Role In Emergency Response Research Articles

Mental health of nursing students regarding the Moroccan earthquake: A cross-sectional study

ObjectiveIn addition to the economic and social impact, mental health issues are one of health needs during natural disaster such as earthquake. Thus, surveillance for mental health variables is crucial for public health planning. Nursing students as professional students may be particularly vulnerable to adverse mental health effects after an earthquake because of their potential role in emergency response and the challenges associated with providing medical care in crisis conditions. The aim of this research was to assess the mental health of students after six months of the Moroccan earthquake and associated factors. MethodA cross-sectional survey of student nurses was conducted on March 2024; six months after the Moroccan earthquake in front to 261 students using class sampling method. Three validated psychometric measures, Post-Traumatic Stress Disorder (PCL-C), Depression, Anxiety and Stress Scale (DASS-21), and The Connor-Davidson Resilience Scale (CD-RISC) were used to assess the nursing student mental health after Moroccan earthquake. ResultsAnxiety, Depression, Stress and abnormal post-traumatic stress rank was present respectively in 44.8%, 37.1%, 7.7%, 61.3% of participants. However, a minority of students obtained the high resilience score (13.8%). The results showed that the DAS scale correlated negatively with age (p = 0.034). Furthermore, the female gender, 3rd grade students (as final year for the nursing diploma) and those who had lost a family member in the natural disaster obtained higher medians with a significant difference in the DAS scale score (p < 0.05). The post-traumatic stress scale was only affected by material damage (p = 0.044). However, the high level of scores resilience obtained significantly for students living with their families. In contrast, no association between the mental health of nursing students and attending the phenomenon or living near earthquake foci. ConclusionThis study has demonstrated the crucial need to train healthcare providers in emotion management in the event of a natural disaster, and to launch a priori initiatives, particularly with regard to the mental health of students in health universities, in order to prepare them psychologically for any intervention in the case of an alert.

Seasonally inundated area extraction based on long time-series surface water dynamics for improved flood mapping

Accurate extraction of Seasonally Inundated Area (SIA) is pivotal for precise delineation of Flood Inundation Area (FIA). Current methods predominantly rely on Water Inundation Frequency (WIF) to extract SIA, which, due to the lack of analysis of dynamic surface water changes, often yields less accurate and robust results. This significantly hampers the rapid and precise mapping of FIA. In the study, based on the Harmonic Models constructed from Long Time-series Surface Water (LTSW) dynamics, an SIA extraction approach (SHM) was introduced to enhance their accuracy and robustness, thereby improving flood mapping. The experiments were conducted in Poyang Lake, a region characterized by active hydrological phenomena. Sentinel-1/2 remote sensing data were utilized to extract LTSW. Harmonic analysis was applied to the LTSW dataset, using the amplitude terms in the harmonic model to characterise the frequency of variation between land and water for the surface units, thus extracting the SIAs. The results reveal that the harmonic model parameters are capable of portraying SIA. In comparison to the commonly used WIF thresholding method for SIA extraction, the SHM approach demonstrates superior accuracy and robustness. Leveraging the SIA extracted through SHM, a higher level of accuracy in FIA extraction is achieved. Overall, the SHM offers notable advantages, including high accuracy, automation, and robustness. It offers reliable reference water extents for flood mapping, especially in areas with active and complex hydrological dynamics. SHM can play a crucial role in emergency response to flood disasters, providing essential technical support for natural disaster management and related departments.

A digital twin framework for efficient electric power restoration and resilient recovery in the aftermath of hurricanes considering the interdependencies with road network and essential facilities

The community's resilience in the face of natural hazards relies heavily on the rapid and efficient restoration of electric power networks, which plays a critical role in emergency response, economic recovery, and the functionality of essential lifeline and social infrastructure systems. Leveraging the recent data revolution, the digital twin (DT) concept emerges as a promising tool to enhance the effectiveness of post-disaster recovery efforts. This paper introduces a novel framework for post-hurricane electric power restoration using a hybrid DT approach that combines physics-based and data-driven models by utilizing a dynamic Bayesian network. By capturing the complexities of power system dynamics and incorporating the road network's influence, the framework offers a comprehensive methodology to guide real-time power restoration efforts in post-disaster scenarios. A discrete event simulation is conducted to demonstrate the proposed framework's efficacy. The study showcases how the electric power restoration DT can be monitored and updated in real-time, reflecting changing conditions and facilitating adaptive decision-making. Furthermore, it demonstrates the framework's flexibility to allow decision-makers to prioritize essential, residential, and business facilities and compare different restoration plans and their potential effect on the community.

