Emergency Supplies Research Articles

Research on Scenario Modeling for V-Tail Fixed-Wing UAV Dynamic Obstacle Avoidance

With the advantages of long-range flight and high payload capacity, large fixed-wing UAVs are often used in anti-terrorism missions, disaster surveillance, and emergency supply delivery. In the existing research, there is little research on the 3D model design of the V-tail fixed-wing UAV and 3D flight environment modeling. The study focuses on designing a comprehensive simulation environment using Gazebo and ROS, referencing existing large fixed-wing UAVs, to design a V-tail aircraft, incorporating realistic aircraft dynamics, aerodynamics, and flight controls. Additionally, we present a simulation environment modeling approach tailored for obstacle avoidance in no-fly zones, and have created a 3D flight environment in Gazebo, generating a large-scale terrain map based on the original grayscale heightmap. This terrain map is used to simulate potential mountainous terrain threats that a fixed-wing UAV might encounter during mission execution. We have also introduced wind disturbances and other specific no-fly zones. We integrated the V-tail fixed-wing aircraft model into the 3D flight environment in Gazebo and designed PID controllers to stabilize the aircraft’s flight attitude.

ASSESSMENT OF BYSTANDERS PREPAREDNESS AND KNOWLEDGE IN TRAUMA PATIENT MANAGEMENT: A STUDY IN KAKAMEGA COUNTY, WESTERN KENYA

Objective:The objective of the study was to assess Bystanderscapability to handle trauma patients at the prehospital environment in Kakamega County, Western Kenya. Design:The study utilized a descriptive cross-sectional design. Setting:The study was carried out in four Sub-counties in Kakamega County. Sample:Multistage sampling was used to select a sample of two hundred and fifty-six participants(n = 256) Analysis:Data was analyzed using measures of central tendency and dispersion. Main outcome measures:Demographic characteristics, Level of knowledge, attitude and practice among bystanders towards trauma patients. Results:Most of the participants (44.5%) were between the ages 18-27 years old, majority 74.6% being of male gender. 90% respondents had witnessed injuries with a number of accidents witnessed averaging 1-5 (65%) in a period of 3 months. While 22% responded by taking the victims to the hospital, nearly half of the participants either called the police (29%) or stared at the incident (20%). Majority,(51.2%) lacked confidence in handling persons with obstructed airway, while (46.7%) were abit confident in handling patients with bleeding. 64.8% of the respondents lacked knowledge of contacts for emergency response. Availability of Emergency care equipment and supplies was 20% at Lurambi, with the remaining three sub-counties having lowest at (6.7%). Conclusion:There is inadequate knowledge of trauma care among Bystanders and lack of essential emergency care equipment and supplies in management of trauma patients in the prehospital environment of Kakamega County. Recommendations:The County government through the Ministry of Health to train first responders on Basic First Aid and Cardiopulmonary resuscitation and establish booths where bystanders can access equipment and supplies for trauma care.

A humanitarian vehicle routing problem synchronized with drones in time-varying weather conditions

This paper applies the cooperative delivery mode of trucks synchronized with drones to humanitarian logistics (HVRP-SD), considers the impact of time-varying weather conditions on the synchronous delivery from two dimensions (HVRP-SD-TVW): drone safety and drone delivery efficiency, and investigate a multi-objective optimization problem. This issue concerns not only the delivery timeliness of relief supplies, but also the fairness of supplies allocation. First, we establish a basic multi-objective mixed integer programming model for HVRP-SD, and then establish an extended mathematical model for HVRP-SD-TVW. To solve the multi-objective optimization problem, we develop a hybrid multi-objective evolutionary algorithm (HMOEA). According to the characteristics of HVRP-SD-TVW, HMOEA designs a variable-length two-dimensional array encoding method, fitness evaluation rules, multimodal mutation, and specialized local search operators. A set of numerical experiments prove that HMOEAS is highly competitive, and both the multimodal mutation and local search have significant effects on improving the quality of solutions. Further, taking the emergency supplies distribution in flood-stricken areas of Gongyi City, China in 2021 as a sample case, we prove that weather conditions play an important role in the truck-drone synchronized delivery decision by comparing the results of the basic model and extended model. In addition, we respectively analyze the variation in solutions under different weather scenarios, departure times, and drone risk resilience to guide decision-making.

