Although first responders (FRs) represent a high-risk group for exposure, little information is available regarding their risk of coronavirus disease 2019 (COVID-19) infection. The purpose of the current study was to determine the serological prevalence of past COVID-19 infection in a cohort of municipal law enforcement (LE) and firefighters (FFs).

Descriptive analysis of a de-identified data reporting Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) immunoglobulin G (IgG), or COR2G, serology results for municipal FRs. As part of the serology process, FRs were surveyed for COVID-19-like symptoms since February 2020 and asked to report any prior COVID-19 nasal swab testing. Descriptive statistics and two-sided Chi Square tests with Yates correction were used to compare groups.

Of 318 FRs, 225 (80.2%) underwent serology testing (LE: 163/207 [78.7%]; FF: 92/111 [82.9%]). The prevalence of positive serology for all FRs tested was 3/255 (1.2%). Two LE (1.2%) and one FF (1.1%) had positive serology (P = 1.0). Two hundred and twenty-four FRs responded to a survey regarding prior symptoms and testing. Fifty-eight (25.9%) FRs (44 LE; 14 FFs) reported the presence of COVID-19-like symptoms. Of these, only nine (15.5%) received reverse transcriptase – polymerase chain reaction (RT-PCR) testing; none were positive. Two of the three FRs with positive serology reported no COVID-19-like symptoms and none of these responders had received prior nasal RT-PCR swabs. The overall community positive RT-PCR rate was 0.36%, representing a three-fold higher rate of positive seroprevalence amongst FRs compared with the general population (P = .07).

Amongst a cohort of municipal FRs with low community COVID-19 prevalence, the seroprevalence of SARS-CoV-19 IgG Ab was three-fold greater than the general community. Two-thirds of positive FRs reported a lack of symptoms. Only 15.5% of FRs with COVID-19-like symptoms received RT-PCR testing. In addition to workplace control measures, increased testing availability to FRs is critical in limiting infection spread and ensuring response capability.

Hurricane Harvey (2017) forced the closure of hemodialysis centers across Harris County, Texas (USA) disrupting the provision of dialysis services. This study aims to estimate the percentage of hemodialysis clinics flooded after Harvey, to identify the proportion of such clinics located in high-risk flood zones, and to assess the sensitivity of the Federal Emergency Management Agency (FEMA) Flood Insurance Rate Maps (FIRMs) for estimation of flood risk.

Data on 124 hemodialysis clinics in Harris County were extracted from Medicare.gov and geocoded using ArcGIS Online. The FIRMs were overlaid to identify the flood zone designation of each hemodialysis clinic.

Twenty-one percent (26 of 124) of hemodialysis clinics in Harris County flooded after Harvey. Of the flooded clinics, 57.7% were in a high-risk flood zone, 30.8% were within 1km of a high-risk flood zone, and 11.5% were not in or near a high-risk flood zone. The FIRMs had a sensitivity of 58%, misidentifying 42% (11 of 26) of the clinics flooded.

Hurricanes are associated with severe disruptions of medical services, including hemodialysis. With one-quarter of Harris County in the 100-year floodplain, projected increases in the frequency and severity of disasters, and inadequate updates of flood zone designation maps, the implementation of new regulations that address the development of hemodialysis facilities in high-risk flood areas should be considered.

This study compared 2019 values for the National Health Security Preparedness Index (NHSPI) with 2020 rates of coronavirus disease 2019 (COVID-19)-related mortality as reported by the 50 US states and Puerto Rico during the first six months of the US pandemic (March 1 - August 31, 2020).

Data regarding provisional death counts and estimates of excess deaths for COVID-19 according to state and territory were downloaded from the Centers for Disease Control and Prevention (CDC) National Center for Health Statistics website. Reporting included the six-month-long period of March 1 - August 31, 2020. Excess mortality rates were calculated as the number of excess deaths per 100,000 persons in each state population using 2019 US Census Bureau data. Mean values for state and territorial NHSPI domain indices were compared to state and territorial rates of COVID-19-related excess mortality using multiple linear regression, including analysis of variance. Correlations between the 51 state and territorial NHSPI values and corresponding COVID-19 excess mortality rates were calculated using Pearson’s correlation coefficient.

These calculations revealed a high degree of variance (adjusted r square = 0.02 and 0.25) and poor correlation (P = .16 and .08) among values for the overall NHSPI as compared to low and high estimates of excess COVID-19 mortality rates for 50 US states and Puerto Rico.