Automated external defibrillator drones and their role in emergency response.

Automated external defibrillator drones and their role in emergency response.

The Role of Social Capital in the Response and Recovery Process of Post-Disaster Affected Communities

Many studies highlight human and physical capital’s role in the emergency response and post-disaster recovery phases. Even though social capital also plays a major role in emergency response and disaster recovery. Social capital can reduce disaster risk at the community level, especially for those who live in disaster areas. For this reason, the role of social capital in the emergency response and recovery phase is important, and its utilization must be developed. This study is expected to provide an overview of the role and influence of social capital in emergency response and post-disaster recovery in two different settings, both geographically and in the type of disaster that occurred. The research was conducted using a qualitative approach with a systematic literature review method, data collection was carried out by collecting literature, studies, articles, journals, reports, and previous research related to the role of social capital in post-disaster recovery process. The cases in this study are the eruption in Eyjafjallajökull in Iceland and the earthquake in Gili Trawangan, Indonesia. This review focuses on three forms of social capital, bonding, bridging, and linking, available in disaster-affected communities and how these forms of social capital affect the recovery process of communities affected by disasters. The results show that in both areas, bonding social capital plays the strongest role, but there are differences in the impact of disasters on the condition of social capital in both area.

Addressing the Dilemma of a “Crisis within a crisis”: Exploring the Penetration Testing challenges in a Mobile Field Hospital Setting

This paper focuses on evaluating the security challenges faced by mobile field hospitals, which play a crucial role in emergency response and disaster management in remote and austere environments. The authors conducted a penetration test using the Open Source Security Testing Methodology Manual (OSSTMM) framework to assess the security posture of a mobile field hospital. The methodology employed in the study included a combination of automated and manual techniques such as network scanning, vulnerability assessments, social engineering, and exploitation. The penetration test revealed several security vulnerabilities in the mobile field hospital, including weak passwords, unpatched software, and inadequate network segmentation. Additionally, the study identified vulnerabilities in the hospital's medical devices and equipment, posing a risk of cyber-attacks that could disrupt operations and compromise patient safety. The results underscore the importance of implementing enhanced security measures in mobile field hospitals to mitigate cyber threats and ensure the uninterrupted functioning of medical operations during emergencies and disasters. This study provides a comprehensive analysis of the mobile field hospital's security posture using the OSSTMM framework and emphasizes the urgent need for improved security practices in such settings. Keywords: Cybersecurity, Healthcare, Penetration Testing, Mobile Field Hospitals, Data, Emergency Response, Open Source, Security Testing, Ethical Hacking, Security Frameworks, Proceedings Citation Format Ahmed, N.B., Daclin, N., Olivaux, M. &amp; 4usserre, G. (2023): Addressing the Dilemma of a “Crisis within a crisis”: Exploring the Penetration Testing challenges in a Mobile Field Hospital Setting. Proceedings of the Cyber Secure Nigeria Conference. Nigerian Army Resource Centre (NARC) Abuja, Nigeria. 11-12th July, 2023. Pp 67-80 https://www.csean.org.ng/. dx.doi.org/10.22624/AIMS/CSEAN-SMART2023P9

Application and Improvement of the Particle Swarm Optimization Algorithm in Source-Term Estimations for Hazardous Release

Hazardous gas release can pose severe hazards to the ecological environment and public safety. The source-term estimation of hazardous gas leakage serves a crucial role in emergency response and safety management practices. Nevertheless, the precision of a forward diffusion model and atmospheric diffusion conditions have a significant impact on the performance of the method for estimating source terms. This work proposes the particle swarm optimization (PSO) algorithm coupled with the Gaussian dispersion model for estimating leakage source parameters. The method is validated using experimental cases of the prairie grass field dispersion experiment with various atmospheric stability classes. The results prove the effectiveness of this method. The effects of atmospheric diffusion conditions on estimation outcomes are also investigated. The estimated effect in extreme atmospheric diffusion conditions is not as good as in other diffusion conditions. Accordingly, the Gaussian dispersion model is improved by adding linear and polynomial correction coefficients to it for its inapplicability under extreme diffusion conditions. Finally, the PSO method coupled with improved models is adapted for the source-term parameter estimation. The findings demonstrate that the estimation performance of the PSO method coupled with improved models is significantly improved. It was also found that estimated performances of source parameters of two correction models were significantly distinct under various atmospheric stability classes. There is no single optimal model; however, the model can be selected according to practical diffusion conditions to enhance the estimated precision of source-term parameters.

