• Korean journal of aerospace and environmental medicine
• /
• v.31 no.1
• /
• pp.21-23
• /
• 2021

Purpose: Human papillomavirus (HPV) vaccination schedule is recommended by Strategic Advisory Group of Experts on Immunization of World Health Organization to achieve high efficacy and immunogenicity. However, the patients often cannot keep up their schedule for several reasons. Methods: Monthly numbers of visitors for HPV vaccination between 2019 and 2021 were analyzed to measure the impact of coronavirus disease-19 (COVID-19) outbreak which was the main cause of this delay. Results: In February 2020, the number of foreign patients vaccinated with HPV was dropped suddenly due to COVID-19. Prior to this impact, the average patients per month for HPV vaccination was 160 (95% confidence interval [CI]: 143-176). It was then 30 (95% CI: 20-40). However recent trends show a gradual recovery. Conclusion: If a woman is pregnant after starting the HPV vaccine series, the reminder doses should be delayed until she is no longer pregnant. If this series is interrupted for any length of time, it can be resumed without restarting the series. HPV vaccine series need to be administered with a minimum interval of 14 days before or after administration of COVID-19 vaccines.

• The Journal of Industrial Distribution & Business
• /
• v.14 no.4
• /
• pp.33-46
• /
• 2023

Purpose: During the coronavirus disease-19 (COVID-19) outbreak, mask-wearing is required to protect against and limit the spread of infection, but it can directly affect skin problems. Change in skin condition might be related to mental health. This study explored the association between skin conditions and behavior of skin cares and stress levels during the Covid-19pandemics. Research design, data and methodology: A survey was conducted on 516 adults who were aware of damaged skin due to continuous wearing of masks for a long time during the COVID-19 Pandemic. The study included 164 men and 352 women in the Republic of Korea. Results: Skin conditions and behavior of skin cares associated with stress perceptions. A multiple linear regression model was used adjusting for potential confounder. Conclusion: Since management so far in the COVID-19 Pandemic can cause skin concerns and change the original skin type, it is necessary to redefine and improve the use of skin care, face-washing methods, and functional cosmetics. People with high and low interest in skin type recognition and management were evenly identified, and it was confirmed that stress awareness decreases as awareness of skin care attitude increases.

• International Journal of Contents
• /
• v.17 no.3
• /
• pp.1-14
• /
• 2021

Since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, a lot of efforts have been made in the field of data science to help combat against this disease. Among them, forecasting the number of cases of infection is a crucial problem to predict the development of the pandemic. Many deep learning-based models can be applied to solve this type of time series problem. In this research, we would like to take a step forward to incorporate spatial data (geography) with time series data to forecast the cases of region-level infection simultaneously. Specifically, we model a single spatio-temporal graph, in which nodes represent the geographic regions, spatial edges represent the distance between each pair of regions, and temporal edges indicate the node features through time. We evaluate this approach in COVID-19 in a Korean dataset, and we show a decrease of approximately 10% in both RMSE and MAE, and a significant boost to the training speed compared to the baseline models. Moreover, the training efficiency allows this approach to be extended for a large-scale spatio-temporal dataset.

• Journal of Multimedia Information System
• /
• v.8 no.4
• /
• pp.251-258
• /
• 2021

In 2019, a novel coronavirus (COVID-19) outbreak started in China and spread all over the world. The countries went into lockdown and closed their borders to minimize the spread of the virus. Shortage of testing kits and trained clinicians, motivate researchers and computer scientists to look for ways to automatically diagnose the COVID-19 patient using X-ray and ease the burden on the healthcare system. In recent years, multiple frameworks are presented but most of them are trained on a very small dataset which makes clinicians adamant to use it. In this paper, we have presented a lightweight deep learning base automatic COVID-19 detection system. We trained our model on more than 22,000 dataset X-ray samples. The proposed model achieved an overall accuracy of 96.88% with a sensitivity of 91.55%.

• Journal of The Korean Society of Integrative Medicine
• /
• v.9 no.1
• /
• pp.109-121
• /
• 2021

Purpose : The first case of coronavirus disease-2019 (COVID-19) disease outbreak in Korea occurred in January 2020, and the cumulative number of confirmed cases by the Central Defense Response Headquarters of the Quality Management Administration as of November 30 was 34,201. Looking at the incidence trend of domestic confirmed cases by age, the incidence rate of COVID-19 in the age group of 20-29 years, which corresponds to college students, was 27.4 %, the highest compared by age group. Considering the current status of the infection rate, universities will become the centers of new COVID-19 cases if face-to-face lectures are recommenced without preparatory measures and analysis of infection prevention (e.g., infection awareness and education for university students). Thus, this study intended to investigate the level of knowledge, educational needs, and preventive behavior performance of college students about COVID-19 and provide basic data for the development of an education program for the prevention of COVID-19 for college students. Methods : This study is a descriptive correlational study aimed to investigate the correlation between knowledge about COVID-19, educational needs, and degree of preventive behavior performance in 407 college students attending one University in Gyeonggi-do. Results : The subjects' knowledge score about COVID-19 was 12.46±1.39 points, average educational needs score was 29.16±3.14 points, and prevention behavior performance survey result was 35.50±3.61 points. Moreover, positive correlation was observed between the knowledge about COVID-19 and educational needs (r=.203, p<.001) and knowledge and preventive behavior performance (r=.140, p=.005). Further, educational needs and preventive behavior performance demonstrated a statistically significant positive relationship (r=.311, p<.001). Conclusion : Therefore, organizing an educational program to acquire accurate knowledge is necessary to make it a habit for college students to practice preventive behavior against COVID-19.

