference signals: Evidence from Beijing’s first red haze alerts

Article References: Wang, W., Lu, B., Zhang, X., Fan, X., & Zhang, W. (2026). High-severity environmental alarms as reference signals: Evidence from Beijing’s first red haze alerts. Air Quality, Atmosphere & Health, 19(10), Article 228. https://doi.org/10.1007/s11869-026-02117-y

Image Credits: AI Generated

DOI: 10.1007/s11869-026-02117-y

Keywords: air pollution, PM2.5, red haze alert, risk perception, Beijing, environmental communication, survey experiment, public trust, protective behavior, salience theory, emergency response, environmental monitoring

The study, conducted in May 2025, recruited resident physicians from nine tertiary Grade III, Class A general hospitals spread across eight provinces spanning the southern, eastern, northern, western, and central regions of China. Participants were drawn through a combination of convenience and stratified sampling, a design intended to capture the diversity of China’s hospital landscape rather than a single institution’s experience. Of the 151 physicians enrolled, 133, or 88.1 percent, completed assessments both one week before and immediately after the exercise, giving the researchers a substantial paired dataset for analysis.

Perhaps the most striking finding in the baseline data is how unprepared this cohort was on paper before the training began. Only 7.52 percent of participants reported having received any previous disaster training, and a mere 0.75 percent, effectively one or two individuals in the entire sample, had actual disaster response experience. For a country that faces earthquakes, floods, industrial accidents, and mass-casualty events, the near-total absence of hands-on disaster preparation among frontline trainee physicians underscores a systemic vulnerability that the authors argue deserves urgent attention from medical educators and hospital administrators alike.

The intervention itself was a disaster-management-focused tabletop exercise, or TTX, a format long used in military planning, public health preparedness, and corporate crisis management. In a tabletop exercise, participants gather around a table and work through a scripted but realistic disaster scenario, discussing and deciding how they would triage patients, allocate scarce resources, communicate with command structures, and coordinate with prehospital services. Unlike full-scale simulation drills, tabletop exercises require no physical equipment, no simulated casualties, and no disruption to hospital operations, which makes them inexpensive, scalable, and easy to embed into existing residency curricula. The trade-off is that they test decision-making and communication rather than physical procedural skills, which is why the researchers paired the exercise with independent instructor observation rather than relying solely on self-report.

The statistical results were consistent across every psychological outcome the team measured. Perceived disaster management capability, self-confidence, satisfaction with learning, and critical thinking all improved significantly after the exercise, with all comparisons reaching P < 0.001. Because the data were not normally distributed, the researchers used non-parametric Wilcoxon signed-rank tests, reporting a Z statistic of −9.945 for the change in perceived capability. The effect size of r = 0.86 is unusually large for an educational intervention, suggesting that the exercise did not merely nudge perceptions but fundamentally restructured how these physicians understood their own readiness for disaster work.

Regression analysis added an important layer of nuance to the findings. When the researchers modeled which factors independently predicted higher post-exercise perceived capability, two variables emerged: self-confidence in learning (B = 9.385, β = 0.315, P = 0.003) and critical thinking (B = 4.142, β = 0.303, P = 0.001). In practical terms, residents who came away from the exercise feeling more confident and thinking more critically about disaster scenarios also rated their overall disaster management capability higher. This pattern supports a theoretical model in which scenario-based learning works not by transmitting facts but by activating metacognitive processes, forcing learners to reason through uncertainty, defend decisions to peers, and confront the limits of their own knowledge in a psychologically safe setting.

The study did not rely exclusively on subjective self-assessment, and this is where its design becomes particularly instructive. During the training, instructors independently completed a surge-capacity assessment checklist, evaluating how well participants executed specific disaster-response tasks. The instructors rated a significantly higher proportion of fully implemented items during the in-hospital phase of the exercise than during the prehospital phase, 57.9 percent versus 36.7 percent, a difference that reached statistical significance at P = 0.031. When the researchers drilled down into the first-level dimensions of the checklist and applied a Holm correction for multiple comparisons, only resource requirements remained significantly different between phases (adjusted P = 0.047), while no second-level dimension survived the correction. The pattern, however, was clear enough to carry a practical message: these young physicians were notably weaker at the prehospital interface, the chaotic zone between the disaster scene and the hospital doors.