Demand Prediction of Emergency Supplies in Campus Public Health Emergencies Based on GM-GA-BP Neural Network

Medical alcohol is the most widely used and highly demanded emergency supply in both campus public environments and medical settings. It has a sharp contradiction between supply and demand in the event of a public health event. For this reason, forecasting the demand for medical alcohol is crucial for averting and managing unexpected public health issues on campus. An enhanced GM-GA-BP neural network prediction model was put out in this article. The benefits of the equal dimension and new information complement GM(1,1) model's new and old information replacement and small sample data prediction are combined. Following data fitting and modification, a BP neural network based on conjugate gradient algorithm is built to carry out training and prediction. Meanwhile, the connection weight and threshold were globally optimized through genetic algorithm.To forecast the demand for medical alcohol at a certain university in Yibin City from 2022 to 2023, a thorough comparison of a combination model vs the conventional BP neural network model was made. The results showed that the MAPE had been decreased by roughly 3% and the absolute percentage error was as low as 0.12686%. These findings have provided a scientific reference for the university to improve its emergency material reserve strategy represented by medical alcohol.

Multi-objective medical supplies distribution open vehicle routing problem with fairness and timeliness under major public health emergencies

Fair and timely delivery of supplies plays a critical role under major public health emergencies. In this paper, aiming at fairness and timeliness, an optimization model of open vehicle routing problem for medical supplies distribution is established considering the urgency of the demand. We adopt a differential evolutionary algorithm with fast non-dominated solution sorting to solve the proposed model, obtaining an approximate Pareto optimal solution set. Through the comparison of algorithms, the results showed that the differential evolutionary algorithm with non-dominated sorting is superior with a shorter runtime and more diverse solutions, while the epsilon constraint method has more accurate solutions. In the case verification, the quality of the solutions of both algorithms was within the acceptable range, but the runtime of the epsilon constraint method was too long to be applicable. The results can provide theoretical suggestions and practical guidance for decision-makers in emergency supplies distribution.

Emergency order response strategy under supply chain collaboration

This paper studies the production and ordering response strategy with uncertain demand in two-tier supply chain composed of a social planner and a manufacturer. In light of the uncertain market demand, the manufacturer needs advance production before receiving the regular order from social planner to make quick response, and reserve some additional production capacity in case of emergency orders. We derive the conditions whereby the manufacturer can benefit from the emergency production and emergency orders and the social planner is willing to place the emergency orders and upgrade the optimal decisions with Pareto improvement. Besides, we find that, (1) the unit cost for emergency order is either too high or low, which might be worse off if the emergency order opportunity is provided to social planner; (2) even if the centralized case is better than the decentralized case in terms of the total cost, the social planner prefers decentralized case to centralized case. Finally, we use the real data to prove the theoretical analysis and show that the emergency supply mechanism can almost meet domestic demand. At the same time, we determine the optimal unit cost for emergency order based on total cost and respective costs for both parties.

Prey preference in a kleptoplastic dinoflagellate is linked to photosynthetic performance

