Emergency Calls Research Articles

FiReS: A semantic model for advanced querying and prediction analysis for first responders in post-disaster response plans

Natural disasters have emerged as a recurring and severe menace to the sustainability of countries, resulting in compromised environmental and infrastructural integrity, human fatalities, and significant economic repercussions. Prompt and effective response by first responders is essential in Disaster Risk Management (DRM) to reduce individuals' vulnerability and minimize environmental and infrastructural damages. However, disaster-related information is often generated by heterogeneous sources, making the first responders’ decision-making process complex and time-consuming. To address these challenges, a common conceptual model is imperative to improve interoperability among diverse organizations and software systems, enabling effective collaboration. Semantic Web technologies offer a promising solution for integrating heterogeneous data and providing well-defined meaning in the representation and exchange of DRM-related knowledge. In this context, this study introduces FiReS (First Responders System), an ontological model designed to enhance data interoperability among first responders in post-disaster response plans for advanced data analysis and machine learning prediction. The validation of FiReS is conducted through a series of case studies exploring various aspects of disaster response, such as the response time of emergency services and the volume and classification of emergency calls. This approach facilitates streamlined access, thorough analysis, and seamless exchange of information, empowering stakeholders to strengthen their disaster response strategies and foster resilience within communities.

Mortality after paediatric emergency calls for patients with or without pre-existing comorbidity: a nationwide population based cohort study

BackgroundLife-threatening conditions are infrequent in children. Current literature in paediatric prehospital research is centred around trauma and paediatric out-of-hospital cardiac arrests (POHCA). The aims of this study were to (1) outline the distribution of trauma, POHCA or other medical symptoms among survivors and non-survivors after paediatric emergency calls, and (2) to investigate these clinical presentations’ association with mortality in children with and without pre-existing comorbidity, respectively.MethodsNationwide population-based cohort study including ground and helicopter emergency medical services in Denmark for six consecutive years (2016–2021). The study included all calls to the emergency number 1-1-2 regarding children ≤ 15 years (N = 121,230). Interhospital transfers were excluded, and 1,143 patients were lost to follow-up. Cox regressions were performed with trauma or medical symptoms as exposure and 7-day mortality as the outcome, stratified by ‘Comorbidity’, ‘Severe chronic comorbidity’ and ’None’ based on previous healthcare visits.ResultsMortality analysis included 76,956 unique patients (median age 5 (1–12) years). Annual all-cause mortality rate was 7 per 100,000 children ≤ 15 years. For non-survivors without any pre-existing comorbidity (n = 121), reasons for emergency calls were trauma 18.2%, POHCA 46.3% or other medical symptoms 28.9%, whereas the distribution among the 134 non-survivors with any comorbidity was 7.5%, 27.6% and 55.2%, respectively. Compared to trauma patients, age- and sex-adjusted hazard ratio for patients with calls regarding medical symptoms besides POHCA was 0.8 [0.4;1.3] for patients without comorbidity, 1.1 [0.5;2.2] for patients with comorbidity and 6.1 [0.8;44.7] for patients with severe chronic comorbidity.ConclusionIn both non-survivors with and without comorbidity, a considerable proportion of emergency calls had been made because of various medical symptoms, not because of trauma or POHCA. This outline of diagnoses and mortality following paediatric emergency calls can be used for directing paediatric in-service training in emergency medical services.

KEY CHALLENGES AND THREATS FOR OPERATORS OF THE 112 EMERGENCY NUMBER DURING THE COVID-19 PANDEMIC ON THE EXAMPLE OF THE MAZOWIECKIE VOIVODESHIP

The article attempts to analyze emergency calls to the 112 number and demonstrate the challengesand threats faced by the 112 operators in the Mazowieckie Voivodeship during the COVID-19pandemic, a disease caused by the SARS-CoV-2 coronavirus. The research focuses on changes inthe type of calls, the increase in the number of calls and other difficulties that operators have hadto face. The analysis is based on data from the period of 2017 to 2022, particularly highlighting thenew challenges caused by the pandemic, such as handling requests connected with COVID-19.The authors draw attention to the important role of operators in public health protection andtheir exposure to stress in difficult working conditions. The study aims to understand the burdenon the emergency notification system in the context of the pandemic and to highlight the role ofoperators in this process.