There was also a high degree of variance (adjusted r square = 0.001 and 0.03) and poor correlation (P values ranging from .09 to .94) for values for the six individual domains of the NHSPI as compared to low and high estimates of excess COVID-19 mortality rates for 50 US states and Puerto Rico.

The NHSPI does not appear to be a valid predictor of excess COVID-19 mortality rates for 50 US states and Puerto Rico during the first six months of the pandemic.

Coronavirus disease 2019 (COVID-19) pandemic influences health care facilities world-wide. The flow rate, type, and severity of cases presented to emergency departments varied during the pandemic in comparison to the past years. However, this change has not been well-described among the cases of hospital admission due to toxic exposure.

Recognition of the pattern of toxic exposure among the cases refereed to Tanta Poison Control Center (TPCC; Tanta, Egypt) during the past five years, and furthermore, exploration of the impact of lockdown due to the COVID-19 pandemic on the pattern of presented cases.

The current study is a five-year retrospective, comparative cross-sectional study carried out among acutely intoxicated patients admitted to TPCC during the spring months (March through May) of 2016-2020. A total of 1,916 patients with complete medical records were recruited. The type and manner of toxic exposure, demographic, clinical data, and outcomes were analyzed.

The current study noted that there were delays in time from toxic exposure to emergency services during the lockdown period. This was reflected in significant lower recovery rates (884.8/1,000 population; z = −3.0) and higher death rates (49.4/1,000 population; z = 2.1) despite the marked decrease in the total number of hospital admissions in comparison to the past four years. The lockdown period showed significantly higher phosphides (z = 3.5; χ2 = 34.295; P <.001) and antipsychotics exposure (z = 3.6; χ2 = 21.494; P <.001) than the previous years. However, predominance of female exposure and intentional self-poisoning was maintained over the past five years, including the lockdown.

COVID-19-associated lockdown greatly reformed the usual intoxication pattern of the cases admitted to emergency room. Also, it played a role in delaying time of hospital arrival, which was reflected as lower recovery rates and higher death rates.

On-boat resuscitation can be applied by lifeguards in an inflatable rescue boat (IRB). Due to Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-COV-2) and recommendations for the use of personal protective equipment (PPE), prehospital care procedures need to be re-evaluated. The objective of this study was to determine how the use of PPE influences the amount of preparation time needed before beginning actual resuscitation and the quality of cardiopulmonary resuscitation (CPR; QCPR) on an IRB.

Three CPR tests were performed by 14 lifeguards, in teams of two, wearing different PPE: (1) Basic PPE (B-PPE): gloves, a mask, and protective glasses; (2) Full PPE (F-PPE): B-PPE + a waterproof apron; and (3) Basic PPE + plastic blanket (B+PPE). On-boat resuscitation using a bag-valve-mask (BVM) and high efficiency particulate air (HEPA) filter was performed sailing at 20km/hour.

Using B-PPE takes less time and is significantly faster than F-PPE (B-PPE 17 [SD = 2] seconds versus F-PPE 69 [SD = 17] seconds; P = .001), and the use of B+PPE is slightly higher (B-PPE 17 [SD = 2] seconds versus B+PPE 34 [SD = 6] seconds; P = .002). The QCPR remained similar in all three scenarios (P >.05), reaching values over 79%.

The use of PPE during on-board resuscitation is feasible and does not interfere with quality when performed by trained lifeguards. The use of a plastic blanket could be a quick and easy alternative to offer extra protection to lifeguards during CPR on an IRB.

Prehospital blood component therapy poses a possible treatment option among patients with severe bleeding. The aim of this paper was to characterize patients receiving prehospital blood component therapy by a paramedic-doctor-staffed, ground-based prehospital critical care (PHCC) service.

Bleeding patients with a clinical need for prehospital blood transfusion were included prospectively. The following data were collected: indication for transfusion, mechanism of injury, vital parameters, units of red blood cells (RBCs)/plasma transfused, degree of shock, demographics, and mortality.

Twenty-one patients received blood products: 12 (57%) traumatic injuries and nine (43%) non-traumatic bleeds, with a median of 1.5 (range 1.0-2.0) units of RBCs and 1.0 (range 0.0-2.0) unit of plasma. The most frequent trigger to initiate transfusion was on-going excessive bleeding and hypotension. Improved systolic blood pressure (SBP) and milder degrees of shock were observed after transfusion. Mean time from initiation of transfusion to hospital arrival was 24 minutes. In-hospital, 11 patients (61%) received further transfusion and 13 (72%) had urgent surgery within 24 hours. Overall, 28-day mortality was 29% at 24-hours and 33% at 28-days.

