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In this paper, a new method for obtaining the basic reproduction number is proposed, called the path analysis method. Compared with the traditional next-generation method, this method is more convenient and less error-prone. We develop a general model that includes most of the epidemiological characteristics and enumerate all disease transmission paths. The path analysis method is derived by combining the next-generation method and the disease transmission paths. Three typical examples verify the effectiveness and convenience of the method. It is important to note that the path analysis method is only applicable to epidemic models with bilinear incidence rates. The Volterra-type Lyapunov function is given to prove the global stability of the system. The simulations prove the correctness of our conclusions.
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For epidemic prevention and control, molecular diagnostic techniques such as field-effect transistor (FET) biosensors is developed for rapid screening of infectious agents, including Mycobacterium tuberculosis, SARS-CoV-2, rhinovirus, and others. They obtain results within a few minutes but exhibit diminished sensitivity (<75%) in unprocessed biological samples due to insufficient recognition of low-abundance analytes. Here, an electro-enhanced strategy is developed for the precise detection of trace-level infectious agents by liquid-gate graphene field-effect transistors (LG-GFETs). The applied gate bias preconcentrates analytes electrostatically at the sensing interface, contributing to a 10-fold signal enhancement and a limit of detection down to 5 × 10−16 g mL−1 MPT64 protein in serum. Of 402 participants, sensitivity in tuberculosis, COVID-19 and human rhinovirus assays reached 97.3% (181 of 186), and specificity is 98.6% (213 of 216) with a response time of <60 s. This study solves a long-standing dilemma that response speed and result accuracy of molecular diagnostics undergo trade-offs in unprocessed biological samples, holding unique promise in high-quality and population-wide screening of infectious diseases. © 2023 Wiley-VCH GmbH.
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Objective To understand the proper handwashing behavior of preschool children and primary school students in Beijing and to analyze associated family factors to provide reference for further health intervention related to handwashing. Methods From November to December 2020 parents of 36 kindergartens and 18 primary schools in 9 districts of Beijing were investigated online by using a self-designed questionnaire with questionnaire star software. The contents of the survey included the basic situation of children and their families parents' correct knowledge of the prevention of novel coronavirus pneumonia their perception of the epidemic risk the provision of handwashing guidance for children and children's handwashing behavior. Results The proportion of proper handwashing of preschool children was 70.2% which was higher than that of primary school students 61.9% χ2 = 57.63 P<0.01. The proportion of parents of preschool children who correctly knew handwashing related knowledge 36.2% 33.4% had low perception of epidemic risk 28.9% 25.4% and provided handwashing guidance 99.1% 97.9% was higher than that of parents of primary school students and the differences were statistically significant χ2 = 6.72 22.84 18.68 P<0.05. But the proportion of parents of preschool children who had high self-efficacy 75.7% 78.2% was lower compared to parents of primary school students χ2 = 6.43 P = 0.04. Multivariate regression results showed that whether preschool children or primary school students urban areas and parents had high self-efficacy low risk perception and provided hand washing guidance for children children were more likely to wash their hands correctly. For preschool children non-only children were 0.79 95%CI= 0.69-0.92 times more likely to wash their hands correctly than only children. For primary school students girls were 1.21 95%CI = 1.06-1.39 times more likely to wash their hands correctly than boys and parents who know knowledge correctly were 1.20 95%CI = 1.04-1.40 times more likely to know it incorrectly P<0.05. Conclusion Proper hand washing behavior of preschool children is higher than that of primary school students. Parental awareness of COVID-19 epidemic handwashing behavior self-efficacy and guidance behavior have effects on the development of children's health behavior. Measures should be taken to enhance parents' awareness of infectious diseases and their ability and self-efficacy of guiding children in disease prevention. © 2022 The authors.