Perceptions of utilizing a symptom self-management app for breast cancer patients receiving outpatient chemotherapy

PurposeBreast cancer (BC) patients who are undergoing outpatient chemotherapy encounter difficulties in symptom self-management at home. We have developed a mobile app with the support of self-regulation activities and nurse-led social service to empower self-management of BC patients during outpatient chemotherapy. The study aimed to explore the perceptions of breast cancer patients and nurses in utilizing an app with the functions of proactive nursing support and empowerment. MethodsThis is a qualitative study including group interviews with nurses and patients with breast cancer receiving outpatient chemotherapy. A total of eleven patients and five nurses were enrolled from August 2022 to October 2022. Thematic analysis was adopted to analyze the interview transcripts. Main themes and related sub-themes were drawn from the transcripts. ResultsBarriers (the lack of a contractual spirit) and facilitators (social support and native high-adherence) to app usage were identified. Following the six-week program, patients underwent various transformations such as improved health awareness and a tendency to pay more attention to psychological symptoms. This program also led to various changes in the nurses, including a transformation from taking the reactive emergency calls to a proactive approach of incorporating a self-regulation process and social support. ConclusionsThe findings from the group interviews stressed the importance of integrating technology and nursing social support in facilitating patient symptom self-management.

Revisiting the Effect of Rapid Response on the Frequency of Reported Crimes Using an Instrumental Variable Approach

Rapid response to emergency calls for service is among the most widely adopted crime prevention strategies used by police today while practitioners, policy makers, and researchers differ on its crime prevention efficacy. Using observational research designs to examine the relationship between rapid response and crime can give the appearance that faster response times lead to more crime because larger law enforcement agencies often allocate greater patrol resources to areas with greater crime counts. An instrumental variable approach is one research design solution to this research problem. Using a pair of instruments based on characteristics of beat boundaries and counts of adjoining beats, we find average response times are unrelated to the frequency of reported violent crimes. However, we also find that quicker rapid response is tied to fewer reported property crimes, specifically burglaries and motor vehicle thefts, with additional findings suggesting incapacitation is the mechanism behind the differences.

Reduced Pharmacological Intervention of Prehospital Services for Acute Alcohol Intoxication during the COVID-19 Pandemic in A Large District of Southern Italy.

Background Stress during a pandemic increases the risk of alcohol consumption, which may require pharmacological management. Methods An observational single-center retrospective study was conducted from 1 January 2018 to 31 December 2021, and divided into 2-year periods (2018-2019 and 2020-2021). This study focused on calls to one of the emergency departments (EDs) of seven hospitals in the Bari (Italy) metropolitan area for patients requiring emergency services (ESs) who were either admitted or not admitted, due to their refusal. Results A 30% reduction in emergency calls for alcohol-related issues and a 41.17% reduction in calls for patients who refused to be admitted to the ED were observed during the pandemic. During the pandemic, an inverse association was found between pharmacological treatment and number of calls coded green (non-critical) and yellow (fairly critical) in patients admitted to EDs. An inverse association was also found for calls coded green in patients not admitted to EDs and pharmacological treatment. Metadoxine was administered in almost all alcohol-related emergencies, primarily in conjunction with drugs acting on the gastrointestinal tract, irrespective of age, the period considered, and whether patients were admitted or not admitted to the ED. Conclusions ES is the first and only out-of-hospital service encountered by numerous patients with alcohol-use disorders who refuse to be admitted to the ED. These patients should be directed by ES personnel to a multidisciplinary program to receive treatment for drinking, improve their quality of life, and reduce sanitation costs.

Development of violence-associated penetrating trauma in the Düsseldorf metropolitan region over a5-year period (GewPen study)

