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In December 2019, a novel coronavirus broke out in Wuhan City, Hubei Province, and, as the center of the coronavirus disease 2019 (COVID-19) epidemic, the economy and production throughout Hubei Province suffered huge temporary impacts. Based on the input–output and industrial pollution emissions data of 33 industrial industries in Hubei from 2010 to 2019, this article uses the non-parametric frontier analysis method to calculate the potential production losses and compliance costs caused by environmental regulations in Hubei's industrial sector by year and industry. Research has found that the environmental technology efficiency of the industrial sector in Hubei is showing a trend of increasing year-on-year, but the overall efficiency level is still not high, and there is great room for improvement. The calculation results with and without environmental regulatory constraints indicate that, generally, production losses and compliance costs may be encountered in the industrial sector in Hubei, and there are significant differences by industry. The potential production losses and compliance costs in pollution-intensive industries are higher than those in clean production industries. On this basis, we propose relevant policy recommendations to improve the technological efficiency of Hubei's industrial environment, in order to promote the high-quality development of Hubei's industry in the post-epidemic era.
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Objective: To investigate the relationship between negative attentional bias and post-traumatic stress disorder(PTSD) in the context of higher depression and anxiety symptoms after the outbreak of COVID-19, so as to provide scientific basis for mental health education in primary and secondary schools. Methods: From March to April 2021, a total of 708 students from primary school and junior high school (grade 6 through grade 9) in Beijing, Shanxi, Hunan, Shandong, Hebei, Hubei of China were selected. The Children's Revised Impact of Event Scale(CRIES), the Attention to Positive and Negative Information Scale (APNI)and Depression, Anxiety and Stress Scale-21(DASS-21) were used in a questionnaire survey. Results: A total of 242 students were diagnosed with PTSD, and the detection rate was 34.2%. The scores of intrusion and high arousal of boys(7.92+or-5.33, 8.60+or-5.41) were lower than those of girls(8.72+or-4.85, 9.50+or-4.76), and the difference was statistically significant (t=-2.04, -2.32, P < 0.05). There were statistically significant differences of negative attention bias, CRIES score, intrusion, debarb and high arousal among primary and middle school students of different grades (F=3.57, 5.99, 4.45, 4.60, 7.40, P < 0.05). Negative attention bias, anxiety, depression and post-traumatic stress symptoms were significantly positively correlated (r=0.27-0.84, P < 0.05). Logistic regression analysis showed that anxiety (OR=1.13, 95%CI=1.06-1.20) and negative attention bias (OR=1.10, 95%CI=1.07-1.12) were positively associated with PTSD symptoms in primary and middle school students(P < 0.01). Conclusion: Anxiety and depressive symptoms show impacts on negative attention bias and might exacerbate the symptoms of post-traumatic stress disorder. Therefore, emotional adjustments can help reduce the post-traumatic stress response in the post-epidemic period.
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Non-grain production (NGP) on cultivated land has become a common phenomenon due to the prosperity of the rural economy and the optimisation of the agricultural structure. However, the excessive use of cultivating land for NGP has threatened food production and the sustainable use of cultivated land. To halt this trend and to ensure food security, the authors of this paper applied a novel non-grain index to measure NGP, which could reflect multiple NGP activities;designated Hubei Province as its object of research;and revealed NGP's spatio-temporal patterns of the past 30 years. We then assessed the characteristics of NGP based on spatial autocorrelation analysis, the Theil index, and geographically weighted regression. The results showed that the value of the non-grain index grew from 0.497 to 1.113 as NGP increased significantly in Hubei Province. The number of high-NGP counties increased, spatial agglomeration became obvious, and the eastern and western sides of Hubei Province witnessed an observable growth in NGP. As a result, the NGP in the eastern and western regions overtook production in the central region. Despite a series of historical subsidy policies and agricultural modernisation initiatives that promoted the planting of grain crops, the policy of "grain on valuable cultivated land” could be better implemented. We conclude by making some suggestions for reducing NGP and protecting cultivated land.
