No abstract

In this paper, we present a visual analysis system to explore sparse traffic trajectory data recorded by transportation cells. Such data contains the movements of nearly all moving vehicles on the major roads of a city. Therefore it is very suitable for macro-traffic analysis. However, the vehicle movements are recorded only when they pass through the cells. The exact tracks between two consecutive cells are unknown. To deal with such uncertainties, we first design a local animation, showing the vehicle movements only in the vicinity of cells. Besides, we ignore the micro-behaviors of individual vehicles, and focus on the macro-traffic patterns. We apply existing trajectory aggregation techniques to the dataset, studying cell status pattern and inter-cell flow pattern. Beyond that, we propose to study the correlation between these two patterns with dynamic graph visualization techniques. It allows us to check how traffic congestion on one cell is correlated with traffic flows on neighbouring links, and with route selection in its neighbourhood. Case studies show the effectiveness of our system.

Several vaccines have been developed for COVID-19 since the pandemic began. This study aimed to evaluate the factors associated with COVID-19 vaccination intention. A global survey was conducted across 26 countries from October, 2020 to December, 2021 using an online self-administered questionnaire. Demographic information, socio-economic status, and clinical information were collected. A logistic regression examined the associations between vaccine intention and factors such as perceptions and the presence of chronic physical and mental conditions. The sample included 2459 participants, with 384 participants (15.7%) expressing lower COVID-19 vaccination intent. Individuals who identified as female; belonged to an older age group; had a higher level of education; were students; had full health insurance coverage; or had a previous history of influenza vaccination were more willing to receive vaccination. Conversely, those who were working part-time, were self-employed, or were receiving social welfare were less likely to report an intention to get vaccinated. Participants with mental or physical health conditions were more unwilling to receive vaccination, especially those with sickle cell disease, cancer history within the past five years, or mental illness. Stronger vaccination intent was associated with recommendations from the government or family doctors. The presence of chronic conditions was associated with lower vaccine intention. Individuals with health conditions are especially vulnerable to health complications and may experience an increased severity of COVID-19 symptoms. Future research should evaluate the effectiveness of interventions targeting the vaccine perceptions and behaviours of at-risk groups. As such, public awareness campaigns conducted by the government and proactive endorsement from health physicians may help improve COVID-19 vaccination intention.

Background The coronavirus disease 2019 (COVID-19) pandemic has resulted in changes in lifestyle habits and experiences of mental health outcomes, some of which were possibly related to weight gain, leading to an increase in the prevalence of obesity, which is associated with the development of several severe diseases. Concerns regarding weight gain and its impact on health outcomes are prevalent worldwide, with obesity being one of the highest causes of mortality in current society. Methods A self-reported questionnaire collected data from participants aged 18 years of age and above from 26 countries and regions worldwide. Post-hoc multiple logistic regression analyses have been done to evaluate the association between demographic and socioeconomic factors, and the perspectives that were identified to be associated with weight gain. Results Participants belonging to a younger age group; with a higher level of education; living in an urban area; living with family members; employed full-time; and had obesity were found to be more vulnerable to weight gain. After adjusting for socio-demographic factors, participants who were quarantined; exercised less prior to the pandemic; consumed unhealthy foods; and reported negative thoughts such as helplessness and the perceived risk of COVID-19, were more likely to experience weight gain; while negative thoughts such as having no means of control over the COVID-19 pandemic and the consequences of the COVID-19 pandemic will have great personal effect were associated with females, students, and people living in the rural area. Conclusions Weight gain risk during the pandemic was significantly associated with certain socio-demographic and COVID-19 related factors. To improve public health outcomes, future research should conduct a longitudinal evaluation on the effects of COVID-19 experiences upon health choices. Streamlined mental support should also be provided to the vulnerable groups which were prone to negative thoughts that were associated with weight gain.