That weakness matters because prehospital emergency response is where disaster medicine most often fails in real events. Decisions about field triage, casualty collection points, ambulance distribution, and communication with incident command happen before a patient ever reaches the emergency department, and a hospital physician who has never rehearsed that interface may struggle to integrate incoming information with in-hospital surge capacity. The authors explicitly highlight the need for greater emphasis on prehospital emergency response in future disaster preparedness training, suggesting that tabletop scenarios should deliberately extend their narratives beyond the hospital walls to include the full chain of evacuation, transport, and handover.

The study’s methodology reflects careful attention to research ethics and validity. The protocol was approved by the Ethics Committee of Naval Military Medical University prior to data collection, and the study was conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent after being fully informed of the study’s background, procedures, and objectives, and questionnaires deliberately excluded names and personal identifiers to protect confidentiality. The research team, led by first authors Dan Han, Chen Qiu, and Mengxing Qian, with corresponding author Jingjing Liu of the First Affiliated Hospital of Naval Medical University, also acknowledged eleven experts who helped develop the surge-capacity assessment indicator system, lending the observational component a structured, consensus-based foundation rather than an ad hoc checklist.

For the international medical education community, the implications extend well beyond China. Resident physicians worldwide receive notoriously little formal disaster training, and full-scale simulation drills are expensive, logistically complex, and difficult to repeat frequently enough to build durable competence. The Chinese results, showing very large gains in perceived capability, confidence, satisfaction, and critical thinking from a single scenario-based tabletop session, make a compelling economic and pedagogical case for embedding TTX into standard residency curricula. The authors are careful to frame their findings as associations rather than proof of causation, and the single-group pre-post design without a control arm means some improvement could reflect test-retest effects or enthusiasm. Still, the magnitude of the changes, the multi-province sampling, and the independent instructor observations together make a strong argument that when it comes to disaster preparedness, a table, a scenario, and a room full of trainee physicians thinking aloud may be one of the most cost-effective educational interventions available to hospitals today.

Subject of Research: Scenario-based tabletop exercise training for disaster preparedness among resident physicians in China

Article Title: Educational effectiveness of scenario-based tabletop exercises for disaster preparedness among resident physicians in China

Article References: Han, D., Qiu, C., Qian, M., Hu, X., Gao, J., & Liu, J. (2026). Educational effectiveness of scenario-based tabletop exercises for disaster preparedness among resident physicians in China. BMC Medical Education. https://doi.org/10.1186/s12909-026-10527-w

Image Credits: AI Generated

DOI: 10.1186/s12909-026-10527-w

Keywords: tabletop exercises, disaster preparedness, resident physicians, medical education, emergency response, surge capacity, critical thinking, self-confidence, prehospital care, China, simulation training, BMC Medical Education

The study arrives at a moment when wildfire has become an inescapable feature of Southern California life. Los Angeles sits in a landscape where fire ecology predates human settlement by a millennium; chaparral ecosystems historically burned roughly every thirty years, with extended droughts allowing dead vegetation to accumulate as fuel. Fire, in turn, rejuvenates chaparral seeds that inhibit germination until after a blaze, returning nutrients to the soil and enabling new growth. That natural cycle now collides with millions of residents, and the catastrophic fires of recent years have pushed questions about disaster and social order into public debate. Popular narratives often assume that disasters unleash looting and lawlessness, but decades of criminological research on hurricanes, floods, and tornadoes tell a more complicated story, and wildfires have remained a conspicuous gap in that literature.

To close that gap, the researchers assembled tract-level data for the City of Los Angeles and identified seven major wildfires that occurred inside the municipal boundaries during the 2016 to 2022 window. Their statistical strategy centered on random-effects negative binomial regression models, a choice tailored to the structure of crime data. Crime counts in small geographic units are overdispersed, meaning their variance exceeds their mean, and a negative binomial framework accommodates that distribution far better than ordinary linear regression. The random-effects specification, meanwhile, accounts for unobserved, stable characteristics of each census tract, such as entrenched disadvantage or built environment features, that could otherwise confound the estimated relationship between fire exposure and crime.

