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1.
ACM Transactions on Internet Technology ; 22(3), 2021.
Article in English | Scopus | ID: covidwho-2038354

ABSTRACT

Edge/fog computing works at the local area network level or devices connected to the sensor or the gateway close to the sensor. These nodes are located in different degrees of proximity to the user, while the data processing and storage are distributed among multiple nodes. In healthcare applications in the Internet of things, when data is transmitted through insecure channels, its privacy and security are the main issues. In recent years, learning from label proportion methods, represented by inverse calibration (InvCal) method, have tried to predict the class label based on class label proportions in certain groups. For privacy protection, the class label of the sample is often sensitive and invisible. As a compromise, only the proportion of class labels in certain groups can be used in these methods. However, due to their weak labeling scheme, their classification performance is often unsatisfactory. In this article, a labeling privacy protection support vector machine using privileged information, called LPP-SVM-PI, is proposed to promote the accuracy of the classifier in infectious disease diagnosis. Based on the framework of the InvCal method, besides using the proportion information of the class label, the idea of learning using privileged information is also introduced to capture the additional information of groups. The slack variables in LPP-SVM-PI are represented as correcting function and projected into the correcting space so that the hidden information of training samples in groups is captured by relaxing the constraints of the classification model. The solution of LPP-SVM-PI can be transformed into a classic quadratic programming problem. The experimental dataset is collected from the Coronavirus disease 2019 (COVID-19) transcription polymerase chain reaction at Hospital Israelita Albert Einstein in Brazil. In the experiment, LPP-SVM-PI is efficiently applied for COVID-19 diagnosis. © 2021 Association for Computing Machinery.

2.
28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2022 ; : 4279-4289, 2022.
Article in English | Scopus | ID: covidwho-2020397

ABSTRACT

Recurring outbreaks of COVID-19 have posed enduring effects on global society, which calls for a predictor of pandemic waves using various data with early availability. Existing prediction models that forecast the first outbreak wave using mobility data may not be applicable to the multiwave prediction, because the evidence in the USA and Japan has shown that mobility patterns across different waves exhibit varying relationships with fluctuations in infection cases. Therefore, to predict the multiwave pandemic, we propose a Social Awareness-Based Graph Neural Network (SAB-GNN) that considers the decay of symptom-related web search frequency to capture the changes in public awareness across multiple waves. Our model combines GNN and LSTM to model the complex relationships among urban districts, inter-district mobility patterns, web search history, and future COVID-19 infections. We train our model to predict future pandemic outbreaks in the Tokyo area using its mobility and web search data from April 2020 to May 2021 across four pandemic waves collected by Yahoo Japan Corporation under strict privacy protection rules. Results demonstrate our model outperforms state-of-the-art baselines such as ST-GNN, MPNN, and GraphLSTM. Though our model is not computationally expensive (only 3 layers and 10 hidden neurons), the proposed model enables public agencies to anticipate and prepare for future pandemic outbreaks. © 2022 Owner/Author.

3.
Chinese Journal of Evidence-Based Medicine ; 22(8):932-947, 2022.
Article in Chinese | EMBASE | ID: covidwho-2006473

ABSTRACT

Objective To evaluate the evidence of the experience with medical sewage treatment procedures in medical institutions in China. Methods Databases including CNKI, WanFang Data, PubMed, Web of Science, and EBSCO were electronically searched to collect studies on the medical sewage treatment process, flow, and specifications in medical institutions in China. We used the quality evaluation system to classify and grade the experiences based on the principles and methods of evidence-based science and performed a descriptive analysis. Results After the SARS pandemic in 2003, China systematically established and standardized the technical criteria of medical sewage treatment and discharge. Moreover, a prevention system for the epidemic using medical sewage was constructed, which guaranteed that the quality of medical sewage treatment and discharge would meet the criteria and protect the citizens, and the technical specifications of medical sewage treatment would progress and increase strictly. At present, medical sewage treatment in medical institutions in China was based on mechanical and biological methods, and disinfection was mainly performed using chlorine and its compounds, ozone, and ultraviolet light. Conclusion The COVID-19 pandemic requires a higher quality of medical sewage treatment and discharge criteria for medical institutions in China. To meet these criteria, all medical institutions in China should check, replace, and update their old facilities;strengthen personnel training and effectively ensure the quality of medical sewage treatment.