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Background: Coronavirus disease 2019 (COVID-19), caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has imposed great medical and economic burdens on human society, and nanotechnology is a promising technique for managing the ongoing COVID-19 pandemic. To drive further studies on anti-COVID-19 nanotechnology, this paper provides an analysis, from a bibliometric perspective, of the intersection of nanotechnology and SARS-CoV-2/COVID-19. Methods: We analyzed the 2585 publications on nanotechnology and SARS-CoV-2/COVID-19 included in the Web of Science Core Collection from January 2019 to March 2022 to determine the bibliometric landscape. The basic bibliometric characteristics are summarized in this article. Results: Our bibliometric analysis revealed that the intersection between nanotechnology and SARS-CoV-2/COVID-19 is a cutting-edge field in the science community and that the related studies were multidisciplinary in nature. Studies on the structural basis of SARS-CoV-2, SARS-CoV-2 detection assays, and mRNA vaccines against COVID-19 provided the development foundation for this field. Conclusions: The current research focuses are the development of nanomaterial-based vaccines and SARS-CoV-2 detection methods, and the design of nanomedicines carrying SARS-CoV-2 inhibitors is a relatively burgeoning frontier. In summary, this bibliometric analysis of the intersection of nanotechnology and SARS-CoV-2/COVID-19 highlights the current research focuses of this field to inspire future studies on anti-COVID-19 nanotechnologies. © 2022
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This Research to Practice Work-In-Progress paper presents a virtualized breadboard solution for FPGAs and ARM microcontrollers in remote laboratories. The circumstances that rose amidst the COVID-19 pandemic demonstrated the vulnerability of current engineering education practices, particularly in dealing with hardware resources. Pivoting to the emergency online instruction presented challenges to the traditional practices in delivering hands-on engineering labs, which necessitated a solution that handles hardware prototyping without compromising creativity and instruction. One vital aspect of the embedded systems learning experience is ensuring students and faculty members alike have opportunities to learn and build custom prototyping circuits that interact with microprocessors on breadboards. In this paper, we build on the prior work that our group implemented on using virtualization to interface a virtual breadboard with physical hardware through web applications. Our previous work was limited to interfacing with one particular kind of hardware, designed to explore the capabilities of fundamental transducers and actuators that interface with hardware I/O pins. In hardware engineering practice, however, designers are not constrained by a single microprocessor selection to control their system and designs and are not limited by the type of transducers and actuators that provide the external circuit functionality. This paper presents a solution by scaling the existing virtual breadboard research to support FPGAs and ARM microcontrollers and intermediate logic gate integrated circuits for practical use in engineering curriculums. Providing this increased selection of supporting hardware helps facilitate student learning and simulates hardware development in an industrial setting. Due to the rising popularity of FPGAs and ARM microcontrollers in industry and in education, we expect that our solution will serve a larger audience through this broader selection of supported hardware. Our solution virtualizes the breadboard prototyping experience without sacrificing the nature of real-time embedded systems by taking the user prototyped inputs and outputs and directly programming the functionality of the surrounding system to physical hardware. This balance between a virtualized interface and physical hardware implementation preserves a hardware curriculum embedded systems engineering education and brings a promising solution to expand the scalability and accessibility of engineering labs. © 2022 IEEE.
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During the COVID-19 pandemic, the demand for video calling and video conferencing is at peak and continues to grow. Integrating Augmented Reality (AR) with a regular video call can deliver a more interactive, immersive, and collaborative communication experience. This paper presents an AR video calling system that uses WebRTC protocol for establishing real-time video communication and uses AR SDK such as Google AR Core for adding AR features over the lively streaming video feed. To evaluate the performance and feasibility of the proposed AR video calling system, we implemented it on an Android mobile device and measured the relevant performance data, such as frame rate, CPU usage and network usage. The experimental results suggest that the proposed system is practicable and stable. © 2022 IEEE.