The team measured wildfire exposure in two distinct ways, and that distinction turned out to be analytically decisive. The first measure identified census tracts that experienced direct wildfire damage, that is, tracts where the fire itself burned. The second captured proximity, identifying tracts located within a quarter mile of burned areas even if no fire touched them directly. Separating these two forms of exposure allowed the authors to test whether the crime effects of wildfire are confined to physically damaged neighborhoods or spill over into surrounding communities, a question with direct implications for how police and emergency managers allocate resources after a disaster.

The results paint a nuanced picture. Census tracts that experienced direct wildfire damage reported significantly lower levels of property crime. Violent crime was also marginally lower in those directly burned tracts, though the evidence there was weaker. When the researchers accounted for proximity to wildfire damage, however, the direct-damage effect on property crime was no longer statistically significant. What proved most robust was the proximity effect: tracts within a quarter mile of burned areas reported significantly lower levels of both violent and property crime. In other words, the strongest crime-suppressing signal appeared not in the neighborhoods the flames consumed, but in the neighborhoods standing just outside them.

The authors interpret these findings through the lens of two foundational criminological frameworks. Social disorganization theory holds that neighborhood crime is shaped by the capacity of local communities to exercise informal social control, a capacity rooted in stable networks, shared trust, and collective efficacy. Disasters can disrupt or reorganize those networks in unpredictable ways. Research after Hurricane Katrina, for example, documented both crime displacement and, in some domains, strengthened collective resources among repopulating residents. The routine activities approach offers a complementary mechanism: crime requires a motivated offender, a suitable target, and the absence of a capable guardian converging in time and space. Wildfires radically alter that convergence calculus. Evacuations empty neighborhoods of suitable targets, closed roads and fire-perimeter checkpoints supply guardianship, and burned or damaged structures simply cease to be burglarizable.

The proximity finding fits neatly into this routine-activities logic. A quarter-mile buffer around a burned area is precisely the zone where emergency access controls, evacuation orders, utility shutoffs, and heavy first-responder presence are most intense, even when the homes themselves remain intact. Fewer people on the street, restricted vehicular movement, and a saturated official guardianship presence can suppress both opportunistic property offenses and interpersonal violence. At the same time, the social disorganization perspective suggests that shared threat experiences can galvanize neighborly cohesion, with residents monitoring one another’s properties and coordinating informally during and after evacuations. The study cannot adjudicate between these mechanisms, but the spatial pattern it documents, with effects strongest near rather than within fire perimeters, is consistent with guardianship and mobility explanations operating at the edge of disaster zones.

The findings also connect to a broader and rapidly growing research program on environment, green space, and crime. Recent work has linked urban greenspace to lower crime risk across hundreds of major U.S. cities, examined park size and community safety, and used quasi-experimental designs to test whether urban greenways such as the Atlanta Beltline reduce offending. Related studies have explored how drought conditions relate to violent crime trends in California counties and how natural hazards reshape spatiotemporal crime patterns nationally. The Los Angeles wildfire analysis adds a distinctive dimension to this literature: rather than a gradual environmental amenity, wildfire is an acute, spatially bounded shock, and its crime effects appear to radiate outward from the burn scar in measurable ways.

For practitioners, the implications are concrete. If crime genuinely declines in and around burned neighborhoods, then post-fire policing strategies premised on looting panics may be misdirected, diverting officers from communities where they are actually needed and potentially exposing evacuated areas to over-policing. Emergency response planning, similarly, could incorporate the finding that a quarter-mile buffer around fire perimeters functions as a distinct criminological zone, one where the priorities may be public safety and recovery support rather than crime suppression. For neighborhood recovery, the results hint that the social fabric of fire-adjacent communities may be more resilient than disaster folklore assumes, though the authors caution that their analysis captures associations over a defined study period rather than the full arc of long-term recovery.

