A pedestrian-based model for simulating COVID-19 transmission on college campus

Nowadays the integration of pedestrian dynamics and epidemiology is heating up due to the pandemic of COVID-19. In this paper, we introduce a pedestrian-based epidemic transmission model that combines cellular automata-based pedestrian dynamics with stochastic infection spread dynamics. Based on this model, we simulate COVID-19 transmission in different indoor scenarios on the college campus. We confirm that COVID-19 patients' infectivity during the incubation period and the presence of asymptomatic patients are key reasons for the difficulty in controlling the epidemic. Then, several non-pharmaceutical interventions at different operational levels are proposed and their effectiveness is evaluated by using computational models. We find that indoor-level interventions can slow the speed of disease transmission while quarantine can downsize the scale of disease transmission. And the combination of these two levels of intervention is superior to any single intervention in reducing the number of new infections.

The impact of COVID-19 on turnover intention among hotel employees: A moderated mediation model

This study examines the influence of COVID-19 event strength on the turnover intention of hotel employees by incorporating perceived operating performance and job insecurity as mediators and hotel size as a moderator. A moderated mediation model was employed to test the relationship between COVID-19 event strength and turnover intention. The study reveals that COVID-19 event strength might not significantly affect turnover intention through perceived operating performance, likely affecting job insecurity perception. We infer that such a finding might result from a series of policies implemented by authorities to prevent job insecurity perception of hotel employees during the COVID-19 pandemic. Furthermore, we also reveal that small- and middle-sized hotels mitigate the effect of job insecurity on turnover intention somewhat different from our expectations. We infer that most of the entrepreneurs and employees in such hotels are from the same town and unlikely to intensify the effect of job insecurity on turnover intention because of close friendships among them. This finding is closely related to cultural factors in China and has rarely been discussed in the existing literature. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Environment and COVID-19 incidence: A critical review

The coronavirus disease 2019 (COVID-19) pandemic is an unprecedented worldwide health crisis. Many previous research studies have found and investigated its links with one or some natural or human environmental factors. However, a review on the relationship between COVID-19 incidence and both the natural and human environment is still lacking. This review summarizes the inter-correlation between COVID-19 incidence and environmental factors. Based on keyword searching, we reviewed 100 relevant peer-reviewed articles and other research literature published since January 2020. This review is focused on three main findings. One, we found that individual environmental factors have impacts on COVID-19 incidence, but with spatial heterogeneity and uncertainty. Two, environmental factors exert interactive effects on COVID-19 incidence. In particular, the interactions of natural factors can affect COVID-19 transmission in micro- and macro- ways by impacting SARS-CoV-2 survival, as well as human mobility and behaviors. Three, the impact of COVID-19 incidence on the environment lies in the fact that COVID-19-induced lockdowns caused air quality improvement, wildlife shifts and socio-economic depression. The additional value of this review is that we recommend future research perspectives and adaptation strategies regarding the interactions of the environment and COVID-19. Future research should be extended to cover both the effects of the environment on the COVID-19 pandemic and COVID-19-induced impacts on the environment. Future adaptation strategies should focus on sustainable environmental and public policy responses.

Identification of Cell Types and Transcriptome Landscapes of Porcine Epidemic Diarrhea Virus-Infected Porcine Small Intestine Using Single-Cell RNA Sequencing.

Swine coronavirus-porcine epidemic diarrhea virus (PEDV) with specific susceptibility to pigs has existed for decades, and recurrent epidemics caused by mutant strains have swept the world again since 2010. In this study, single-cell RNA sequencing was used to perform for the first time, to our knowledge, a systematic analysis of pig jejunum infected with PEDV. Pig intestinal cell types were identified by representative markers and identified a new tuft cell marker, DNAH11. Excepting enterocyte cells, the goblet and tuft cells confirmed susceptibility to PEDV. Enrichment analyses showed that PEDV infection resulted in upregulation of cell apoptosis, junctions, and the MAPK signaling pathway and downregulation of oxidative phosphorylation in intestinal epithelial cell types. The T cell differentiation and IgA production were decreased in T and B cells, respectively. Cytokine gene analyses revealed that PEDV infection downregulated CXCL8, CXCL16, and IL34 in tuft cells and upregulated IL22 in Th17 cells. Further studies found that infection of goblet cells with PEDV decreased the expression of MUC2, as well as other mucin components. Moreover, the antimicrobial peptide REG3G was obviously upregulated through the IL33-STAT3 signaling pathway in enterocyte cells in the PEDV-infected group, and REG3G inhibited the PEDV replication. Finally, enterocyte cells expressed almost all coronavirus entry factors, and PEDV infection caused significant upregulation of the coronavirus receptor ACE2 in enterocyte cells. In summary, this study systematically investigated the responses of different cell types in the jejunum of piglets after PEDV infection, which deepened the understanding of viral pathogenesis.

