• 제목/요약/키워드: Pre-COVID19

검색결과 183건 처리시간 0.029초

Effects of the Coronavirus Disease 2019 (COVID-19) Pandemic on Outcomes among Patients with Polytrauma at a Single Regional Trauma Center in South Korea

  • Kim, Sun Hyun;Ryu, Dongyeon;Kim, Hohyun;Lee, Kangho;Jeon, Chang Ho;Choi, Hyuk Jin;Jang, Jae Hoon;Kim, Jae Hun;Yeom, Seok Ran
    • Journal of Trauma and Injury
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    • 제34권3호
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    • pp.155-161
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    • 2021
  • Purpose: The coronavirus disease 2019 (COVID-19) pandemic has necessitated a redistribution of resources to meet hospitals' service needs. This study investigated the impact of COVID-19 on a regional trauma center in South Korea. Methods: We retrospectively reviewed cases of polytrauma at a single regional trauma center in South Korea between January 20 and September 30, 2020 (the COVID-19 period) and compared them to cases reported during the same time frame (January 20 to September 30) between 2016 and 2019 (the pre-COVID-19 period). The primary outcome was in-hospital mortality, and secondary outcomes included the number of daily admissions, hospital length of stay (LOS), and intensive care unit (ICU) LOS. Results: The mean number of daily admissions decreased by 15% during the COVID-19 period (4.0±2.0 vs. 4.7±2.2, p=0.010). There was no difference in mechanisms of injury between the two periods. For patients admitted during the COVID-19 period, the hospital LOS was significantly shorter (10 days [interquartile range (IQR) 4-19 days] vs. 16 days [IQR 8-28 days], p<0.001); however, no significant differences in ICU LOS and mortality were found. Conclusions: The observations at Regional Trauma Center, Pusan National University Hospital corroborate anecdotal reports that there has been a decline in the number of patients admitted to hospitals during the COVID-19 period. In addition, patients admitted during the COVID-19 pandemic had a significantly shorter hospital LOS than those admitted before the COVID-19 pandemic. These preliminary data warrant validation in larger, multi-center studies.

Sentiment Analysis of Airline Satisfaction Using Social Big Data: A Pre- and Post-COVID-19 Comparison

  • Ju-Yang Lee;Phil-Sik Jang
    • 한국컴퓨터정보학회논문지
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    • 제29권6호
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    • pp.201-209
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    • 2024
  • COVID-19는 항공산업에 큰 영향을 주어 전 세계적인 여행 제한과 보안 강화 등의 변화를 불러 왔다. 본 연구는 COVID-19 전후 항공 서비스 만족도의 변화양상을 파악하기 위해 2016년부터 2023년까지 SKYTRAX 웹사이트에 게시된 147개 항공사에 대한 59,818개의 리뷰를 수집하고 감성 분석 기법을 활용하여 COVID-19 전후의 항공사 만족도, 리뷰 감성, 만족도에 영향을 미치는 속성을 비교 분석하였다. 분석 결과, COVID-19 이후 항공사 만족도 전반이 통계적으로 유의미하게 하락했으며 (p<0.001), 모든 항공사 선택 속성에 대한 긍정적 감성 비율이 유의미하게 감소한 반면, 부정적 감성 비율은 객실 및 기내서비스를 제외한 모든 속성에서 유의미하게 증가했다. 또한, 운항 서비스는 COVID-19 전후 기간 모두 전반적인 서비스 만족도에 가장 큰 영향을 미치는 것으로 나타났다. 이 연구는 COVID-19 전후 글로벌 주요 항공사의 만족도 속성에 대한 정량적 분석을 제공함으로써 향후 항공산업의 서비스 만족도 제고에 이바지할 것으로 기대된다.