Building on Success Serving the Nation: Codifying Key Pharmacy Practice Authorities Beyond COVID-19.

Building on Success Serving the Nation: Codifying Key Pharmacy Practice Authorities Beyond COVID-19.

Study on calculation model and risk area of radionuclide diffusion in coastal waters under nuclear leakage accidents with different levels

Abstract Study on calculation model and risk area of radionuclide diffusion in coastal waters under nuclear leakage accidents with different levels can help predict and evaluate consequences of radionuclide leakage accidents. Thus they play an important role in emergency response and accident mitigation. In the first step of the study, a climate hydrodynamic model in China coastal waters was established based on the climate data. In the next step, according to the real-time meteorological data, a hydrodynamic model in coastal waters of Haiyang nuclear power station was founded using the result of the climate hydrodynamic as a boundary. Then, according to the result of the hydrodynamic model in coastal waters of Haiyang nuclear power station, a radionuclide diffusion model in coastal waters of Haiyang nuclear power station was set up, in which the Euler method was adopted. With the radionuclide diffusion model, the total leaked radioactivity of radionuclides was set from 1018 Bq to 1012 Bq with a decrease of every two orders of magnitude. Thus, scenarios of radionuclide diffusion under assumed nuclear leakage accidents with different levels were calculated and their corresponding risk area were analyzed under the assumption that radionuclides leaked for consecutive five days. The results show that when the leaked radioactivity of radionuclides is 1018 Bq, the risk area on the seventh day is about 41 km east, 22 km south and 19 km west of the power station; on the fourteenth day, the risk area is about 65 km east, 22 km south and 25 km west of the power station. When the total leaked radioactivity of radionuclides declines by two orders of magnitude, the risk area will be reduced by about 10 km–20 km in the east direction accordingly. When it declines to 1014 Bq, the risk area decreases sharply to a small area. When it declines to 1012 Bq, the risk area is barely found. This model was verified from two aspects, namely the flow field and the radionuclide concentration. Hydrodynamic results can well describe the Yellow Sea cold water mass, Yellow Sea warm current and tidal current. Changes of radioactivity in different positions are fundamentally consistent with that in Fuikushima nuclear leakage accident. It indicates the hydrodynamic model and radionuclide diffusion model in the study are feasible and reliable.

Parallel Emergency Management of Incidents by Integrating OODA and PREA Loops: The C2 Mechanism and Modes

Given the differences of command and control (C2) activities between the field command center and the emergency operations center (EOC), this article combined the edge C2 theory with the parallel C2 theory, and proposed a parallel incident C2 mode based on the observe–orient–decide–act (OODA) loop and planning–readiness–execution–assessment (PREA) loop. The aim is to build up a PREA loop-based parallel incident C2 mode and its related operating mechanism of edge empowerment and energy release in parallel incident C2 mode. The parallel incident C2 mode based on the PREA loop and OODA loop supports the co-existence and connection of the two roles of the incident C2 agent at the emergency scene. The two roles are the executive role of emergency response and operation and the command and organization role of the edge emergency system. This article initiates a deep integration of two different C2 process mechanisms in the emergency response and operation process, taking into account the local emergency scene and the global emergency system. Taken together, a key issue has been well addressed regarding the contradiction that the traditional emergency response cannot be reconciled in terms of rapidity and thoroughness.

Gender, sexual orientation, ethnicity and socioeconomic factors influence how wildland firefighters communicate their work experiences

As climates change, natural resource professionals are often working on the frontlines of intensifying environmental disasters, acting in both scientific and emergency response roles. One subset of this group, wildland firefighters often engage in multifaceted careers that incorporate elements of resource planning, conservation management, community disaster relief, and operational management. Despite these STEM roles and nearly half (48%) of them having earned at least a bachelor's degree, usually in a STEM field, wildland firefighters are almost exclusively lumped with emergency responders in the scientific literature. We surveyed 708 wildland firefighters with 9 open response questions as part of a larger survey asking about experiences and attitudes in the United States federal workplace. From their responses and voluntarily provided demographic data, we extracted information about response length, use of hedges, tag questions and imperatives, use of personal language, use of expletives and derogatory language, use of apologetic language, and the types of responses provided. We then analyzed whether certain demographic and socioeconomic factors were statistical predictors of language use in wildland firefighter survey responses with the goal of ultimately providing a framework for differentiating and identifying factors that may influence employee retention, attitudes, morale, and experiences among wildland firefighter sub-demographics. We found that different demographic groups varied in their responses to questions: Minority groups used fewer words and were more likely to relate personal experiences than majority groups.