Using Shannon Entropy to Improve the Identification of MP-SBM Models with Undesirable Output.

In the context of the COVID-19 global epidemic, it is particularly important to use limited medical resources to improve the systemic control of infectious diseases. There is a situation where a shortage of medical resources and an uneven distribution of resources in China exist. Therefore, it is important to have an accurate understanding of the current status of the healthcare system in China and to improve the efficiency of their infectious disease control methods. In this study, the MP-SBM-Shannon entropy model (modified panel slacks-based measure Shannon entropy model) was proposed and applied to measure the disposal efficiency of the medical institutions responding to public health emergencies (disposal efficiency) in China from 2012 to 2018. First, a P-SBM (panel slacks-based measure) model, with undesirable outputs based on panel data, is given in this paper. This model measures the efficiency of all DMUs based on the same technical frontier and can be used for the dynamic efficiency analysis of panel data. Then, the MP-SBM model is applied to solve the specific efficiency paradox of the P-SBM model caused by the objective data structure. Finally, based on the MP-SBM model, undesirable outputs are considered in the original efficiency matrix alignment combination for the deficiencies of the existing Shannon entropy-DEA model. The comparative analysis shows that the MP-SBM-Shannon model not only solves the problem of the efficiency paradox of the P-SBM model but also improves the MP-SBM model identification ability and provides a complete ranking with certain advantages. The results of the study show that the disposal efficiency of the medical institutions responding to public health emergencies in China shows an upward trend, but the average combined efficiency is less than 0.47. Therefore, there is still much room for improvement in the efficiency of infectious disease prevention and control in China. It is found that the staffing problem within the Center for Disease Control and the health supervision office are two stumbling blocks.

Has COVID-19 increased the intention to undertake health tourism? Examination using a conditional process model

As the major public health emergency with the fastest spread, the greatest range, and the most difficulty in controlling recently, COVID-19 has created a huge shock and exerted an impact on public physical and mental health. Health tourism is an effective way of alleviating the general public's physical and mental health. Thus, it is necessary to examine the event strength of COVID-19 with respect to the willingness to undertake health tourism. Such research into tourists' behavior following the spread of COVID-19 could help identify potential areas of development for the tourism industry in the period of the pandemic under normal control. Many studies have investigated the negative shock and impact of COVID-19. However, little research has focused on behavioral responses in that regard. Hitherto, studies have ignored development opportunities in the tourism industry following COVID-19. By applying the stimulus-organism-response (SOR) model and event system theory, we conducted a survey among 313 participants by means of an online questionnaire. Using the structural equation modeling technique, we aimed to identify the effect of recognizing the event strength of COVID-19 (novelty recognition, disruption recognition, criticality recognition) on the intention to undertake health tourism;we did so by taking into account the mediating role of risk perception and moderating role of risk communication. We obtained the following findings. (1) The novelty recognition of the event strength of COVID-19 tended to decrease the willingness to undertake health tourism;disruption recognition did not affect that intention. However, criticality recognition did increase such willingness.(2) Novelty recognition exerted a negative impact on risk perception;criticality and disruption recognition positively improved risk perception. (3) Novelty and criticality recognition indirectly affected the intention to undertake health tourism through the partial mediating effect of risk perception. Disruption recognition indirectly affected such intention through the mediating role of risk perception.(4) Risk communication did not directly promote the intention to undertake health tourism, but it did moderate the impact of risk perception with respect to such intention. Thus, releasing more risk information makes the public more aware of health matters, which increases the intention to undertake health tourism. This study makes an important contribution to research and tourism management. First, we constructed and empirically examined a conceptual framework using the SOR model: it provided a good theoretical framework to analyze the mechanism between recognition of event strength and the intention to undertake health tourism;it broadens the application possibilities of the SOR model. Second, we clarified practical means for developing the tourism industry in the period of the pandemic under normal control;examples here are the wellness tourism industry promoting the planning and design of wellness tourism products as well as increasing investment in safety and sanitation. Such measures could also help improve risk communication, raise public awareness of risk and wellness, and promote wellness tourism.