Dinoflagellates of the family Kryptoperidiniaceae, known as “dinotoms”, possess diatom-derived endosymbionts and contain individuals at three successive evolutionary stages: a transiently maintained kleptoplastic stage; a stage containing multiple permanently maintained diatom endosymbionts; and a further permanent stage containing a single diatom endosymbiont. Kleptoplastic dinotoms were discovered only recently, in Durinskia capensis; until now it has not been investigated kleptoplastic behavior and the metabolic and genetic integration of host and prey. Here, we show D. capensis is able to use various diatom species as kleptoplastids and exhibits different photosynthetic capacities depending on the diatom species. This is in contrast with the prey diatoms in their free-living stage, as there are no differences in their photosynthetic capacities. Complete photosynthesis including both the light reactions and the Calvin cycle remain active only when D. capensis feeds on its habitual associate, the “essential” diatom Nitzschia captiva. The organelles of another edible diatom, N. inconspicua, are preserved intact after ingestion by D. capensis and expresses the psbC gene of the photosynthetic light reaction, while RuBisCO gene expression is lost. Our results indicate that edible but non-essential, “supplemental” diatoms are used by D. capensis for producing ATP and NADPH, but not for carbon fixation. D. capensis has established a species-specifically designed metabolic system allowing carbon fixation to be performed only by its essential diatoms. The ability of D. capensis to ingest supplemental diatoms as kleptoplastids may be a flexible ecological strategy, to use these diatoms as “emergency supplies” while no essential diatoms are available.

Building rural community disaster resilience in developing countries: insights from a Chinese NGO's Safe Rural Community Program.

As rural areas in developing countries are generally more vulnerable to disasters triggered by natural hazards than urban areas, it has become critical to strengthen rural community disaster resilience (CDR) to reduce the disaster risks. Using follow-up interviews, surveys, and secondary data, this study reviewed the "Safe Rural Community" (SRC) program implemented by One Foundation, a Chinese civilian NGO, after the 2013 Lushan earthquake in China. The study focused on five main key resilience elements; networks, infrastructure, institutions, capabilities, and culture. It was found that the SRC program successfully developed standardized, systematic, interrelated, and practical activities, such as local volunteer rescue teams, emergency supplies, disaster reduction training, community emergency plans, and regular emergency rescue drills. Third-party evaluations and a 2022 Lushan earthquake test revealed that this NGO-led, community-based, and team-oriented program had been effective. The SRC program in Lushan, therefore, provides some guidance on the development of effective CDR programs in rural communities in developing countries.

Research on the Distribution of Emergency Supplies during the COVID-19 Epidemic

The COVID-19 virus spreads quickly and is highly contagious, and the timeliness of emergency supplies is extremely demanding, so adequate and efficient emergency supplies have become a necessary prerequisite for strict prevention and control during the outbreak. However, the available research results are still relatively few, and using the brain storm optimization algorithm to solve the emergency supplies distribution problem is still blank. In order to optimize the emergency supplies distribution system in the context of COVID-19, this paper studies the open vehicle routing problem by considering the load weight constraints, demand constraints, and time window constraints. With the shortest total distribution distance as the objective function, a mathematical model of mixed integer linear programming is established, and the crossover operation of the genetic algorithm, the destruction operator and the repair operator of the large neighborhood search algorithm are introduced in the brain storm optimization algorithm to enhance the diversity of the solution while making the solution toward the optimal direction. Through the verification of two sets of examples, we found that compared with the other 13 solution algorithms, the solution capability and solution efficiency of the brain storm optimization algorithm are better than the comparison algorithms, which can significantly reduce the length of the distribution route and lower the distribution cost, and has excellent convergence and stability. Meanwhile, it can effectively improve the distribution efficiency of emergency supplies, which is of great significance to help the emergency reception and regular prevention and control during the outbreak of the COVID-19 epidemic. In addition, it has the necessary guidance for the improvement of personnel efficiency in the supply chain and logistics industry.