Prehospital blood component therapy is feasible in a ground-based prehospital service in a medium-sized Scandinavian city. Following transfusion, patient physiology and degree of shock were significantly improved.

This study was aimed to assess if combining the evaluation of blood glucose level (BGL) and the Triage Revised Trauma Score (T-RTS) may result in a more accurate prediction of the actual clinical outcome, both in general adult population and in elderly patients with trauma.

This is a retrospective cohort study, conducted in the emergency department (ED) of an urban teaching hospital, with an average ED admission rate of 75,000 patients per year. Those excluded: known diagnosis of diabetes, age <18 years old, pregnancy, and mild trauma (classified as isolate trauma of upper or lower limb, in absence of exposed fractures). A combined Revised Trauma Score Glucose (RTS-G) score was obtained adding to T-RTS: two for BGL <160mg/dL (8.9mmol/L); one for BGL ≥160mg/dL and < 200mg/dL (11.1mmol/L); and zero for BGL ≥ 200mg/dL. The primary outcome was a composite of patient’s death in ED or admission to intensive care unit (ICU). Receiver Operating Characteristic (ROC) curve analysis was used to evaluate the overall performance of T-RTS and of the combined RTS-G score.

Among a total of 68,933 traumas, 9,436 patients (4,407 females) were enrolled, aged from 18 to 103 years; 4,288 were aged ≥65 years. A total of 577 (6.1%) met the primary endpoint: 38 patients died in ED (0.4%) and 539 patients were admitted to ICU. The T-RTS and BGL were independently associated to primary endpoint at multivariate analysis. The cumulative RTS-G score was significantly more accurate than T-RTS and reached the best accuracy in elderly patients. In general population, ROC area under curve (AUC) for T-RTS was 0.671 (95% CI, 0.661 - 0.680) compared to RTS-G ROC AUC 0.743 (95% CI, 0.734 - 0.752); P <.001. In patients ≥65 years, T-RTS ROC AUC was 0.671 (95% CI, 0.657 - 0.685) compared to RTS-G ROC AUC 0.780 (95% CI, 0.768 - 0.793); P <.001.

Results showed RTS-G could be used effectively at ED triage for the risk stratification for death in ED and ICU admission of trauma patients, and it could reduce under-triage of approximately 20% compared to T-RTS. Comparing ROC AUCs, the combined RTS-G score performs significantly better than T-RTS and gives best results in patients ≥65 years.

In South Korea, the law concerning automated external defibrillators (AEDs) states that they should be installed in specific places including apartment complexes. This study was conducted to investigate the current status and effectiveness of installation and usage of AEDs in South Korea.

Installation and usage of AEDs in South Korea is registered in the National Emergency Medical Center (NEMC) database. Compared were the installed number, usage, and annual rate of AED use according to places of installation. All data were obtained from the NEMC database.

After excluding AEDs installed in ambulances or fire engines (n = 2,003), 36,498 AEDs were registered in South Korea from 1998 through 2018. A higher number of AEDs were installed in places required by the law compared with those not required by the law (20,678 [56.7%] vs. 15,820 [43.3%]; P <.001). Among them, 11,318 (31.0%) AEDs were installed in apartment complexes. The overall annual rate of AED use was 0.38% (95% CI, 0.33-0.44). The annual rate of AED use was significantly higher in places not required by the law (0.62% [95% CI, 0.52-0.72] versus 0.21% [95% CI, 0.16-0.25]; P <.001). The annual rate of AED use in apartment complexes was 0.13% (95% CI, 0.08-0.17).

There were significant mismatches between the number of installed AEDs and the annual rate of AED use among places. To optimize the benefit of AEDs in South Korea, changes in the policy for selecting AED placement are needed.

The 2017 International Liaison Committee on Resuscitation (ILCOR) guideline recommends that Emergency Medical Service (EMS) providers can perform cardiopulmonary resuscitation (CPR) with synchronous or asynchronous ventilation until an advanced airway has been placed. In the current literature, limited data on CPR performed with continuous compressions and asynchronous ventilation with bag-valve-mask (BVM) are available.

In this study, researchers aimed to compare the effectiveness of asynchronous BVM and laryngeal mask airway (LMA) ventilation during CPR with continuous chest compressions.