Diffusion Characteristics and Driving Factors of the Smart Tourism City Policy—Event History Analysis

It is of great significance to explore the spatial-temporal characteristics and analyze the driving factors of the diffusion of smart tourism city policy, which promotes the adoption of smart tourism city policy and the sustainable development of tourism. We aimed to explore the diffusion law and influencing factors of smart tourism city so as to provide reference for the construction of smart tourism city. By employing the 249 cases in China from 2012 to 2019, we revealed the spatial-temporal characteristics and driving factors influencing the diffusion of smart tourism city policy by employing the event history analysis method. The results reveal that the diffusion of smart tourism city policy presents the typical S-shaped curve in cumulative adoptions over time. Furthermore, the diffusion of smart tourism city policy presents the spatial distribution characteristic of the Hu Line, which spreads from the eastern coastal areas to the central inland areas. Moreover, there are multiple driving sources for the diffusion of smart tourism city policy, among which economic lift force, intellectual support force, technological pull force and demand impetus force are the important driving sources for the policy diffusion.

The impact of COVID-19 on turnover intention among hotel employees: A moderated mediation model

This study examines the influence of COVID-19 event strength on the turnover intention of hotel employees by incorporating perceived operating performance and job insecurity as mediators and hotel size as a moderator. A moderated mediation model was employed to test the relationship between COVID-19 event strength and turnover intention. The study reveals that COVID-19 event strength might not significantly affect turnover intention through perceived operating performance, likely affecting job insecurity perception. We infer that such a finding might result from a series of policies implemented by authorities to prevent job insecurity perception of hotel employees during the COVID-19 pandemic. Furthermore, we also reveal that small- and middle-sized hotels mitigate the effect of job insecurity on turnover intention somewhat different from our expectations. We infer that most of the entrepreneurs and employees in such hotels are from the same town and unlikely to intensify the effect of job insecurity on turnover intention because of close friendships among them. This finding is closely related to cultural factors in China and has rarely been discussed in the existing literature.

Environment and COVID-19 incidence: A critical review

The coronavirus disease 2019 (COVID-19) pandemic is an unprecedented worldwide health crisis. Many previous research studies have found and investigated its links with one or some natural or human environmental factors. However, a review on the relationship between COVID-19 incidence and both the natural and human environment is still lacking. This review summarizes the inter-correlation between COVID-19 incidence and environmental factors. Based on keyword searching, we reviewed 99 relevant peer-reviewed articles and other research literature published since January 2020. This review is focused on three main findings. One, we found that individual environmental factors have impacts on COVID-19 incidence, but with spatial heterogeneity and uncertainty. Two, environmental factors exert interactive effects on COVID-19 incidence. In particular, the interactions of natural factors can affect COVID-19 transmission in micro- and macro- ways by impacting SARS-CoV-2 survival, as well as human mobility and behaviors. Three, the impact of COVID-19 incidence on the environment lies in the fact that COVID-19-induced lockdowns caused air quality improvement, wildlife shifts and socio-economic depression. The additional value of this review is that we recommend future research perspectives and adaptation strategies regarding the interactions of the environment and COVID-19. Future research should be extended to cover both the effects of the environment on the COVID-19 pandemic and COVID-19-induced impacts on the environment. Future adaptation strategies should focus on sustainable environmental and public policy responses.

The impact of geo-environmental factors on global COVID-19 transmission: A review of evidence and methodology.

Studies on Coronavirus Disease 2019 (COVID-19) transmission indicate that geo-environmental factors have played a significant role in the global pandemic. However, there has not been a systematic review on the impact of geo-environmental factors on global COVID-19 transmission in the context of geography. As such, we reviewed 49 well-chosen studies to reveal the impact of geo-environmental factors (including the natural environment and human activity) on global COVID-19 transmission, and to inform critical intervention strategies that could mitigate the worldwide effects of the pandemic. Existing studies frequently mention the impact of climate factors (e.g., temperature and humidity); in contrast, a more decisive influence can be achieved by human activity, including human mobility, health factors, and non-pharmaceutical interventions (NPIs). The above results exhibit distinct spatiotemporal heterogeneity. The related analytical methodology consists of sensitivity analysis, mathematical modeling, and risk analysis. For future studies, we recommend highlighting geo-environmental interactions, developing geographically statistical models for multiple waves of the pandemic, and investigating NPIs and care patterns. We also propose four implications for practice to combat global COVID-19 transmission.