• Asian Journal for Public Opinion Research
• /
• v.8 no.3
• /
• pp.351-376
• /
• 2020

A low level of transparency and trust in the release of government information during the COVID-19 pandemic could decrease the chance of success in handling the coronavirus outbreak. This worldwide pandemic has damaged not only human health but also created an economic and social crisis. Indonesia is no exception. Unfortunately, an analysis of a mixed-method survey of 500 participants found that public perception of transparency in the government's release of COVID-19 information is still at a low level. This perceived low level of transparency generates minimum trust in the information. Only 8% of participants trust the government's information regarding the virus. Even though the Indonesian government launched an official website, www.covid19.go.id, which is intended as a primary source of valid information about COVID-19 in Indonesia, most survey participants had never used the website. However, contrary to the low levels of perceived transparency and trust, most participants said that the messages from the government are clear and easy to understand. This contradiction resulted from skepticism toward the government. Therefore, this research presents a better understanding of how the level of transparency and trust is also related to the level of skepticism of the government.

• Asian Journal for Public Opinion Research
• /
• v.8 no.3
• /
• pp.324-350
• /
• 2020

COVID-19 has challenged the pandemic response capability of many countries. Many governments around the world have imposed strict quarantine measures and border control to slow the spread of the virus. In the Philippines, the longest community quarantine has been imposed in the National Capital Region (NCR). However, the effectiveness of such measures is dependent on the cooperation of the public. The objective of this study was to gain an understanding of the knowledge, attitudes, and practices (KAP) of selected employees in the NCR. An online survey was conducted June 4-18, 2020, with 100 employed people living in the NCR. Frequencies and percentages were computed to describe the respondents' answers, and the Kruskal-Wallis test was used to determine the differences in the respondents' KAP levels according to selected demographic characteristics. Of those surveyed, 92% have a high knowledge of COVID-19. The respondents have a positive attitude toward the need for health education and the seriousness of COVID-19, as well as stricter measures against the pandemic, but are less positive in terms of how the government is responding to the pandemic. They also follow strict measures that will prevent the further spread of the virus. The results highlight the respondents' favorability of stricter government measures to control the spread of COVID-19, including the reimposition of an enhanced community quarantine in the NCR.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.5
• /
• pp.523-531
• /
• 2021

Vietnam's Oil and gas industry make a significant contribution to the Gross Domestic Product of Vietnam. The ongoing COVID-19 pandemic has hit every industry hard, but perhaps the one industry which has taken the biggest hit is the global oil and gas industry. The purpose of this article is to examine how the COVID-19 pandemic affects the share price of the Vietnam Oil and Gas industry. The event study method applied to Oil and Gas industry index data around three event days includes: (i) The date Vietnam recognized the first patient to be COVID-19 positive was January 23, 2020; (ii) The second outbreak of COVID-19 infection in the community began on March 6, 2020; (iii) The date (30/3/2020) when Vietnam announced the COVID-19 epidemic in the whole territory. This study found that the share price of the Vietnam Oil and Gas industry responded positively after the event (iii) which is manifested by the cumulative abnormal return of CAR (0; 3] = 3.8% and statistically significant at 5 %. In the study, event (ii) has the most negative and strong impact on Oil and Gas stock prices. Events (i) favor negative effects, events (iii) favor positive effects, but abnormal return change sign quickly from positive to negative after the event date and statistically significant shows the change on investors' psychology.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.7
• /
• pp.1-9
• /
• 2021

This paper investigates the impact of the domestic and global outbreak of the coronavirus (COVID-19) pandemic on the trading size of the Malaysian stock (MS) market. The theoretical model posits that stock markets are affected by their response to disasters and events that arise in the international or local environments, as well as to several financial factors such as stock volatility and spread bid-ask prices. Using daily time-series data from 27 January to 12 May 2020, this paper utilizes the traditional Augmented Dickey and Fuller (ADF) technique and Zivot and Andrews with structural break' procedures for a stationarity test analysis, while the autoregressive distributed lag (ARDL) method is applied according to the trading size of the MS market model. The analysis considered almost all 789 listed companies investing in the main stock market of Malaysia. The results confirmed our hypotheses that both the daily growth in the active domestic and global cases of coronavirus (COVID-19) has significant negative effects on the daily trading size of the stock market in Malaysia. Although the COVID-19 has a negative effect on the Malaysian stock market, the findings of this study suggest that the COVID-19 pandemic may have an asymmetric effect on the market.

• International Journal of Computer Science & Network Security
• /
• v.22 no.1
• /
• pp.225-233
• /
• 2022

The recent outbreak of corona virus (COVID-19) infectious disease had made its forecasting critical cornerstones in most scientific studies. This study adopts a machine learning based time series model - Auto Regressive Integrated Moving Average (ARIMA) model to forecast COVID-19 confirmed cases in Botswana over 60 days period. Findings of the study show that COVID-19 confirmed cases in Botswana are steadily rising in a steep upward trend with random fluctuations. This trend can also be described effectively using an additive model when scrutinized in Seasonal Trend Decomposition method by Loess. In selecting the best fit ARIMA model, a Grid Search Algorithm was developed with python language and was used to optimize an Akaike Information Criterion (AIC) metric. The best fit ARIMA model was determined at ARIMA (5, 1, 1), which depicted the least AIC score of 3885.091. Results of the study proved that ARIMA model can be useful in generating reliable and volatile forecasts that can used to guide on understanding of the future spread of infectious diseases or pandemics. Most significantly, findings of the study are expected to raise social awareness to disease monitoring institutions and government regulatory bodies where it can be used to support strategic health decisions and initiate policy improvement for better management of the COVID-19 pandemic.