Current Spread Of COVID-19 Research Articles

Online health information seeking and digital health literacy among information and learning resources undergraduate students

BackgroundDuring the COVID-19 pandemic, students have trouble coping with the available health information regarding the coronavirus in their daily lives because of misinformation. ObjectivesThe aim of this study was to evaluate online health information seeking and digital health literacy among information and learning resources undergraduate students at Taibah University during the COVID-19 pandemic. MethodsTo investigate the primary goal, this study used a simultaneous exploratory mixed methods design. Seventeen students participated in phone interviews, and 306 were invited to complete an online survey. AnalysisThe collected data was analyzed using both quantitative (SPSS) and qualitative (NVivo 10) methods. ResultsSearch engines, social media, and YouTube were most often used by the respondents as sources to search for COVID-19-related information. COVID-19 symptoms, restrictions, and the current spread of COVID-19 were the most searched topics by the respondents. Significant and relevant differences emerged for the digital health literacy subscales “information search” and “adding self-generated content”. However, there were no significant differences in the digital health literacy subscale “determining relevance”. ConclusionUsing the internet to provide health information tailored to the needs and interests of students to seek health information online and thereby improve their health literacy.

Stress Akademik antara Laki-laki dan Perempuan Siswa School from Home

The current spread of Covid-19 has forced the government to come up with a policy that forces students to study from home, which was eventually known as school from home. This study was conducted with the aim of knowing the differences in academic stress between male and female students from home schooling. The research method used is quantitative research. The subjects in this study were students of Darut Taqwa High School, which consisted of 30 male students and 30 female students. Data was collected using the academic stress scale. Based on the calculation of the validity test, obtained 30 valid items from the stress scale with an academic reliability coefficient of 0.99. The data obtained showed that the level of academic stress of male students who were in the low category was 30% and the medium category was 70%. Meanwhile, female students have academic stress levels which are in the medium category of 36.6% and the high category of 73.4%. Based on the results of data analysis using the t-test between groups, the results were 2,632 with a t-table of 5%, which was 2,000. This means that the results of this study indicate that there are differences in academic stress between male and female students studying from home.

COVID-SGIS: A Smart Tool for Dynamic Monitoring and Temporal Forecasting of Covid-19.

Background: The global burden of the new coronavirus SARS-CoV-2 is increasing at an unprecedented rate. The current spread of Covid-19 in Brazil is problematic causing a huge public health burden to its population and national health-care service. To evaluate strategies for alleviating such problems, it is necessary to forecast the number of cases and deaths in order to aid the stakeholders in the process of making decisions against the disease. We propose a novel system for real-time forecast of the cumulative cases of Covid-19 in Brazil.Methods: We developed the novel COVID-SGIS application for the real-time surveillance, forecast and spatial visualization of Covid-19 for Brazil. This system captures routinely reported Covid-19 information from 27 federative units from the Brazil.io database. It utilizes all Covid-19 confirmed case data that have been notified through the National Notification System, from March to May 2020. Time series ARIMA models were integrated for the forecast of cumulative number of Covid-19 cases and deaths. These include 6-days forecasts as graphical outputs for each federative unit in Brazil, separately, with its corresponding 95% CI for statistical significance. In addition, a worst and best scenarios are presented.Results: The following federative units (out of 27) were flagged by our ARIMA models showing statistically significant increasing temporal patterns of Covid-19 cases during the specified day-to-day period: Bahia, Maranhão, Piauí, Rio Grande do Norte, Amapá, Rondônia, where their day-to-day forecasts were within the 95% CI limits. Equally, the same findings were observed for Espírito Santo, Minas Gerais, Paraná, and Santa Catarina. The overall percentage error between the forecasted values and the actual values varied between 2.56 and 6.50%. For the days when the forecasts fell outside the forecast interval, the percentage errors in relation to the worst case scenario were below 5%.Conclusion: The proposed method for dynamic forecasting may be used to guide social policies and plan direct interventions in a cost-effective, concise, and robust manner. This novel tools can play an important role for guiding the course of action against the Covid-19 pandemic for Brazil and country neighbors in South America.