Introduction
In the landscape of 21st-century public health, early warning systems are recognized as profound life-saving interventions. Whether triggered by seismic activity, severe weather events, or flash emergencies, sirens and mobile alerts provide civilian populations with a critical, albeit brief, window of time to seek refuge.Reference Braun-Lewensohn and Mosseri Rubin 1 , Reference Palgi, Gelkopf and Berger 2 However, this compression of time, often ranging from mere seconds to a minute, forces an abrupt, high-stress physical response. While these systems successfully mitigate direct external trauma, the frantic rush to safety generates an epidemiological blind spot in public health preparedness: a secondary wave of non-kinetic morbidity driven by panic-induced falls and blunt trauma within residential and neighborhood settings.
The existing literature on emergency-related casualties has traditionally focused on direct physical trauma or profound long-term psychological sequelae.Reference Khorram-Manesh, Burkle and Goniewicz 3 -Reference Wild, Stewart and LeBoa 5 Yet, the process of navigating localized environments under acute stress represents a substantial community health challenge. The urgency to reach safety transforms private households and shared residential infrastructures into hazardous obstacle courses, particularly for vulnerable populations with limited baseline mobility. In this context, structural and architectural factors interact dynamically with human behavior, shifting the risk of unintentional injuries from the public sphere into the immediate domestic environment.
During the “Lion’s Roar” emergency in Israel (2026)—a sustained rocket and missile crisis—civilians were subjected to an unprecedented volume of rapid alerts, necessitating repeated evacuations to protected spaces over several weeks. This sustained crisis precipitated a massive surge in emergency department (ED) visits strictly related to the physical act of rushing to shelter, presenting a unique, national-scale model to study population behavior and environmental risk factors. Beyond identifying demographic vulnerabilities, the overarching narrative of community-level emergency evacuation remains underexplored. How does a population’s physical response to alerts evolve as an acute crisis transforms into a prolonged, daily domestic routine? Furthermore, within the community and household structure, who bears the physical burden of ensuring the safety of a family’s most vulnerable members?
This study provides a comprehensive national analysis of ED visits resulting from fall-related injuries sustained en route to protected spaces. By calculating exposure-adjusted risk over time and analyzing the demographics of the injured, we map the behavioral and spatial dynamics that precipitate these community-level traumas. Ultimately, this research aims to translate these empirical findings into evidence-based preventive medicine interventions, community-level safety guidelines, and tailored public health protocols designed to protect vulnerable households during rapid evacuation scenarios.
Methods
Study Design and Setting
A nationwide, retrospective observational study was conducted to analyze ED visits resulting from falls and blunt trauma sustained while seeking shelter during the “Lion’s Roar” emergency in Israel. This emergency (February 28 to April 8, 2026) was a 40-day sustained rocket and missile crisis. The geographic scope of the threat was unprecedented, encompassing nearly the entirety of Israel and placing approximately 10 million civilians, spanning diverse sociodemographic and urban-rural settings, under continuous threat. The affected population was subjected to an extreme frequency of alerts, forcing repeated and sudden evacuations to designated protected spaces (e.g., residential safe rooms, communal shelters, or stairwells). Alert volumes peaked dramatically on the first day of the conflict with 13,093 national alerts, before fluctuating and stabilizing at an average of 800 to 2,800 daily alerts in the subsequent weeks. 6 This extensive duration and national scope provided a unique setting to evaluate community-level behavioral responses to prolonged and repetitive emergency warnings.
The study protocol and reporting adhere to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for retrospective observational studies.
Data Source and Study Population
Clinical and demographic data were extracted from the “ADAM” system, operated by the Israeli Ministry of Health (MoH), which aggregates nationwide real-time data from acute care hospital EDs. At the onset of the emergency, the MoH issued a standardized directive to ensure uniform coding across all facilities. Consequently, specific data fields and triage protocols regarding the exact circumstances of injuries (e.g., falls sustained while racing to a protected space) were activated within hospital electronic medical record (EMR) systems. This standardized information was then transmitted to the central ADAM system. To ensure data integrity, the MoH, in coordination with hospital data coordinators, conducted validation and quality assurance procedures, cross-referencing diagnostic codes and triage records.
Variables and Measurements
De-identified data included age (categorized into 5-year intervals), gender, date of the ED visit, and municipality of residence. To evaluate the true behavioral risk within local communities, we calculated an exposure-adjusted rate (injury-to-alert ratio). This rate was derived by dividing the daily volume of fall-related ED visits by the total number of national alerts issued on that specific day, based on official Home Front Command (HFC) daily publications. The resulting fraction was then multiplied by 1,000 to express the risk as the number of ED visits per 1,000 national alerts.