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The year 2019 ended with the official report of an unknown pneumonia outbreak in Wuhan, Hubei Province, China. Subsequently, this novel pneumonia was named COVID-19, which mainly attacks the respiratory system, causing severe damage. Although vaccination has relieved the stress of combating pandemics around the world after one year, there are still unknowns and challenges that come with hope. In this regard, stem cell therapy has been proposed as an effective approach to treating COVID-19. Mesenchymal stem cells (MSCs) can potentially be used as a hopeful tool in the cell-based therapy due to their ability to regenerate and regulate immune response. Although research and clinical results have shown encouraging achievement in patients who were treated with MSCs, drawbacks and challenges still exist in the face of new opportunities. This review aims to introduce the challenges of the COVID-19 vaccine and the possible clinical use of MSC-based therapy. Through analysis of COVID-19 and MSC-based therapy, the author aims to find the possibilities and feasibility of using MSCs to treat acute respiratory diseases, such as COVID. As a result, the author finds that MSC treatment is very practical, and it shows significant potential to treat COVID-19. © 2023 SPIE.
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Since the emergence of the Coronavirus disease outbreak, the world has witnessed great changes that have impacted humanity. A study of the pattern of the pandemic would be of great importance to understand the trending behavior for the spreading of the disease within any country. Visualization of the outbreak progression - through accumulated records in the datasets - using statistical tools showed that the initial fast increase rate of the affected cases in the original province in China was followed by a stability period till the end of the reporting date. Hong Kong - which was next to Hubei province in the cases - showed a different surge of slow growth curve with distinct major wave levels. The remaining territories showed a much smaller magnitude of morbidities. However, investigating the similarity levels for the daily kinetics of cases showed a clustering tendency between different political regions suggesting a significant correlation. The technique would be useful for public health authorities work.
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Background & Aims: In early January 2020, a new corona virus called corona was identified as an infectious agent by the World Health Organization and caused a viral pneumonia outbreak, the first of which was reported in Wuhan, China in December 2019. The virus has so far infected most countries in the world and has become a global problem. By this time in December 2021, about 265 million people in the world have been infected with this virus and 5 million 270 thousand people have died from this disease. According to the World Health Organization, the incidence of this disease is still increasing and will become the third leading cause of death in the world by 2030. This disease has a special complexity and has multiple dimensions and consequences that have caused many problems in the field of health, social and economic as well as psychological for people. The emergence of this disease is now a public health crisis. According to this research, exposure to news and restrictions caused by this disease can lead to many mental health problems. In fact, one of the situations that puts a lot of stress on people during the outbreak of covid 19 disease is the inability to predict and uncertainty about the control and end of the disease. Mental health is defined as a harmonious and harmonious behavior with society, recognizing and accepting social realities, the power to adapt to them and meeting one's balanced needs and is an important factor for the health of society. The prevalence of the disease can also increase feelings of loneliness, decrease social support, feelings of fear and anxiety to clinical stress and anxiety, obsessive-compulsive disorder associated with the disease, and decreased life expectancy. One of the hopeful factors is health and the disease can cause despair, fear and even despair of the patient. The outbreak of a disease has a much deeper and wider impact and affects not only the affected community and relatives, but the entire community. Because everyone finds themselves at risk, and therefore people's feel of safe and healthy changes, and this situation causes people to despair. Hope is the capacity to imagine the ability to create paths to desirable goals and to imagine the motivation to move in those paths. Hope predicts physical and mental health such as positive response to medical interventions, mental health, effective getting along, and health-promoting behaviors. Covid 19 disease can also lead to psychological problems due to its infectious nature and unpredictable nature. In this regard, various researchers consider the implementation of public health policies, including areas related to individual and collective mental health in accordance with the different stages of the epidemic of this disease is very necessary. Mindfulness can be an effective tool for achieving peace of mind and body that helps people become aware of their current feelings. Mindfulness-based interventions are considered as one of the third generation or third wave cognitive-behavioral therapies. Mindfulness is a form of meditation rooted in Eastern religious teachings and rituals, especially Buddhism. Segal has defined mindfulness as paying attention to specific and purposeful ways, in the present time, without judgment or prejudice. Linhan stressed for the first time the need to pay attention to mindfulness as one of the essential components of psychological therapy. Mindfulness requires the development of three components: judgment avoidance, purposeful awareness, and focus on the present moment. Focusing on the present and processing all aspects of the above experience makes one aware of the daily activities and automatic functioning of the mind in the past and future world and he controls emotions, thoughts, and physical states through moment-to-moment awareness of thoughts. As a result, it is released from the everyday and automatic mind focused on the past and the future. Although general vaccination has reduced the virus in some countries, including Iran, and reduced the number of infected people, a large num
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The Public Health Commission of Hubei Province, China, at the end of 2019reported cases of severe and unknown pneumonia, marked by fever, malaise, dry cough, dyspnea, and respiratory failure, that occurred in the urban area of Wuhan, according to the World Health Organization (WHO). The lung infection, SARS-CoV-2, also known as COVID-19, was caused by a brand-new coronavirus (coronavirus disease 2019). Since then, infections have increased exponentially, and the WHO labeled the outbreak a worldwide emergency at the beginning of March 2020. Infected and asymptomatic individuals who can spread the virus are the main sources of it. The transmission occurs mainly by airthrough the air through the droplets, however indirect transmission is also possible, such as through contact with infected surfaces. It becomes essential to identify viral carriers as soon as possible in order to stop the spread of the disease and reduce morbidity and mortality. Imaging examinations, which are among the specific tests used to make the definite diagnosis, are crucial in the patient's management when COVID-19 is suspected. Numerous papers that use machine learning techniques discuss the use of X-ray chest radiographs as a component that aids in diagnosis and permits disease follow-up. The goal of this work is to supply the scientific community with information on the most widely used Machine Learning algorithms applied to chest X-ray images. © 2022 IEEE.
