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Objectives: This study explores the factors influencing the construction duration of public health emergency medical facilities and the ways in which they can be enhanced. Methods: Combining 30 relevant emergency medical facility construction cases in different cities in China from 2020 to 2021, seven condition variables and an outcome variable were selected, and necessary and sufficient condition analyses of duration influence factors were conducted using the fsQCA method. Results: The consistency of seven condition variables was <0.9, which shows that the construction period of public health emergency medical facilities is not independently affected by a single condition variable but by multiple influencing factors. The solution consistency value of the path configurations was 0.905, indicating that four path configurations were sufficient for the outcome variables. The solution coverage of the four path configurations was 0.637, indicating that they covered ~63.7% of the public health emergency medical facility cases. Conclusion: To reduce the construction duration, the construction of emergency medical facilities should focus on planning and design, the selection of an appropriate form of construction, the reasonable deployment of resources, and the vigorous adoption of information technology.
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Health Facilities , Public Health , ChinaABSTRACT
In order to improve the scientificity of site selection decision⁃making of emergency medical facilities for rural public health emergencies, based on the characteristics of public health emergencies with rapid spread and strong harmfulness of corona virus disease 2019(COVID-19), according to the design standards of emergency medical facilities, taking into account the characteristics of small rural medical budget and rugged emergency roads, firstly, six influencing factors of engineering geological conditions, unit cost, infection rate, arrival time, site scale and service coverage area of alternative sites of facilities were selected. The Entropy value method(EVM) method and analytic hierarchy process(AHP) method were effectively combined to determine the weight of influencing factors. Secondly, a multi⁃objective location model considering the minimum sum of the distance from patients to emergency medical facilities and the optimal comprehensive evaluation value of the selected emergency medical facilities was established. Then, an IPSO algorithm was designed to solve the model and get the location decision. Finally, some villages in Tianmen city were selected for empirical analysis to verify the effectiveness of the model algorithm. The results show that infection rate and unit cost are the main influencing factors for the construction of emergency medical facilities. IPSO algorithm selects three emergency medical facilities, which can meet the treatment needs of patients in eight villages, and ensure that patients can seek medical treatment within 4-7 minutes,providing guarantee for efficient epidemic prevention and control activities. © 2023 China Safety Science Journal. All rights reserved.
ABSTRACT
In order to improve the scientificity of site selection decision⁃making of emergency medical facilities for rural public health emergencies, based on the characteristics of public health emergencies with rapid spread and strong harmfulness of corona virus disease 2019(COVID-19), according to the design standards of emergency medical facilities, taking into account the characteristics of small rural medical budget and rugged emergency roads, firstly, six influencing factors of engineering geological conditions, unit cost, infection rate, arrival time, site scale and service coverage area of alternative sites of facilities were selected. The Entropy value method(EVM) method and analytic hierarchy process(AHP) method were effectively combined to determine the weight of influencing factors. Secondly, a multi⁃objective location model considering the minimum sum of the distance from patients to emergency medical facilities and the optimal comprehensive evaluation value of the selected emergency medical facilities was established. Then, an IPSO algorithm was designed to solve the model and get the location decision. Finally, some villages in Tianmen city were selected for empirical analysis to verify the effectiveness of the model algorithm. The results show that infection rate and unit cost are the main influencing factors for the construction of emergency medical facilities. IPSO algorithm selects three emergency medical facilities, which can meet the treatment needs of patients in eight villages, and ensure that patients can seek medical treatment within 4-7 minutes,providing guarantee for efficient epidemic prevention and control activities. © 2023 China Safety Science Journal. All rights reserved.
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Accurate evaluation of the accessibility of medical facilities is a prerequisite for the reasonable allocation of medical resources in a city. The accessibility of medical facilities depends not only on the distance to the supply and demand points, but also on the time spent in the process, and the supply capacity of the supply points. Taking Xi'an City of Shaanxi Province as an example, this paper comprehensively considers the facility supply capacity and introduces the selection probability function based on the two-step floating catchment area (2SFCA) method. In addition, in order to approximate the residents' acceptance of different types of hospitals for long-distance medical treatment in real situations, different levels of search radius were set for the different levels of hospitals, and ArcGIS was used to measure the accessibility and evaluate the spatial layout of medical facilities in the main urban area of Xi'an. The results show that there is a significant difference in the accessibility of medical facilities in the main urban area of Xi'an, and the accessibility tends to decrease gradually from the central city to the periphery. The inequity in the allocation of medical facilities in the main urban area of Xi'an is more obvious, with about 81.64% of people having access to 54.88% of medical resources. The accessibility evaluation model established by the improved 2SFCA method can obtain more accurate and objective evaluation results. This study can provide a reference basis for urban medical facilities' planning and rational spatial layout.