Penetrating injuries are arare but recurring emergency situation in the out-of-hospital and in-hospital emergency settings. The purpose of this study was to determine the incidence and characteristics of injuries associated with penetrating violence across aGerman metropolitan region over a5-year period. In the retrospective study, adatabase query of the control center of the Düsseldorf rescue service area was used to identify and descriptively analyze all rescue service operations with penetrating violence-associated injuries in the years 2015, 2017, and 2019. For those patients who were transferred to the major trauma center, afurther analysis of the in-hospital course was performed. In the 3 years 2015, 2017 and 2019 atotal of 266 patients (age: 33 ± 14years, male: 79%) could be recorded (2015 vs. 2017 vs. 2019: n = 81 vs. n = 93 vs. n = 92, respectively). The most common age group involved had an age range of 15-34years. Aparticularly higher frequency of emergency calls was found for the areas of Old Town, City Center, and one other district (Oberbilk). Ahigh frequency of rescue missions was found in the nights from Saturday to Sunday between 20.00 p.m. and 04.00 a.m. Rescue missions with emergency physicians on board increased over the years (2015 vs. 2019: 27 vs. 42%, p = 0.04). The primary weapons used were knives (56%), broken glass bottles (18%) and broken glasses (6%). Out of all patients 71 (27%, injury severity score11 ± 14) were admitted to the major trauma center. Among these patients, the proportion of immediate surgical care (2015 vs. 2019: 20% vs. 35%, p < 0.05) and positive alcohol detection increased over the years (2015 vs. 2019: 10% vs. 43%, p < 0.05). The 30-day mortality in the 3 years studied was 1.1% (n = 3). Penetrating injuries associated with violence are relevant but rare rescue missions. Future care strategies should focus on deployment of rescue resources close to the scene of the incident ("old town guard", central station), and prevention strategies should focus on weapon prohibition zones. A control of alcohol consumption should be discussed.

Reasons for calling in medical emergencies: development of a structured semantic model based on a randomised sample of medical emergency calls from an integrated emergency dispatch centre

Zusammenfassung Hintergrund Rettungsleitstellen sehen sich mit steigenden Herausforderungen durch kontinuierlich steigende Notrufzahlen konfrontiert. Zur besseren Strukturierung und Priorisierung der Notrufgespräche werden vielerorts standardisierte Abfragesysteme implementiert. Aktuelle Entwicklungen im Bereich der künstlichen Intelligenz eröffnen neue Möglichkeiten der Entscheidungsunterstützung von Disponierenden. Voraussetzung hierfür ist ein prozesshaftes Modell des Notrufdialogs. Ziel der Arbeit Auf Basis einer Analyse der komplexen Anrufgründe von Notrufgesprächen wird deren übergreifende Struktur abgeleitet und modellhaft dargestellt. Material und Methoden 50 randomisiert ausgewählte Aufzeichnungen medizinischer Notrufe einer integrierten Rettungsleitstelle aus dem Jahr 2022 wurden transkribiert, unter Anwendung einer qualitativen Inhaltsanalyse induktiv codiert, kategorisiert und in ein prozesshaftes Modell des Notrufdialogs überführt. Ergebnisse Das typische Notrufgespräch besteht aus zwei konsekutiven Prozessen, einem Einstiegs- und einem Rückfrageprozess. Der Einstiegsprozess dient der Informationsgewinnung mit dem Ziel, abschätzen zu können, ob es sich beim Notrufgrund um ein einzelnes Hauptproblem, die Kombination aus mehreren Gesundheitsbeeinträchtigungen oder ein Ereignis vor bzw. nach einer Gesundheitsbeeinträchtigung handelt. Der Rückfrageprozess dient der Präzisierung der Zustands- bzw. Problembeschreibung. Diskussion Auf Basis der zufällig ausgewählten Notrufgespräche konnte der idealtypische Ablauf des Notrufgesprächs abgeleitet und in einem phasen- bzw. prozesshaften Modell dargestellt werden, auf dessen Grundlage nun KI-gestützte Notrufabfragesysteme entwickelt werden können.

AI Powered Sign Language Translator

The purpose of this effort is to promote equitable environments and allow people with hearing disabilities to communicate in their native language by proposing an AI-based sign language translator. We used a transformer neural network, which can analyze over 500 data points from a person's face and gestures, to translate sign language into text. The translator can expand, produce new datasets, and build models for sign language recognition thanks to our machine learning process. As a proof of concept, we developed an interpreter for emergency calls using more than 200 sign language words. The main goal is to empower people who are deaf to participate in social, political, economic, and cultural spheres of life. We see a lot of people with illnesses, including blindness, deafness, and dumbness, every day. They have trouble interacting with other people. The suggested method can translate sign language into text and voice since this study describes two-way communication between deaf, dumb, and normal individuals. Key Words: Sign Language, Inclusion, Social Development, Artificial Intelligence, Machine Learning.

Predictive modelling of transport decisions and resources optimisation in pre-hospital setting using machine learning techniques.