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Background: Anticoagulants are promising regimens for treating coronavirus disease 2019 (COVID-19). However, whether prophylactic or intermediate-to-therapeutic dosage is optimal remains under active discussion. Methods: We comprehensively searched PubMed, Embase, Scopus, Web of Science, Cochrane Library, ClinicalTrials, and MedRxiv databases on April 26, 2022. Two independent researchers conducted literature selection and data extraction separately according to predetermined criteria. Notably, this is the first meta-analysis on COVID-19, taking serious consideration regarding the dosage overlap between the 2 comparison groups of prophylactic anticoagulation (PA) and intermediate-to-therapeutic anticoagulation (I-TA). Results: We included 11 randomized controlled trials (RCTs) and 36 cohort studies with 27,051 COVID-19 patients. By analyzing all the RCTs, there was no significant difference in mortality between the PA and I-TA groups, which was further confirmed by trial sequential analysis (TSA) (odds ratio [OR]: 0.93;95% confidence interval [CI]: 0.71–1.22;P = 0.61;TSA adjusted CI: 0.71–1.26). The rate of major bleeding was remarkably higher in the I-TA group than in the PA group, despite adjusting for TSA (OR: 1.73;95% CI: 1.15–2.60;P = 0.009;TSA adjusted CI: 1.09–2.58). RCTs have supported the beneficial effect of I-TA in reducing thrombotic events. After including all studies, mortality in the I-TA group was significantly higher than in the PA group (OR: 1.38;95% CI: 1.15–1.66;P = 0.0005). The rate of major bleeding was similar to the analysis from RCTs (OR: 2.24;95% CI: 1.86–2.69;P < 0.00001). There was no distinct difference in the rate of thrombotic events between the 2 regimen groups. In addition, in both critical and noncritical subgroups, I-TA failed to reduce mortality but increased major bleeding rate compared with PA, as shown in meta-analysis of all studies, as well as RCTs only. Meta-regression of all studies suggested that there was no relationship between the treatment effect and the overall risk of mortality or major bleeding (P = 0.14, P = 0.09, respectively). Conclusion: I-TA is not superior to PA for treating COVID-19 because it fails to lower the mortality rate but increases the major bleeding rate in both critical and noncritical patients. Copyright © 2022 Shandong University, published by Wolters Kluwer, Inc.
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Coronavirus disease 2019 (COVID-19) has gained utmost attention in the current time from academic research and industrial practices because it continues to rage in many countries. Pharmacophore models exploit molecule topological similarity as well as functional compound similarity so that they can be reliable via the application of the concept of bioisosterism. In this work, we analyze the targets for coronavirus protein and the structure of RNA virus variation, thereby complete the safety and pharmacodynamic action evaluation of small-molecule anti-coronavirus oral drugs. Common pharmacophore identifications could be converted into subgraph querying problems, due to chemical structures can also be converted to graphs, which is a knotty problem pressing for a solution. We adopt simplified representation pharmacophore graphs by reducing complete molecular structures to s to detect isomorphic topological patterns and further to improve the substructure retrieval efficiency. Our threefold architecture subgraph isomorphism-based method retrieves query subgraphs over large graphs. First, by means of extracting a sequence of subgraphs to be matched and then comparing the number of vertex and edge between the potential isomorphic subgraphs and the query graph, we lower the computational scaling markedly. Afterwards, the directed vertex and edge matrix recording vertex and edge positional relation, directional relation and distance relation has been created. Then, on the basis of permutation theorem, we calculate the row sum of vertex and edge adjacency matrix of query graph and potential sample. Finally, according to equinumerosity theorem, we check the eigenvalues of the vertex and edge adjacency matrices of the two graphs are equinumerous. The topological distance could be calculated based on the graph isomorphism and the subgraph isomorphism can be implemented after the combination of the subgraph. The proposed quantitative structure-function relationships (QSFR) approach can be effectively applied for pharmacophoric patterns identification. The framework of new drug development for covid-19 has been established based on this triangle. © 2022 ACM.