텍스트 마이닝을 활용한 코로나 19 전후 온라인 동영상 서비스(OTT) 리뷰 비교분석 연구 - 정서 중심 대처와 노스탤지어를 중심으로 (A Comparative Analysis of OTT Service Reviews Before and After the Onset of the Pandemic Using Text Mining Technique: Focusing on the Emotion-Focused Coping and Nostalgia)

  • 고민정;이상원
    • 한국콘텐츠학회논문지
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    • 제21권11호
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    • pp.375-388
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    • 2021
  • 본 연구에서는 팬데믹 전후로 온라인 동영상 서비스(OTT) 이용자들의 리뷰를 비교분석 함으로써 코로나 19 시대를 살아가는 소비자에 대한 이해에 기여하고자 하였다. 코로나 19 이후 통제감 상실이 회피 동기의 발현으로 이어져 정서 중심 대처 수단으로써의 OTT 서비스 이용과 노스탤지어를 해소해주는 콘텐츠에 대한 관심이 증가할 것으로 보고 이를 텍스트 분석을 통해 검증하였다. 먼저 블로그 제목 분석결과, 코로나 19 이후 넷플릭스 경쟁사에 대한 언급이 줄었으며, 국내 콘텐츠에 대한 소개와 회피-거부 전략으로써의 OTT 서비스 이용이 증가하였다. 이어 블로그 본문 분석결과, OTT 서비스의 실용적인 장점을 중요시한 코로나 19 전과는 달리 코로나 19 이후 콘텐츠의 분위기, 감정, 대사에 초점을 두었으며 코미디와 로맨스 장르에 대한 관심이 증가했다. 또한, 코로나 19 이전의 현실을 잘 표현한 일상 콘텐츠에 대한 선호가 증가하였다. 본 연구는 코로나 19가 온라인 동영상 서비스 이용에 미치는 영향을 처음으로 살펴본 연구로써 코로나 시대의 OTT 서비스 이용자들에 대한 이해를 넓히고 OTT 서비스 시장에 실무적 제언을 제시함으로써 도움을 줄 수 있을 것으로 기대한다.

COVID-19 유행 전·후 고용형태에 따른 우울의 변화와 영향요인: 한국복지패널 12~17차 자료 이용 (Pre and Post Covid-19 Changes in Depression Scores by Employment Type, and Its Influencing Factors: Using the 12th~17th Data of the Korea Welfare Panel)

  • 김주혜;허경화;정진욱
    • 한국직업건강간호학회지
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    • 제32권4호
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    • pp.215-224
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    • 2023
  • Purpose: This study uses data from the 12th~17th Korea Welfare Panel (2017~2022) to analyze changes in depression scores due to the COVID-19 outbreak and the factors that influenced depression scores according to employment type. Methods: The difference in depression scores according to employment types before COVID-19 (12th~14th) and after COVID-19 (15th~17th) was analyzed. A fixed-effect model analysis was conducted before and after the occurrence of COVID-19. Results: After the outbreak of COVID-19, job satisfaction and family life satisfaction influenced the depression scores of regular wage workers. After the outbreak of COVID-19, annual income, health status, and satisfaction with family life affected the depression scores of non-regular wage workers. After the outbreak of COVID-19, leisure life satisfaction and family relationship satisfaction influenced the depression scores of self-employed. Self-esteem played a role as a control variable in lowering the depression scores of regular and non-regular workers, but did not play a role as a control variable for self-employed. Conclusion: Rather than the direct impact of infectious diseases such as COVID-19, social and economic changes resulting from policies implemented to prevent the spread affect workers' depression, and the impact varies depending on the type of employment. When implementing policies to prevent the spread of infectious diseases in the future, policies that take employment type into consideration rather than uniform policies should be prepared, and measures for mental health also need to be prepared.

빅데이터 분석을 통한 메타버스에 대한 인식 변화 분석 - 코로나19 발생 전후 비교를 중심으로 - (An Analysis of Changes in Perception of Metaverse through Big Data - Comparing Before and After COVID-19 -)

  • 강유림;김문영
    • 한국의류산업학회지
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    • 제24권5호
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    • pp.593-604
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    • 2022
  • The purpose of this study is to analyze the flow of change in perception of metaverse before and after COVID-19 through big data analysis. This research method used Textom to collect all data, including metaverse for two years before COVID-19 (2018.1.1~2019.11.30) and after COVID-19 outbreak (2020.1.11~2021.12.31), and the collection channels were selected by Naver and Google. The collected data were text mining, and word frequency, TF-IDF, word cloud, network analysis, and emotional analysis were conducted. As a result of the analysis, first, hotels, weddings, and glades were commonly extracted as social issues related to metaverse before and after COVID-19, and keywords such as robots and launches were derived, so the frequency of keywords related to hotels and weddings was high. Second, the association of the pre-COVID-19 metaverse keywords was platform-oriented, content-oriented, economic-oriented, and online promotion-oriented, and post-COVID-19 clusters were event-oriented, ontact sales-oriented, stock-oriented, and new businesses. Third, positive keywords such as likes, interest, and joy before COVID-19 were high, and positive keywords such as likes, joy, and interest after COVID-19. In conclusion, through this study, it was found that metaverse has firmly established itself as a new platform business model that can be used in various fields such as tourism, travel, festivals, and education using smart technology and metaverse.