4.
Journal of Geo-Information Science ; 23(11):1894-1909, 2021.
Article in Chinese | Scopus | ID: covidwho-1643910

ABSTRACT

The spread of infectious diseases is usually a highly nonlinear space-time diffusion process. Epidemiological models can not only be used to predict the epidemic trend, but also be used to systematically and scientifically study the transmission mechanism of the complex processes under different hypothetical intervention scenarios, which provide crucial analytical and planning tools for public health studies and policy-making. Since host behavior is one of the critical driven factors for the dynamics of infectious diseases, it is important to effectively integrate human spatiotemporal behavior into the epidemiological models for human-hosted infectious diseases. Due to the rapid development of human mobility research and applications aided by big trajectory data, many of the epidemiological models for Coronavirus Disease 2019 (COVID-19) have already coupled human mobility. By incorporating real trajectory data such as mobile phone location data at an individual or aggregated level, researchers are working towards the direction of accurately depicting the real world, so as to improve the effectiveness of the model in guiding actual epidemic prevention and control. The epidemic trend prediction, Non-pharmaceutical Interventions (NPIs) evaluation, vaccination strategy design, and transmission driven factors have been studied by the epidemiological models coupled with human mobility, which provides scientific decision-making aid for controlling epidemic in different countries and regions. In order to systematically understand this important progress of epidemiological models, this study collected and summarized relevant literatures. First, the interactions between the COVID-19 epidemic and human mobility were analyzed, which demonstrated the necessity of integrating the complex spatiotemporal behavior, such as population-based or individual-based mobility, activity, and contact interaction, into the epidemiological models. Then, according to the modeling purpose and mechanism, the models integrated with human mobility were discussed by two types: short-term epidemic prediction models and process simulation models. Among them, based on the coupling methods of human mobility, short-term epidemic prediction models can further be divided into models coupled with first-order and second-order human mobility, while process simulation models can be divided into models coupled with population-based mobility and individual-based mobility. Finally, we concluded that epidemiological models integrating human mobility should be developed towards more complex human spatiotemporal behaviors with a fine spatial granularity. Besides, it is in urgent need to improve the model capability to better understand the disease spread processes over space and time, break through the bottleneck of the huge computational cost of fine-grained models, cooperate cutting-edge artificial intelligence approaches, and develop more universal and accessible modeling data sets and tools for general users. 2021, Science Press. All right reserved.

5.
IEEE Transactions on Computational Social Systems ; 2021.
Article in English | Scopus | ID: covidwho-1566251

ABSTRACT

According to the World Health Organization and the CDC, social distancing is currently one of the most effective ways to slow the transmission of COVID-19. However, most existing epidemic models do not consider the impact of social distancing on the COVID-19 pandemic. In this article, we propose a new method to deterministic modeling of the effects of social distancing on the COVID-19 pandemic in a low transmission setting. Our model dynamic is expressed by a single predictive variable that satisfies an integro-differential equation. Once the dynamic variable is calculated, the process of agents from the normal state, infection state to rehabilitation state, or death state can be explored. Besides, an important parameter is added to the model to measure the impact of social distancing on epidemic transmission. We performed qualitative and quantitative experiments on various scenarios, and the results showed that 2 m is a safe social distancing on the COVID-19 pandemic in a low transmission setting. IEEE

6.
Journal of Hospitality and Tourism Insights ; ahead-of-print(ahead-of-print):20, 2021.
Article in English | Web of Science | ID: covidwho-1522487

ABSTRACT

Purpose - The objective of this study was to improve understanding of frontline staff's subjective happiness and anxiety during the COVID-19 pandemic by investigating the roles of employees' busy mindset and leader conscientiousness. Design/methodology/approach - The link between employee anxiety and subjective happiness was also explored, and the cross-level mediating effect of employee anxiety was tested using a multilevel design. A survey of 373 frontline staffers and 74 team leaders in the integrated resorts (IRs) was conducted in three waves: April (Time 1), May (Time 2) and June (Time 3) in 2020. The data were analysed with SPSS and Mplus using a hierarchical linear modelling (HLM) method. Findings - The results indicated that during the COVID-19 pandemic, a busy mindset increased frontline staff's anxiety and thus decreased their subjective happiness, and leader conscientiousness remedied the effect of anxiety on subjective happiness. Practical implications - The findings are relevant to frontline staffers, team leaders in the hospitality industry and corporate service departments. Against the background of COVID-19, conscientious leaders can significantly help employees to overcome their anxiety and insecurity and improve their subjective happiness, answering the urgent call to deal with the challenges of the new work-life environment. Originality/value - The study differs from previous other studies in two dimensions: First, the authors explored the interactions of the affective events from the cross-level perspectives, i.e. both team level and individual level. Second, the authors conducted this research on the mental issues of the hospitality frontline staffers in the context of the COVID-19 pandemic, which remains a black box to be explored.