Socioeconomic status (SES) was determined using the Israeli Central Bureau of Statistics (CBS) socioeconomic index based on the patient’s municipality of residence. This established national index assigns a cluster ranking from 1 (lowest) to 10 (highest) to each local authority. The index is calculated using a weighted combination of demographic, economic, and social variables, including financial resources (e.g., average per capita income, proportion of residents receiving income support), education levels, employment profiles, and housing density. To facilitate our analysis, we grouped this 10-cluster scale into three broader socioeconomic tiers: low (clusters 1-3), medium (clusters 4-6), and high (clusters 7-10). Municipal population sizes were used to calculate normalized incidence rates per 100,000 residents. To analyze the impact of available warning times on injury mechanisms, patient municipalities were cross-referenced with official HFC defense polygons to categorize cases into designated warning windows (0-15, 30, 45, 60, or 90 seconds) based on the location of injury.
Statistical Analysis
Descriptive statistics summarized demographic characteristics, using means for continuous variables and frequencies or percentages for categorical variables. Spatial analysis focused on normalized absolute case numbers by municipal population size to identify geographic and environmental risk hotspots within local communities.
Ethical Considerations
Due to the retrospective nature of the study and the use of de-identified administrative health data, the requirement for informed consent was waived.
Results
Baseline Characteristics and Mortality
Between February 28 and April 8, 2026, 2,941 patients presented to EDs across Israel due to fall-related injuries sustained while seeking shelter (daily average: 73.5). Notably, this specific cohort of indirect casualties accounted for a substantial 36.9% of all war-related ED presentations (7,961 total visits) during the emergency operation, highlighting that the physical toll of evacuation constitutes a major component of the overall medical burden. Three cases were fatal (0.1% mortality rate among admitted patients). All fatalities occurred in the older adult demographic (two males aged 91 and 103, one female aged 69). The demographic, socioeconomic, and clinical characteristics of the study population are summarized in Table 1.
Demographic and socioeconomic characteristics of patients presenting to emergency departments with evacuation-related fall injuries (Israel, 2026; N = 2,941)

Table 1. Long description
The table consists of three columns: Characteristic, N (percentage), and National population baseline (percentage).
Overall Patients: 2,941 (100 percent).
Age group (years):
- 0 to 17 (Pediatric): 278 (9.5 percent) vs 32.7 percent baseline.
- 18 to 25: 294 (10.0 percent) vs 11.8 percent baseline.
- 26 to 45: 665 (22.6 percent) vs 25.5 percent baseline.
- 46 to 65: 661 (22.5 percent) vs 18.5 percent baseline.
- 66 to 80: 650 (22.1 percent) vs 8.7 percent baseline.
- Greater than 80: 393 (13.4 percent) vs 3.0 percent baseline.
Gender (overall):
- Female: 1,705 (58.0 percent).
- Male: 1,232 (41.9 percent).
- Unknown: 4 (0.1 percent).
Gender (pediatric cohort: 0 to 17 years):
- Female: 110 (39.6 percent).
- Male: 168 (60.4 percent).
Socioeconomic status (S E S cluster):
- Low (1 to 3): 460 (15.6 percent) vs 31 percent baseline.
- Medium (4 to 6): 942 (32.0 percent) vs 28 percent baseline.
- High (7 to 10): 1,485 (50.5 percent) vs 41 percent baseline.
- Unknown: 54 (1.8 percent).
Clinical outcome:
- Fatalities: 3 (0.1 percent).
a Percentages for SES are calculated out of the total number of patients with successfully reported residential cluster data.
b Values in this column represent the percentage of each group within the total Israeli population, based on data from the Central Bureau of Statistics (CBS, 2024). 15
Comparison with national demographic data reveals a profound disparity in injury rates. While children (0-17) are under-represented relative to their 32.7% share of the population, older adults exhibit a stark over-representation. Specifically, those aged 80+ were injured at a rate 4.5 times higher than their proportion in the general population (13.4% of casualties vs. 3.0% of the population).
The Temporal Paradox: Exposure-Adjusted Risk
While the absolute number of ED visits peaked on the first day of the conflict (141 cases corresponding to 13,093 national alerts), calculating the injury-to-alert ratio revealed a striking paradox across the 40-day study period (Figure 1).
Temporal trends of fall-related ED visits and alert volume.

Figure 1. Long description
The X-axis represents a timeline from February 28, 2026, to April 8, 2026. The primary Y-axis on the left ranges from 0 to 160, measuring E D visits. The secondary Y-axis on the right ranges from 0 to 14,000, measuring alert volume.
* E D Visits (Blue Bars): The data begins at a peak of 141 on February 28, followed by a general decline with significant fluctuations. Notable local peaks occur on March 4 (102), March 18 (105), and March 26 (130). The lowest point is recorded on March 6 with 26 visits. Toward the end of the period, values stabilize between 41 and 83.
* Alert Volume (Black Line): The line starts at its highest point, exceeding 12,000 on February 28, then drops sharply to approximately 2,500 by March 1. For the remainder of the period, the alert volume fluctuates between approximately 1,000 and 4,000.