Stock Market Response during COVID-19 Lockdown Period in India: An Event Study

  • ALAM, Mohammad Noor;ALAM, Md. Shabbir;CHAVALI, Kavita
    • The Journal of Asian Finance, Economics and Business
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    • 제7권7호
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    • pp.131-137
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    • 2020
  • The research investigates the impact of the lockdown period caused by the COVID-19 to the stock market of India. The study examines the extent of the influence of the lockdown on the Indian stock market and whether the market reaction would be the same in pre- and post-lockdown period caused by COVID-19. Market Model Event study methodology is used. A sample of 31 companies listed on Bombay Stock Exchange (BSE) are selected at random for the purpose of the study. The sample period taken for the study is 35 days (24 February-17 April, 2020). An event window of 35 days was taken with 20 days prior to the event and 15 days during the event. The event (t1) being the official announcement of the lockdown. The results indicate that the market reacted positively with significantly positive Average Abnormal Returns during the present lockdown period, and investors anticipated the lockdown and reacted positively, whereas in the pre-lockdown period investors panicked and it was reflected in negative AAR. The study finds evidence of a positive AR around the present lockdown period and confirms that lockdown had a positive impact on the stock market performance of stocks till the situation improves in the Indian context.

COVID-19: Improving the accuracy using data augmentation and pre-trained DCNN Models

  • Saif Hassan;Abdul Ghafoor;Zahid Hussain Khand;Zafar Ali;Ghulam Mujtaba;Sajid Khan
    • International Journal of Computer Science & Network Security
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    • 제24권7호
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    • pp.170-176
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    • 2024
  • Since the World Health Organization (WHO) has declared COVID-19 as pandemic, many researchers have started working on developing vaccine and developing AI systems to detect COVID-19 patient using Chest X-ray images. The purpose of this work is to improve the performance of pre-trained Deep convolution neural nets (DCNNs) on Chest X-ray images dataset specially COVID-19 which is developed by collecting from different sources such as GitHub, Kaggle. To improve the performance of Deep CNNs, data augmentation is used in this study. The COVID-19 dataset collected from GitHub was containing 257 images while the other two classes normal and pneumonia were having more than 500 images each class. There were two issues whike training DCNN model on this dataset, one is unbalanced and second is the data is very less. In order to handle these both issues, we performed data augmentation such as rotation, flipping to increase and balance the dataset. After data augmentation each class contains 510 images. Results show that augmentation on Chest X-ray images helps in improving accuracy. The accuracy before and after augmentation produced by our proposed architecture is 96.8% and 98.4% respectively.

Impact Assessment of First Wave of Covid-19 Pandemic on Goods and Services Tax (GST) Revenue Collection & Distribution in India

  • NAIK, Dr. Maithili;HALDANKAR, Gajanan B.
    • 유통과학연구
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    • 제19권10호
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    • pp.43-54
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    • 2021
  • Purpose: The restrictions posed by the COVID-19 pandemic have affected the normal functioning of the economy. A country like India is facing a lot of concerns in all its sectors especially, in its fiscal system. This paper makes an attempt to examine the impact of COVID-19 first wave on Goods and Service Tax revenue collection and distribution in India and also studies the impact of COVID-19 first wave on the state wise GST revenue of the country. Research Design, Data and Methodology: Our study is based on published GST revenue data. Tools such as Paired Sample t-test, Wilcoxon signed rank test are employed to analyze the data. Results: Our results provide evidence that there is a sharp decline in the GST revenue in the months after the lockdown announcement. The large states show no significance impact of COVID-19 pandemic on GST collection. Whereas, small states like Manipur and Goa show significant difference in GST revenue collection & distribution between the pre and post lockdown period. Conclusion: The outcome of this study will help the policymakers to analyze the extent of the GST revenue loss to the government treasury and will allow them to take appropriate measures in the future.