7.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-291738

ABSTRACT

Recurring outbreaks of COVID-19 have posed enduring effects on global society, which calls for a predictor of pandemic waves using various data with early availability. Existing prediction models that forecast the first outbreak wave using mobility data may not be applicable to the multiwave prediction, because the evidence in the USA and Japan has shown that mobility patterns across different waves exhibit varying relationships with fluctuations in infection cases. Therefore, to predict the multiwave pandemic, we propose a Social Awareness-Based Graph Neural Network (SAB-GNN) that considers the decay of symptom-related web search frequency to capture the changes in public awareness across multiple waves. SAB-GNN combines GNN and LSTM to model the complex relationships among urban districts, inter-district mobility patterns, web search history, and future COVID-19 infections. We train our model to predict future pandemic outbreaks in the Tokyo area using its mobility and web search data from April 2020 to May 2021 across four pandemic waves collected by _ANONYMOUS_COMPANY_ under strict privacy protection rules. Results show our model outperforms other baselines including ST-GNN and MPNN+LSTM. Though our model is not computationally expensive (only 3 layers and 10 hidden neurons), the proposed model enables public agencies to anticipate and prepare for future pandemic outbreaks.

8.
IEEE Transactions on Computational Social Systems ; 2021.
Article in English | Scopus | ID: covidwho-1483778

ABSTRACT

Corona Virus Disease 2019 (COVID-19), due to its extremely high infectivity, has been spreading rapidly around the world and bringing huge influence to socioeconomic development and people's daily life. Taking for example the virus transmission that may occur after college students return to school, we analyze the quantitative influence of the key factors on the virus spread, including crowd density and self-protection. One Campus Virus Infection and Control Simulation (CVICS) model of the novel coronavirus is proposed in this article, fully considering the characteristics of repeated contact and strong mobility of crowd in the closed environment. Specifically, we build an agent-based infection model, introduce the mean field theory to calculate the probability of virus transmission, and microsimulate the daily prevalence of infection among individuals. The experimental results show that the proposed model in this article efficiently simulates how the virus spreads in the dense crowd in frequent contact under a closed environment. Furthermore, preventive and control measures, such as self-protection, crowd decentralization, and isolation during the epidemic, can effectively delay the arrival of infection peak, reduce the prevalence, and, finally, lower the risk of COVID-19 transmission after the students return to school. IEEE