The authors are explicit about the limits of their design and the directions it opens. Their data cover seven wildfires within one city over seven years, and census tracts, while useful units of neighborhood analysis, aggregate individual behavior into coarse spatial bins. The proximity threshold of a quarter mile is one plausible buffer among many, and future work could test whether the effect decays smoothly with distance or exhibits spatial spillovers of the kind modeled in wildfire risk mitigation research. Longer follow-up periods could reveal whether suppressed crime rebounds as neighborhoods rebuild, whether reconstruction and gentrification dynamics, of the kind documented after the 1994 Northridge earthquake in Los Angeles, reshape local crime trajectories, and whether the patterns hold in other fire-prone regions. As climate change intensifies fire regimes across the American West, understanding how wildfires reshape not only landscapes but also the social order of the neighborhoods that survive them is becoming an urgent scientific question, and this study provides one of the clearest spatial maps yet of where that reshaping begins.

Subject of Research: The association between neighborhood wildfire exposure and violent and property crime patterns in Los Angeles

Article Title: We Didn’t Start the Fire: How Neighborhood Crime Patterns in the City of Los Angeles Were Associated with Wildfires

Article References: Barton, M. S., Valasik, M., LaPointe, R., & Lopez, S. (2026). We Didn’t Start the Fire: How Neighborhood Crime Patterns in the City of Los Angeles Were Associated with Wildfires. American Journal of Criminal Justice. https://doi.org/10.1007/s12103-026-09955-7

Image Credits: AI Generated

DOI: 10.1007/s12103-026-09955-7

Keywords: wildfires, crime, Los Angeles, violent crime, property crime, social disorganization theory, routine activities approach, disasters, criminology, neighborhoods, negative binomial regression, emergency response

The rationale for studying mobile units in disaster contexts is grounded in a well-documented pattern of care interruption. After the 2011 Christchurch earthquake, all appointments were canceled for two weeks because neither patients nor providers could reach offices, laboratories, or electronic medical records. Hurricane Katrina produced a longer and larger disruption, contributing to a 15.9 percent increase in morbidity among older, nonwhite residents of New Orleans in the year after the storm. When the Boston Marathon bombing occurred in 2013, hospitals activated emergency responses and canceled inpatient and outpatient services to free resources for the surge of blast victims. In some cases, disaster aid can temporarily expand capacity, as when international funding after the 2010 Haiti earthquake rebuilt seven of eight damaged facilities and brought twelve new ones online. Yet the COVID-19 pandemic was unique in its temporal and geographic scope, and about half of surveyed U.S. hospital leaders reported reduced quality of care and worse outcomes for non-COVID patients between November 2020 and June 2021.

Mobile health units occupy a distinctive niche in this landscape. They are community-based vehicles that deliver direct clinical services, from primary and preventive care to dental work, cancer screenings, substance use treatment, and maternal and child health. After Hurricane Sandy, MHUs delivered services disrupted by damage to New York’s healthcare infrastructure and reached residents displaced from damaged homes. Globally, they range from basic nutrition and infectious disease surveillance to urgent surgical care. The mobile healthcare field in the United States and Canada is represented largely by the Mobile Healthcare Association, founded in 2005, and the Mobile Health Map. During the pandemic, the MHA hosted virtual meetings on the strengths and limitations of MHUs for pandemic response, and members contributed to a resource library of seminars and literature. One member, an Atrium Health unit in Charlotte, North Carolina, documented key lessons from its COVID-19 vaccination program for vulnerable communities, including the need to reach people where they live, address financial and legal barriers, confront longstanding mistrust of healthcare, and overcome logistical challenges.

To capture operational lessons systematically, the research team conducted key informant interviews with leaders of the MHA’s fourteen regional coalitions, which span Florida, Illinois, the Mid-Atlantic, Missouri, Native American communities, New England, New York City, North Carolina, Northern California, Ohio, the Pacific Northwest, the Southeast, Southern California, and Texas. Coalition leadership teams totaling forty-one individuals were contacted by email with up to three reminders. The five-question interview guide, developed with Delaware-based mobile health clinicians, asked about roles in the COVID-19 response, alterations to services, experience with other disasters, impacts of emergency orders and control measures, and lessons that might carry into routine operations. Thirty-minute interviews were conducted over Zoom, recorded with verbal consent, and transcribed. Analysis followed Braun and Clarke’s six-phase thematic coding approach, with themes mapped onto the public health emergency preparedness constructs of Handler and colleagues and Mays and colleagues. The University of Delaware Institutional Review Board determined the study exempt.