Knowledge of Emergency Colour Codes among Healthcare Workers in a Tertiary Care Hospital of Wardha, Maharashtra, India: A Cross-sectional Study

Introduction: An emergency refers to any crisis caused by humans or natural disasters that requires prompt and effective action to protect life and property. Consequently, a wellcoordinated and carefully planned emergency response is crucial. Medical emergency codes are utilised globally to alert hospital staff about various emergencies. Aim: To assess the knowledge of healthcare workers regarding emergency colour codes in a tertiary care hospital. Additionally, it aims to develop standardised operating procedures and policies based on these codes and provide guidance on their implementation in hospitals for different emergency situations. Materials and Methods: This cross-sectional study was conducted at Jawaharlal Nehru Medical College, Wardha, Maharashtra, India, from December 2021 to May 2022. A total of 100 healthcare workers aged &gt;18 years, employed at a tertiary care hospital, were included in the study. A survey was conducted using a structured questionnaire to assess the knowledge of the participants. The questionnaire consisted of two sections: the first section collected demographic information such as age, gender, qualifications, and profession, while the second section consisted of nine items to evaluate knowledge related to the role of emergency response codes in managing hospital emergencies. Descriptive statistics, including percentages and frequencies, were used to present the results. Results: In the present study, out of 100 study subjects, the maximum percentage (40%) belonged to the age group of 36- 55 years, while the minimum percentage (18%) belonged to the age group of 18-25 years. Among the participants, 25% were male and 75% were female. A significant proportion (92.7%) of the population demonstrated knowledge of the codes for handling hospital emergencies. Specifically, 98% of participants were familiar with the use of code red for fire emergencies, and 88% understood the process of activating code red. All participants had a basic understanding that code blue is used for cardiac arrest, and 85% had knowledge of paediatric emergency codes. Additionally, 96% were aware of the indications for Cardiopulmonary Resuscitation (CPR), and 100% knew the abbreviation for CPR. Conclusion: The present study revealed that 96% of the population had good knowledge, while 4% had average knowledge regarding the codes for handling hospital emergencies. Implementing standardised operating procedures and ensuring staff awareness of all emergency response codes used in the hospital are recommended.

Governing partnerships with technology companies as part of the COVID-19 response in Canada: A qualitative case study.

Cross-sector partnerships are vital for maintaining resilient health systems; however, few studies have sought to empirically assess the barriers and enablers of effective and responsible partnerships during public health emergencies. Through a qualitative, multiple case study, we analyzed 210 documents and conducted 26 interviews with stakeholders in three real-world partnerships between Canadian health organizations and private technology startups during the COVID-19 pandemic. The three partnerships involved: 1) deploying a virtual care platform to care for COVID-19 patients at one hospital, 2) deploying a secure messaging platform for physicians at another hospital, and 3) using data science to support a public health organization. Our results demonstrate that a public health emergency created time and resource pressures throughout a partnership. Given these constraints, early and sustained alignment on the core problem was critical for success. Moreover, governance processes designed for normal operations, such as procurement, were triaged and streamlined. Social learning, or the process of learning from observing others, offset some time and resource pressures. Social learning took many forms ranging from informal conversations between individuals at peer organisations (e.g., hospital chief information officers) to standing meetings at the local university's city-wide COVID-19 response table. We also found that startups' flexibility and understanding of the local context enabled them to play a highly valuable role in emergency response. However, pandemic fueled "hypergrowth" created risks for startups, such as introducing opportunities for deviation away from their core value proposition. Finally, we found each partnership navigated intense workloads, burnout, and personnel turnover through the pandemic. Strong partnerships required healthy, motivated teams. Visibility into and engagement in partnership governance, belief in partnership impact, and strong emotional intelligence in managers promoted team well-being. Taken together, these findings can help to bridge the theory-to-practice gap and guide effective cross-sector partnerships during public health emergencies.

Damage assessment of mobile communication facilities subjected to major earthquakes

ABSTRACT Communication systems play a critical role in emergency response during disasters. In this study, we proposed a methodology for assessing damage to mobile communication facilities subjected to major earthquakes, with consideration of both ground shaking and power outage effects. Fragility curves were employed to evaluate the damage to base stations due to ground shaking. The power transmission relationship among electrical substations was established to analyze the impact of power outage on base stations. Integration of the two evaluations yielded the total number of affected base stations and the distribution of malfunctioning base stations in a city or county. The 2016 Meinong earthquake and the 2018 Hualien earthquake were selected as case studies to verify the analytical results. The predictions exhibited acceptable agreement with disaster investigation reports from the two earthquake events. The proposed methodology enables a prompt evaluation of the seismic impact on mobile communication facilities, which could help governments in allocating rehabilitation resources during emergency response or disaster mitigation planning.