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Objective: To analyze the distribution and drug resistance of pathogenic bacteria in blood culture specimens of patients with bloodstream infections before and after COVID-19 (2018-2019 and 2020-2021), and to provide scientific basis and reference for rational treatment and effective control of bloodstream infections in the post-epidemic period. Methods: Blood culture specimens were collected from patients in Zhongnan Hospital of Wuhan University in the two years before and after the COVID-19 outbreak (2018-2021). The Automated Blood Culture Systems were used to perform blood culture on blood specimens sent for clinical inspection, and the Vitek MS automatic bacterial identification mass spectrometer was used for strain identification and the Vitek 2 automatic bacterial drug susceptibility analyzer was used for drug susceptibility testing and drug resistance analysis. Results: Blood culture specimens were performed on 28 736 patients with suspected bloodstream infection submitted for inspection from January 2018 to December 2019, and a total of 2 181 strains of pathogenic bacteria were detected after removing duplicate strains, with a positive rate of 7.69%, including 1 046 strains of Gram-negative bacteria, accounting for 47.96%. From January 2020 to December 2021, blood culture specimens from 26 083 patients with suspected bloodstream infection were submitted for inspection, and a total of 2 111 strains of pathogenic bacteria were detected after excluding duplicate strains, with a positive rate of 8.09%, including 1 000 strains of Gram-negative bacteria accounted for 47.37%. The drug resistance of Klebsiella pneumoniae was relatively serious, and the sensitivity rate to ertapenem, polymyxin B and tigecycline was more than 90%. The main non-fermentative bacteria Acinetobacter baumannii was more than 50% sensitive to piperacillin/tazobactam, amikacin and polymyxin B. The sensitivity rates of Pseudomonas aeruginosa to piperacillin/tazobactam, ceftazidime, cefepime, amikacin, gentamicin, tobramycin, ciprofloxacin, levofloxacin, piperacillin and meropenem were more than 50%. Conclusions: In the two years before and after COVID-19, there are many types of pathogenic bacteria in bloodstream infection, but the distribution do not differ significantly. The pathogens of bloodstream infection are mainly distributed in ICU, hepatobiliary research institute, and nephrology department. Among them, Gram-negative bacteria such as Escherichia coli, Klebsiella pneumoniae and Acinetobacter baumannii are the main ones, and different pathogens showed great differences in drug resistance.
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Vehicle exhaust has been important source of atmospheric pollution in China. In terms of the environmental effects of vehicle emission control policies (VECPs), changes in air pollutants and greenhouse gases (GHG) emissions are receiving increasing attention. Hubei has implemented many traffic controls to accelerate pollution abatement. However, few studies have reported how they would affect pollutant emissions in Hubei in the future, as most concentrate on assessments during COVID-19. Further, there has been little research on whether these controls bring observable health benefits. Thus, this study comprehensively evaluates the emission of major air pollutants (including NOx, CO, VOCs, PM2.5, PM10, and PMTSP) and GHGs (CO2, CH4, and N2O) from the transportation sector concerning different VECPs in Hubei during 2015–2050, together with health outcomes. It highlights that individual VECPs contribute differently to environmental and health benefits, encouraging innovation in mechanisms and technologies to mitigate atmospheric pollution while generating health benefits.