COVID-19 and credit risk: A long memory perspective.

The COVID-19 pandemic shows significant impacts on credit risk, which is the key concern of corporate bond holders such as insurance companies. Credit risk, quantified by agency credit ratings and credit default swaps (CDS), usually exhibits long-range dependence (LRD) due to potential credit rating persistence. With rescaled range analysis and a novel affine forward intensity model embracing a flexible range of Hurst parameters, our studies on Moody's rating data and CDS prices reveal that default intensities have shifted from the long-range to the short-range dependence regime during the COVID-19 period, implying that the historical credit performance becomes much less relevant for credit prediction during the pandemic. This phenomenon contrasts sharply with previous financial-related crises. Specifically, both the 2008 subprime mortgage and the Eurozone crises did not experience such a great decline in the level of LRD in sovereign CDS. Our work also sheds light on the use of historical series in credit risk prediction for insurers' investment.

The effects of community safety support on COVID-19 event strength perception, risk perception, and health tourism intention: The moderating role of risk communication.

The community is crucial in preventing COVID-19 pandemic. By employing 313 online surveys, it is found that the community safety support enhances risk perception, disruption recognition, and criticality recognition but it negatively impacts on novelty recognition. Additionally, risk communication could moderate the relationship between risk perception and health tourism intention. These findings reveal that people would pay more attention to the risk information and they could join health tourism in the post-pandemic period to enhance their personal physical and mental health. Therefore, health tourism enterprises should appropriately strengthen risk communication and improve people's health awareness to further promote healthy tourism consumption.

Coronary microvascular dysfunction pathophysiology in COVID-19.

Recently, accumulating evidence has highlighted the role of endothelial dysfunction in COVID-19 progression. Coronary microvascular dysfunction (CMD) plays a pivotal role in cardiovascular disease (CVD) and CVD-related risk factors (eg, age, gender, hypertension, diabetes mellitus, and obesity). Equally, these are also risk factors for COVID-19. The purpose of this review was to explore CMD pathophysiology in COVID-19, based on recent evidence. COVID-19 mechanisms were reviewed in terms of imbalanced renin-angiotensin-aldosterone-systems (RAAS), systemic inflammation and immune responses, endothelial dysfunction, and coagulatory disorders. Based on these mechanisms, we addressed CMD pathophysiology within the context of COVID-19, from five perspectives. The first was the disarrangement of local RAAS and Kallikrein-kinin-systems attributable to SARS-Cov-2 entry, and the concomitant decrease in coronary microvascular endothelial angiotensin I converting enzyme 2 (ACE2) levels. The second was related to coronary microvascular obstruction, induced by COVID-19-associated systemic hyper-inflammation and pro-thrombotic state. The third was focused on how pneumonia/acute respiratory distress syndrome (ARDS)-related systemic hypoxia elicited oxidative stress in coronary microvessels and cardiac sympathetic nerve activation. Fourthly, we discussed how autonomic nerve dysfunction mediated by COVID-19-associated mental, physical, or physiological factors could elicit changes in coronary blood flow, resulting in CMD in COVID-19 patients. Finally, we analyzed reciprocity between the coronary microvascular endothelium and perivascular cellular structures due to viremia, SARS-CoV-2 dissemination, and systemic inflammation. These mechanisms may function either consecutively or intermittently, finally culminating in CMD-mediated cardiovascular symptoms in COVID-19 patients. However, the underlying molecular pathogenesis remains to be clarified.

Effect of the event strength of the coronavirus disease (COVID-19) on potential online organic agricultural product consumption and rural health tourism opportunities.

The coronavirus disease (COVID-19) outbreak has raised consumer concerns about health. By employing 306 online questionnaires, we identify COVID-19's effect on online organic agriculture product consumption and rural health tourism intention based on stimulus-organism-response theory and event system theory by incorporating risk information disclosure of COVID-19 as the moderating variable and health consciousness and risk perception as the mediating variables. These findings suggest that considering the impact of COVID-19 can help focus the production and online sales of organic agricultural products, the establishment and improvement of rural health facilities, and the marketing of rural health tourism.