* Correlation: There is a visible but inconsistent relationship where spikes in E D visits often correspond with smaller upward ticks in alert volume, though the initial massive alert volume on day one does not repeat despite later surges in E D visits.
The relative risk of injury per individual alert was lowest on the first day (10.8 injuries per 1,000 alerts) (Figure 2). However, as the conflict extended beyond the initial acute phase and total daily alert volumes decreased and stabilized (averaging between 800 and 2,800 alerts per day in late March and early April), the relative risk surged dramatically. For example, on March 23, the ratio spiked to 76.3 injuries per 1,000 alerts. This trend culminated in a peak on April 5, when 74 ED visits occurred despite only 833 national alerts—resulting in a staggering ratio of 88.8 injuries per 1,000 alerts. This indicates that the physical danger associated with each individual siren increased by more than 8-fold as the conflict wore on and populations attempted to resume daily domestic routines amidst ongoing, sporadic threats.
ED admissions per 1,000 alerts (injury-to-alert ratio).

Figure 2. Long description
The x-axis lists dates daily from 2 forward slash 28 forward slash 2026 to 4 forward slash 8 forward slash 2026. The y-axis represents the ratio of admissions.
Data points by date:
* 2/28: 10.8
* 3/1: 14.7
* 3/2: 33.5
* 3/3: 22.6
* 3/4: 42.0
* 3/5: 24.0
* 3/6: 19.1
* 3/7: 16.9
* 3/8: 16.6
* 3/9: 33.1
* 3/10: 22.5
* 3/11: 32.0
* 3/12: 56.7
* 3/13: 23.4
* 3/14: 44.9
* 3/15: 46.9
* 3/16: 37.7
* 3/17: 44.9
* 3/18: 57.7
* 3/19: 34.1
* 3/20: 26.2
* 3/21: 52.9
* 3/22: 57.6
* 3/23: 76.3
* 3/24: 50.4
* 3/25: 45.3
* 3/26: 47.2
* 3/27: 30.2
* 3/28: 33.3
* 3/29: 32.7
* 3/30: 40.9
* 3/31: 41.4
* 4/1: 19.6
* 4/2: 41.1
* 4/3: 43.4
* 4/4: 47.4
* 4/5: 88.8 (highest peak)
* 4/6: 38.5
* 4/7: 42.4
* 4/8: 49.9
The chart shows high volatility with local peaks occurring roughly every 6 to 10 days.
Demographic Vulnerability and the Gender Divide
Falls disproportionately affected older adults, with the 66-80 age group representing a substantial injured cohort (650 cases, 22.1%). A profound correlation between age and gender emerged across the extended study period (Figure 3). Overall, females accounted for 58% of all injuries (n = 1,705) compared to 42% for males (n = 1,232).
Age and gender distribution of casualties (stacked bar chart).

Figure 3. Long description
The x-axis represents age groups in five-year increments from 0-4 to 101-105. The y-axis represents the volume of casualties. Each bar is stacked with Male at the bottom in blue and Female at the top in gray.
Key data points from left to right include:
* 0-4: 52 percent male, 48 percent female.
* 5-9: 72 percent male, 28 percent female.
* 15-17: 62 percent male, 38 percent female.
* 21-25: 60 percent male, 40 percent female.
* 26-30: 50 percent male, 50 percent female.
* 46-50: 38 percent male, 61 percent female.
* 71-75: This group represents the highest total volume of casualties, with 34 percent male and 66 percent female.
* 76-80: 29 percent male, 70 percent female.
* 86-90: 27 percent male, 73 percent female.
* 91-95: 28 percent male, 72 percent female.
The trend shows males make up the majority of casualties in younger age groups (under 25), while females represent a significantly higher percentage in older age groups (above 45), peaking in total volume between ages 61 and 85.
While the gender distribution remained remarkably balanced among young and middle-aged adults (hovering at approximately 50% for each gender between ages 26 and 45), a dramatic demographic shift occurred starting at age 46. From the 46-50 age bracket onwards, females became the distinct majority (61%), a disparity that continued to widen drastically with advancing age. Among all casualties aged 46 and older, women accounted for roughly two-thirds (66.7%) of fall-related ED visits, peaking at an overwhelming 73% within the 86-90 age group. This widening gap underscores specific sociological and physiological vulnerabilities inherent to older female populations during sudden evacuations.
The Pediatric Sub-Cohort
Children and adolescents (ages 0-17) constituted a smaller, yet notable, portion of the casualties, accounting for a total of 278 ED visits. Within this pediatric cohort, the highest incidences were observed among the youngest demographic brackets, specifically ages 5-9 (76 cases) and ages 0-4 (75 cases). Older children and adolescents accounted for progressively fewer injuries.