9.
Chest ; 160(4):A511, 2021.
Article in English | EMBASE | ID: covidwho-1458470

ABSTRACT

TOPIC: Chest Infections TYPE: Original Investigations PURPOSE: Sepsis is common in critically ill COVID-19 patients and is associated with high mortality. However, the diagnosis of sepsis and the prediction of mortality are challenging in COVID-19 patients, especially in the early stage of sepsis. Research about the performance of SIRS criteria and qSOFA score in patients with COVID sepsis is limited. Therefore, this study aimed to compare the performance of SIRS, qSOFA, and a combination of both in hospitalized COVID-19 adult patients regarding the diagnosis of sepsis and the prediction of in-hospital mortality. METHODS: Retrospective data analysis included 341 patients who were hospitalized with laboratory-confirmed COVID-19 infection during April 2020 and January 2021 (the peaks of the first and second waves in New York state) at a 242-bed university-affiliated community-based hospital. Data from the initial patient encounter at the emergency room was collected by reviewing the electronic health records. SIRS criteria, qSOFA score, and a combination of both (SIRS+qSOFA) were analyzed by the MATLAB software. SIRS+qSOFA includes 5 parameters: tachypnea (respiratory rate ≥ 22), tachycardia (heart rate >90/min), fever or hypothermia (temperature >38°C (100.4°F) or < 36°C (96.8°F)), leukocytosis, leukopenia or bandemia (WBC > 12000/mm³, < 4000/mm³, or > 10% bands), altered mentation, and hypotension (systolic blood pressure ≤100 mmHg). The area under the receiver operating characteristic curves (AUC) was calculated to evaluate the performance of SIRS, qSOFA, and SIRS+qSOFA. RESULTS: In 341 COVID-19 patients, 128 patients were diagnosed with sepsis (37.5%), which included 77 expired patients (60.2%);213 patients were not diagnosed with sepsis (62.5%), which included 50 expired patients (23.5%). The AUCs for the diagnosis of sepsis with SIRS, qSOFA, and SIRS+qSOFA were 0.739, 0.731, and 0.793, respectively. The AUCs for the prediction of mortality with SIRS, qSOFA, and SIRS+qSOFA were 0.593, 0.665, and 0.646, respectively. For diagnosing sepsis, the sensitivity of SIRS (≥ 2), qSOFA (≥ 2), and SIRS+qSOFA (≥ 3) were 82.0%, 48.4%, and 68.8%, respectively;the specificity of SIRS (≥ 2), qSOFA (≥ 2), and SIRS+qSOFA (≥ 3) were 54.9%, 85.4%, and 76.5%, respectively. For predicting mortality, the sensitivity of SIRS (≥ 2), qSOFA (≥ 2), and SIRS+qSOFA (≥ 3) were 68.5%, 42.5%, and 55.9%, respectively;the specificity of SIRS (≥ 2), qSOFA (≥ 2), and SIRS+qSOFA (≥ 3) were 46.7%, 81.8%, and 68.7%, respectively. CONCLUSIONS: For diagnosing sepsis in COVID-19 patients, the performance of SIRS+qSOFA with 5 parameters (AUC=0.793) is better than either SIRS (AUC=0.739) or qSOFA (AUC=0.731). For predicting mortality, the performance of qSOFA (AUC=0.665) is superior to either SIRS (AUC=0.593) or SIRS+qSOFA (AUC=0.646). CLINICAL IMPLICATIONS: This study will facilitate the diagnosis of sepsis and the prediction of mortality in the hospitalized COVID-19 adult patients. DISCLOSURES: No relevant relationships by Shraddha Acharya, source=Web Response No relevant relationships by Inigo Atienza, source=Web Response No relevant relationships by Stephen Jesmajian, source=Web Response No relevant relationships by Jeffrey Lederman, source=Web Response No relevant relationships by Liyun Liu, source=Web Response No relevant relationships by Junfeng Xue, source=Web Response

