• Title/Summary/Keyword: 코로나 19

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Changes in Public Bicycle Usage Patterns before and after COVID-19 in Seoul (코로나19 전후 서울시 공공 자전거 이용 패턴의 변화)

  • Il-Jung Seo;Jaehee Cho
    • The Journal of Bigdata
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    • v.6 no.2
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    • pp.139-149
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    • 2021
  • Ddareungi, a public bicycle service in Seoul, establishes itself as a means of daily transportation for citizens in Seoul. We speculated that the pattern of using Ddareungi may have changed since COVID-19. This study explores changes in using Ddareungi after COVID-19 with descriptive statistical analysis and network analysis. The analysis results are summarized as follows. The average traveling distance and average traveling speed have decreased over the entire time in a day since COVID-19. The round trip rate has increased at dawn and morning and has decreased in the evening and night. The average weighted degree and average clustering coefficient have decreased, and the modularity has increased. The clusters, located north of the Han River in Seoul, had a similar geographic distribution before and after COVID-19. However, the clusters, located south of the Han River, had different geographic distributions after COVID-19. Traveling routes added to the top 5 traffic rankings after COVID-19 had an average traveling distance of fewer than 1,000 meters. We expect that the results of this study will help improve the public bicycle service in Seoul.

코로나19의 백신개발 동향 및 백신비축 규모에 관한 소론

  • Park, Ho-Jeong;Im, Jae-Yeong
    • Environmental and Resource Economics Review
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    • v.29 no.2
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    • pp.273-292
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    • 2020
  • 본고는 코로나19라는 글로벌 팬데믹 상황에서 감염병 역학모형에 관한 내용과 기초재생산수, 집단면역임계, 백신비축 등의 주요 개념을 개론 수준에서 다루었다. 국내 첫 감염자 발생 이후 4월 12일까지의 데이터를 기준으로 분석해 볼 때 한국의 기초재생산수는 약 2의 값을 가지는데 이는 코로나19가 발생한 다른 나라에 비해 현저히 낮은 수치로 평가된다. 만일에 코로나19 백신이 개발되는 것을 가정하여 이의 비축규모를 추정해보면 인구의 최소 62%에 공급할 수 있는 수준이어야 하는 것으로 나타났다. 한편, 한국의 코로나19의 성공적 대응에는 사회적 거리두기 정책이 주된 요인 중의 하나라는 점도 발견하였다. 그러나 5월 이후 사회적 거리두기에 대한 다소 느슨해진 경향이 없지 않은데, 지역감염의 확산을 위해서는 원론적으로 대응할 필요가 있다. 본고는 학술적 관점이 아닌, 방역의 실무적 차원에서 역학모형, 그리고 경제-역학 모형을 활용하는 방법을 소개한 것 뿐이다. 보다 정교한 역학 모형을 제대로 연구하기 위해서는 상당한 규모의 팀워크가 필요하다. 2015년 메르스 이후 역학조사를 위한 자원이 보강되었다 하지만, 앞으로 역학조사 인력, 데이터 시스템 구축, 그리고 보건·경제·통계·수학 분야 등의 연구진이 보강되어야 할 것이다.

코로나19 경기 대응을 위한 환경 분야 재정지출 확대의 유효성: 그린뉴딜의 경제학

  • Kim, Ho-Seok
    • Environmental and Resource Economics Review
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    • v.29 no.2
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    • pp.293-312
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    • 2020
  • 코로나19의 확산으로 야기된 경기침체를 극복하기 위해 세계 각국이 적극적인 확장 재정정책을 도입하고 있다. 1930년대 대공황 시기와 비교되며 '뉴딜식' 정책이 제안되기도 하는데, 그중 하나가 이른바 '그린뉴딜'이다. 그린뉴딜은 경기부양을 목적으로 환경 분야 지출을 확대하는 것으로서, 재정정책과 환경정책 두 가지 측면의 효과를 모두 '주목적'으로 하는 정책 수단이다. 우리 정부도 경기를 부양하고 포스트 코로나19 시대에 대응하기 위해 그린뉴딜을 한 축으로 하는 '한국판 뉴딜' 정책 추진 방안을 발표하였다. 최근 녹색전환과 기후변화 대응의 필요성에 대한 사회적 관심이 높아지면서 그린뉴딜 추진 방안과 관련하여 다각도로 구체적인 논의가 이루어지고 있다. 이 글은 환경 분야 사업을 그린뉴딜 방식으로 추진할 때 기대되는 재정 정책 및 환경정책 측면에서의 효과를 고찰하는 한편 향후 국내 코로나19로 야기되는 경기침체에 대응하기 위한 목적으로 그린뉴딜을 추진할 때 염두에 두어야 할 정책적 고려사항을 제안한다.