Interestingly, the gender disparity observed in the adult population was reversed in the broader pediatric cohort: males constituted the clear majority (60.4%) of injured children and adolescents, a trend typical of impulsive pediatric trauma. However, a detailed breakdown of the youngest sub-cohort (ages 0-4) reveals a striking exception. In stark contrast to the pronounced male majority observed among older children (e.g., reaching 72% male in the 5-9 age group), the gender distribution within the 0-4 infant and toddler group was nearly balanced, comprising 39 males (52%) and 36 females (48%). This distinct gender parity in the youngest age bracket strongly supports the “passive trauma” hypothesis, indicating that these infants were likely injured not due to their own independent rushing, but rather sustained indirect trauma when their burdened caregivers fell while carrying them to shelter.
Spatial and Socioeconomic Distribution
While the city of Tel Aviv recorded the highest absolute number of casualties (330 cases), normalizing the data by municipal population size revealed a more nuanced geographic risk profile. Among municipalities with a population exceeding 10,000 residents (Figure 4), the highest incidence rates of fall-related injuries were observed in the northern city of Ma’alot-Tarshiha (116.8 cases per 100,000 residents), followed by Hatzor HaGlilit (108.1 per 100,000), Bat Yam (103.4 per 100,000), Or Yehuda (102.1 per 100,000), and Ashkelon (93.9 per 100,000). Analysis of these top-ranking municipalities reveals a dual geographic risk profile. High incidence rates were heavily concentrated either in acute warning zones subject to immediate or 15-second alerts (e.g., Ma’alot-Tarshiha, Hatzor HaGlilit, and Ashkelon), or in densely populated urban centers with a 90-second warning time but a high concentration of elderly residents in older, multi-story architectural structures (e.g., Bat Yam, Or Yehuda, Holon, and Ramat Gan).
Population-normalized incidence of falls per municipality (top 15).

Figure 4. Long description
The horizontal axis lists fifteen municipalities, and the vertical axis represents the population-normalized incidence rate. The bars are dark blue with numerical values printed directly above each bar. From left to right, the data points are as follows.
* Ma’alot-Tarshiha: 116.8
* Hatzor HaGlilit: 108.1
* Bat Yam: 103.4
* Or Yehuda: 102.1
* Ashkelon: 93.9
* Maghar: 92.4
* Deir al-Asad: 86.2
* Safed: 85.0
* Gan Yavne: 76.9
* Kafr Yasif: 76.1
* Holon: 76.0
* Ramat Gan: 75.9
* Nahariya: 75.1
* Givatayim: 73.8
* Kiryat Shmona: 67.9
The chart shows a steady decline from the highest incidence in Ma’alot-Tarshiha to the lowest in Kiryat Shmona.
Analysis of the patients’ socioeconomic background revealed that the majority of ED visits with successfully reported residential cluster data (51.4%, n = 1,485) originated from patients residing in high SES municipalities (clusters 7-10). In contrast, 32.6% (n = 942) originated from medium SES municipalities (clusters 4-6), and only 15.9% (n = 460) from low SES municipalities (clusters 1-3). This distribution, which remained consistent even as the sample size increased, reinforces the hypothesis that structural vulnerability in rapid-warning scenarios is not solely a function of economic deprivation but is significantly influenced by specific urban architectural environments and behavioral health-seeking patterns among higher SES populations.
The Impact of Warning Time on Age-Specific Vulnerability
When casualties were stratified by the designated warning time of their municipalities, 62.5% (n = 1,840) of injuries occurred in 90-second zones. In these regions, the age distribution was characterized by a high concentration of older adults, with those aged 66 and older accounting for 41.6% (n = 766) of the cases. This high incidence indicates that even with extended warning windows, baseline mobility constraints remain a primary driver of fall-related morbidity among the elderly.
In stark contrast, in municipalities with acute warning times (0-15 and 30 seconds), the proportion of young and middle-aged adults (ages 26-65) was notably higher (Figure 5). This age cohort accounted for 49.4% (n = 81 out of 164) of casualties in the 0-15 second zones and 53.3% (n = 153 out of 287) in the 30-second zones. This significant demographic shift highlights the vulnerability of typically mobile populations during high-velocity, panic-induced evacuations where the available time dictates an “acute flight response.”
Age distribution of fall-related injuries by warning time.

Figure 5. Long description
A stacked bar chart with the Y-axis labeled Percentage of Casualties (%) from 0 to 100 and the X-axis labeled Warning Time. A legend on the right identifies six age groups by color: 0-17 (Pediatric) in light gray, 18-25 in medium gray, 26-45 in dark gray, 46-65 in light blue, 66-80 in medium blue, and >80 in dark blue.
Data by Warning Time column from bottom to top:
* 0-15 seconds: 13.4% (0-17), 7.3% (18-25), 23.2% (26-45), 26.2% (46-65), 21.3% (66-80), 8.5% (>80).
* 30 seconds: 11.8% (0-17), 12.2% (18-25), 26.1% (26-45), 27.2% (46-65), 18.1% (66-80), 4.5% (>80).
* 45 seconds: 8.5% (0-17), 15.9% (18-25), 23.9% (26-45), 21.0% (46-65), 19.3% (66-80), 11.4% (>80).
