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Background:High profile terrorist attacks in major capital cities have seemingly become a regular occurrence and the resultant mass-casualty events continue to challenge health care systems. Counter-Terrorism Medicine (CTM) addresses unique terrorism-related issues relating to the mitigation, preparedness, and response measures to asymmetric, multi-modality terrorist attacks. This study is an epidemiological examination of all terrorism-related events sustained from 1970-2019, analyzing historical weapon types used and the resulting fatal injuries (FI) and non-fatal injuries (NFI) sustained.Methods:The Global Terrorism Database (GTD) was searched for all attacks from 1970-2019. Attacks met inclusion criteria if they fulfilled the three terrorism-related criteria, as set by the GTD codebook. Ambiguous events were excluded. State-sponsored terrorist events do not meet the codebook’s definition, and as such, are excluded from the study. Available counts of FI and NFI in each incident were then sorted and aggregated by weapon type to enable mean and standard deviation calculations.Results:In total, 168,003 events were recorded from the years 1970-2019. Explosives, bombs, and/or dynamite (E/B/D) were the most commonly used weapon type and accounted for 48.78% of all terrorism events, followed by the use of firearms in 26.77% of events. A total of 339,435 FI and 496,225 NFI resulted from all terrorism events that occurred during the study period. Combined, E/B/D and firearms accounted for 75.55% of all events, 67.1% of all FI, and 79.3% of all NFI. Each individual terrorism event inflicted a mean FI rate of 2.14 FI per event (SD = 10.2) and a mean NFI rate of 3.22 NFI per event (SD = 45.19).Conclusions:Although terrorism is complex and does not solely rely on death tolls as a measure of success, this analysis shows a historic mean FI rate of 2.14 and NFI rate of 3.22 per event over the past 50 years. Proven weapons such as E/B/D and firearms combine to account for over 75% of weapon types used in all events. Use of weapons of mass destruction (WMDs) such as chemical, biological, radiation, and nuclear (CBRN) weapons has been rare (0.2%), yet has extreme high potential to inflict mass casualties with mean NFI rates of 49.62 and 28.75 for chemical and biological weapons, respectively.

The early conversations on social media by emergency physicians offer a window into the ongoing response to the COVID-19 pandemic. This retrospective observational study of emergency physician Twitter use details how the health care crisis has influenced emergency physician discourse online and how this discourse may have use as a harbinger of ensuing surge. Followers of the three main emergency physician professional organizations were identified using Twitter's application programming interface. They and their followers were included in the study if they identified explicitly as US-based emergency physicians. Statuses, or tweets, were obtained between January 4, 2020, when the new disease was first reported, and December 14, 2020, when vaccination first began. Original tweets underwent sentiment analysis using the previously validated Valence Aware Dictionary and Sentiment Reasoner (VADER) tool as well as topic modeling using latent Dirichlet allocation unsupervised machine learning. Sentiment and topic trends were then correlated with daily change in new COVID-19 cases and inpatient bed utilization. A total of 3463 emergency physicians produced 334,747 unique English-language tweets during the study period. Out of 3463 participants, 910 (26.3%) stated that they were in training, and 466 of 902 (51.7%) participants who provided their gender identified as men. Overall tweet volume went from a pre-March 2020 mean of 481.9 (SD 72.7) daily tweets to a mean of 1065.5 (SD 257.3) daily tweets thereafter. Parameter and topic number tuning led to 20 tweet topics, with a topic coherence of 0.49. Except for a week in June and 4 days in November, discourse was dominated by the health care system (45,570/334,747, 13.6%). Discussion of pandemic response, epidemiology, and clinical care were jointly found to moderately correlate with COVID-19 hospital bed utilization (Pearson r=0.41), as was the occurrence of \"covid,\" \"coronavirus,\" or \"pandemic\" in tweet texts (r=0.47). Momentum in COVID-19 tweets, as demonstrated by a sustained crossing of 7- and 28-day moving averages, was found to have occurred on an average of 45.0 (SD 12.7) days before peak COVID-19 hospital bed utilization across the country and in the four most contributory states. COVID-19 Twitter discussion among emergency physicians correlates with and may precede the rising of hospital burden. This study, therefore, begins to depict the extent to which the ongoing pandemic has affected the field of emergency medicine discourse online and suggests a potential avenue for understanding predictors of surge.

Launched in 2014, the RARE Compassion Program is the first international educational program to pair medical students with rare disease patients in order to enhance exposure to and comfort with rare diseases. As part of ongoing quality improvement, this study retrospectively reviewed four years of participant registration data to conduct a program evaluation of the RARE Compassion Program between 2014–2018. During the study period, there were 334 student participants, representing 67.3% of Association of American Medical Colleges (AAMC) member medical schools, and 5389 rare disease volunteers. Despite not requiring in-person interaction, 90.64% of student–volunteer interactions were in-person, while only 5.89% and 3.46% were by video messaging or email correspondence, respectively (p = 0.0002). In a limited post participation survey, 91.7% of students, who matched to 19 out of 27 residency specialities, indicated they would recommend the program to their peers. These findings suggest that the RARE Compassion Program, designed to increase medical student engagement with rare disease patients, has broad appeal. It serves as a novel case study of how extracurricular initiatives supported by non-profit organizations can augment the medical training experience and improve understanding of important and often neglected perspectives.