An Experimental Study on the Resistance of a High-Speed Air Cavity Craft

For the marine industry, resistance reduction can reduce energy consumption and achieve protection of the marine environment. The use of air lubrication to reduce the resistance of ships is one of the most important ways. With this technology, high-speed air cavity crafts show immense potential as they can be utilized in various marine activities, such as emergency rescue, supply, and maritime security. Through experiments, this study presents an in-depth analysis of the effects of bubble chamber pressure and initial stern inclination on the resistance of high-speed air cavity crafts at different speeds. The results show that air pressure has a significant impact on resistance. It was found that as the speed of the ship increased, the resistance reduction effect became more prominent under the same pressure conditions. Moreover, the resistance tended to stabilize when the pressure reached a certain value. In addition to the air pressure, the longitudinal inclination does have an effect on resistance reduction. To achieve better resistance reduction, the initial stern inclination angle should be chosen appropriately. Furthermore, adjusting the angle with speed changes can optimize the resistance reduction effect. This experimental study provides critical support for conducting further research on high-speed air cavity crafts. The findings offer valuable insights into improving hull forms, guiding host selection, and assessing performance.

Dynamic Optimization of Emergency Logistics for Major Epidemic Considering Demand Urgency

In recent years, epidemic disasters broke through frequently around the world, posing a huge threat to economic and social development, as well as human health. A fair and accurate distribution of emergency supplies during an epidemic is vital for improving emergency rescue efficiency and reducing economic losses. However, traditional emergency material allocation models often focus on meeting the amount of materials requested, and ignore the differences in the importance of different emergency materials and the subjective urgency demand of the disaster victims. As a result, it is difficult for the system to fairly and reasonably match different scarce materials to the corresponding areas of greatest need. Consequently, this paper proposes a material shortage adjustment coefficient based on the entropy weight method, which includes indicators such as material consumption rate, material reproduction rate, durability, degree of danger to life, and degree of irreplaceability, to enlarge and narrow the actual shortage of material supply according to the demand urgency. Due to the fact that emergency materials are not dispatched in one go during epidemic periods, a multi-period integer programming model was established to minimize the adjusted total material shortage based on the above function. Taking the cases of Wuhan and Shanghai during the lockdown and static management period, the quantitative analysis based on material distribution reflected that the model established in this paper was effective in different scenarios where there were significant differences in the quantity and structure of material demand. At the same time, the model could significantly adjust the shortage of emergency materials with higher importance and improve the satisfaction rate.

Allocation strategy of medical supplies during a public health emergency: a tripartite evolutionary game perspective

Ensuring the rational and orderly circulation of medical supplies during a public health emergency is crucial to quickly containing the further spread of the epidemic and restoring the order of rescue and treatment. However, due to the shortage of medical supplies, there are challenges to rationalizing the allocation of critical medical supplies among multiple parties with conflicting interests. In this paper, a tripartite evolutionary game model is constructed to study the allocation of medical supplies in the rescue environment of public health emergencies under conditions of incomplete information. The game’s players include Government-owned Nonprofit Organizations (GNPOs), hospitals, and the government. By analyzing the equilibrium of the tripartite evolutionary game, this paper makes an in-depth study on the optimal allocation strategy of medical supplies. The findings indicate that: (1) the hospital should reasonably increase its willingness to accept the allocation plan of medical supplies, which can help medical supplies allocate more scientifically. (2) The government should design a reasonable reward and punishment mechanism to ensure the rational and orderly circulation of medical supplies, which can reduce the interference of GNPOs and hospitals in the allocation process of medical supplies. (3) Higher authorities should strengthen the supervision of the government and the accountability for loose supervision. The findings of this research can guide the government in promoting better circulation of medical supplies during public health emergencies by formulating more reasonable allocation schemes of emergency medical supplies, as well as incentives and penalties. At the same time, for GNPOs with limited emergency medical supplies, the equal allocation of emergency supplies is not the optimal solution to improve the efficiency of emergency relief, and it is simpler to achieve the goal of maximizing social benefits by allocating limited emergency resources to the demand points that match the degree of urgency. For example, in Corona Virus Disease 2019, emergency medical supplies should be prioritized for allocation to government-designated fever hospitals that are have a greater need for medical supplies and greater treatment capacity.