* 60 seconds: 13.3% (0-17), 12.6% (18-25), 29.4% (26-45), 21.9% (46-65), 16.8% (66-80), 6.0% (>80).
* 90 seconds: 7.9% (0-17), 8.7% (18-25), 20.1% (26-45), 21.7% (46-65), 24.5% (66-80), 17.2% (>80).
Injuries in the youngest pediatric group (0-4 years) were distributed across all warning time categories, further reinforcing the hypothesis that their safety is heavily contingent upon the caregiver’s stability, regardless of the time available. Notably, data completeness improved significantly in this expanded cohort, with only 0.7% of the total sample (n = 22) lacking specific warning time data.
Discussion
This study illuminates a critical, yet often overlooked, dimension of morbidity in the modern era of early warnings: the severe physical toll of panic-induced evacuation. The data from the “Lion’s Roar” operation suggests that the primary dangers en route to safety are not randomly distributed but are tied to the evolution of human behavior under sustained threat. Specifically, the observed “complacency-panic mismatch”—where injury rates per alert surged as the conflict transitioned from an acute phase to a period of normalized, albeit unpredictable, daily routines—indicates that civilian populations increasingly prioritize returning to domestic activities, thereby neglecting safety protocols in their immediate environment. This shift underscores a vital need for dynamic, phase-specific public health messaging that adapts to the shifting cognitive burden of the population throughout an emergency.
The Three Stages of Evacuation Behavior
The counter-intuitive finding that the relative risk of falling increased as the conflict progressed can be understood through a framework of three distinct behavioral stages, which has significant implications for how public health warnings should be issued over time:
-
• Stage 1: Acute Shock and “Shelter-in-Place” (Days 1-3): Overwhelmed by unprecedented alert volumes, populations abandon regular movement. They remain inside or adjacent to shelters,Reference Dailey and Kaplan 7 , Reference Yantosik, Lerner and Maloney 8 minimizing physical transit and thereby drastically lowering the risk of falling per alert.
-
• Stage 2: The “Complacency-Panic Mismatch” (Weeks 2-3): As alert frequency drops, civilians attempt to reclaim domestic routines (e.g., cooking, sleeping in regular bedrooms).Reference Agam, Godler and Calif 9 This creates cognitive complacency—environments are no longer primed for rapid escape (toys on floors, improper footwear). Yet, when a siren sounds, the biological “fight-or-flight” panic response is triggered at full force.Reference Milosevic, Milosevic and McCabe 10 , Reference Wise 11 Executing a high-speed sprint through an unprepared environment causes the injury-to-alert ratio to surge.
-
• Stage 3: Prolonged Routine and Fatigue: Cumulative stress, sleep deprivation, and eroded safety protocols compound physical clumsiness. As demonstrated by the extreme peaks in the injury-to-alert ratio during the final weeks of the operation, this prolonged phase maintains and even escalates high relative injury rates even as the external threat normalizes.Reference Artelli 12 –Reference Zeidner and Hammer 14
The disproportionality of risk
The normalization of casualty data against the national population baseline 15 transforms the understanding of evacuation-related risk. The finding that adults over 80 are 4.5 times more likely to appear in ED records than their demographic weight suggests that the journey to shelter is not merely “difficult” for the elderly, but constitutes a high-risk event. This disproportionate toll validates the shift from generic alerts to specialized protection protocols for geriatric populations, as their baseline mobility constraints intersect fatally with the requirements of rapid evacuation.
Kin-Keeping: The Physical Toll of Preserving the Family
While physiological aging factors such as post-menopausal osteoporosis or sarcopenia certainly contribute to the higher incidence of fragility fractures and falls among older women,Reference Duque, Allen and Huang 16 -Reference Testa, Callanan and Evans 18 they may not provide a complete explanation for the abrupt demographic shift observed from age 46 onwards. Instead, these biological vulnerabilities likely interact with the sociological burden of “kin-keeping,”Reference Ciciolla and Luthar 19 -Reference Rosenthal 21 which emerges as a primary potential driver of indirect trauma in this cohort.
In familial structures, women frequently assume the role of primary caregivers. During the acute panic of an alarm, a kin-keeper’s immediate reaction is not solely self-preservation, but to gather and assist dependents.Reference Bateman and Edwards 22 For middle-aged women, this means carrying toddlers or assisting aging parents; for older women, it often involves physically supporting an ailing spouse.Reference McGhan, Loeb and Baney 23 , Reference Staight and Harvey 24 This caregiving instinct severely compromises biomechanical stability. Running while bearing the weight of another human removes the ability to use arms to break a fall and divides cognitive attention.
This hypothesis is tragically supported by pediatric data. While older boys show higher injury rates due to impulsivity,Reference Chapple and Johnson 25 -Reference Shulman, Harden and Chein 27 the high concentration of injuries among infants and toddlers aged 0-4 (where the gender distribution is nearly equal) strongly suggests a mechanism of “passive trauma.” It is highly probable that these infants were not injured by their own impulsive running, but rather suffered trauma when their burdened, frantic caregivers fell while carrying them. This transformed their attempts at protection into a hazardous endeavor.
