Exploring spatio-temporal characteristics of tourist travel behavior before and after COVID-19: A case study in Hong Kong, China

The COVID-2019 pandemic has a huge impact on tourism industry, and mastering the spatial and temporal characteristics of tourists' travel behavior during the period is very crucial for the recovery and the development of the tourism industry. This study adopts time series statistics and complex network analysis to compare and examine the network evolution features of Hong Kong before and during the COVID-19 pandemic based on the comments data generated from TripAdvisor website in 2019 and 2020. The results show that: (1) Tourists' travel behavior patterns have changed to a certain degree, and they prefer to visit a small number of destinations during an itinerary. (2) Key destinations still play important roles in connecting other destinations, but the tourism community formed around the key destinations has varied from extremely dense to relatively sparse gathering. (3) The number of tourists in extremely hot destinations has been greatly declined, those destinations with fewer tourists and relatively far away from the downtown have attracted more attention. Moreover, industrial destinations have been always the most popular type of tourism destination. © 2022, Science Press. All rights reserved.

Impact of COVID-19 on Tourists’ Travel Intentions and Behaviors: The Case Study of Hong Kong, China

Over the past two years, the COVID-19 pandemic had a major worldwide health, economic and daily life impact. Amongst many dramatic consequences, such as major human mobility disruptions at all scales, the tourism sector has been largely affected. This raises the need for the development of quantitative and qualitative research to favor a better understanding of the impact of the pandemic on human travel behaviors. This study introduces a computational approach that combines inference mechanisms and statistics to quantify tourists’ travel behaviors before and during the pandemic by exploring the evolution of the patterns extracted from a local tourism social network from 2019 to 2020 in the city of Hong Kong. The results show that the COVID-19 pandemic: 1) has a major influence on travel intentions that mainly swift from journeys with generally long sequences of attractions to rather single attractions;2) lead to a decline when considering connections between popular attractions, while the strength of connections within other attractions increase;3) generates novel patterns such as tourists preferring relaxing visits and even minor attractions. © 2022, Springer Nature Switzerland AG.

[Clinical characteristics and outcome of 64 patients with severe COVID-19].

Objective: To investigate the causes of death in patients with severe COVID-19. Methods: A retrospective analysis was performed on 64 patients with severe COVID-19 admitted to Wuhan Pulmonary Hospital from January 12, 2020 to February 28, 2020. There were 36 males and 28 females, aging from 44 to 85 years[median 68 (62, 72)]. Fifty-two patients (81%) had underlying comorbidities. The patients were divided into the death group (n=40) and the survival group (n=24) according to the treatment outcomes. In the death group, 24 were male, and 16 were female, aging from 49 to 85 years [median 69 (62, 72)], with 31 cases (78%) complicated with underlying diseases. In the survival group, there were 12 males and 12 females, aging from 44 to 82 years[median 66 (61,73)], with 21 cases (88%) with comorbidities. Clinical data of the two groups were collected and compared, including general information, laboratory examinations, imaging features and treatments. For normally distributed data, independent group t test was used; otherwise, Mann Whitney test was used to compare the variables. χ(2) test and Fisher exact test was used when analyzing categorical variables. Results: The median of creatine kinase isozyme (CK-MB) in the death group was 19.0 (17.0,23.0) U/L, which was higher than that in the survival group 16.5 (13.5,19.6) U/L. The median level of cTnI in the death group was 0.03 (0.03, 0.07) µg/L, which was significantly higher than that in the survival group (0.02, 0.03) µg/L, with a statistically significant difference between the two groups (P=0.007). The concentration of myoglobin in the death group was 79.5 (28.7, 189.0) µg/L, which was higher than 33.1 (25.7, 54.5) µg/L in the survival group. The level of D-dimer in the death group was 2.0 (0.6, 5.2) mg/L, which was higher than 0.7 (0.4, 2.0) mg/L in the survival group. The LDH level of the death group was 465.0 (337.5,606.5) U/L, which was higher than that of the survibal group, 341.0 (284.0,430.0) U/L, the difference being statistically significant (P=0.006). The concentration of alanine aminotransferase in the death group was 40.0 (30.0, 48.0) U/L, which was higher than 32.5 (24.0, 40.8) U/L in the survival group, and the difference was statistically significant (P=0.047).Abnormal ECG was found in 16 cases (62%) in the death group, which was significantly higher than that in the survival group (29%), the difference being statistically significant (P=0.024) .The main causes of death were severe pneumonia with acute respiratory distress syndrome (ARDS, n=20), acute heart failure(n=9), atrial fibrillation(n=3) and multiple organ dysfunction syndrome (MODS, n=3). Conclusions: ARDS caused by severe pneumonia and acute heart failure and atrial fibrillation caused by acute viral myocarditis were the main causes of death in severe COVID-19 patients. Early prevention of myocardial injury and treatment of acute viral myocarditis complicated with disease progression may provide insights into treatment and reduction of mortality in patients with severe COVID-19.