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Background: Immune checkpoint inhibitors (ICIs) can cause a variety of inflammatory autoimmune tissue damage, referred to as immune-related adverse events (irAEs). COVID-19 is associated with increased amounts of proinflammatory cytokines, which may synergistically affect the outcome of irAEs. Data are limited regarding the impact of COVID-19 on irAEs in ICI-treated cancer patients. Methods: We retrospectively analyzed adult patients with malignant solid tumors treated with ICIs at AdventHealth Orlando between August 2020 and August 2021. All COVID-19 infections were confirmed by PCR. Patients who had the most recent ICI treatment over one month before or after the positive COVID- 19 test were excluded from the study. For COVID-19 positive group, only the irAEs that developed after COVID-19 infection were considered as events. Results: A total of 579 patients were included in our study, with 46 (7.9%) in COVID-19 positive group, and 533 (92.1%) in COVID-19 negative group. The baseline characteristics of patients in the two groups were similar in terms of age, ethnicity, ECOG, cancer histology, and type of ICI. With a median follow-up of 10 months (1-73 months), no differences in the time from ICI initiation to irAE onset, corticosteroid use, or additional immunosuppressant use were seen. A trend in higher incidence of all-grade diarrhea/colitis (8.7% vs. 3.0%, p=0.07) and grade 3 and 4 hepatitis (4.3% vs. 0.8%, p=0.08) was noted in the COVID-19 positive group, however the difference was not statistically significant. No significant difference in the incidence of pneumonitis (2.2% vs. 1.1%, p=0.44), nephritis (2.2% vs. 0.8%, p=0.34) or dermatitis (6.5% vs. 6.4%, p=1.00) were noted between COVID-19 positive and negative groups. We noticed a higher incidence of all-grade irAEs in the COVID-19 positive group (30.4% vs. 19.9%, p=0.18), but the difference was not statistically significant. The incidence of grade 3 and 4 irAEs was significantly higher in the COVID- 19 positive group (10.9% vs. 3.2%, p=0.02). Nine COVID-19 related death occurred while no irAE-related death was noted in the entire cohort. Conclusions: Our study suggested that COVID-19 may pose a risk of severe irAEs in cancer patients receiving ICIs. Close monitoring and possible delaying ICI administration could be considered when cancer patients were infected with COVID-19. (Table Presented).
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Mass suspension of anthropogenic activities is extremely rare, the quarantine due to the coronavirus disease 2019 (COVID-19) represents a natural experiment to investigate the impact of anthropogenic activities on air quality. The mitigation of air pollution during the COVID-19 lock-down has been reported from a global perspective;however, the air pollution levels vary in different regions. This study initiated a novel synthesis of multiple-year satellite observations, national ground measurements towards SO2, NO2 and O3 and meteorological conditions to evaluate the impact of the COVID-19 lockdown in Beihai, a specific city in a less developed area in southwest China, to reveal the potential implications of control strategies for air pollution. The levels of the major air pollutants during the COVID-19 lockdown (LP) and during the same period of previous years (SP) were compared and a series of statistical tools were applied to analyze the sources of air pollution in Beihai. The results show that air pollutant levels decreased with substantial diversity during the LP. Satellite-retrieved NO2 and SO2 levels during the LP decreased by 5.26% and 22.06%, while NO2, SO2, PM2.5 and PM10 from ground measurements during the LP were 25.6%, 2.7%, 22.2% and 22.2% lower than during SP, respectively. Ground measured SO2 concentrations during the LP were only 2.7% lower than during the SP, which may be attributed to uninterrupted essential industrial activ-ities, such as power plants. Polar plots analysis shows that NO2 concentrations were strongly associated with local emission sources, such as automobiles and local industry. Additionally, the much lower levels of NO2 concentrations during the LP and the absence of an evening peak may highlight the significant impact of the traffic sector on NO2. The decrease in daily mean O3 concentrations during the LP may be associated with the reduction in NO2 concentrations. Indications in this study could be beneficial for the formulation of atmospheric protection policies. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
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This study investigated the impacts of risk perception of COVID-19 on anxiety and depression symptoms among hospital pharmacists in China. We conducted a cross-sectional study with hospital pharmacists during the COVID-19 pandemic in China. Some 4,219 hospital pharmacists completed an online survey including demographic questions, risk perception of COVID-19, General Anxiety Disorder-7, Patient Health Questionnaire-9, and Positive and Negative Affect Schedule. Multivariate regression and mediation analyses were conducted. The results indicated that 41.9% and 29.4% of hospital pharmacists experienced mild to severe levels of anxiety and depression symptoms, respectively. In older age, a higher level of risk perception of COVID-19, and negative affect experience were risk factors, whereas positive affect experience was a protective factor for anxiety and depression symptoms among pharmacists. Experience of positive and negative affect mediated the relationship between risk perception of COVID-19 and anxiety and depression among hospital pharmacists in China. Timely mental health services need to be provided for hospital pharmacists during the COVID-19 pandemic.