Mobility Constraints vs. Acute Flight Response
The stratification of injuries by warning time suggests two distinct mechanisms of morbidity. In 90-second zones, the prevalence of elderly casualties, who comprise 41.6% of all injuries in these areas, indicates that falls are primarily driven by baseline mobility constraints. While the longer warning window theoretically allows for a safer pace, the physical demands of reaching a protected space, often navigating obstacles or stairs in older urban environments, still pose a significant risk to the frailest individuals.
Conversely, the increased representation of younger, mobile adults (ages 26-65) in 0-15 and 30-second zones (accounting for 49.4% and 53.3% of casualties in these areas, respectively) illustrates the impact of an Acute Flight Response (or Panic-Induced Flight). When the warning window is extremely narrow, the physiological “fight-or-flight” response may trigger a frantic, high-speed evacuation. In these high-pressure scenarios, the urgency to reach safety severely compromises biomechanical stability, even in healthy individuals. This risk is likely exacerbated by the “kin-keeping” burden; the consistent injury rates of infants (0-4 years) across all timeframes suggest that regardless of the time available, a child’s safety remains dependent on the caregiver’s stability, which is most vulnerable during an acute, rapid rush.
Simultaneously, the relative under-representation of the elderly in these acute warning zones (0-15 seconds) suggests a potential self-regulatory behavioral pattern. Recognizing that their mobility constraints make reaching a designated shelter within seconds impossible, many older adults may opt for a “shelter-in-place” strategy, remaining in their immediate location rather than attempting a high-risk sprint. This decision, while increasing potential exposure to direct threats, effectively mitigates the immediate biomechanical risk of fall-related trauma.
Global Public Health Implications
The findings from this study extend far beyond the geopolitical borders of Israel and armed conflict. As global early warning systems become more sophisticated,Reference Calvo-Solano and Quesada-Román 28 , Reference Debnath and Dhanekula 29 the “warning window” is universally shrinking. This compressed timeframe is highly relevant globally:
-
• Natural Disasters: Systems like the US ShakeAlert for earthquakes,Reference Lux, Smith and Böse 30 tornado sirens in the American Midwest,Reference Jackson, Cutter, Gall and Rubin 31 and tsunami warning systems in the Pacific RimReference Mori, Satake and Cox 32 all rely on the public taking immediate physical action within seconds to minutes.
-
• The Universality of the “Mismatch”: The “Complacency-Panic Mismatch” is a universal human response to prolonged, intermittent threats.Reference Aguirre 33 Public health agencies managing prolonged disaster warnings (e.g., hurricane seasons, wildfire watch periods) must recognize that the physical risk of evacuation does not remain static but can exponentially multiply as populations attempt to normalize their daily lives amidst the ongoing threat.
-
• Redefining Vulnerability: Global disaster preparedness protocols often categorize the elderly and children as vulnerable because they cannot run fast enough.Reference Onyejesi, Alsabri and Del Castillo Miranda 34 This study provides compelling evidence suggesting that the caregivers themselves—particularly middle-aged and older females—may become highly vulnerable specifically because they are assisting others. International evacuation guidelines must shift to address the biomechanics of caregiving under duress.
-
• Urban and Architectural Constraints: As demonstrated by the high injury rates in affluent, densely populated municipalities, structural vulnerability is not solely a function of socioeconomic deprivation. Global urbanization and high-rise living mean that longer warning times (e.g., 90 seconds) can become hazardous “traps” if the evacuation route involves navigating multiple flights of stairs. Global protocols must tailor physical evacuation guidelines to the specific built environment of the population.
Preventive Strategies and Interventions
The leadership of the Ministry of Health has placed a central emphasis on the planning of emergency policy that underscores the primacy of addressing the needs of vulnerable populations, particularly older adults. Within this policy framework, a series of tactical measures were undertaken, including the preparation of health maintenance organizations and the provision of guidance regarding structured, controlled discharge processes. These processes were accompanied by targeted provisions ensuring access to medications, mobility and accessibility aids, guidance for families, and transfers to protected facilities for continued inpatient care. Hospitals were instructed to establish a “discharge staff”—comprising social workers, allied health care professionals, nurses, and doctors—to engage in the process of clinical and functional assessment.
In addition, “pop-up” rehabilitation units were established to enable the continuity of rehabilitation processes in protected structures, aiming to prevent physical and functional deterioration while safeguarding elderly patients and maintaining continuity of care.
A further critical component of this systemic effort was addressing the out-of-hospital risk environment. In response to the escalating burden of these indirect casualties, the Israel Ministry of Health launched a targeted, multi-lingual public awareness campaign on March 8, 2026. Disseminated across mass media platforms, the campaign emphasized simple, practical, and actionable measures for the home environment. Providing tailored guidance on fall prevention en route to protected spaces, the initiative sought to mitigate the acute stress and rapid rushing that primarily precipitate these falls.