Computational modeling of first responders' willingness to accept radiation exposure during radiological or nuclear events.

Since the events of 9/11, a concerted interagency effort has been undertaken to create comprehensive emergency planning and preparedness strategies for the management of a radiological or nuclear event in the US. These planning guides include protective action guidelines, medical countermeasure recommendations, and systems for diagnosing and triaging radiation injury. Yet, key areas such as perception of risk from radiation exposure by first responders have not been addressed. In this study, we identify the need to model and develop new strategies for medical management of large-scale population exposures to radiation and examine the phenomena of radiation dread and its role in emergency response using an agent-based modeling approach. Using the computational modeling platform NetLogo, we developed a series of models examining factors affecting first responders' willingness to work (WTW) in the context of entering areas where radioactive contamination is present or triaging individuals potentially contaminated with radioactive materials. In these models, the presence of radiation subject matter experts (SMEs) was found to increase WTW. Degree of communication was found to be a dynamic variable with either positive or negative effects on WTW dependent on the initial WTW demographics of the test population. Our findings illustrate that radiation dread is a significant confounder for emergency response to radiological or nuclear events and that increasing the presence of radiation SME in the field and communication among first responders when such radiation SMEs are present will help mitigate the effect of radiation dread and improve first responder WTW during future radiological or nuclear events.

Launchable rotary wing UAV designs and launch mechanism designs for rotary wing UAV

In recent years, rotary-wing unmanned aerial vehicles have been used in many areas. Rotary wing unmanned aerial vehicle (UAV) can carry different payloads according to their duties. For example; if they carry cameras, they are used for reconnaissance / surveillance, cargo if they carry cargo, agriculture if they carry pesticides, mapping if they carry an advanced camera and mapping system, and communication if they carry a base station or relay. Rotary-wing unmanned aerial vehicles are usually commanded to take off manually by a trained UAV operator. Before takeoff, the rotary-wing unmanned aerial vehicle is prepared for take-off by the UAV operator and this preparation takes approximately five minutes. It takes time for rotary-wing unmanned aerial vehicles to take off from the runway and reach their cruising speed, causing time loss in critical areas. A rotary-wing unmanned aerial vehicle launch assembly and a rotary-wing unmanned aerial vehicle with an opening mechanism that can open the thrust arms after launch and continue to fly can be the solution to this time loss. Rotary-wing drones capable of launching and without the intervention of the UAV operator will play an important role in emergency response and defense, where situational awareness is often required. For example; firefighters responding to fires can take advantage of the ability to quickly launch rotary-wing unmanned aerial vehicles from a stationary or moving fire truck. Thanks to the day / thermal camera on the launched rotary wing unmanned aerial vehicles, valuable information can be obtained about the progress of the fire and the damage caused by the fire. Thanks to rapid awareness, the fire can be intervened and fought faster. Similarly, military personnel can quickly deploy launchable rotary-wing drones for reconnaissance and surveillance and perform their duties. In order to be applicable to various types of missions, it is important that the rotary wing unmanned aerial vehicle be portable and low in volume. Since the launchable rotary-wing unmanned aerial vehicle proposed in the thesis has an arm release mechanism after launch, it can automatically open and generate thrust after launching its arms. In this way, it helps lower volume coverage before being launched. This also reduces air friction during launch. It can be deployed to autonomous systems effortlessly as it has closed package, mobile and self-arm management. Different mechanisms will be studied to create an efficient design. A mechanism that allows it to open its arms in a short time will be used in the self-arm-opening management design. Throwable rotary wing unmanned aerial vehicle and launch mechanism will be designed and 3D printers will be used for prototype.

The impact of radiation dread on mass casualty medical management during a radiological or nuclear event.

Since the events of 9/11, a concerted interagency effort has been undertaken to create comprehensive emergency planning and preparedness strategies for management of a radiological or nuclear event in the US. These planning guides include protective action guidelines, medical countermeasure recommendations, and systems for diagnosing and triaging radiation injury. Yet, key areas such as perception of risk from radiation exposure by first responders have not been addressed. In this article, we identify the need to model and develop new strategies for the medical manage-ment of large-scale population exposures to radiation, examine the phenomena of radiation dread and its role in emergency response, and review recent findings on the willingness to work of first responders and other personnel involved in mass casualty medical management during a radiological or nuclear event.