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This review focuses on the characteristics of coronavirus disease-19 (COVID-19) including virus structure, ecoepidemiology and pathophysiology, signs and symptoms in infected people, and data on virus pathogenicity, severity, and survivability in COVID-19 infected patients. The emphasis is on immunological reactions, diagnosis, prophylactic methods, and the zoonotic significance of COVID-19. The authors feel that the review's contents will be valuable to epidemiologists, virologists, public health officials, diagnosticians, laboratory workers, environmentalists, and socioeconomic experts. It has information on the many types of coronavirus variants, the disease situation in Pakistan and the WHO criteria for COVID-19 prevention is given. Moreover, lessons learned from the COVID-19 pandemic are also outlined.
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The needs of volunteer community service providers (VCSPs), who are the main responders to community crises, have received significantly less attention for the contributions they have been making during the COVID‐19 crisis. A mixed‐method research framework was used in this study, which involved semi‐structured interviews with 13 NGOs and questionnaire responses from 430 VCSPs in Hubei, China to assess the VCSPs' personal needs based on Maslow's hierarchy of needs. It was found that the VCSPs had safety, love, belonging, self‐esteem, and self‐actualization personal needs, all of which were closely related to family, partners, organizations, society and the government. The discussions revealed that the more experienced VCSPs needed special attention and family support was extremely significant for VCSPs in crisis. Several recommendations to meet VCSPs' personal needs are proposed that could have valuable reference value for emergency managers when organizing and supporting VCSPs in contingencies. [ FROM AUTHOR] Copyright of Journal of Contingencies & Crisis Management is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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ObjectiveTo analyze the influenza surveillance data in Ezhou City, Hubei Province from 2016 to 2021, determine the epidemiological characteristics and etiological trend of influenza like illness (ILI), and to provide scientific evidence for influenza prevention and control. MethodsThe ILI surveillance data were reported by Ezhou influenza sentinel hospitals and etiological examination results were collected by network laboratory. Influenza surveillance data from 2016 to 2021 were analyzed. ResultsFrom 2016 to 2021, the percentage of ILI visits (ILI%) in Ezhou city was 2.81% and increased over years. Majority (55.55%) of ILI cases were 0-4 years. A total of 7 716 ILI samples were examined from 2016 to 2021, of which 1 467 tested positive with a positive rate of 19.01%. Influenza A H1N1 was mainly concentrated in January-April, A H3N2 mainly in August-December, B Victoria mainly in April-July and December-March, and B Yamagata mainly in December-February. Influenza network laboratory isolated influenza virus from the 1 467 positive samples by using MDCK cells and SPF chicken embryos. The overall isolation rate was 32.78%, which was 26.93% by MDCK cells and 5.86% by SPF chicken embryos. From 2016 to 2021, a total of 13 ILI outbreaks were reported in Ezhou City. Temporally, the outbreaks mainly occurred in winter and spring. Spatially, they were mainly in primary schools, middle schools and kindergartens. ConclusionThe winter and spring are the key time period of influenza prevention and control in Ezhou City, as they are susceptible to influenza outbreaks. Children aged 0-14 are the key population of prevention and control. Diverse subtypes of influenza virus alternate by years, which warrants continually strengthening monitoring. Additionally, certain countermeasures against COVID-19 may be recommended in the prevention and control of influenza.
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COVID-19 pandemic which the first outbreak was found on December 2019 in Wuhan, China, has given great impact to tourism industries worldwide. Since then, most countries implemented lockdown and quarantine system, issued tight regulations about travel restriction. In order to survive the COVID-19 pandemic, which the ending has yet to be determined, every tourism industry must be able to work efficiently to maintain the usage of operating costs as low as possible since the revenue could not be optimized. This research aims to measure efficiency score of 41 companies in Tourism and Recreation Industry (code E51) listed on Indonesia Stock Exchange (IDX) from 2018 to 2021. At the first stage, data envelopment analysis (DEA) method with variable-return-to-scale (VRS) input-oriented approach is employed to estimate technical efficiency scores. At the second stage, left-truncated regression estimation with double-bootstrap is employed to test the significance of some explanatory factors. Cost of Sales and Revenue, Operating expenses, Interest expenses, and Fixed Assets are chosen as input variables, while Sales and Revenue, Profit (Loss) from Operation, and Asset Turnover Ratio as output variables of DEA. The result shows that efficiency score dropped by 20.42% in 2020 compared to the score in 2019. A slight increase of 2.39% in 2021 compared to the score in 2020. Another result also denotes that several explanatory factors such as Stock Price positively affected efficiency score of, meanwhile Liability to Asset Ratio gave negative influences. Finally, this research may contribute to the development of operation and management science in hospitality and tourism field as well as to support the business operators to adjust their strategic plans, especially in financial budgeting, to face the long-impact of COVID-19 pandemic. Efficiency measurement using advanced DEA Double Bootstrap method with selected financial parameters that are different from any previous studies in tourism provides novelty to this research. © 2023 WITPress. All rights reserved.
