• Title/Summary/Keyword: 확진자

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Visualization of COVID-19 data (코로나19 데이터의 시각화)

  • Kim, Sun-Ok;Kim, Hye-Young
    • Proceedings of the Korean Society of Computer Information Conference
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    • pp.149-152
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    • 2021
  • 본 논문은 실시간 코로나-19 전국 확진자 수를 이용하여 데이터를 추출하고 분리하여 시각적으로 표현했다. 추출된 데이터를을 각 지역에 따라 구분하고 전국 지도에 확진자 수를 표시하여 보기 쉽게 나타냈다. 확진자의 경로는 코로나-19 데이터에서 사후 관리를 위해 가장 중요한 데이터이다. 따라서 확진자의 경로는 정부에서 실시간으로 제공되고 있다. 하지만 이러한 데이터는 텍스트 형태로 되어있어 보기에 불편하다. 따라서 본 논문은 확진자 데이터를 분석하고 정리하여 지도에 표시하고자 한다. 이러한 시각화 방법은 확진자의 경로를 쉽게 파악 할 수 있고 감염 경로를 미리 예방 할 수 있게 한다.

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Analysis of the Information in the COVID-19 Emergency Alert : Focusing on Essential Information Factors and Privacy Invasion Information Factors (코로나19 안전안내문자 정보 속성 분석 : 필수 정보 요인과 프라이버시 침해 정보 요인을 중심으로)

  • Kim, Minjin;Kim, Miyea;Kim, Beomsoo
    • Knowledge Management Research
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    • v.22 no.2
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    • pp.227-246
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    • 2021
  • In the context of the global pandemic caused by COVID-19, emergency alert text messages can violate the privacy of confirmed corona positive cases. This study used conjoint analysis to identify the essential information factors and the privacy invasion information factors of local government initiated safety notices. As a result of this study, we found eight essential information factors, including all routes of the confirmed case and ten privacy invasion factors of safety notices. In addition, we found that there is a similarity between the combinations of information perceived to be the most essential and perceived as the most significant privacy invasion; both combinations include the confirmed case's personal and route information. This study ultimately tried to suggest a way to lower the concern about privacy invasion of the confirmed cases without damaging the emergency alert text messages' essential information. We expect that this study will provide researchers and policymakers interested in disaster communication with valuable theoretical and practical implications.

Mixed-effects zero-inflated Poisson regression for analyzing the spread of COVID-19 in Daejeon (혼합효과 영과잉 포아송 회귀모형을 이용한 대전광역시 코로나 발생 동향 분석)

  • Kim, Gwanghee;Lee, Eunjee
    • The Korean Journal of Applied Statistics
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    • v.34 no.3
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    • pp.375-388
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    • 2021
  • This paper aims to help prevent the spread of COVID-19 by analyzing confirmed cases of COVID-19 in Daejeon. A high volume of visitors, downtown areas, and psychological fatigue with prolonged social distancing were considered as risk factors associated with the spread of COVID-19. We considered the weekly confirmed cases in each administrative district as a response variable. Explanatory variables were the number of passengers getting off at a bus station in each administrative district and the elapsed time since the Korean government had imposed distancing in daily life. We employed a mixed-effects zero-inflated Poisson regression model because the number of cases was repeatedly measured with excess zero-count data. We conducted k-means clustering to identify three groups of administrative districts having different characteristics in terms of the number of bars, the population size, and the distance to the closest college. Considering that the number of confirmed cases might vary depending on districts' characteristics, the clustering information was incorporated as a categorical explanatory variable. We found that Covid-19 was more prevalent as population size increased and a district is downtown. As the number of passengers getting off at a downtown district increased, the confirmed cases significantly increased.

The effect of ambiguity of information on Covid-19 patients' contact trace on intention to visit the commercial district: Comparison of residents in Gangnam-gu and Seocho-gu (코로나19 확진자 동선정보의 모호성 차이가 유관 상권 방문의도에 미치는 영향 연구: 강남구민과 서초구민의 비교)

  • Min, Dongwon
    • Journal of Digital Convergence
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    • v.18 no.8
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    • pp.179-184
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    • 2020
  • This study aims to investigate the effect that local government's information release range on Covid-19 patients' contact trace on consumer sentiment in the region. One hundred twenty-eight residents of Gangnam-gu and Seocho-gu participated in the study. The results showed that when ambiguity of information increased perceived anxiety on Covid-19 patients' contact trace, which in turn led lower intention to visit the commercial district near the Covid-19 patients' contact trace. Based on the findings, several suggestions was proposed for future research, including longitudinal studies covering even the "long-term" changes in consumer sentiment, the effect of implicit anxiety, and the behavioral difference between residence and non-residence.