Key public health guidelines included preemptively clearing physical obstacles from evacuation routes, ensuring adequate lighting, utilizing closed, non-slip footwear, and keeping mobility and sensory aids readily accessible. Furthermore, the messaging explicitly advised against running, advocating instead for a swift but measured pace, while urging the public to actively monitor and assist vulnerable neighbors during alerts.
More generally, effective public health strategies must move beyond the basic instruction to “seek shelter immediately” and actively incorporate behavioral guardrails and structural modifications:
-
• Dynamic Messaging: Messaging must combat the “complacency-panic mismatch” by evolving throughout the conflict. Given that the highest injury-to-alert ratios were recorded in the final weeks of the operation (peaking at 88.8 on April 5), sustained and repetitive campaigns are essential to remind populations that domestic safety protocols must not be neglected as routines normalize.
-
• Addressing the Caregiver Burden: Guidelines must explicitly address the biomechanics of kin-keeping. Rather than frantic running while carrying a child, campaigns should advocate for a “swift but measured pace” and pre-planned household roles to distribute the burden. Crucially, in zones with immediate warning times (0-15 seconds), the emphasis should shift from “reaching the primary shelter” to “seeking the nearest protected space” to minimize the high-velocity sprint. For older adults and individuals with significant mobility impairments in these areas, public health guidelines should explicitly prioritize immediate protective actions within the current room (e.g., lying on the floor below window level) over the attempt to reach a distant shelter. In such extreme time-compressed scenarios, the clinical risk of a catastrophic fall may outweigh the marginal protective benefit of a rapid evacuation attempt.
-
• Household Environmental Modifications: Checklist-based programs should target home “hazard-free zones,” securing rugs and ensuring accessible mobility aids. In high-SES and densely populated urban areas, specific focus must be placed on stair safety and the risks associated with internal stairs in multi-level homes, accounting for the 51.4% of casualties residing in these affluent clusters.
-
• Addressing Socioeconomic and Architectural Disparities: Our findings revealed a counterintuitive trend: the majority of casualties (51.4%, n = 1,485) resided in high-SES municipalities (clusters 7-10). This distribution is likely influenced by an “evacuation bias.” During the operation, populations from high-risk border zones—which predominantly consist of lower-SES municipalities (clusters 1-4)—underwent mass evacuation. Consequently, the relative proportion of middle- and high-SES populations remaining in the active warning zones artificially increased, naturally skewing the national casualty demographics.
However, even accounting for this demographic shift, structural vulnerabilities and variations in health-seeking behaviors play a crucial role. High-SES populations often reside in multi-level private homes or large apartments with internal stairs, which pose a unique falling hazard during a rapid rush to a shelter. Furthermore, higher-SES individuals may be more inclined to visit an ED for minor injuries. Consequently, preventive interventions must be bifurcated: high-SES areas require targeted campaigns on stair safety and internal “luxury” hazards, while lower-SES neighborhoods require continued focus on public shelter accessibility and infrastructure safety where reporting might be lower but environmental risks remain high.
-
• Tailored Architectural Interventions: Our findings suggest that structural vulnerability is influenced by the built environment. In municipalities with longer warning times (e.g., Bat Yam, Or Yehuda), where elderly populations face the challenge of navigating multi-story buildings, policy should prioritize the accessibility of floor-level shelters and the improvement of communal stairwell lighting.
Limitations
This study has several limitations. First, it relies on retrospective ED administrative data, which inherently captures only injuries severe enough to warrant hospital admission or emergency care. Consequently, our reported incidence rates likely underestimate the true community-level burden of evacuation-related falls, as minor injuries (e.g., mild sprains, contusions) managed at community clinics or self-treated at home are excluded. This reliance on ED data introduces potential selection biases that may impact the reported demographic distributions. For instance, older adults are clinically more likely to be referred to the ED following a fall due to the higher risk of fractures, whereas younger adults might self-manage similar falls, potentially exaggerating the observed age disparities. Furthermore, differences in health care-seeking behaviors among various socioeconomic groups may skew the data, as higher-SES populations might be more inclined or have better logistical access to utilize ED services for non-life-threatening injuries. Second, the database lacks granular narrative details regarding the exact micro-mechanism of the fall (e.g., tripping over a rug vs. slipping on stairs) and lacks direct confirmation of the caregiver status at the exact moment of injury, requiring the use of demographic proxies to infer “kin-keeping” behaviors.