Emergency medicine residents and interns were included in the study. The participants were randomly assigned to resuscitation teams with two rescuers. The cross-over simulation study was conducted on two CPR scenarios: asynchronous ventilation via BVM during a continuous chest compression and asynchronous ventilation via LMA during a continuous chest compression in cardiac arrest patient with asystole. The primary endpoints were the ventilation-related measurements.

A total of 92 volunteers were included in the study and 46 CPRs were performed in each group. The mean rate of ventilations of the LMA group was significantly higher than that of the BVM group (13.7 [11.7-15.7] versus 8.9 [7.5-10.3] breaths/minute; P <.001). The mean volume of ventilations of the LMA group was significantly higher than that of the BVM group (358.4 [342.3-374.4] ml versus 321.5 [303.9-339.0] ml; P = .002). The mean minute ventilation volume of the LMA group was significantly higher than that of the BVM group (4.88 [4.15-5.61] versus 2.99 [2.41-3.57] L/minute; P <.001). Ventilations exceeding the maximum volume limit occurred in two (4.3%) CPRs in the BVM group and in 11 (23.9%) CPRs in the LMA group (P = .008).

The results of this study show that asynchronous BVM ventilation with continuous chest compressions is a reliable and effective strategy during CPR under simulation conditions. The clinical impact of these findings in actual cardiac arrest patients should be evaluated with further studies at real-life scenes.

The dispatch of Advanced Life Support (ALS) teams in Emergency Medical Services (EMS) is still a hardly studied aspect of prehospital emergency logistics. In 2015, the dispatch algorithm of Emilia Est Emergency Operation Centre (EE-EOC) was implemented and the dispatch of ALS teams was changed from primary to secondary based on triage of dispatched vehicles for high-priority interventions when teams with Immediate Life Support (ILS) skills were dispatched.

This study aimed to evaluate the effects on the appropriateness of ALS teams’ intervention and their employment time, and to compare sensitivity and specificity of the algorithm implementation.

This was a retrospective before-after observational study.

Primary dispatches managed by EE-EOC involving ambulances and/or ALS teams were included. Two groups were created on the basis of the years of intervention (2013-2014 versus 2017-2018).

A switch from primary to secondary dispatch of ALS teams in case of high-priority dispatches managed by ILS teams was implemented.

Appropriateness of ALS team intervention, total task time of ALS vehicles, and sensitivity and specificity of the algorithm were reviewed.

The study included 242,501 emergency calls that generated 56,567 red code dispatches. The new algorithm significantly increased global sensitivity and specificity of the system in terms of recognition of potential need of ALS intervention and the specificity of primary ALS dispatch. The appropriateness of ALS intervention was significantly increased; total tasking time per day for ALS and the number of critical dispatches without ALS available were reduced.

The revision of the dispatch criteria and the extension of the two-tiered dispatch for ALS teams significantly increased the appropriateness of ALS intervention and reduced both the global tasking time and the number of high-priority dispatches without ALS teams available.

Case reports are commonly used to report the health outcomes of mass gatherings (MGs), and many published reports of MGs demonstrate substantial heterogeneity of included descriptors. As such, it is challenging to perform rigorous comparisons of health services and outcomes between similar and dissimilar events. The degree of variation in published reports has not yet been investigated.

Examine patterns of post-event medical reporting in the existing literature and identify inconsistencies in reporting.

A systematic review of case reports was conducted. Included were English studies, published between January 2009 and December 2018, in Prehospital and Disaster Medicine (PDM) or Current Sports Medicine Reports (CSMR). Analysis of each paper was used to develop a list of 27 categories of data.

Seventy-five studies were initially reviewed with 54 publications meeting the inclusion criteria. Forty-two were full case reports (78%) and 12 were conference proceedings (22%). Of the 27 categories of data studied, only 13 were consistently reported in more than 50% of publications. Reporting patterns included inconsistent use of terminology/language and variable retrievability of reports. Reporting on event descriptors, hazard and risk analysis, and clinical outcomes were also inconsistent.

Case reports are essential tools for researchers and event team members such as medical directors and event producers. The authors found that current case reports, in addition to being inconsistent in content, were generally descriptive rather than explanatory; that is, focused on describing the outcomes as opposed to exploring possible connections between context and health outcomes.