Ten interviews were completed, a 71.4 percent response rate from the fourteen coalitions, conducted over eleven months in 2023 and 2024. Respondents represented clinics in the Northeast, Midwest, South, and West, providing primary and preventive care, maternal and child health, substance use services, cancer screening, dental care, and vision services. Most were funded by hospitals or universities, with others supported by state government, federal funds, or grants. Eight units were operational before the pandemic public health emergency declaration; two launched during it. Four themes emerged from the analysis: the temporary halt of care during COVID-19, adjustments made when operations resumed, the evolving complexity of preparedness needs, and concerns about other natural disasters and emergencies.

The halt of services was universal among pre-pandemic units, and the consequences for vulnerable patients were stark. One respondent described people struggling with addiction who lost access to counseling and mutual support meetings, leading to a visible uptick in use, overdoses, and deaths. Dental clinics faced longer shutdowns because CDC guidance on aerosol-producing procedures halted their work entirely. Community partnerships proved decisive during this period. A Mid-Atlantic hospital system was inspired to create its own mobile health program after witnessing a community organization’s unit at a COVID-19 response event, and the two now partner to build engagement and trust. A Southeast clinic emphasized tailoring services to what the community says it needs. Perhaps most striking was a Midwest substance use clinic once viewed with suspicion as a so-called Pied Piper by its host community. When it began providing COVID-19 tests required for work, school, and nursing home visits, perceptions shifted. The clinic director recalled that the unit suddenly became a solution to the problem, forming partnerships with shelters, community centers, schools, and group homes.

When operations resumed, the pace and shape of recovery varied. Independently operated clinics returned to service faster than those affiliated with hospitals or academic institutions, while specialty providers such as dental and cancer screening units faced longer interruptions under stricter federal safety protocols. Staffing was restructured to reduce exposure and improve efficiency: volunteers and part-time staff were reduced, check-in processes were streamlined with prepopulated forms, and some clinics spaced appointments across alternating weekends to avoid becoming vectors of transmission. Units that did not pivot to testing or vaccination instead targeted disparities that widened during the pandemic, particularly childhood immunizations. One respondent noted that many people fell behind on mammograms, blood pressure checks, HPV vaccinations, and childhood shots because they were afraid to leave their houses, and that mobile units are a way to bring people back up to date on multiple types of health screenings.

Preparedness itself evolved during the pandemic, sometimes in durable ways. Local and state policies and cultural norms often complicated vaccination and masking efforts, with respondents noting hesitancy in their states and contrasting American norms with the governmental mandates common in European countries. Yet many clinics institutionalized improvements born of necessity. One translated its consent forms into Spanish and migrated operations into the Epic electronic medical record system. Others redesigned vehicles: a new unit with two completely separated lanes and entrances more than six feet apart can still see forty patients during a future pandemic, while another clinic converted its vehicle into a mobile command center with a removable exam table, a conference table, full teleconferencing capability, and updated satellite-based internet connectivity. Seventy percent of informants said flexibility was essential to preparedness planning, and while most parent organizations had formal disaster response plans, not all specifically included mobile health. One leader cautioned that in novel situations, teams must stay educated and give the best advice they can based on the knowledge available at the time.

Concerns about non-pandemic hazards revealed the physical vulnerabilities of mobile operations. Half of respondents relied on the National Weather Service, the National Oceanic and Atmospheric Administration, and school or government closures for guidance, and three specifically cited air quality and high temperature warnings. Heat, snow, and poor air quality regularly forced cancellations or relocations. A Western clinic that has operated for years adjusts its schedule around snow, avalanches, and wildfires, staying in the metro area through winter and early spring, and when wildfires canceled a planned trip in 2022, its contingency plan allowed it to load the vehicle with donated supplies and hygiene items for the affected community. Flooding and hurricanes pose harder problems: respondents doubted an RV could traverse floodwater, and one noted that during hurricanes the unit must be moved to higher ground because its usual campus parking spot floods completely. Some newer clinics have yet to face a disaster but imagine distributing water or food after a severe hurricane, when utilities may take more than a month to restore.