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Health Facilities , Health Services Accessibility , Humans , China , Cities , HospitalsABSTRACT
Recent concerns raised by the World Health Organization over the Coronavirus raised a worldwide reaction. Governments are racing to contain and stop the Coronavirus from reaching an epidemic/pandemic status. This research presents a way in tracking such a virus or any contagious germ capable of transferring through air specifically where such a transfer can be assisted by a mechanical room ventilation system. Tracking the spread of such a virus is a complicated process, as they can exist in a variety of forms, shapes, sizes, and can change with time. However, a beginning has to be made at some point. Assumptions had to be made based on published scientific data, and standards. The tracking of airborne viruses was carried out on the following assumption (for illustrative purposes);one person with one sneeze in a period of 600 s. The presence of viruses was tracked with curves plotted indicating how long it could take to remove the sneezed viruses from the mechanically ventilated room space. Results gave an indication of what time span is required to remove airborne viruses. Thus, we propose the following: (a) utilizing CFD software as a possible tool in optimizing a mechanical ventilation system in removing contagious viruses. This will track the dispersion of viruses and their removal. The numerical solution revealed that with one typical adult human sneeze, it can take approximately 640 s to reduce an average sneeze of 20,000 droplets to a fifth;(b) upscaling the status of human comfort to a “must have” with regards to the 50% relative humidity, and the use of Ultraviolet germicidal irradiation (UVGI) air disinfection in an epidemic/pandemic condition. A recommendation can be presented to the local authorities of jurisdiction in enforcing the above proposals partially/fully as seen fit as “prevention is better than cure”. This will preclude the spread of highly infectious viruses in mechanically ventilated buildings.
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Purpose The purpose of this study is to discuss the principles and factors that influence the site selection of emergency medical facilities for public health emergencies. This paper discusses the selection of the best facilities from the available facilities, proposes the capacity of new facilities, presents a logistic regression model and establishes a site selection model for emergency medical facilities for public health emergencies in megacities. Design/methodology/approach Using Guangzhou City as the research object, seven alternative facility points and the points' capacities were preset. Nine demand points were determined, and two facility locations were selected using genetic algorithms (GAs) in MATLAB for programing simulation and operational analysis. Findings Comparing the results of the improved GA, the results show that the improved model has fewer evolutionary generations and a faster operation speed, and that the model outperforms the traditional P-center model. The GA provides a theoretical foundation for determining the construction location of emergency medical facilities in megacities in the event of a public health emergency. Research limitations/implications First, in this case study, there is no scientific assessment of the establishment of the capacity of the facility point, but that is a subjective method based on the assumption of the capacity of the surrounding existing hospitals. Second, because this is a theoretical analysis, the model developed in this study does not consider the actual driving speed and driving distance, but the speed of the unified average driving distance and the driving distance to take the average of multiple distances. Practical implications The results show that the method increases the selection space of decision-makers, provides them with stable technical support, helps them quickly determine the location of emergency medical facilities to respond to disaster relief work and provides better action plans for decision makers. Social implications The results show that the algorithm performs well, which verifies the applicability of this model. When the solution results of the improved GA are compared, the results show that the improved model has fewer evolutionary generations, faster operation speed and better model than the intermediate model GA. This model can more successfully find the optimal location decision scheme, making that more suitable for the location problem of megacities in the case of public health emergencies. Originality/value The research findings provide a theoretical and decision-making basis for the location of government emergency medical facilities, as well as guidance for enterprises constructing emergency medical facilities.
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The characteristics of coronavirus disease 2019 (COVID-19) clusters in medical and social welfare facilities and the factors associated with cluster size are still not yet fully understood. We reviewed COVID-19 cases in Japan identified from January 15 to April 30, 2020 and analyzed the factors associated with cluster size in medical and social welfare facilities. In this study, COVID-19 clusters were identified in 56 medical and 34 social welfare facilities. The number of cases in those facilities peaked after the peak of the general population. The duration of occurrence of new cases in clusters was positively correlated with the number of cases in both types of facilities (rho = 0.44, P < 0.001; and rho = 0.69, P < 0.001, respectively). However, the number of days between the first case in a prefecture and the onset of clusters was negatively correlated with the number of cases only in clusters in social welfare facilities (rho = - 0.4, P = 0.004). Our results suggest that COVID-19 cases in those facilities were prevalent in the latter phase of the disease's community transmission, although the underlying mechanisms for such a trend could differ between medical and social welfare facilities.
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COVID-19 , COVID-19/epidemiology , Humans , Japan/epidemiology , Social WelfareABSTRACT
Background: The coronavirus disease 2019 (COVID-19) has a tremendous influence in general public's behaviors; however, changes in the status of regularly scheduled outpatient visits in Japan during COVID-19 pandemic are still unknown. Methods: This cross-sectional study was conducted in May 2020. Participants were recruited by an Internet-based survey company. A total of 659 patients (54% male, average age 60 ± 14 years) who had regularly scheduled outpatient visits prior to the onset of COVID-19 were enrolled. Participants answered four questions ("decrease in medical visit frequency," "inability to take regular medication," "deterioration of a chronic disease," and "utilization of telephone/online medical care") and stated whether they had a fear of acquiring infection at a medical facility. The associations between answers, fear of infection, and socio-demographic factors were examined. Results: Among the participants, 37.8% had decreased their medical visits, 6.8% were unable to take regular medications, 5.6% experienced a deterioration of chronic disease, and 9.1% utilized telephone/online medical care. Fear of being infected by COVID-19 at medical facilities was strongly associated with a reduced frequency of medical visits and lack of regular medications even after adjusting for socio-demographic factors and current medical histories. Conclusions: During the first wave of COVID-19, approximately 40% of participants reduced their frequency of medical visits. It is important to continue implementing thorough infection control measures at facilities and educating the public the importance of keeping chronic diseases in good condition, as well as promoting telephone/online medical care.