• 셀메드
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• 제11권4호
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• pp.20.1-20.23
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• 2021

Background: The pandemic COVID-19 caused by a novel coronavirus SARS-COV-2 has spread like a forest fire. This disease may have serious consequences for pregnant women. Presently, no specific drugs or vaccines exist to battle this disease and researches are underway. Unani medicine has a unique role in prevention and management during epidemics. Here, we reviewed the overview of COVID-19 infection and pregnancy, concept and practices in Unani medicine for flu-like epidemics in general and pregnancy, and safety of Unani drugs for the prevention and treatment of mild symptomatic cases of COVID-19 during pregnancy. Methodology: Unani classical texts and pharmacopoeia were meticulously explored for concepts and practices for flu-like epidemic diseases. Further, we browsed scientific databases such as PubMed, Scopus and others for an overview, epidemics and Unani medicine, effectiveness and safety of Unani drugs in COVID-19 and pregnancy. Results: Unani medicine includes prevention and management of flu-like epidemic include quarantine and isolation, aromatic herbal drugs fumigation and spraying for environmental disinfection, ilaj bid tadbir for health promotion and use of health-protecting drugs and symptom-specific drugs in general and related to pregnancy. Lahsun, asalussus, behidana, banafsha, zanjabeel, unnab, etc are in use since antiquity for the prevention and treatment of asymptomatic and mildly symptomatic pregnant women during infectious and epidemic diseases. Conclusion: Currently, the aforementioned plants are proven for antiviral, antioxidant, immunomodulatory and anti-inflammatory activities, probably useful in the COVID-19 pandemic. Additionally, scientific studies have provided new insight into the mechanism underlying the therapeutic effect of Unani medicines that are safe in pregnancy.

• 한국학교보건학회지
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• 제23권1호
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• pp.63-70
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• 2010

Purpose: To identify the need to reform in the crisis response of Health Teacher, School Nurse, in elementary school during epidemic outbreak of influenza H1N1. Methods: 139 elementary health teachers, school nurse, in seoul elementary school responded in the questionnaire, and we analysed by using frequency and percent, t-test, and paired t-test. Results: The Job status became 121% more 'during influenza H1N1 (flu) outbreak' than Job status of 'before outbreak'. The proportion of the flu-related duty among their daily workload was up to 77.5%. The administration-related workload of the flu-related duty was 30.8%. and students' health assessment including temperature measurement 18.7%. Furthermore, an impediment of usual daily work due to an increaed flu-related workload was 95.7%, and no alternative plan such as disposition of assistant labor force was 86.1%. Especially, an impediment of health education was 61.0%, so the major concern was the loss of health education. We compared average scores (a five-point Likert scale) of health teachers' work motivation, exhaustion, work relationship and Job management of 'during' with 'before' flu-outbreak. The difference range of 'during' minus 'before' work motivation score was from -0.4 points to -0.9; work exhaustion range from 1.8 to 1.9; the difficulty of relationship between students, school personnel, parents of students, and health teachers from 1.4 points to 1.3 points; and the consideration of changing Job, taking time off from the Job and retirement from 1.4 to 1.6 points. Conclusion: The health teachers had a heavy workload due to flu-outbreak. They also experienced the impediment of usual work implementation. However, there was a shortage of alternative plan such as disposition of an assistant labor force. Under their Job status like this, the health teachers' motivation score was decreased and work exhaustion was increased. Furthermore, they had a lot of relation difficulty with students and school personnel. Therefore, we suggested that in contrast to the usual Job status, there is a need to have a prepared response during school crisis like flu-outbreak such as improved response system in seoul metropolitan education office, simplification or dispersion of administrative work, and temporary call-center for simple inquiries or advices.

• Journal of the Korean Data and Information Science Society
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• 제27권4호
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• pp.1075-1081
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• 2016

The big data analysis has received much attention from the researchers working in various fields because the big data has a great potential in detecting or predicting future events such as epidemic outbreaks and changes in stock prices. Reflecting the current popularity of big data analysis, many authors have proposed methods tracking influenza epidemics based on internet-based information. The recently proposed 'autoregressive model using Google (ARGO) model' (Yang et al., 2015) is one of those influenza tracking models that harness search queries from Google as well as the reports from the Centers for Disease Control (CDC), and appears to outperform the existing method such as 'Google Flu Trends (GFT)'. Although the ARGO predicts well the outbreaks of influenza, this study demonstrates that a classical seasonal autoregressive integrated moving average (SARIMA) model can outperform the ARGO. The SARIMA model incorporates more accurate seasonality of the past influenza activities and takes less input variables into account. Our findings show that the SARIMA model is a functional tool for monitoring influenza epidemics.

• 한국멀티미디어학회논문지
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• 제16권6호
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• pp.667-677
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• 2013

소셜 네트워크 서비스의 인기가 증가하면서 현재 이슈가 되는 정보를 추출하거나 증상 등을 추적하는 분석연구가 활발히 진행되고 있다. 특히 트위터에서는 트윗을 통해 이벤트 현상에 대한 반응과 사용자의 개인적인 상태 등이 잘 반영되어 트윗을 센서로 적용한 이벤트 추출이 가능하다. 최근에는 지진과 같은 재난 이벤트뿐만 아니라 사회 전반적으로 관심을 갖고 있는 질환이나 질병에 대한 사회적 신호가 질병의 확산을 조기에 감지하는데 도움을 주고 있다. 논문에서는 감기를 대상 이벤트로 지정하여 트위터로부터 수집한 정보를 감기 신호라는 사회적 신호로 간주하고 분석하였다. 추출된 감기 신호의 신뢰성을 확인하기 위해 감기 확산의 환경적 요인으로 알려진 세 가지 기후 요소와 기상청에서 제공하는 감기 기상지수와의 상관분석을 통해 변수들 사이의 상관관계를 파악한다.