The global evolution of pre-hospital care systems faces dynamic challenges, particularly in multinational settings. Machine learning (ML) techniques enable the exploration of deeply embedded data patterns for improved patient care and resource optimisation. This study's objective was to accurately predict cases that necessitated transportation versus those that did not, using ML techniques, thereby facilitating efficient resource allocation. ML algorithms were utilised to predict patient transport decisions in a Middle Eastern national pre-hospital emergency medical care provider. A comprehensive dataset comprising 93,712 emergency calls from the 999-call centre was analysed using R programming language. Demographic and clinical variables were incorporated to enhance predictive accuracy. Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and Adaptive Boosting (AdaBoost) algorithms were trained and validated. All the trained algorithm models, particularly XGBoost (Accuracy = 83.1%), correctly predicted patients' transportation decisions. Further, they indicated statistically significant patterns that could be leveraged for targeted resource deployment. Moreover, the specificity rates were high; 97.96% in RF and 95.39% in XGBoost, minimising the incidence of incorrectly identified "Transported" cases (False Positive). The study identified the transformative potential of ML algorithms in enhancing the quality of pre-hospital care in Qatar. The high predictive accuracy of the employed models suggested actionable avenues for day and time-specific resource planning and patient triaging, thereby having potential to contribute to pre-hospital quality, safety, and value improvement. These findings pave the way for more nuanced, data-driven quality improvement interventions with significant implications for future operational strategies.

When do medical operators choose to use, or not use, video in emergency calls? A case study

BackgroundAn evaluation report for a pilot project on the use of video in medical emergency calls between the caller and medical operator indicates that video is only used in 4%...

Multiple Table Models Based on Queuing Theory for Firefighting Traffic Problems

With the development of global urbanization, urban planning has been a hot spot of most concern. Since the traditional urban fire station setting method has been gradually unable to meet the emergency needs of a city. In this paper, a series of methods are developed to achieve the best balance between economic expenditure and reliability. According to the heat maps about emergency calls in a city in recent years, different types of alarm phones have obvious regional distribution characteristics. Inspired by the Queuing Theory algorithm, we abstract this complex problem into a parallel multi-server waiting queuing model to find each average queue length of three kinds of alarm calls and success in converting the multiplicity problem into solving the vehicle number and location problems respectively. Based on this planning problem, new combinations with different numbers of vehicles can be gotten. Then based on the assignment model, the optimal deployment plan can also be different with different numbers and geographical locations of the three kinds of stations. Our method significantly improves the firefighting traffic problems and can be applied in the actual situation.

The Spatio-Temporal Distribution of Suicide-related Emergency Calls in a European City: Age and Gender Patterns, and Neighborhood Influences.

Objective: The aim of this study was to conduct a comprehensive spatio-temporal analysis of suicide-related emergency calls in the city of Valencia (Spain) over a six-year period. To this end we first examined age and gender patterns and, second, the influence of neighborhood characteristics on general and gender-specific spatio-temporal patterns of suicide-related emergency calls. Method: Geocoded data on suicide-related emergency calls between 2017 and 2022 (N = 10,030) were collected from the 112 emergency service in Valencia. Data were aggregated at the census block group level, used as a proxy for neighborhoods, and trimesters were considered as the temporal unit. Two set of analyses were performed: (1) demographic (age and gender) and temporal descriptive analyses and (2) general and gender-specific Bayesian spatio-temporal autoregressive models. Results: Descriptive analyses revealed a higher incidence of suicide-related emergency calls among females and an increase in calls among the 18-23 age group from 2020 onwards. The general spatio-temporal model showed higher levels of suicide-related emergency calls in neighborhoods characterized by lower education levels and population density, and higher residential mobility, aging population, and immigrant concentration. Relevant gender differences were also observed. A seasonal effect was noted, with a peak in calls during spring for females and summer for males. Conclusions: These findings highlight the need for comprehensive mental health targeted interventions and preventive strategies that account for gender-specific disparities, age-related vulnerabilities, and the specific characteristics of neighborhoods.

Exploring factors influencing time from dispatch to unit availability according to the transport decision in the pre-hospital setting: an exploratory study.