The Influence of Infectious Disease Recognition and Perceived Risk of the COVID19 of Air Traveller on Risk reduction behavior and Tourist Destination Switching Intention (항공사 고객들의 코로나19의 감염병 인식과 지각된 위험이 위험감소행동과 관광지 전환의도에 미치는 영향)

  • Joo, Shin-Ok
    • The Journal of the Korea Contents Association
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    • v.21 no.12
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    • pp.250-263
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    • 2021
  • This study tries to understand the Infectious disease recognition and perceived risk of the COVID19 of air traveller on risk reduction behavior and tourist destination switching intention. The study method was to conduct a online survey research targeting air travelers with airline experience within a year. The empirical survey was conducted between Jun 2 and Jun 24, 2021, and 250 valid questionnaires were analyzed. data analysis was conducted using SPSS 20.0 and AMOS 23.0 the hypothesis was tested through structural equation modeling. First, Infectious disease recognition of the COVID19 has effect on perceived risk and risk reduction behavior. Second, perceived risk of the COVID19 has effects risk reduction behavior, but has no effect on tourist destination switching intention. Third, risk reduction behavior has effect on tourist destination switching intention. The findings has significant implications for infectious disease recognition and perceived risk of the COVID19, risk reduction behavior, tourist destination switching intention and academic researchers. This study has shown that infectious disease recognition of the COVID19 is critical for preventing the spread of infectious diseases.

Trend Analysis of Sports for All-Related Issues in Early Stage of COVID-19 Using Topic Modeling (토픽 모델링을 활용한 코로나19 초기 생활체육 이슈 분석)

  • Chung, Yunkil;Seo, Sumin;Kang, Hyunmin
    • Journal of Intelligence and Information Systems
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    • v.28 no.3
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    • pp.57-79
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    • 2022
  • COVID-19, which started in December 2019, has had a great impact on our lives in general, including politics, economy, society, and culture, and activities in sports and arts have also been significantly reduced. In the case of sports, sports for all fields in which ordinary citizens participate were particularly affected, and cases of infection in places closely related to people's lives, such as gyms, table tennis, and badminton clubs, also amplified the social fear of the spread of COVID-19. Therefore, in this study, we analyzed news articles related to sports for all at the time when COVID-19 was first spread, and investigated what issues were emerging and being discussed in the sports for all field under the COVID-19 situation. Specifically, we collected news articles dealt with sports for all issues under the COVID-19 situation from Korea's leading portal news sites and identified key sports for all issues by performing topic modeling on these articles. Through the analysis, we found meaningful issues such as COVID-19 outbreak in sports facilities and support for sports activities. In addition, through wordcloud analysis of these major issues, we visually understood the issues and identified the changes in these issues over time.

Analysis of News Agenda Using Text mining and Semantic Network Analysis: Focused on COVID-19 Emotions (텍스트 마이닝과 의미 네트워크 분석을 활용한 뉴스 의제 분석: 코로나 19 관련 감정을 중심으로)

  • Yoo, So-yeon;Lim, Gyoo-gun
    • Journal of Intelligence and Information Systems
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    • v.27 no.1
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    • pp.47-64
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    • 2021
  • The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

Effect of medium sized hospital nurses' nursing intention, infection prevention environment, and social psychological well-being on infection control performance of COVID-19 outbreak (코로나19 발생 상황에서 중소병원 간호사의 코로나19 환자 간호의도, 감염예방환경 및 사회심리적 건강이 코로나 관련 감염관리 수행도에 미치는 영향)

  • Yang Sin Kim;Jae Woo Oh;Seon Ok Kim
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.2
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    • pp.133-141
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    • 2023
  • This study was conducted to identify the effects of medium sized hospital nurses' nursing intention, infection prevention environment, and social psychological well-being on infection control performance of COVID-19 outbreak. The data collection period was from May 2 to May 31, 2022, and the questionnaires of 161 nurses who were working at I and B medium sized hospital in incheon and agree to participate in this study, were analyzed. Using the IBM SPSS/Win 25.0, the collected data was analyzed through the descriptive statistics, t-test, ANOVA, Pearson correlation, and multiple regreβion analysis. As a result, the infection prevention environment(β=.225, p<.001) and the experience of participating in new infectious disease education(β=.208, p=.008) had a significant effect and these variables were found to have 10.9% explanatory power for COVID-19 related infection control performance. Therefore, in the context of the outbreak of COVID-19, it is important to create an environment for infection prevention and to provide continuous and diverse education related to infectius diseases.