The study’s discussion distills several factors critical to mobile health resilience. Leaders who advocated for continuous provision or rapid restart of services were pivotal, pushing governing healthcare systems to resume operations with new safety protocols, though pandemic-era burnout and turnover made such leaders difficult to replace. Strong community support emerged as the other major ingredient: clinics with existing collaborations with community and governmental partners adapted faster and reached their target populations more reliably, and three coalition leaders confirmed their operations resumed more rapidly because parent organizations prioritized community-based initiatives. The authors acknowledge limitations, including possible recall bias from interviews conducted up to four years after the pandemic began, a small sample of ten of forty-one potential participants, a sampling frame limited to coalition leaders, and the possibility that thematic saturation was not reached. Still, the implications are clear. Because local systems are generally expected to be self-sufficient for the first seventy-two hours after a disaster, mobile health units, with authentic community-engaged needs assessments, strong support from parent organizations and funders, and trust-building marketing in non-disaster times, should be embedded in emergency preparedness planning, training, and exercises as a resource for shortening care interruptions when disasters strike.

Subject of Research: Operational adaptations of mobile health units during the COVID-19 pandemic and their implications for disaster and emergency preparedness

Article Title: Mobile health units adapt to COVID-19: Lessons for operations in emergencies and disasters

Article References: Storm, A. H., Cuffee, Y. L., Ruggiero, L., Maguire, M., & Horney, J. A. (2026). Mobile health units adapt to COVID-19: Lessons for operations in emergencies and disasters. Public Health in Practice, 12, Article 100860. https://doi.org/10.1016/j.puhip.2026.100860

Image Credits: AI Generated

DOI: 10.1016/j.puhip.2026.100860

Keywords: mobile health units, COVID-19, disaster preparedness, public health, healthcare access, emergency response, community partnerships, health equity, surge capacity, qualitative research, Mobile Healthcare Association, care disruption

“In the first 48 hours of a major disaster like a hurricane, responders show up from all over the country to help and are often operating in an information vacuum,” says Brandon McConnell, co-author of the study and an associate research professor in NC State’s Edward P. Fitts Department of Industrial and Systems Engineering. The model was built specifically to address that vacuum, giving operational planners a data-driven starting point for deciding where to send boats, helicopters, and ground teams first, rather than relying on intuition or waiting for distress calls to accumulate.

The framework, described in a paper published open access in the International Journal of Disaster Risk Reduction under the title “Anticipating Household Rescue Demand in Hurricanes Using Socio-Demographic Data and Machine Learning,” rests on a straightforward but powerful premise: not all households face the same probability of needing rescue when a hurricane strikes. Decades of disaster research have identified factors that make people more vulnerable during such events, including physical disabilities that limit mobility, fewer financial resources that make evacuation difficult, lack of access to a vehicle, advanced age, and housing located in areas prone to flooding. The research team translated these established vulnerability factors into a predictive computational model.

Technically, the model draws on two complementary streams of publicly available federal data. U.S. Census data provide a fine-grained picture of the socio-demographic composition of each census tract, allowing the model to identify communities where a large share of residents are likely to have trouble evacuating in advance of a storm. National Flood Insurance Program data supply information on which areas face the greatest risk of flooding, indicating where those less-mobile populations are most likely to become trapped by rising water. By combining these inputs, the model produces a ranked map of expected rescue demand across an affected region before responders arrive on the scene.

A distinctive feature of the project is the perspective of its first author. Patrick Leavitt, who began the work while a graduate student at NC State, is an active-duty Coast Guard officer, and his first-hand experience with emergency response operations shaped how the team approached the problem. Rather than designing an abstract academic exercise, the researchers built the framework around the practical constraints responders face: the need for fast computation, the availability of data in real time, and the reality that every area will eventually be checked, but the order in which areas are searched can mean the difference between life and death for people trapped in attics or on rooftops.

“Specifically, we developed a predictive modeling framework to identify census tracts where residents are most likely to require rescue,” says Ben Rachunok, corresponding author of the paper and an assistant professor in NC State’s Fitts Department. “Responders will ultimately look in every area, but which areas are most likely to have people who require rescuing? If we can predict that, we can prioritize search efforts in those areas.” That prioritization logic is what distinguishes the tool from existing hazard maps, which typically show where flooding will occur but not where the intersection of flooding and human vulnerability will generate the greatest demand for rescue.