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To cope with the COVID-19 pandemic, the Chinese government initiated a medical resource allocation and assistance mechanism that was characterized as a large-scale and regional mutual approach. Specifically, thirty provinces delivered medical resources (e.g., medical staff, medical supplies, and living materials) to "1+16” cities severely affected by the epidemic within a small amount of time, which solved the dilemma of medical collapse and governance "downtime” in epidemic areas, thereby changing the prevalence curve of the pandemic in China. "Campaign-style” targeted assistance can be interpreted based on the Chinese dual party-government model as well as the governance model of vertical accountability and horizontal competition, drawing from previous experience of normalized "designated assistance.” Consequently, paired assistance contributes to intergovernmental situations of decreasing divisibility and increasing cooperation. This study has the potential to bring insights to other countries around the world that are fighting the COVID-19 pandemic.
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Since the discovery of novel coronavirus pneumonia (Covid-19) in Wuhan, China, in December 2019, it has spread to other Chinese provinces and continents in just one month, becoming a "public health emergency of international concern". The undesired behaviors of the public and patients during the Covid-19 epidemic cannot be ignored, but few scholars have studied them. In this study, we firstly adopted a qualitative analysis method based on a theoretical paradigm to to summarize the human factors in the spread of the COVID-19 epidemic, and defined the concept of "human factors of the epidemic". Then, we analyzed the distribution characteristics of "human factors of epidemic" at each stage by using statistical analysis, and constructed a human factors model of epidemic evolution. Finally, a multi-subject risk assessment model was constructed using a fuzzy Bayesian network analysis method to quantify the human factors risk in the spread of the COVID-19 epidemic. The results of the study are as follows. (1) The human factors of the COVID-19 epidemic mainly focused on five aspects, including cognitive bias, defective design, management bias, environmental defects, and intentional violations. (2) There were differences in the human factors at different stages of the spread of the COVID-19 epidemic. In the outbreak stage, human factors of the COVID-19 epidemic showed complex trends, with factors such as lack of knowledge and low awareness still prevailing on the one hand, and factors such as lack of capacity, overtly agree but covertly oppose, dereliction of duty, concealment and misreporting, lack of resources, protection defects, design defects, escape/fleeing, and public gathering on the other hand also being more prominent. (3) The risk of the spread of the COVID-19 epidemic due to undesired human factors in the subjects involved was high (p=0.641) under conventional intervention scenarios. Risk factors such as low awareness, poor decision making, lack of resources, lack of awareness, system deficiencies, public agglomeration, inadequate protection, misreporting, and dereliction of duty had relatively large sensitivity factors and were key human factors for the spread of the epidemic in Wuhan. Finally, targeted recommendations are proposed based on the evolutionary pattern and risk level of the human factors of the COVID-19 epidemic.
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Covid-19, one of the coronaviruses, emerged in Wuhan, China, due to zoonotic infection towards the end of December 2019. According to WHO data, Covid-19 has been present among 267.865.289 people in 222 countries, causing death for 5.285.888 (December 12, 2021). Furthermore, these figures are increasing every day. In Turkey, 8.984.407 people have been infected thus far, and 78.602 have died (December 12, 2021). The following questions were investigated in this study: Does Covid-19 affect the use of medicinal and aromatic plants? If it does, what are the changes? What types of herbs are used and in which ways are they used? Who advises people to use these herbs? According to the results, 113 taxa belonging to 61 families and 105 genera were used by the participants at the genus, species and subspecies levels. Herbs that were widely used are Thymus spp., Tilia spp., Salvia spp., Zingiber officinale Roscoe, Mentha spp., Curcuma longa L., Rosa canina L., Camellia sinensis (L.) Kuntze, Lavandula spp., Matricaria spp., respectively. There was a positive and moderate-level relationship between medicinal and aromatic plants before and after COVID-19 and another positive and moderate-level relationship between the frequencies of using medicinal and aromatic plants before and after the pandemic. The relationships were significant for both questionnaire items. Moreover, there was a significant difference between the frequency of use of medicinal and aromatic plants before and after Covid-19. © 2023 Universidad Complutense. All rights reserved.