10.
Chest ; 160(4):A394, 2021.
Article in English | EMBASE | ID: covidwho-1457548

ABSTRACT

TOPIC: Chest Infections TYPE: Medical Student/Resident Case Reports INTRODUCTION: More than a year has passed since the first reported cases of COVID-19 worldwide. We present a case of a patient with COVID-19 who acquired bilateral pulmonary fibrosis then later developed a pneumothorax of the right lung. Ironically, it was this fibrosis that prevented a catastrophic collapse of the lung. CASE PRESENTATION: This is a 60-year-old Caucasian female with hypertension, type II diabetes mellitus and obstructive sleep apnea (OSA) who was admitted due to a four-day history of worsening shortness of breath four days due to COVID pneumonia. She was admitted to the ICU due to worsening respiratory status and was maintained on bi-level positive airway pressure ventilation (BIPAP) for two weeks. Repeated chest radiographs in the ICU showed diffuse infiltrates with ground glass opacities bilaterally. She began to improve on the 3rd week of hospitalization, allowing titration down to high flow nasal cannula with BIPAP at night for OSA. On the 4th week, a routine chest radiograph incidentally revealed a small right apical pneumothorax. She had no desaturations, tachypnea, or increased work of breathing at this time. A CT scan of the chest confirmed the extensive pulmonary fibrosis and ground glass opacities and demonstrated the pneumothorax (Figure 1). A repeat 36 hour chest radiograph (Figure 2) showed expansion of the pneumothorax to a volume of 25% of the right hemithorax, with no signs of tension. The patient's clinical status remained unchanged. Follow-up chest CT scan (Figure 1) showed fibrotic attachments tethering the lungs to the pleura that may have limited its further collapse. Patient underwent a CT-guided pigtail catheter insertion the same day. Follow-up imaging the next day confirmed resolution of the pneumothorax. The pigtail catheter was later removed. The patient remained hospitalized, but improving. DISCUSSION: Pulmonary fibrosis is a known sequelae of COVID pneumonia. Bullae and cyst formation can form as a result of this extensive airspace disease. Secondary spontaneous pneumothorax in COVID-19 could be due to damage to the subpleural alveoli from the formation of cysts and bullae leading to spontaneous alveolar rupture into the pleural space. The use of BIPAP could have contributed to it, due to additional volume and barotrauma. Our patient developed pulmonary fibrosis after remaining hospitalized for more than 4 weeks. The fibrosis caused the lung to tether to portions of the pleura, preventing a quick, catastrophic collapse of the lung. The delay in progression gave the patient an opportunity to undergo a CT-guided pigtail catheter insertion, as opposed to an emergent chest tube thoracostomy which would have been a more invasive, traumatic, and painful procedure. CONCLUSIONS: This case highlights the possibility of extensive lung fibrosis, via thick pleural adhesions, protecting patients from developing fatal pneumothorax. REFERENCE #1: Wu, C., et al., Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China. JAMA Intern Med, 2020. 180(7): p. 934-943. REFERENCE #2: Rai, D.K., P. Sharma, and R. Kumar, Post covid 19 pulmonary fibrosis- Is it reversible? Indian Journal of Tuberculosis, 2020. REFERENCE #3: Martinelli, A.W., et al., COVID-19 and pneumothorax: a multicentre retrospective case series. Eur Respir J, 2020. 56(5) DISCLOSURES: No relevant relationships by Patrick Benjamin, source=Web Response No relevant relationships by Marvyn Allen Chan, source=Web Response No relevant relationships by Josemaria Demigillo, source=Web Response No relevant relationships by Ma Pamela Demigillo, source=Web Response No relevant relationships by Stephen Jesmajian, source=Web Response No relevant relationships by Junfeng Xue, source=Web Response

11.
IEEE Int. Conf. Ind. Eng. Eng. Manage. ; 2020-December:339-343, 2020.
Article in English | Scopus | ID: covidwho-1054459

ABSTRACT

For the "COVID-19"pandemic spreading around the globe, the successful development of nucleic acid testing reagents is critical to disease prevention and control. It has also made governments and institutions aware of the importance of original innovation for disruptive technology. Based on the literature review, this paper discusses the concepts of disruptive technology and original innovation. It then extracts the core elements for original innovation by analyzing two cases of the fundamental research teams of Tsinghua University. Finally, it puts forward a model on achieving original innovation for disruptive technology to a project or team. © 2020 IEEE.

12.
Commun. Comput. Info. Sci. ; 1300:112-119, 2020.
Article in English | Scopus | ID: covidwho-986441

ABSTRACT

During this year’s Novel Coronavirus (2019-nCoV) outbreak, the spread of fake news has caused serious social panic. This fact necessitates a focus on fake news detection. Pictures could be viewed as fake news indicators and hence could be used to identify fake news effectively. However, fake news pictures detection is more challenging since fake news picture identification is more difficult than the fake picture recognition. This paper proposes a multi-vision fusion neural network (MVFNN) which consists of four main components: the visual modal module, the visual feature fusion module, the physical feature module and the ensemble module. The visual modal module is responsible for extracting image features from images pixel domain, frequency domain, and tamper detection. It cooperates with the visual features fusion module to detect fake news images from multi-vision fusion. And the ensemble module combines visual features and physical features to detect the fake news pictures. Experimental results show that our model could achieve better detection performance by at least 4.29% than the existing methods in benchmark datasets. © 2020, Springer Nature Switzerland AG.