Development of Infographic Method providing Global Corona Information using Open API (Open API를 활용한 국내외 코로나 정보 Inforgraphic 제공 방법 개발)

  • Choi, Hyo Hyun;Lee, Yeon-Guk
    • Proceedings of the Korean Society of Computer Information Conference
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    • pp.513-514
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    • 2021
  • 본 논문에서는 코로나-19에 대한 국내외 코로나 확진자 정보에 대한 Infographic 제공 방법 개발을 제안한다. 코로나-19에 대한 국내외 코로나 정보는 행정안전부에서 운영하는 공공 데이터 포털의 open API를 사용함으로써 신뢰성 있는 정보를 바탕으로 일반적으로 Text 형식으로 제공되는 코로나-19 정보를 다양한 Infographic 방법으로 제시하여 사용자에게 보다 효과적으로 정보를 제공할 수 있도록 개발하였다.

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Factors related to COVID-19 Incidence and Mortality rate in Gyeongsangbuk-do, Korea (경상북도 지역의 코로나19 발생률 및 사망률 관련요인)

  • Kim, Dong-Hwi;Park, Sung-Jun;Kang, Hyun-Jun;Yeom, Eun-Jung;Yoo, Na-Eun;Lee, Jeong-Min;Nam, Eun-Ha;Park, Ji-Hyuk;Lee, Kwan
    • Journal of agricultural medicine and community health
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    • v.45 no.4
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    • pp.235-244
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    • 2020
  • Objectives: Gyeongsangbuk-do has entered a super-aged society with 20.7% of the population aged 65 and older. As of April 30, 2020, the death rate of COVID-19(3.8 people) in Gyeongsangbuk-do is higher than the national mortality rate (2.3 people), and the fatality rate of COVID-19 by age accounts for more than half of the total of 58.6%, so it is time to propose to prevent infectious diseases in the event of additional infectious disease disasters COVID-19. Methods: We collected daily data on the number of confirmed cases and deaths due to COVID-19 from 19 February to 30 April 2020. The data collected was evaluated using the SPSS 21.0 statistical package. Results: As a result of comparing the incidence and death-related factors of confirmed patients in Gyeongsangbuk-do, there were significant differences in age group (p<0.001), underlying disease (p<0.001), and residence type (p<0.033). Conclusion: Factors affecting the mortality rate of confirmed patients in Gyeongsangbuk-do have been combined with individual level factors(age, gender, underlying disease), which means individual characteristics that have existed since before the disease, and regional level factors(Type of Residence), which are external factors that enable the use of medical resources. Therefore, each local government is required to establish preventive measures considering individual and regional level factors.

A Study on the Construction of Moving Route Information Sharing System of COVID-19 Confirmed Cases

  • Kim, Byungkyu;You, Beom-Jong;Shim, Hyoung-Seop
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.12
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    • pp.155-163
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    • 2020
  • This study developed a system that can collect, manage, and utilize the travel routes of individuals who tested positive for coronavirus disease 2019 (COVID-19) based on the data standardization and quality management principles and presented the analysis data collected from the existing system. Unlike many other countries in the world, Korea demonstrated a rapid response by conducting epidemiological investigations. Further, the local governments have actively shared the travel routes of individuals who tested positive for COVID-19 to facilitate proactive prevention of the infectious disease per the Infectious Disease Control and Prevention Law. However, currently, there is no standard protocol for the local governments to share the information, thus complicating the process of sharing, managing, and utilizing the collected data. Therefore, this study developed a system that can facilitate sharing of the travel routes of individuals who tested positive for COVID-19 by establishing database construction procedures and using the travel route of COVID-19 patients as per the Disaster & Safety Information Sharing Platform and developing a data processing guideline, a data entry system with default templates, and Open API. Although this sharing system was designed to communicate the travel routes of COVID-19 patients, it can also be utilized in case of other infectious diseases. Therefore, it can be used as a response strategy for future outbreaks of infectious diseases.