Clinical characteristics of COVID-19-infected cancer patients: a retrospective case study in three hospitals within Wuhan, China.

BACKGROUND: Cancer patients are regarded as a highly vulnerable group in the current Coronavirus Disease 2019 (COVID-19) pandemic. To date, the clinical characteristics of COVID-19-infected cancer patients remain largely unknown. PATIENTS AND METHODS: In this retrospective cohort study, we included cancer patients with laboratory-confirmed COVID-19 from three designated hospitals in Wuhan, China. Clinical data were collected from medical records from 13 January 2020 to 26 February 2020. Univariate and multivariate analyses were carried out to assess the risk factors associated with severe events defined as a condition requiring admission to an intensive care unit, the use of mechanical ventilation, or death. RESULTS: A total of 28 COVID-19-infected cancer patients were included; 17 (60.7%) patients were male. Median (interquartile range) age was 65.0 (56.0-70.0) years. Lung cancer was the most frequent cancer type (n = 7; 25.0%). Eight (28.6%) patients were suspected to have hospital-associated transmission. The following clinical features were shown in our cohort: fever (n = 23, 82.1%), dry cough (n = 22, 81%), and dyspnoea (n = 14, 50.0%), along with lymphopaenia (n = 23, 82.1%), high level of high-sensitivity C-reactive protein (n = 23, 82.1%), anaemia (n = 21, 75.0%), and hypoproteinaemia (n = 25, 89.3%). The common chest computed tomography (CT) findings were ground-glass opacity (n = 21, 75.0%) and patchy consolidation (n = 13, 46.3%). A total of 15 (53.6%) patients had severe events and the mortality rate was 28.6%. If the last antitumour treatment was within 14 days, it significantly increased the risk of developing severe events [hazard ratio (HR) = 4.079, 95% confidence interval (CI) 1.086-15.322, P = 0.037]. Furthermore, patchy consolidation on CT on admission was associated with a higher risk of developing severe events (HR = 5.438, 95% CI 1.498-19.748, P = 0.010). CONCLUSIONS: Cancer patients show deteriorating conditions and poor outcomes from the COVID-19 infection. It is recommended that cancer patients receiving antitumour treatments should have vigorous screening for COVID-19 infection and should avoid treatments causing immunosuppression or have their dosages decreased in case of COVID-19 coinfection.

[Management strategies for three patients with gynecological malignancies during the outbreak of COVID-19].

Objective: To explore the management strategies for patients with gynecological malignant tumors during the outbreak and transmission of COVID-19. Methods: We retrospectively analyzed the clinical characteristics, treatment, and disease outcomes of three patients with gynecological malignancies associated with COVID-19 in Renmin Hospital of Wuhan University, and proposed management strategies for patients with gynecological tumors underriskof COVID-19. Results: Based on the national diagnosis and treatment protocol as well as research progress for COVID-19, three patients with COVID-19 were treated. Meanwhile, they were also appropriately adjusted the treatment plan in accordance with the clinical guidelines for gynecological tumors. Pneumonia was cured in 2 patients, and one patient died of COVID-19. Conclusions: Patients with gynecological malignant tumors are high-risk groups prone to COVID-19, and gynecological oncologists need to carry out education, prevention, control and treatment according to specific conditions. While, actively preventing and controlling COVID-19, the diagnosis and treatment of gynecological malignant tumors should be carried out in an orderly and safe manner.