To test the framework, the researchers conducted a case study focused on Hurricane Harvey, the Category 4 storm that struck Texas in 2017 and caused catastrophic flooding across the Houston metropolitan area. Harvey is a particularly valuable test case because it produced one of the largest urban rescue operations in American history, with thousands of water rescues carried out by the Coast Guard, first responders, and volunteer rescuers. The team fed regional Census data and National Flood Insurance Program data into their model to generate predictions of which areas would be most likely to have residents trapped by floodwaters, and then compared those predicted high-priority zones against publicly available records of where rescues actually took place.

The comparison showed that the model performed well in identifying the areas where rescue demand concentrated. “Our framework did pretty well – it should be useful for responders in practice,” says Rachunok. “It’s not perfect, but even this version would be helpful – and we can put in the work to make it even better.” The researchers emphasize that the model is an initial version, and that its accuracy should improve with better data and continued refinement. Importantly, the model is computationally lightweight: it does not take long to run, which means it could be executed while responders are still deploying, handing them a prioritized list of search areas as soon as they arrive in the disaster zone.

“Being able to achieve these results with this initial version suggests we’re optimistic about its utility if we fine-tune the tool – particularly in instances where we have access to better data,” says McConnell. The team also sees applications beyond the immediate response phase. According to Leavitt, the research could support emergency managers during the planning phases of disaster preparedness, helping them develop response plans and design exercises that reflect realistic patterns of rescue demand. Because the model relies on data that are already collected and publicly available, jurisdictions could use it in advance of hurricane season to identify their most vulnerable communities and pre-position resources accordingly.

The researchers say they are open to collaborating with emergency management and disaster response leaders to improve the model itself and to make the tool more user-friendly for practical field use. As climate change increases the intensity of Atlantic hurricanes and coastal populations continue to grow, the demand for rapid, well-targeted search and rescue operations is only expected to rise. A predictive framework that turns census data and flood risk information into an actionable rescue priority map offers a glimpse of how data science can be woven into the earliest, most chaotic hours of disaster response – when every minute of saved search time can translate directly into lives saved.

Subject of Research: A predictive mathematical model that prioritizes census tracts for post-hurricane search and rescue operations using socio-demographic and flood risk data.

Article Title: New tool helps responders ID highest-risk areas for post-hurricane rescue efforts

Article References: New tool helps responders ID highest-risk areas for post-hurricane rescue efforts. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: hurricane, search and rescue, emergency response, flood risk, machine learning, census data, National Flood Insurance Program, Hurricane Harvey, disaster preparedness, Coast Guard, North Carolina State University, vulnerability mapping

The study was conducted by Omar Afeef Wattad of Assuta Medical Centers and the Emergency Department of Hillel Yaffe Medical Center, together with Merav Ben Natan of Tel Aviv University and the Hillel Yaffe Academic School of Nursing. Between May 2023 and May 2024, the researchers surveyed 300 registered nurses employed at a tertiary medical center in Israel, a country where the health system maintains a high state of alert for emergencies ranging from armed conflict to natural disasters. Participants completed validated self-report questionnaires measuring disaster preparedness, psychological disaster preparedness, the organizational work environment, resilience, optimism, and trait anxiety.

A central conceptual contribution of the work is the distinction it draws between two related but separate constructs. Operational disaster preparedness refers to the practical readiness to perform during an emergency: knowing the protocols, having the technical skills, and being able to function within a coordinated response. Psychological disaster preparedness, by contrast, captures the mental and emotional readiness to face a catastrophic event, including the ability to tolerate stress, anticipate one’s own emotional reactions, and remain psychologically stable under extreme pressure. The researchers found that the two dimensions were moderately correlated, with a correlation coefficient of 0.56, statistically significant at p less than 0.001. In plain terms, a nurse who feels operationally ready is somewhat more likely to feel psychologically ready, but knowing the drill does not guarantee emotional readiness, and vice versa.

To understand what drives each dimension, the team used descriptive statistics, correlation analyses, and multiple regression models that allowed them to isolate the independent contribution of each variable while controlling for the others. The results were striking. The full model predicting operational disaster preparedness explained 45.4 percent of the variance, a substantial share for a behavioral outcome in a real-world clinical population. Within that model, several factors emerged as positive independent correlates: workplace disaster training, optimism, lower trait anxiety, participation in organizational decision-making, adequate staffing and resources, good collegial nurse-physician relations, and completion of an advanced nursing course.