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Coronavirus disease 2019 (COVID-19) is caused by a novel strain of coronavirus, designated as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It has caused a global pandemic rapidly sweeping across all countries, bringing social and economic hardship to millions. Most countries have implemented early warning measures to detect, isolate, and treat patients infected with SARS-CoV-2. This minireview summarizes some of those steps, in particular, testing methods and drug development in the context of chemical biology, and discusses the molecular basis of COVID-19's virulent transmissibility.
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As one of the manifestations of virtual reality (VR) in education, virtual classroom allows students to enjoy a near-real classroom experience. VR class creates much better engagement and helps to stimulate interest and motivation in learning, making it an ideal solution to online teaching and learning activities, especially during the COVID-19 pandemic. Distraction is an unavoidable problem in immersive virtual classes, which has a great detrimental impact on learning. However, how to intervene in students' distraction behaviors in immersive virtual environments has not been thoroughly investigated up to now. In this paper, inspired by teachers' instructional techniques in real-life classes, we propose three intervention strategies, namely eye contact, verbal warning and text warning, and explore the intervening effects of these strategies on the inattention of students seated at the front or back of a virtual classroom via eye tracking. Our results show that all of the proposed intervention strategies have positive impacts on the attention of students. This research gives evidence that teachers' instructional techniques in the real world can be transferred to the virtual class, which provides a new insight for the future design of educational VR. © 2022 ACM.
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Since the first cased of COVID-19 was identified in December 2019, a plethora of different drugs have been tested for COVID-19 treatment, making it a daunting task to keep track of the rapid growth of COVID-19 research landscape. Using the existing scientific literature search systems to develop a deeper understanding of COVID-19 related clinical experiments and results turns to be increasingly complicated. In this paper, we build a named entity recognition-based framework to extract information accurately and generate knowledge graph efficiently from a myriad of clinical test results articles. Of the tested drugs to treat COVID-19, we also develop a question answering system answers to medical questions regarding COVID-19 related symptoms using Wikipedia articles. We combine the state-of-the-art question answering model - Bidirectional Encoder Representations from Transformers (BERT), with Knowledge Graph to answer patients' questions about treatment options for their symptoms. This generated knowledge graph is user-friendly with intuitive and convenient tools to find the supporting and/or contradictory references of certain drugs with properties such as side effects, target population, etc. The trained question answering platform provides a straightforward and error-tolerant way to query for treatment suggestions given uses' input symptoms. © 2021 ACM.
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The topological distance is to measure the structural difference between two graphs in a metric space. Graphs are ubiquitous, and topological measurements over graphs arise in diverse areas, including, e.g. COVID-19 structural analysis, DNA/RNA alignment, discovering the Isomers, checking the code plagiarism. Unfortunately, popular distance scores used in these applications, that scale over large graphs, are not metrics, and the computation usually becomes NP-hard. While, fuzzy measurement is an uncertain representation to apply for a polynomial-time solution for undirected multigraph isomorphism. But the graph isomorphism problem is to determine two finite graphs that are isomorphic, which is not known with a polynomial-time solution. This paper solves the undirected multigraph isomorphism problem with an algorithmic approach as NP=P and proposes a polynomial-time solution to check if two undirected multigraphs are isomorphic or not. Based on the solution, we define a new fuzzy measurement based on graph isomorphism for topological distance/structural similarity between two graphs. Thus, this paper proposed a fuzzy measure of the topological distance between two undirected multigraphs. If two graphs are isomorphic, the topological distance is 0;if not, we will calculate the Euclidean distance among eight extracted features and provide the fuzzy distance. The fuzzy measurement executes more efficiently and accurately than the current methods.