13.
Chinese General Practice ; 23(35):4425-4429, 2020.
Article in Chinese | Scopus | ID: covidwho-891675

ABSTRACT

Background: Under the increasingly severe situation of COVID-19 pandemic, Hebei Province has received a large number of individuals returned from abroad.Therefore, on the occasion of returning to work, production and school, it is imperative to effectively strengthen SARS-CoV-2 screening and management of overseas imported cases and to take actions to cut off the transmission channels to prevent the spread of SARS-CoV-2 from this group.Objective: To study the clinical characteristics of overseas imported and local COVID-19 cases in Hebei Province, to provide a reference for developing targeted programs to prevent the recurrence of the pandemic.Methods: 28 patients with COVID-19(7 overseas imported and 21 local )who were admitted to Shijiazhuang Fifth Hospital from January 21 to April 5, 2020 were selected.The epidemiological characteristics, clinical manifestations, laboratory and imaging examinations of them were summarized and analyzed.Results (1)The imported group included 5 men and 2 women, mostly were young adults〔4(57.1%)were 19-29 years〕, with an average age of (23.6±11.1) years.The local group included 14 men and 7 women, mostly were middle-aged and elderly adults〔19(90.5%)aged 30-72 years〕, with an average age of(43.6±19.7) years, mainly were infected with COVID-19 after family gatherings.(2)Among the imported cases, 1 had fever, 1 had diarrhea, and 5 had no clinical symptoms;6(85.7%)had common type COVID-19, 1(14.3%)had severe type, no mild and critically severe types.Among the local cases, 15 had fever, 9 had cough, 5 had sore throat, 3 had fatigue, 2 had muscle pain, and 1 had diarrhea;1(4.8%) had mild type COVID-19, 15(71.4%)had common type, 4(19.0%)had severe type, and 1(4.8%)had critically severe type.(3)The imported cases showed lower average cycle threshold(Ct) value of SARS-CoV-2 N gene(t=14.430, P<0.001) than the local cases.Moreover, the average Ct value of SARS-CoV-2 N gene and ORF1ab gene was also lower in the imported cases(t=17.856, P<0.001).The prevalence of reduced CD4+ T lymphocytes was above 50.0% in both groups compared with the normal reference range value.The prevalence of reduced lymphocyte count and CD3+ T lymphocytes, and elevated C-reactive protein, aspartate aminotransferase, alanine aminotransferase and lactate dehydrogenase was higher than 40.0% in the imported cases.The prevalence of elevated C-reactive protein and lactate dehydrogenase was higher than 40.0% in the local cases.(4)The lung CT examination of two groups indicated that the lesions were mainly distributed in bilateral lung lobes, followed by unilateral unilobe, and then unilateral multiple lobes.Ground-glass opacity was the main image finding in the imported group, while ground-glass opacity and consolidation opacity were the main image findings in the local group.Conclusion: In Hebei Province, the imported COVID-19 cases showed milder symptoms, lower Ct values of SARS-CoV-2 N gene and ORF1ab gene and higher SARS-CoV-2 viral nucleic acids from nasopharyngeal swabs, which indicate that the virus from imported cases may be more contagious.Therefore, it is necessary to strengthen isolation, screening and early diagnosis of imported cases, so as to prevent the spread of disease as much as possible. Copyright © 2020 by the Chinese General Practice.

14.
Chinese General Practice ; 23(9):1083-1089 and 1090, 2020.
Article in Chinese | Scopus | ID: covidwho-826665

ABSTRACT

Background: The medical device-related pressure injury(DRPI), which mainly occurs in critical patients and orthopedic patients, has been a research hotspot for the safety management and specialized care of inpatients worldwide, but there have been few reports on DRPI of medical staff. During the prevention and control of COVID-19, a large number of medical staff are fighting at the front. However, wearing protective equipment for a long time can easily cause skin injury, which seriously harms the medical staff and increases their risk of infection. Therefore, how to protect medical personnel from skin damage is an urgent problem. Objective: To investigate the incidence and epidemic characteristics of medical staff's skin injuries caused by personal protective equipment in fighting against the COVID-19 in order to provide a basis for the formulation of effective protection countermeasures. Methods: A research questionnaire was developed by our research group, including the basic information of medical staff, the wearing situation of protective equipment, the skin damage situation, preventive measures against skin damage, and the post-injury treatment. The questionnaire was released through the Questionnaire Star website to front-line medical staff fighting against the COVID-19 through Wechat app from February 8 to 15 in 2020.The survey was completed by voluntary participation and online filling. The survey data were collected in one week and a database was established. Statistical analysis was made on the incidence of skin injuries, the types of injuries, and epidemic characteristics. Results: A total of 2 901 effective questionnaires were collected from 145 hospitals in 19 provinces, 3 autonomous regions and 4 municipalities in China. Among them, there were 214(7.38%) males and 2 687(92.62%) females, and 147(5.07%) doctors and 2 754(94.93%) nurses. And 825(28.44 %) cases of the medical staff suffered skin injuries due to wearing protective equipment, and the total number of skin damage sites was 2 794.The main types of skin injuries were pressure injury〔771(26.58%)cases, 2.53 per capita〕, moisture-associated skin damage〔256(8.83%)cases, 2.77 per capita〕, and skin tear〔42(1.45%)cases, 3.12 per capita〕.Of the 825 medical staff who had skin injuries, 221(26.79%) cases had skin injuries≥2 types. Univariate analysis showed that the incidence of skin injuries caused by protective equipment was higher in men than in women(P 0.05), in those aged 31-45 than in those ≤30(P 0.016 7), in those who worked 10 years than in those who worked 5 years(P 0.016 7), in doctors than in nurses(P 0.05), in designated epidemic prevention hospitals in Wuhan than in other hospitals(P 0.003 3)and among other hospitals, in Infectious Disease Department than in other departments(P 0.003 3), and in tertiary protection than in secondary protection followed by primary protection(P 0.016 7).However, there was no significant difference in the incidence of skin injuries among medical staff with different continuous wearing time of protective equipment(P 0.05).Conclusion The incidence of skin injuries caused by personal protective equipment in fighting against COVID-19 is high among medical staff. Multiple types and multiple sites of skin injuries are coexisted. It is recommended to take comprehensive preventive measures of pressure relief, friction reduction, moisture absorption, and skin care to reduce skin damage of medical staff. Meanwhile, it is suggested to pay attention to human resource management factors such as gender, age, and job position. Copyright © 2020 by the Chinese General Practice.