The picture for psychological preparedness was markedly different. The full model for that outcome explained 45.1 percent of the variance, almost identical in strength, but the predictor pattern diverged in important ways. Age, ward experience, resilience, staffing and resource adequacy, positive nurse-nurse interaction, and male gender were all positive independent correlates of psychological readiness. Most notably, workplace disaster training, which strongly boosted operational preparedness, was a negative correlate of psychological preparedness, and higher trait anxiety also predicted lower psychological readiness. In other words, the very training programs that make nurses technically proficient may, in some circumstances, leave them feeling less emotionally equipped, perhaps by heightening awareness of how overwhelming a real disaster could be.

These findings carry significant implications for how hospitals prepare their nursing workforce. For decades, disaster preparedness programs have concentrated on drills, protocols, and technical competencies, treating readiness as a matter of knowledge and skill. The new data suggest this approach captures only half the picture. A nurse can complete every training module and still feel psychologically unprepared to face mass casualties, and the regression results indicate that psychological readiness depends more on accumulated clinical experience, personal resilience, and the quality of daily working relationships than on formal instruction alone.

The organizational findings are equally consequential. Staffing and resource adequacy appeared as a positive independent correlate of both operational and psychological preparedness, making it the one organizational factor that bridges the two dimensions. This suggests that nurses who feel their ward has enough staff and adequate resources are not only better positioned to execute emergency procedures but also more confident in their own emotional capacity to cope. Participation in decision-making and collegial nurse-physician relations contributed to operational readiness, while nurse-nurse interaction contributed to psychological readiness, indicating that different facets of the professional practice environment matter for different aspects of preparedness.

The psychological variables tell a coherent story of their own. Optimism and lower trait anxiety both independently predicted stronger operational preparedness, while resilience was the standout psychological predictor of psychological preparedness. Trait anxiety, a stable disposition toward experiencing worry and tension, was associated with lower scores on both outcomes, and it appeared as a negative correlate of psychological preparedness even after adjustment. This pattern implies that anxiety management deserves a place alongside clinical skills in disaster education, and that interventions designed to build resilience could pay dividends in nurses’ emotional readiness for catastrophic events.

The demographic findings add further nuance. Older nurses and those with more ward experience reported greater psychological preparedness, consistent with the idea that emotional readiness for disaster is cultivated over time through repeated exposure to demanding clinical situations. The association between male gender and higher psychological preparedness was an independent correlate in the adjusted model, a finding the authors report without overinterpreting. Completion of an advanced nursing course, meanwhile, strengthened operational preparedness specifically, reinforcing the value of continuing professional education for technical readiness.

Taken together, the study argues that nurses’ disaster preparedness is fundamentally multidimensional, reflecting both the resources the organization provides and the psychological capacity each nurse brings to the ward. The authors conclude that interventions should combine adequate staffing and collaborative practice environments with disaster training that explicitly addresses psychological responses, resilience, and anxiety management. As health systems worldwide confront an era of pandemics, climate-driven disasters, and geopolitical instability, the message for hospital leaders is clear: building a genuinely prepared nursing workforce means investing not only in drills and protocols but in the daily working conditions and inner psychological resources that determine whether nurses believe, deep down, that they can face the worst.

Subject of Research: Predictors of operational and psychological disaster preparedness among hospital nurses in Israel

Article Title: An integrated predictive model of nurses’ disaster preparedness: the joint role of organizational resources and psychological capacity

Article References: Wattad, O. A., & Natan, M. B. (2026). An integrated predictive model of nurses’ disaster preparedness: the joint role of organizational resources and psychological capacity. BMC Nursing. https://doi.org/10.1186/s12912-026-05264-w

Image Credits: AI Generated

DOI: 10.1186/s12912-026-05264-w

Keywords: disaster preparedness, nurses, psychological preparedness, organizational work environment, resilience, trait anxiety, optimism, hospital staffing, emergency response, BMC Nursing, cross-sectional study, Israel