Avoid, Trap, and Mitigate: Development of an Evidence-Based Crisis Management Framework in Surgery

Increasingly, surgeons are adopting broader roles in emergency response, on both clinical and executive levels. These have highlighted the need to develop healthcare-specific crisis management systems. Cross-professional research between safety-critical industries is a valuable method for learning crisis control. Commercial aviation, in particular, has been used to drive innovation in surgical safety. This study aimed to identify, adapt, and operationalize a surgical crisis management framework based on current practice in commercial aviation. A multimethod qualitative study interrogated safety experts in commercial aviation and healthcare. Stage I used immersive observational fieldwork in commercial aviation practice. Stage II performed semi-structured interviews with senior airline pilots. "Snowball" sampling targeted professional networks, recruiting 17 pilots from 4 airlines. Thematic analysis was used to derive a model of crisis management. Stage III undertook 3 focus groups with 5 pilots and 5 healthcare safety specialists. Expert consensus methods were used to adapt the model to clinical practice. Interview data provided 2,698 verbatim quotes on crisis management from aviation experts with a combined flying experience of 188,000 hours. Aviation crisis management was structured in 3 phases: avoid, trap, and mitigate. Adapted to clinical practice, these translated to crisis preparedness, recovery, and containment interventions. Additionally, the study identified 7 types of implementation tools and 9 crisis management skills that could be used to operationalize this framework in surgical practice. Surgical crisis management can follow the avoid, trap, and mitigate framework used in commercial aviation. Implementation relies on the combined use of crisis skills and performance tools. Crisis management should be delivered as part of a systems-based approach that relies on well-integrated failure management models. Simulation and in-situ validation of this framework is needed.

Integration of a geo-ontology-based knowledge model and spatial analysis into emergency response for geologic hazards

Emergency response is an important task in geologic hazard emergency management in China. Rapid emergency response actions can effectively reduce the losses caused by geologic hazards. Emergency plans and emergency command systems play an important role in emergency response. The emergency response still comes with challenges, such as the difficulty of integrating emergency plans with real-time geologic hazard information and the operability of emergency disposal in emergency plans. One possible approach to solving this problem is to model and represent knowledge and to enable the emergency command system to acquire and intelligently provide the required emergency response knowledge. In this paper, we propose a conceptual model of knowledge for geologic hazard emergency response (GHER). The geospatial characteristics of GHER knowledge are represented by the geo-ontology in the modeling process. The ontology enables semantic interoperability of GHER knowledge. A case study is used as an application test to evaluate the framework of GHER knowledge acquisition. In the framework, the GHER knowledge model enables the emergency command system to provide imperative knowledge intelligently for emergency decision-making; knowledge inference enables the emergency command system to provide important implicit knowledge for emergency response; and spatial analysis of geographic information system is applied to visualize and analyze spatial data in the process of emergency response.

Effects of COVID-19 Emergency Response Levels on Air Quality in the Guangdong-Hong Kong-Macao Greater Bay Area, China

The COVID-19 pandemic has affected air quality due to extreme changes in human behavior. We assessed the air quality response to different emergency levels during different COVID-19 periods and the naught period in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). We obtained the following conclusions: (1) The measures implemented to prevent and control of COVID-19 directly impacted ambient air pollutants. The air quality index and the concentrations of NO2, PM2.5, PM10, and CO in the GBA for 1–19 January 2020 declined 19.4%, 16.7%, 27.5%, 15.8%, and 25.7%, respectively, compared to the same time period in 2016–2019. (2) The reduction in air pollution was strongly associated with the first-level emergency response during this pandemic. The AQI, NO2, PM2.5, PM10, O3, and CO in the GBA decreased by 37.4%, 47.0%, 40.5%, 44.8%, 6.7%, and 24.1%, respectively. We found no statistically significant difference in the concentrations of different pollutants, except for NO2, during the second- and third-level responses. (3) The higher the emergency response level, the greater the NO2 pollutants reduction. The NO2 concentration was reduced by 47.0%, 25.5%, and 12.1% at emergency response levels 1, 2, and 3, respectively. The results highlight the importance of understanding the role of emergency response in air quality, and provide reference for authorities to formulate more scientific and reasonable emergency responses to epidemic prevention and control.