Time series analysis for Korean COVID-19 confirmed cases: HAR-TP-T model approach (한국 COVID-19 확진자 수에 대한 시계열 분석: HAR-TP-T 모형 접근법)

  • Yu, SeongMin;Hwang, Eunju
    • The Korean Journal of Applied Statistics
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    • v.34 no.2
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    • pp.239-254
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    • 2021
  • This paper studies time series analysis with estimation and forecasting for Korean COVID-19 confirmed cases, based on the approach of a heterogeneous autoregressive (HAR) model with two-piece t (TP-T) distributed errors. We consider HAR-TP-T time series models and suggest a step-by-step method to estimate HAR coefficients as well as TP-T distribution parameters. In our proposed step-by-step estimation, the ordinary least squares method is utilized to estimate the HAR coefficients while the maximum likelihood estimation (MLE) method is adopted to estimate the TP-T error parameters. A simulation study on the step-by-step method is conducted and it shows a good performance. For the empirical analysis on the Korean COVID-19 confirmed cases, estimates in the HAR-TP-T models of order p = 2, 3, 4 are computed along with a couple of selected lags, which include the optimal lags chosen by minimizing the mean squares errors of the models. The estimation results by our proposed method and the solely MLE are compared with some criteria rules. Our proposed step-by-step method outperforms the MLE in two aspects: mean squares error of the HAR model and mean squares difference between the TP-T residuals and their densities. Moreover, forecasting for the Korean COVID-19 confirmed cases is discussed with the optimally selected HAR-TP-T model. Mean absolute percentage error of one-step ahead out-of-sample forecasts is evaluated as 0.0953% in the proposed model. We conclude that our proposed HAR-TP-T time series model with optimally selected lags and its step-by-step estimation provide an accurate forecasting performance for the Korean COVID-19 confirmed cases.

Design of a Privacy-based Confirmed Case Contact Notification System in the With-Corona Era (With-Corona 시대에 프라이버시 보호 기반의 확진자 접촉 여부 알림 시스템 설계)

  • Mun, Hyung-Jin
    • Journal of Convergence for Information Technology
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    • v.11 no.10
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    • pp.138-143
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    • 2021
  • As of this moment, we are tracing people who are closed contact with Covid-19 patients and trying to block the spread of Covid-19 through diagnostic tests. However, the incubation period of the confirmed case is two weeks, and it takes a lot of human resources, time, and money to trace the routes of the confirmed case. In particular, as the number of confirmed cases have been increasing, the cost for finding closed contacts and blocking them in advance exponentially have almost reached the limitation of the budget. In finding closed contacts, all citizens must record an electronic access list every time they visit an amenities such as a store or a restaurant. This is likely the invasion of the privacy of personal location information. In this study, we designed a system that keeps one's location in real time, it will download the movement information of the confirmed case which is collected by KDCA, and it will notify the user when there is an overlap. Moreover, then guide for diagnostic test in advance will be used. The proposed method can solve the difficulty of recording in an electronic access list when visiting a store, and it can block infringement of privacy without providing personal information from KDCA.

A GSADF bubble test analysis for COVID-19 pandemic (COVID-19 펜데믹에 대한 GSADF 버블 검정 분석)

  • Shin, Jiwon;Shin, Dong Wan
    • The Korean Journal of Applied Statistics
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    • v.33 no.5
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    • pp.655-664
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    • 2020
  • We apply the GSADF bubble test and its date-stamping method for the daily number of new COVID-19 cases. The test indicates statistically significant explosive expansions of the number of new cases whose periods of panic explosion are identified by the date-stamping method of the bubble test. The date-stamping analysis reveals that as of June 30 2020, the number of daily COVID-19 new cases are still explosively increasing for India; however, they stop explosively increasing (or are under control) for USA, Brazil, Russia, Spain, Turkey, China, and South Korea. It also reveals that South Korea has two disjoint periods of explosion: a stable period follows after the first explosion of 2020.02.20-2020.03.06, and then the second explosion occurs 2020.05.27-2020.06.01 with a stable period that continues up to 2020.06.30.