Emergency supplies prepositioning via a government-led supply chain with a loss-averse supplier with anchoring

This paper investigates how to strategically stock and procure disaster supplies to respond to large-scale disasters under government-private framework agreements. We first consider a humanitarian supply chain (HSC) comprised of a humanitarian agency and a loss-averse supplier with anchoring. The agency buys a certain quantity of emergency supplies as regular stocks and simultaneously orders physical options through an option contract before major disasters occur. The supplier determines how many physical emergency products are produced as additional stocks. With backward derivation, the optimal decisions of regular stocks and additional stocks are characterized, respectively. Furthermore, several conditions under which the HSC could achieve coordination are tightly related to the option and exercise prices as well as the supplier’s levels of loss aversion and optimism. Interestingly, either over-ordering and under-stocking or under-ordering and over-stocking would occur, depending on whether the loss aversion effect dominates the anchoring effect. As the level of loss aversion increases, both the utility and profit of the supplier decrease. Moreover, even if the supplier is loss-averse, there is a Pareto option contract mechanism that benefits both parties when compared to the government-managed model. Finally, several numerical experiments are carried out, and some managerial insights based on different disaster scenarios are presented.

Exploring decision-making mechanisms for the metro-based underground logistics system network expansion: An example of Beijing

In facing “big-city diseases”, using urban underground space to build a stratified transportation system is crucial for the sustainable development of the social economy. In recent years, underground logistics systems (ULS) receive broad attention but developing a purpose-built ULS in megacities faces difficulties due to high costs and risks. As a cost-effective alternative, the metro-based ULS (M-ULS) initiatives provide new visions for the city-wide underground transport integration of passengers and freight. This paper explores the decision-making mechanisms of M-ULS network expansion based on multi-source data collection and mathematical programming. A model with three interrelated modules is proposed and applied in the Beijing city case. First, a monetary evaluation framework with 13 flow-based indicators is established to quantify the comprehensive benefits of M-ULS in terms of logistics economics, environment, transportation, urban space expansion, and emergency supplies. Second, correlations between metro freight service pricing and market purchase willingness are formulated based on surveys and interviews. Investment budgets and government subsidies are modeled as scenario variables affected by the project’s benefits and operating profits. Third, a mixed integer programming model is developed to optimize the multi-period facility location, allocation, and pricing during network expansion. Simulation results show that M-ULS has the ability to fully eliminate the road-based e-commerce distribution in city centers. The urban underground logistics businesses are expected to make metro operations profitable and recover the construction costs of both M-ULS and original metro lines. The project’s external benefits are equivalent to 0.8% of the city's GDP, where the most salient contributions come from breaking freight access restriction, energy-saving, efficiency upgrading, pollutant reduction, and traffic mobility improvement. Increasing funding support at the project’s early stage can significantly accelerate the system expansion. More findings related to M-ULS facility deployment, pricing mechanisms, and incentive strategies are disclosed.

Subsidy strategy for reserving flexible capacity of emergency supply production

AbstractThis paper investigates a government's subsidy strategy for motivating a manufacturer to set up a flexible production line for emergency supplies. Four subsidy strategies are proposed to ensure a desired service level in case of an emergency: zero subsidy, a fixed subsidy, a marginal subsidy, and a hybrid subsidy. We develop a game theoretical model to examine how the government can induce a manufacturer to set up a flexible production line that can respond promptly to an emergency, based on the manufacturer's cost structure (fixed and marginal costs). We find that when the marginal profit of an emergency product is higher than that of the manufacturer's regular product, a fixed (marginal) subsidy is the dominant strategy if the manufacturer's fixed (marginal) cost is high, while a hybrid subsidy strategy is dominant if both costs are high. When the marginal profit of an emergency product is lower than that of the manufacturer's regular product, neither a fixed subsidy nor a zero subsidy will be the dominant strategy. We also find that a marginal subsidy can ensure the effectiveness of the strategy, while a fixed subsidy helps improve strategy efficiency. We use government subsidy strategies implemented for Chinese COVID‐19 emergency supplies as examples to demonstrate the effectiveness and efficiency of the subsidy strategies under the proposed framework. We also extend the discussion by considering the manufacturer's social consciousness.