Efficient resource distribution is important. Despite extensive research on response timings within ambulance services, nuances of time from unit dispatch to becoming available still need to be explored. This study aimed to identify the determinants of the duration between ambulance dispatch and readiness to respond to the next case according to the patients' transport decisions. Time from ambulance dispatch to availability (TDA) analysis according to the patients' transport decision (Transport versus Non-Transport) was conducted using R-Studio™ for a data set of 93,712 emergency calls managed by a Middle Eastern ambulance service from January to May 2023. Log-transformed Hazard Ratios (HR) were examined across diverse parameters. A Cox regression model was utilised to determine the influence of variables on TDA. Kaplan-Meier curves discerned potential variances in the time elapsed for both cohorts based on demographics and clinical indicators. A competing risk analysis assessed the probabilities of distinct outcomes occurring. The median duration of elapsed TDA was 173min for the transported patients and 73min for those not transported. The HR unveiled Significant associations in various demographic variables. The Kaplan-Meier curves revealed variances in TDA across different nationalities and age categories. In the competing risk analysis, the 'Not Transported' group demonstrated a higher incidence of prolonged TDA than the 'Transported' group at specified time points. Exploring TDA offers a novel perspective on ambulance services' efficiency. Though promising, the findings necessitate further exploration across diverse settings, ensuring broader applicability. Future research should consider a comprehensive range of variables to fully harness the utility of this period as a metric for healthcare excellence.

Person Reference and a Preference for Association in Emergency Calls

ABSTRACT Person reference is pervasive in talk. Conversation analytic work has identified preferences in person reference relating to recognitional reference. However, the principles shaping nonrecognitional reference are less well understood. We propose a preference for association in an institutional setting in which recognition is not relevant. Our data are calls to the New Zealand police emergency line that were institutionally classified as family harm. Using a collection methodology, we found that nonrecognitional person reference typically takes the form my x which directly associates speaker and referent, for example, “my partner,” “my ex-partner,” “my dad.” Initial references that suggest no association (e.g. “someone” or “an abusive guy”) were subsequently revised by callers using self-repair or targeted by call takers through questions that seek clarification about association. The shifts from nonassociative to associative references demonstrate participants’ orientations to the relevance of association and are evidence of a preference for association in the setting under examination. Data are in English.

VEHICLE ACCIDENT DETECTION AND RESCUE SYSTEM

The "Vehicle Accident Detection And Rescue System" project is a cutting-edge endeavour focused on revolutionizing road safety standards. It leverages a combination of sophisticated components, including Arduino Nano microcontrollers, nRF24L01 transceivers, GPS sensors, and SIM800 modules, to create a robust communication network among vehicles. This network enables real-time exchange of crucial information such as accidents and road conditions, empowering drivers with timely insights to navigate safely. Moreover, the project integrates an automatic accident detection system that swiftly responds to collisions by triggering emergency calls to predefined numbers like 100 for police and 108 for medical services. Through this seamless integration of technology, the project aims to mitigate accident risks and enhance overall road safety. Furthermore, the project addresses the challenges associated with overtaking manoeuvrers by introducing a feature that allows drivers to request passage through a simple button press. This functionality facilitates smooth communication between vehicles, ensuring safer overtaking experiences for all road users. By amalgamating state-of-the-art technologies with real-time communication capabilities, the project presents a comprehensive solution to optimize traffic management, reduce accident rates, and ultimately enhance road safety standards. KEY WORDS: Arduino Nano, nrf24L01, GSM Module, GPS Module, OLED

The Influence of Emergency Call Volume on Occupational Workload and Sleep Quality in Urban Firefighters.

The aim of the study is to determine the impact of emergency call volume on exertion, autonomic activity, and sleep among urban structural firefighters. Thirty-four firefighters wore a wrist-based monitor to track sleep and autonomic parameters and rated their level of perceived exertion (Borg Rating of Perceived Exertion) and subjective sleepiness after a 24-hour shift. Predictive variables included total run time and total run time after 11:59 PM. Total run time and sleep duration accounted for Borg Rating of Perceived Exertion and subjective sleepiness, while total run time and total run time after 11:59 PM accounted for sleep durations on-duty. The current results suggest that emergency call volume is associated with indicators of exertion and sleep. As such, call volume tracking is an important consideration for departments to ensure personnel readiness and wellness and provide a method of tracking the occupational demands experienced by firefighters on-duty.