In 2009, the Institute of Medicine published guidelines for implementation of Crisis Standards of Care (CSC) at the state level in the United States (US). Based in part on the then concern for H1N1 pandemic, there was a recognized need for additional planning at the state level to maintain health system preparedness and conventional care standards when available resources become scarce. Despite the availability of this framework, in the years since and despite repeated large-scale domestic events, implementation remains mixed. Coronavirus disease 2019 (COVID-19) rejuvenates concern for how health systems can maintain quality care when faced with unrelenting burden. This study seeks to outline which states in the US have developed CSC and which areas of care have thus far been addressed. An online search was conducted for all 50 states in 2015 and again in 2020. For states without CSC plans online, state officials were contacted by email and phone. Public protocols were reviewed to assess for operational implementation capabilities, specifically highlighting guidance on ventilator use, burn management, sequential organ failure assessment (SOFA) score, pediatric standards, and reliance on influenza planning. Thirty-six states in the US were actively developing (17) or had already developed (19) official CSC guidance. Fourteen states had no publicly acknowledged effort. Eleven of the 17 public plans had updated within five years, with a majority addressing ventilator usage (16/17), influenza planning (14/17), and pediatric care (15/17), but substantially fewer addressing care for burn patients (9/17). Many states lacked publicly available guidance on maintaining standards of care during disasters, and many states with specific care guidelines had not sufficiently addressed the full spectrum of hazard to which their health care systems remain vulnerable.

Coronavirus disease 2019 (Covid-19) has led to unprecedented healthcare demand. This study seeks to characterize Emergency Department (ED) discharges suspected of Covid-19 that are admitted within 72 h. We abstracted all adult discharges with suspected Covid-19 from five New York City EDs between March 2nd and April 15th. Those admitted within 72 h were then compared against those who were not using descriptive and regression analysis of background and clinical characteristics. Discharged ED patients returning within 72 h were more often admitted if suspected of Covid-19 (32.9% vs 12.1%, p < .0001). Of 7433 suspected Covid-19 discharges, the 139 (1.9%) admitted within 72 h were older (55.4 vs. 45.6 years, OR 1.03) and more often male (1.32) or with a history of obstructive lung disease (2.77) or diabetes (1.58) than those who were not admitted (p < .05). Additional associations included non-English preference, cancer, heart failure, hypertension, renal disease, ambulance arrival, higher triage acuity, longer ED stay or time from symptom onset, fever, tachycardia, dyspnea, gastrointestinal symptoms, x-ray abnormalities, and decreased platelets and lymphocytes (p < .05 for all). On 72-h return, 91 (65.5%) subjects required oxygen, and 7 (5.0%) required mechanical ventilation in the ED. Twenty-two (15.8%) of the study group have since died. Several factors emerge as associated with 72-h ED return admission in subjects suspected of Covid-19. These should be considered when assessing discharge risk in clinical practice. •Covid-19 has challenged Emergency Departments (EDs) in New York City to discharge without definitive diagnosis.•Discharged ED patients returning within 72 h were more often admitted if suspected of Covid-19.•Older males with lung disease or diabetes were more likely to be admitted within 72 hours of discharge.•Gastrointestinal symptoms and decreased platelets and lymphocytes were associated with 72-hour return admission.•The study group suffered significant morbidity and mortality, with most requiring oxygen supplementation.

The Federal Emergency Management Agency (FEMA) divides the United States (US) into ten standard regions to promote local partnerships and priorities. These divisions, while longstanding, do not adequately address known hazard risk as reflected in past federal disaster declarations. From FEMA’s inception in 1979 until 2020, the OpenFEMA dataset reports 4127 natural disaster incidents declared by 53 distinct state-level jurisdictions, listed by disaster location, type, and year. An unsupervised spectral clustering (SC) algorithm was applied to group these jurisdictions into regions based on affinity scores assigned to each pair of jurisdictions accounting for both geographic proximity and historical disaster exposures. Reassigning jurisdictions to ten regions using the proposed SC algorithm resulted in an adjusted Rand index (ARI) of 0.43 when compared with the existing FEMA regional structure, indicating little similarity between the current FEMA regions and the clustering results. Reassigning instead into six regions substantially improved cluster quality with a maximized silhouette score of 0.42, compared to a score of 0.34 for ten regions. In clustering US jurisdictions not only by geographic proximity but also by the myriad hazards faced in relation to one another, this study demonstrates a novel method for FEMA regional allocation and design that may ultimately improve FEMA disaster specialization and response.