Barriers and facilitators to maternal death surveillance and response at a busy urban National Referral Hospital in Uganda.

Background: Preventable maternal and newborn deaths remain a global concern, particularly in low- and- middle-income countries (LMICs) Timely maternal death surveillance and response (MDSR) is a recommended strategy to account for such deaths through identifying contextual factors that contributed to the deaths to inform recommendations to implement in order to reduce future deaths. Implementation of MDSR is still suboptimal due to barriers such as inadequate skills and leadership to support MDSR. With the leadership of WHO and UNFPA, there is momentum to roll out MDSR, however, the barriers and enablers for implementation have received limited attention. These have implications for successful implementation. The aim of this study was: To assess barriers and facilitators to implementation of MDSR at a busy urban National Referral Hospital as perceived by health workers, administrators, and other partners in Reproductive Health. Methods: Qualitative study using in-depth interviews (24), 4 focus-group discussions with health workers, 15 key-informant interviews with health sector managers and implementing partners in Reproductive-Health. We conducted thematic analysis drawing on the Theory of Planned Behaviour (TPB). Results: The major barriers to implementation of MDSR were: inadequate knowledge and skills; fear of blame / litigation; failure to implement recommendations; burn out because of workload and inadequate leadership- to support health workers. Major facilitators were involving all health workers in the MDSR process, eliminate blame, strengthen leadership, implement recommendations from MDSR and functionalize lower health facilities (especially Health Centre -IVs). Conclusions: The barriers of MDSR include knowledge and skills gaps, fear of blame and litigation, and other health system factors such as erratic emergency supplies, and leadership/governance challenges. Recommendation: Efforts to strengthen MDSR for impact should use health system responsiveness approach to address the barriers identified, constructive participation of health workers to harness the facilitators and addressing the required legal framework.

A model for emergency supply management under extended EDAS method and spherical hesitant fuzzy soft aggregation information

Due to the frequent occurrence of numerous emergency events that have significantly damaged society and the economy, the need for emergency decision-making has been manifest recently. It assumes a controllable function when it is critical to limit property and personal catastrophes and lessen their negative consequences on the natural and social course of events. In emergency decision-making problems, the aggregation method is crucial, especially when there are more competing criteria. Based on these factors, we first introduced some basic concepts about SHFSS, and then we introduced some new aggregation operators such as the spherical hesitant fuzzy soft weighted average, spherical hesitant fuzzy soft ordered weighted average, spherical hesitant fuzzy weighted geometric aggregation, spherical hesitant fuzzy soft ordered weighted geometric aggregation, spherical hesitant fuzzy soft hybrid average, and spherical hesitant fuzzy soft hybrid geometric aggregation operator. The characteristics of these operators are also thoroughly covered. Also, an algorithm is developed within the spherical hesitant fuzzy soft environment. Furthermore, we extend our investigation to the Evaluation based on the Distance from Average Solution method in multiple attribute group decision-making with spherical hesitant fuzzy soft averaging operators. And a numerical illustration for “supply of emergency aid in post-flooding the situation” is given to show the accuracy of the mentioned work. Then a comparison between these operators and the EDAS method is also established in order to further highlight the superiority of the established work.

Optimization method of power grid material warehousing and allocation based on multi-level storage system and reinforcement learning

Businesses may save money and make better use of their resources by exercising reasonable control over the storage of power materials. Poor timeliness and ineffectiveness are the result of the old model's inability to fully use a significant volume of acquired data and information. This research presents a reinforcement learning-based material storage control model for the power grid to solve these issues. In order to achieve zero storage, real-time tracking of consumables is implemented. Material for large disasters need manufacturer coordination for storage. The reinforcement learning approach is used to dynamically stock and distribute emergency supplies. The three-tiered dynamic storage approach based on reinforcement learning that is suggested in this study is shown to be very efficient and significantly cuts operational expenses for power grid firms by verifying particular data.