Third, regarding exposure metrics, the use of aggregated daily national alert counts as a denominator for the injury-to-alert ratio (Figures 1 and 2) does not account for the geographic distribution of sirens. Regional surges in alert volume in specific high-risk zones may not be fully captured in the national ratio, potentially masking localized risk dynamics. Furthermore, while this study attempted to stratify casualties by municipal warning time categories (15-90 seconds), this analysis was limited by the use of municipal residence as a proxy for the warning window at the time of injury. Crucially, this official polygon-based categorization relies solely on the formal Home Front Command siren activation time. It does not account for the widespread phenomenon of “advance warnings” (e.g., third-party mobile applications, broadcast media alerts, or the auditory crossover of sirens from adjacent municipalities). These unofficial early alerts often provide civilians with additional, unrecorded seconds prior to the localized siren, meaning the actual time a casualty had to react and seek shelter may have differed from their official municipal designation. However, it should be noted that data completeness in the expanded cohort was exceptionally high, with specific warning-time data available for 99.3% of the sample (n = 2,919).
Additionally, the displacement and evacuation of civilian populations from high-risk border zones likely altered the demographic profile of casualties in the 0-15 and 30-second zones. Because these evacuated border communities are disproportionately represented in lower socioeconomic clusters (1-4), this mass displacement created an inherent “evacuation bias.” This bias not only leads to an underestimation of the risk to elderly populations in these areas, as many vulnerable residents were evacuated early in the conflict, but it also limits our ability to isolate the true effect of SES on fall risk, as the remaining population exposed to sirens nationwide was structurally skewed toward higher-SES demographics.
Finally, the spatial analysis normalized absolute cases by municipal population size, which can introduce statistical noise in smaller communities. Nevertheless, the consistency of findings across broad socioeconomic clusters (n = 2,887) suggests that the overarching trends remain robust across the national population.
Future prospective research should incorporate qualitative interviews and granular, GPS-linked temporal data to further validate the biomechanical and behavioral hypotheses presented here.
Conclusion
Indirect injuries sustained while rushing to safety represent a critical, yet largely preventable, public health crisis inherent to rapid-warning scenarios. This nationwide study of 2,941 casualties over a 40-day period redefines the traditional narrative of evacuation by highlighting a dynamic evolution of public behavior. We identified a profound “complacency-panic mismatch,” where the relative risk per individual siren multiplied more than eightfold as the conflict progressed, peaking during the final stages of the emergency period. This underscores that the peril of evacuation is not a static threat but one that escalates as populations attempt to balance domestic routines with intermittent alerts.
Furthermore, our analysis uncovers the significant physical sacrifices made by caregivers—the “kin-keeping” burden. With a female majority emerging distinctly from age 46 and peaking at 73% among the elderly, it is highly probable that caregiving instincts frequently override self-preservation, leading to biomechanical instability and “passive trauma” in dependents. While these patterns strongly support the kin-keeping hypothesis, further qualitative research is needed to directly observe these dynamics. Crucially, our findings reveal that the warning time itself dictates the mechanism of injury, and that this risk is profoundly age-disproportionate. With individuals over 80 being over-represented by a factor of 4.5 relative to the general population, it is evident that while longer-warning zones (90s) pose a risk to elderly individuals with mobility constraints, high-velocity evacuations (0-30s) shift the danger to healthy adults experiencing an “acute flight response.” Finally, the counterintuitive discovery that 51.4% of injuries occurred in high-SES municipalities further emphasizes that structural vulnerability is shaped both by regional evacuation biases and by architectural environments—such as multi-story urban living and internal stairs—rather than economic deprivation alone.
To effectively mitigate this secondary wave of morbidity, global public health authorities must transition from issuing generic alerts to designing smarter, time-tailored emergency protocols. By addressing the biomechanical dangers of caregiving, mitigating household structural hazards, and adjusting guidelines based on specific warning windows, authorities can actively safeguard the perilous journey to shelter. Ultimately, an early warning system is only as successful as the population’s ability to safely act upon it.
Data availability statement
The data that support the findings of this study were extracted from the “ADAM” national ED information system. Due to strict privacy and confidentiality regulations mandated by the Israeli Ministry of Health regarding medical records, the raw patient-level data cannot be shared publicly. De-identified, aggregated data may be available from the corresponding author upon reasonable request, subject to the approval of the relevant institutional and national regulatory bodies.
Author contribution
AA, YY, MFL, HM, MG, and JM conceptualized and designed the study. YY, MFL, HM, and MG were responsible for data acquisition and curation. AA and YY performed the analyses. AA wrote the original draft of the manuscript and generated the figures. YY, MFL, HM, MG, and JM critically reviewed and edited the manuscript for intellectual content. All authors read and approved the final version of the manuscript.
Funding statement
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Competing interests
None.
Ethical approval
This study was granted a formal exemption from full review by the Institutional Review Board (IRB) of the Israel Ministry of Health. The exemption and the subsequent waiver of informed consent were approved based on the study’s protocol as a retrospective observation utilizing secondary, completely de-identified administrative health data from the national “ADAM” system. Because the research involved no direct patient interaction, clinical interventions, or exposure of personally identifiable information, it strictly fulfilled the institutional criteria for an IRB review waiver.