Network analysis on the diffusion of negative issue related with the government's COVID-19 measures in a crisis situation (위기상황에서 정부의 코로나 19 대책 관련 부정적 이슈의 확산 네트워크 분석)

  • Hong, Juhyun;Cha, Heewon
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.2
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    • pp.109-116
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    • 2022
  • This study conducted YouTube network analysis on YouTube video related with prevention of COVID-19 and COVID-19 vaccine to explores how government's policy is spread via social media in the condition of COVID-19. As a result of network analysis on the Mask chaos, A surge in confirmed cases, supply of vaccine, the influence of media like YTN and KBS is large, their view count is high. Government highlights to inform correct information actively to face negative massage and misinformation. The media has to fact check on the misinformation and disinformation.

The association between COVID-19 and changes in food consumption in Korea: analyzing the microdata of household income and expenditure from Statistics Korea 2019-2022 (코로나19와 한국 식품 소비 변화의 관계: 2019-2022년 통계청 소비자 가계동향조사를 활용하여)

  • Haram Eom;Kyounghee Kim;Seonghwan Cho;Junghoon Moon
    • Journal of Nutrition and Health
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    • v.57 no.1
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    • pp.153-169
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    • 2024
  • Purpose: The main goal of this study was to identify the impact of coronavirus disease 2019 (COVID-19) on grocery purchases (i.e., fresh and processed foods by grain, vegetable, fruit, seafood, and meat categories) in Korea. To understand the specific impact of COVID-19, the study period was divided into 3 segments: PRE-COVID-19, INTER-COVID-19, and POST-COVID-19. Methods: We used the microdata of household income and expenditure from Statistics Korea (KOSTAT), representing households across the country. The data comprised monthly grocery expenditure data from January 2019 to September 2022. First, we compared the PRE-COVID-19 period to INTER-COVID-19 and then INTER-COVID-19 to POST-COVID-19 and used multiple regression analysis. The covariates used were the gender and age of the head of the household, the household's monthly income, the number of family members, the price index, and the month (dummy variable). Results: The expenditures on all grocery categories except fresh fruit increased from PRE-COVID-19 to INTER-COVID-19. From INTER-COVID-19 to POST-COVID-19, almost all grocery category spending declined, with processed meat being the only exception. Most purchases of protein sources, increased during INTER-COVID-19 compared to PRE-COVID-19, while ham/sausage/bacon for meat protein, fish cakes and canned seafood for seafood protein, and soy milk for plant-based protein did not decrease during POST-COVID-19 compared to INTER-COVID-19. Conclusion: These results show an overall increase in in-home grocery expenditure during COVID-19 due to an increase in eating at home, followed by a decrease in this expenditure in the POST-COVID-19 period. Among the trends, the protein and highly processed convenience food categories did not see a decline in spending during the POST-COVID-19 period, which is a reflection of the preferences of consumers in the post-COVID-19 period.

Comparative analysis of performance of BI-LSTM and GRU algorithm for predicting the number of Covid-19 confirmed cases (코로나 확진자 수 예측을 위한 BI-LSTM과 GRU 알고리즘의 성능 비교 분석)

  • Kim, Jae-Ho;Kim, Jang-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.2
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    • pp.187-192
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    • 2022
  • Even the announcing date for the staring date of "With Corona" has been decided, still many people have not completed vaccination, the most important condition for starting the With Corona, because of concerns for its side effects. In addition, although the economy may can be recovered by the With Corona, but the number of infected people may can be surged. In this paper, in order to awaken the people for the awareness of Corona 19 in advance of the With Corona, the Corona 19 is predicted through a non-linear probability process. Here, among the deep learning RNN, BI-LSTM, which is a bidirectional LSTM, and GRU, gates decreased than LSTM have been used. And this has been compared and analyzed through train set, test set, loss function, residual analysis, normal distribution, and autocorrelation, and compared and predicted for which has a better performance.