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Purpose: To better meet people's information needs under the public health crisis, this study explored the information needs and seeking behavior of college students in the context of the COVID-19 pandemic. Design/methodology/approach: This research utilized a survey and the convenience snowball sampling method. A sample of 400 college students was obtained. Findings: The results revealed that college students have paid great attention to COVID-19-related information. They sought the information mainly for personal protection, obtaining the latest information and seeking information for family and friends. Their COVID-19-related information needs were diverse;at different stages, the concerns were different. Social media and mass media were both found to be the most useful tools for seeking COVID-19 information. Too much repetitive information, unclear authoritative and reliable informational sources, and difficulties in judging the authenticity of the information were the most common obstacles for them in information seeking. Nevertheless, the majority of the students agreed that they were very satisfied and somewhat satisfied with the current information services. This did not affect the students' understanding of the importance of health services provided by libraries. Originality/value: Insights into the people's information needs and information-seeking behavior of this study could help the information providers to offer appropriate information in better ways to improve the public's virus protection capabilities and maintain the stability of social order. © 2021, Emerald Publishing Limited.
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In addition to the pandemic caused by the coronavirus disease 2019, many pathogenic bacteria have also been posing a devastating threat to human health. The overuse of antibiotics leads to the emergence of ‘superbugs’;therefore, it is urgent to develop effective strategies to fight bacteria. Herein, a superparamagnetic nickel (Ni) colloidal nanocrystal clusters (SNCNCs) that can kill and capture bacteria without any camouflage is reported. It binds to amino groups on the surface of bacteria, imparts magnetism to them, and orients them in response to magnetic fields. SNCNCs kill and capture bacteria to avoid inflammation, infection, and organ damage caused by lipopolysaccharide and exotoxin released by bacterial rupture in the remaining bacterial remains in comparison with other antibacterial agents. In this study, in the treatment of traumatic oral ulcers, we found that SNCNCs could kill and capture and remove bacteria from the ulcers to reduce inflammation at the site of the wound. Furthermore, the fibrin gel sprayed on the ulcer was used as a substrate, and the bacteria captured by the SNCNCs moved to the surface of the fibrin gel after a magnetic field was applied. Therefore, the bacteria in the ulcer could be removed with the SNCNCs and fibrin gel magnet, alleviating inflammation caused by bacteria and promoting ulcer healing. This magnetically controlled method of directional movement of bacteria may provide an applicative perspective for the therapy of bacterial infections. © 2021 The Author(s)
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Chinese citizens in China were the first affected by the COVID-19 outbreak. Nevertheless, the disease rapidly spread around the world, leading to the worst pandemic experienced in modern societies. Spain has become one of the countries more severely affected by it, while having a large Chinese community. This study aims to explore the perception of Chinese citizens living in Spain regarding the outbreak in their host country. Communicative interviews were conducted with ten Chinese men and women who had been living in Spain for at least five years. Results show cultural differences in the coping strategies of the Chinese as a response to the pandemic, which differ from those observed by the participants in their fellow Spanish citizens. These findings unveil the potential of integrating the cultural knowledge and coping strategies of migrant groups in the host communities in managing a pandemic, as well as the negative outcomes for social cohesion and well-being from new racism emerging in the context of COVID-19.
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The resumption of work and production helps to avoid the short-term suspension of economic development caused by COVID-19 virus epidemic from becoming long-term economic depression. However, during the COVID-19 virus epidemic, the resumption of work may cause infection. Facing the uncertainty of external environment, the pressure of capital turnover and lead time of orders, the resumption of work and production is a severe problem. To judge the schedule of resumption, we analyze the electricity usage of enterprises in Shaoxing, select 200 enterprises in 4 industries, including heavy industries, general industry and commerce, agricultural production industries, agricultural irrigation and drainage industries. Using the electricity usage before and after the epidemic, we use STL decomposition and Mann Kendall trend test to intelligently judge the situation of resumption. At the same time, combined with the date of suspension and resumption of work, we determine the resumption threshold of enterprises and plot the resumption rate of industries. From the threshold and the plots, we can analyze the schedule of resumption one month before and after the Spring Festival to support the effect of epidemic on different industries. © 2020 IEEE.