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Objective: To investigate the quality of life (QOL) of coronavirus disease 2019(COVID-19) patients in the recovery stage of six months after discharge and to analyze the influence factors. Methods: Based on the COVID-19 case registration system whose establishment was led by Beijing University of Chinese Medicine Third Affiliated Hospital, 117 COVID-19 patients in the recovery stage hospitalized in designated hospitals of COVID-19 in Wuhan, Hubei Province from January 17th to March 17th, 2020 were taken as the research objects and were followed up for six months after discharge. The QOL of patients was investigated with the World Health Organization Quality of Life-BREF (WHOQOL-BREF) face to face. The score of the QOL of patients with different clinical characteristics was analyzed and compared. The relationship between different clinical characteristics and the total score of the QOL of patients was analyzed by Pearson correlation analysis. Statistically significant factors were included in the linear regression analysis and the linear correlation equation of the total score of the QOL was obtained. Results: The total score of the QOL of patients in the WHOQOL-BREF scale was 75.79 +or- 13.80 points, the self-evaluation of the QOL was 3.20 +or- 0.78 points, and the self-evaluation of health condition was 2.60 +or- 0.79 points. The total score of the QOL of female patients, patients with high sequelae grade, and patients with history of smoking was lower than that of male patients, patients with low sequelae grade, and patients without history of smoking. The Pearson correlation analysis showed that the typing of the acute stage of COVID-19, sequelae grade, gender, and history of smoking were related to the total score of the QOL of patients at six months after discharge. The linear regression analysis showed that sequelae grade was linearly correlated with the total score of the QOL of patients at six months after discharge. Linear correlation equation was Y=94.179-9.153X. Conclusions: At six months after discharge, COVID-19 patients in the recovery stage were generally dissatisfied with their QOL and health condition. Their overall QOL was relatively low. It was affected by factors such as gender, BMI, underlying diseases, and history of smoking. And the sequelae symptoms had the most significant impact.
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In order to understand the impact of the COVID-19 pandemic on the entire aquaculture value chain in China and what strategy and measures have been taken to support the stakeholders to address the impact of the pandemic on the sector, the Food and Agriculture Organization (FAO) supported the Freshwater Fisheries Research Centre (FFRC) in carrying out a preliminary investigation. The investigation focused on channel catfish (Ictalurus punctatus) farming in Hubei Province and tilapia farming (Oreochromis spp.) in Guangdong Province. The results indicated a significant difference in the impact of the pandemic on different stakeholders in the two subsectors. The investigation also identified the most significant specific impact of the pandemic on production and operation at different value chain links. The investigation also covered the impact of the pandemic on the livelihood of households engaged in the value chain, which significantly reduced income due to lower payment and business revenue. As an important output of the study, a set of strategies and measures were recommended for supporting the aquaculture sector and stakeholders in the value chain to cope with the pandemic and other similar risks in the future.
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In the Chinese city of Wuhan at the end of 2019, an infection by an unknown virus began, which with subsequent studies was called SARS-CoV-2, causing a pandemic that has generated the largest crisis worldwide in recent years, causing a large number of deaths, with multiple systemic manifestations but which has also had clinical pictures at the skin level;recently there have been reports of people who had COVID-19 infections and later had skin manifestations due to herpes virus as a co-infection;the most frequent were herpes simplex type 1-2, varicella zoster, herpes zoster and herpes virus 6-7, generating even more complications in patients. Although the pathogenesis of this association is not entirely clear, it is believed to be secondary to the state of immunosuppression induced by SARS-CoV-2, being important that health personnel are informed about this entity that increases mortality.
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This paper uses social electricity consumption data from 2015-2021 in a city in Hubei province, and uses some methods of artificial intelligence, for example, python function fitting and machine learning to construct an impact analysis and prediction model of the COVID-19 epidemic on Electricity Consumption. Through comparison with the effects of general linear regression and polynomial regression, a better model is developed which comprises four independent variables and uses polynomial regression. The model developed in this paper helps to quantify and measure the impact of the epidemic on society's electricity consumption, and ultimately enables users in the electricity industry to make convenient and rapid forecasts, helping them to make reasonable power supply plans, trading plans and dispatch plans, and to ensure safe and economic operation of the Electricity System. © 2022 ACM.