SAKHII- Empowering Women with One-Tap Safety App

In India, numerous crimes targeting women occur daily. We are far from knowing the actual figures due to hundreds of cases that go unnoticed. Recognizing this pressing issue, the objective of this project is to develop a mobile application that can provide features of self-defense training techniques and emergency services access, such as locating the nearest police station, hospitals, bus stops, and pharmacies. It will include a list of emergency calling options to dial emergency numbers and real-time location sharing. When activated, the app will send the user's location every 3 minutes and enable them to share their location with the nearest police station and government bodies with just one tap in case of an emergency. This application is integrated with numerous features in one app, playing a pivotal role in women’s safety while providing a user-friendly experience.

Time Is Life: Golden Ten Minutes on Scene-EuReCa_Serbia 2014-2023.

Background and Objectives: This study analyzed the frequency of factors influencing the course and outcomes of out-of-hospital cardiac arrest (OHCA) in Serbia and the prediction of pre-hospital outcomes and survival. Materials and Methods: Data were collected during the period from 1 October 2014, to 31 September 2023, according to the protocol of the EuReCa_One study (clinical trial ID number NCT02236819). Results: Overall 9303 OHCA events were registered with a median age of 71 (IQR 61-81) years and 59.7% of them being males. The annual OHCA incidence was 85.60 ± 20.73/100,000. Within all bystander-witnessed cases, bystander-initiated cardiopulmonary resuscitation in 15.3%. Within the resuscitation-initiated group, return-of-spontaneous circulation (ROSC) on scene (any ROSC) was present in 1037/4053 cases (25.6%) and ROSC on admission to the nearest hospital in 792/4053 cases (19.5%), while 201/4053 patients survived to hospital discharge (5.0%). Predictive potential on pre-hospital outcomes was shown by several factors. Also, of all patients having any ROSC, 89.2% were admitted to the hospital alive. The probability of any ROSC dropped below 50% after 17 min passed after the emergency call and 10 min after the EMS scene arrival. These time intervals were significantly associated with survival to hospital discharge (p < 0.001). Five-minute time intervals between both emergency calls and any ROSC and EMS scene arrival and any ROSC also had a significant predictive potential for survival to hospital discharge (p < 0.001, HR 1.573, 95% CI 1.303-1.899 and p = 0.017, HR 1.184, 95% CI 1.030-1.361, respectively). Conclusions: A 10-min time on scene to any ROSC is a crucial time-related factor for achieving any ROSC, and indirectly admission ROSC and survival to hospital discharge, and represents a golden time interval spent on scene in the management of OHCA patients. A similar effect has a time interval of 17 min from an emergency call. Further investigations should be focused on factors influencing these time intervals, especially time spent on scene.

Knowledge of Infection Prevention and Control and Practice Behaviors among Career and Volunteer Firefighters in Rural Communities

Due to the emerging threat conditions in the work environment, firefighters are at a high risk of exposure to not only toxic substances but also biological agents in the dayroom and during emergency runs. The aim of this study is to evaluate firefighter (career and volunteer) knowledge and practice behaviors on infection control. This study surveyed 444 firefighters (210 career, 234 volunteer) in rural Northwestern Kentucky. The self-reported survey focused on individual characteristics, knowledge on exposure incident control, precautionary actions, and personal protections. We evaluated the descriptive characteristics of knowledge and practice scores stratified by firefighter groups (career and volunteers). The associations between infection control training received (yes/no) and firefighter knowledge and practice scores were also examined. Firefighters who were trained on infection control prevention had significantly higher knowledge scores (M = 63.7, SD = 13.4 vs. M = 59.7, SD = 15.9; p = 0.012). Volunteer firefighters exhibited better infection control practice behaviors than career firefighters (M = 70.6, SD = 13.0 vs. M = 67.4, SD = 11.1; p = 0.05). Firefighters who followed infection control guidelines (M = 69.5, SD = 11.9 vs. M = 58.1, SD = 9.9; p = 0.012) and expressed need for a comprehensive training on personal protective equipment (PPE) selection (β = 3.41, SE = 1.54, aOR = 30.22, 95% CI: 1.47–620.87; p = 0.028) had significantly higher practice scores compared to those who did not. The study results have policy implications for infection prevention and control (IPC) in rural fire departments, both career and volunteer. A review of infection control policies is needed, especially as it relates to training and practice behaviors during emergency calls and in the dayroom. Results also suggest the need to develop strategies to improve the culture of PPE use and training on the selection of PPEs appropriate to the emergency response type.