Health Tourism Evolution: A Review Based on Bibliometric Analysis and the China National Knowledge Infrastructure Database

To systematically understand the evolution of health tourism in China, the present study visually analyzes the theme evolution and frontiers of Chinese health tourism research on the basis of the China National Knowledge Infrastructure (CNKI) database through bibliometric analysis. The findings reflect the existence of diverse clustering themes in health tourism research, and the formation time of each theme is different. The findings also indicate that the change in the theme is led by government policy. Theoretically, the findings of the present study can, on the one hand, contribute to the health tourism literature by comprehensively exploring and summarizing the themes and topics of health tourism development in China since its appearance (i.e., 1981), and, on the other hand, provide references for future health tourism exploration directions. Findings of the present study can provide references for effective future development directions of the health tourism industry.

A Proposed DISE Approach for Tourist Destination Crisis Management

Novel coronavirus (COVID-19) has had a huge impact on the global tourism industry over the past couple of years. Most previous studies investigated tourism crises after the pandemic period. Hence, to minimize the research gap, the present study investigates the impact of COVID-19 on tourism during the pandemic period. By assessing this impact, this paper proposes a D (big data) I (impact module) S (strategy module) E (evaluation module) model to cope with the crisis in order to bring about feasible implications for tourism practitioners and governments. This paper is to provide real-time destination management adjustments. This model is based on a crisis management framework and governance theory through retrieving big data from China Unicom and major travel information delivery sources. The major finding shows that the detailed time points of pandemic information release in the early stage of crisis. In conclusion, through proposing a DISE model, the present study assesses the impact of the major emergency public health crisis, assists destination managers in adjusting tourism-related policy and reflects the priority of recovering tourism after the crisis for effective tourist destination management.

Perception, Reaction, and Future Development of the Influence of COVID-19 on the Hospitality and Tourism Industry in China.

The present study examined the perception, reaction (i.e., possible measures), and future development from the perspectives of hotel and tourism practitioners and experts to investigate the influence of coronavirus disease 2019 (i.e., COVID-19) on the hospitality and tourism industry in China. After conducting 58 in-depth interviews among hotel and tourism practitioners and experts, feasible and practical measures were proposed to reduce such influence and predict the future development of China's hospitality and tourism industry. Findings indicate that the influence of COVID-19 on the industry is perceived mainly through the pandemic's economic and social effects. Possible measures that can be adopted for the recovery of China's hospitality and tourism industry include the following aspects: government financial support, employee relationship management and electronic (e)-training, business marketing management, and industry co-operation network. A Perception-Reaction-Predication (PRP) crisis model is also proposed.

Abnormal Liver Function Tests Were Associated With Adverse Clinical Outcomes: An Observational Cohort Study of 2,912 Patients With COVID-19.

Background and Aim: The impact of liver function test (LFTs) abnormality on adverse clinical outcomes in coronavirus disease 2019 (COVID-19) patients remains controversial. The aim of this study was to assess the impact of abnormal LFTs on clinical outcomes in a large cohort of hospitalized patients with COVID-19. Methods: We retrospectively collected data on 2,912 consecutive patients with COVID-19 who were admitted to a makeshift hospital in China between 5 February and 23 March 2020. The association between LFTs abnormalities (baseline and peak values) and clinical outcomes was measured by using Cox regression models. Results: On admission 1,414 patients (48.6%) had abnormal LFTs, with alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), alkaline phosphatase (ALP), and gamma-glutamyltransferase (GGT) elevation in 662 (22.7%), 221 (7.6%), 52 (1.8%), 135 (4.6%), and 536 (18.5%) patients, respectively, and hypoalbuminemia in 737 (25.3%) patients. During a median 13 (IQR: 8-19) days of hospitalization, 61 patients (2.1%) died, 106 patients (3.6%) admitted to intensive care unit (ICU), and 75 patients (2.6%) required mechanical ventilation. After adjustment for confounders, baseline abnormal LFTs were independently associated with increased risks of mortality (adjusted HR 3.66, 95%CI 1.64-8.19, p = 0.002), ICU admission (adjusted HR 3.12 95%CI 1.86-5.23, p < 0.001), and mechanical ventilation (adjusted HR 3.00, 95%CI 1.63-5.52, p < 0.001), which was homogeneous across the severity of COVID-19 infection. Among the parameters of LTFs, the associations with the outcomes were more pronounced for AST and albumin abnormality. In contrast, ALT elevation was not significantly associated with those outcomes. Similar results were observed for peak values of LFTs during hospitalization. Conclusions: Abnormality of AST, albumin, TBIL, ALP, and GGT but not ALT were independently associated with adverse outcomes.