코로나19 팬데믹의 아세안 빈곤에 대한 잠재적 영향 추정 및 시사점 (Estimation of the Potential Impacts of COVID-19 on Poverty in ASEAN Countries)

  • 방호경;양은정
    • 경제분석
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    • 제27권1호
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    • pp.37-66
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    • 2021
  • 본 논문은 COVID-19가 아세안 빈곤에 미칠 잠재적 영향을 실증적으로 추정한다. 빈곤 감소는 국제개발협력의 가장 보편적인 목적이다. 지속가능발전목표(SDGs)에서도 2030년까지 빈곤종식을 목표로 전 세계적 노력을 촉구한 바 있으나 COVID-19는 이러한 노력에 부정적인 영향을 줄 것으로 예상된다. 이러한 배경에서 빈곤에 대한 COVID-19의 영향을 추정하는 것은 개발협력정책의 방향성 수립 및 효과성 제고에 있어 시사하는 바가 크다. 본 논문은 다양한 추정방법을 통해 COVID-19의 빈곤에 대한 잠재적 영향을 정량적으로 추정한다. 첫 번째는 Summer et al. (2020), Nonvide (2020)가 제안한 가계소득 감소 시나리오를 구성한 후 국제빈곤선 조정을 통한 빈곤추정이다. 두 번째는 회귀분석을 통한 추정으로 국가 간 이질성, 불균형데이터, 내생성을 통제한 상관임의효과 모형을 통해 추정한다. 분석결과 COVID-19는 아세안 각국의 빈곤에 악영향을 줄 것으로 나타났다. 특히 빈곤감소를 위해서는 아세안 각국이 경제성장과 더불어 소득불평등도를 감소시키는 정책적 노력을 함께 추진해야 하며, 이는 COVID-19 이전의 빈곤수준으로 빠르게 회복시킬 뿐만 아니라 더 빠른 빈곤감소에 기여할 것으로 분석되었다.

Effects of an Infection Control Protocol for Coronavirus Disease in Emergency Mechanical Thrombectomy

  • Eun, Jin;Lee, Min-Hyung;Im, Sang-Hyuk;Joo, Won-Il;Ahn, Jae-Geun;Yoo, Do-Sung;Park, Hae-Kwan
    • Journal of Korean Neurosurgical Society
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    • 제65권2호
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    • pp.224-235
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    • 2022
  • Objective : Since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, neurointerventionists have been increasingly concerned regarding the prevention of infection and time delay in performing emergency thrombectomy procedures in patients with acute stroke. This study aimed to analyze the effects of changes in mechanical thrombectomy protocol before and after the COVID-19 pandemic on procedure time and patient outcomes and to identify factors that significantly impact procedure time. Methods : The last-normal-to-door, first-abnormal-to-door, door-to-imaging, door-to-puncture, and puncture-to-recanalization times of 88 patients (45 treated with conventional pre-COVID-19 protocol and 43 with COVID-19 protection protocol) were retrospectively analyzed. The recanalization time, success rate of mechanical thrombectomy, and modified Rankin score of patients at discharge were assessed. A multivariate analysis was conducted to identify variables that significantly influenced the time delay in the door-to-puncture time and total procedure time. Results : The door-to-imaging time significantly increased under the COVID-19 protection protocol (p=0.0257) compared to that with the conventional pre-COVID-19 protocol. This increase was even more pronounced in patients who were suspected to be COVID-19-positive than in those who were negative. The door-to-puncture time showed no statistical difference between the conventional and COVID-19 protocol groups (p=0.5042). However, in the multivariate analysis, the last-normal-to-door time and door-to-imaging time were shown to affect the door-to-puncture time (p=0.0068 and 0.0097). The total procedure time was affected by the occlusion site, last-normal-to-door time, door-to-imaging time, and type of anesthesia (p=0.0001, 0.0231, 0.0103, and 0.0207, respectively). Conclusion : The COVID-19 protection protocol significantly impacted the door-to-imaging time. Shortening the door-to-imaging time and performing the procedure under local anesthesia, if possible, may be required to reduce the door-to-puncture and door-to-recanalization times. The effect of various aspects of the protection protocol on emergency thrombectomy should be further studied.