Medical emergency supplies dispatching vehicle path optimization based on demand urgency

Abstract In recent years, the frequency of disasters, natural disasters, and other emergencies has been increasing worldwide. When an emergency occurs, effective rescue measures must be taken promptly to minimize the loss of life and property. In the process of rescuing casualties, a large amount of medical emergency supplies are urgently needed. Therefore, it is of great practical significance to study the vehicle path problem in medical emergency supplies dispatching. In this paper, we take the vehicle path optimization problem of medical emergency supplies dispatching considering the demand urgency as the research object, design the improved cuckoo-ant colony hybrid algorithm to solve the model based on the urgency analysis, and compare it with the ant colony algorithm and cuckoo algorithm to verify the efficiency of the designed algorithm. The results show that compared with the vehicle path scheme without considering the demand urgency, the path optimization scheme considering the demand urgency is more expensive and requires a small increase in time, but improves the efficiency and rationality of medical emergency supplies dispatching. The study of the emergency vehicle path problem can improve the weaknesses in the current emergency rescue decision-making, so that the emergency rescue work can be done quickly, economically, and reasonably, and provide a theoretical basis and suggestions for the emergency management department when making decisions.

Comprehensive emergency management of obstetric and newborn care program implementation at University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia, 2021: an evaluation study

BackgroundMaternal healthcare service is the care given for the woman during her gestation, delivery and postpartum period. The Maternal Mortality Ratio (MMR) was remains high and a public health problem in Ethiopia. Sub-Saharan African (SSA) countries account two-thirds of the global total maternal deaths. To curb such high burden related with child births, comprehensive emergency obstetric care is designed as one of the strategies for maternal healthcare services. However, its implementation status was not well investigated. This study aims to evaluate the implementation of comprehensive emergency obstetric and new born care program in terms of Availability, compliance and acceptability dimensions at University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia.MethodsA single case study design was employed from 01 to 30 April 2021. A total of 265 mothers who gave birth at University of Gondar Comprehensive Specialized Hospital (UoGCSH) during the data collection period for acceptability, 13 key informant interviews (KIIs), 49 non-participatory observations (25 observations during C/S performance and 24 assisted spontaneous vaginal deliver) and 320 retrospective document review were conducted. Availability, compliance and acceptability dimensions were evaluated using 32 indicators. Binary logistic regression model was fitted to identify factors associated with acceptability of the services. Adjusted Odds Ratio (AOR) with 95% confidence interval (CI) and p-value < 0.05 were also used to identify associated variables with acceptability. The qualitative data were recorded using tape recorder, transcribed in Amharic and translated to English language. Thematic analysis was done to supplement the quantitative findings.ResultsThe overall implementation of comprehensive emergency obstetric and newborn care (CEmONC) was 81.6%. Moreover, acceptability, availability and care provider’s compliance with the guideline accounted 81, 88.9 and 74.8%, respectively. There were stocked-out of some essential drugs, such as methyldopa, nifidipine, gentamycin and vitamin K injection. CEmONC training gaps, inadequate number of autoclaves, shortage of water supply and long-distance delivery ward to laboratory unit were also the barriers for the CEmONC service. Short waiting time of clients (AOR = 2.40; 95%CI: 1.16, 4.90) and maternal educational level (AOR = 5.50, 95%CI: 1.95, 15.60) were positively associated with acceptability of CEmONC services.ConclusionThe implementation status of CEmONC program was good as per our judgment parameter. Compliance of healthcare providers with the guideline was fair and needed improvement. Essential emergency drugs, equipment and supplies were stocked-out. The University of Gondar Comprehensive Specialized Hospital was therefore had better to give great emphasis to expand maternity rooms/ units. The hospital had better to avail the resources and provide continuous capacity building for healthcare providers to enhance the program implementation.