15.
Zhonghua Shao Shang Za Zhi ; 36(8): 686-690, 2020 Aug 20.
Article in Chinese | MEDLINE | ID: covidwho-729670

ABSTRACT

For effective resistance to virus attack and infection and reducing virus transmission chance, it is extremely important for the medical staff and related workers to have their own safe protection. The paper summarizes the occurrence causes, common locations, and prevention ways about the device related pressure ulcers on the face resulted from wearing medical-grade protective equipment for a long working time. The paper proposes the prevention and nursing strategies for device related pressure ulcers and other related skin injuries during application of medical-grade protective equipment. The paper aims to provide reference for the prevention and nursing of device related pressure ulcers and related skin diseases for clinical medical staff, especially to the respectable personnel in front line of fighting against coronavirus disease 2019.


Subject(s)
Betacoronavirus , Coronavirus Infections , Pandemics , Pneumonia, Viral , Skin Diseases , COVID-19 , Humans , Protective Devices , SARS-CoV-2
16.
Am Heart J ; 224: 148-155, 2020 06.
Article in English | MEDLINE | ID: covidwho-276755

ABSTRACT

BACKGROUND: Multiple modern Indian hospitals operate at very low cost while meeting US-equivalent quality accreditation standards. Though US hospitals face intensifying pressure to lower their cost, including proposals to extend Medicare payment rates to all admissions, the transferability of Indian hospitals' cost advantages to US peers remains unclear. METHODS: Using time-driven activity-based costing methods, we estimate the average cost of personnel and space for an elective coronary artery bypass graft (CABG) surgery at two American hospitals and one Indian hospital (NH). All three hospitals are Joint Commission accredited and have reputations for use of modern performance management methods. Our case study applies several analytic steps to distinguish transferable from non-transferable sources of NH's cost savings. RESULTS: After removing non-transferable sources of efficiency, NH's residual cost advantage primarily rests on shifting tasks to less-credentialed and/or less-experienced personnel who are supervised by highly-skilled personnel when perceived risk of complications is low. NH's high annual CABG volume facilitates such supervised work "downshifting." The study is subject to limitations inherent in case studies, does not account for the younger age of NH's patients, or capture savings attributable to NH's negligible frequency of re-admission or post-acute care facility placement. CONCLUSIONS: Most transferable bases for a modern Indian hospital's cost advantage would require more flexible American states' hospital and health professional licensing regulations, greater family participation in inpatient care, and stronger support by hospital executives and clinicians for substantially lowering the cost of care via regionalization of complex surgeries and weekend use of costly operating rooms.


Subject(s)
Coronary Artery Bypass/economics , Coronary Artery Disease/surgery , Elective Surgical Procedures/economics , Hospital Costs , Medicare/economics , Patient Transfer/economics , Coronary Artery Disease/economics , Female , Humans , India , Male , United States
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