This paper quantifies and demonstrates the current state of heterogeneity in MG event reporting. This heterogeneity is a significant impediment to the functional use of published reports to further the science of MG planning and to improve health outcomes. Future work based on the insights gained from this analysis will aim to align and standardize reporting to improve the quality and value of event reporting.

Without a robust evidence base to support recommendations for medical services at mass gatherings (MGs), levels of care will continue to vary and preventable morbidity and mortality will exist. Accordingly, researchers and clinicians publish case reports and case series to capture and explain some of the health interventions, health outcomes, and host community impacts of MGs. Streamlining and standardizing post-event reporting for MG medical services and associated health outcomes could improve inter-event comparability, thereby supporting and promoting growth of the evidence base for this discipline. The present paper is focused on theory building, proposing a set of domains for data that may support increasingly comprehensive, yet lean, reporting on the health outcomes of MGs. This paper is paired with another presenting a proposal for a post-event reporting template.

The conceptual categories of data presented are based on a textual analysis of 54 published post-event medical case reports and a comparison of the features of published data models for MG health outcomes.

A comparison of existing data models illustrates that none of the models are explicitly informed by a conceptual lens. Based on an analysis of the literature reviewed, four data domains emerged. These included: (i) the Event Domain, (ii) the Hazard and Risk Domain, (iii) the Capacity Domain, and (iv) the Clinical Domain. These domains mapped to 16 sub-domains.

Data modelling for the health outcomes related to MGs is currently in its infancy. The proposed illustration is a set of operationally relevant data domains that apply equally to small, medium, and large-sized events. Further development of these domains could move the MG community forward and shift post-event health outcomes reporting in the direction of increasing consistency and comprehensiveness.

Currently, data collection and analysis related to understanding health outcomes arising from MGs is not informed by robust conceptual models. This paper is part of a series of nested papers focused on the future state of post-event medical reporting.

Standardizing and systematizing the reporting of health outcomes from mass gatherings (MGs) will improve the quality of data being reported. Setting minimum standards for case reporting is an important strategy for improving data quality. This paper is one of a series of papers focused on understanding the current state, and shaping the future state, of post-event case reporting.

Multiple data sources were used in creating a lean, yet comprehensive list of essential reporting fields, including a: (1) literature synthesis drawn from analysis of 54 post-event case reports; (2) comparison of existing data models for MGs; (3) qualitative analysis of gaps in current case reports; and (4) set of data domains developed based on the preceding sources.

Existing literature fails to consistently report variables that may be essential for not only describing the health outcomes of a given event, but also for explaining those outcomes. In the context of current and future state reporting, 25 essential variables were identified. The essential variables were organized according to four domains, including: (i) Event Domain; (ii) Hazard and Risk Domain; (iii) Capacity Domain; and (iv) Clinical Domain.

The authors propose a first-generation template for post-event medical reporting. This template standardizes the reporting of 25 essential variables. An accompanying data dictionary provides background and standardization for each of the essential variables. Of note, this template is lean and will develop over time, with input from the international MG community. In the future, additional groups of variables may be helpful as “overlays,” depending on the event category and type.

This paper presents a template for post-event medical reporting. It is hoped that consistent reporting of essential variables will improve both data collection and the ability to make comparisons between events so that the science underpinning MG health can continue to advance.

Without a robust evidence base to support recommendations for first aid, health, and medical services at mass gatherings (MGs), levels of care will continue to vary. Streamlining and standardizing post-event reporting for MG medical services could improve inter-event comparability, and prospectively influence event safety and planning through the application of a research template, thereby supporting and promoting growth of the evidence base and the operational safety of this discipline. Understanding the relationships between categories of variables is key. The present paper is focused on theory building, providing an evolving conceptual model, laying the groundwork for exploring the relationships between categories of variables pertaining the health outcomes of MGs.

A content analysis of 54 published post-event medical case reports, including a comparison of the features of published data models for MG health outcomes.

A layered model of essential conceptual components for post-event medical reporting is presented as the Data Reporting, Evaluation, & Analysis for Mass-Gathering Medicine (DREAM) model. This model is relational and embeds data domains, organized operationally, into “inputs,” “modifiers,” “actuals,” and “outputs” and organized temporally into pre-, during, post-event, and reporting phases.

Situating the DREAM model in relation to existing models for data collection vis a vis health outcomes, the authors provide a detailed discussion on similarities and points of difference.

Currently, data collection and analysis related to understanding health outcomes arising from MGs is not informed by robust conceptual models. This paper is part of a series of nested papers focused on the future state of post-event medical reporting.