The Relationship between Nature Deprivation and Individual Wellbeing across Urban Gradients under COVID-19.

Lockdown aiming at slowing COVID-19 transmission has altered nature accessibility patterns, creating quasi-experimental conditions to assess if retracted nature contact and perceived nature deprivation influence physical and emotional wellbeing. We measure through on-line survey methods (n = 529) how pandemic mandates limiting personal movement and outdoor nature access within the United States affect self-assessed nature exposure, perceived nature deprivation, and subsequent flourishing as measured by the Harvard Flourishing Index. Results indicate that perceived nature deprivation strongly associates with local nature contact, time in nature, and access to municipal nature during the pandemic, after controlling for lockdown mandates, job status, household composition, and sociodemographic variables. Our hypothesis is that individuals with strong perceived nature deprivation under COVID-19 leads to diminished wellbeing proved true. Interaction models of flourishing showed positive modification of nature affinity with age and qualitative modification of nature deprivation with race. Our results demonstrate the potential of local nature contact to support individual wellbeing in a background context of emotional distress and social isolation, important in guiding public health policies beyond pandemics.

Monitoring Crop Growth During the Period of the Rapid Spread of COVID-19 in China by Remote Sensing.

The status of crop growth under the influence of COVID-19 is an important information for evaluating the current food security in China. This article used the cloud computing platform of Google Earth Engine, to access and analyze Sentinel-2, MODIS, and other multisource remote sensing data in the last five years to monitor the growth of crops in China, especially in Hubei province, during the period of the rapid spread of COVID-19 (i.e., from late January to mid-March 2020), and compared with the growth over the same period under similar climate conditions in the past four years. We further analyzed the indirect effects of COVID-19 on crop growth. The results showed that: the area of the crops with better growth (51%) was much more than that with worse growth (22%); the crops with better and worse growth were mainly distributed in the North China Plain (the main planting areas of winter wheat in China) and the South China regions (such as Guangxi, Guangdong province), respectively. The area of the crops with a similar growth occupied 27%. In Hubei province, the area of the crops with better growth (61%) was also more than that with worse growth (27%). It was found that there was no obvious effect from COVID-19 on the overall growth of crops in China during the period from late January to mid-March 2020 and the growth of crops was much better than that during the same period in previous years. The findings in this study are helpful in evaluating the impact of the COVID-19 on China's agriculture, which are conducive to serve the relevant agricultural policy formulation and to ensure food security.

Natural and human environment interactively drive spread pattern of COVID-19: A city-level modeling study in China.

A novel Coronavirus COVID-19 has caused high morbidity and mortality in China and worldwide. A few studies have explored the impact of climate change or human activity on the disease incidence in China or a city. The integrated study concerning environment impact on the emerging disease is rarely reported. Therefore, based on the two-stage modeling study, we investigate the effect of both natural and human environment on COVID-19 incidence at a city level. Besides, the interactive effect of different factors on COVID-19 incidence is analyzed using Geodetector; the impact of effective factors and interaction terms on COVID-19 is simulated with Geographically Weighted Regression (GWR) models. The results find that mean temperature (MeanT), destination proportion in population flow from Wuhan (WH), migration scale (MS), and WH*MeanT, are generally promoting for COVID-19 incidence before Wuhan's shutdown (T1); the WH and MeanT play a determinant role in the disease spread in T1. The effect of environment on COVID-19 incidence after Wuhan's shutdown (T2) includes more factors (including mean DEM, relative humidity, precipitation (Pre), travel intensity within a city (TC), and their interactive terms) than T1, and their effect shows distinct spatial heterogeneity. Interestingly, the dividing line of positive-negative effect of MeanT and Pre on COVID-19 incidence is 8.5°C and 1 mm, respectively. In T2, WH has weak impact, but the MS has the strongest effect. The COVID-19 incidence in T2 without quarantine is also modeled using the developed GWR model, and the modeled incidence shows an obvious increase for 75.6% cities compared with reported incidence in T2 especially for some mega cities. This evidences national quarantine and traffic control take determinant role in controlling the disease spread. The study indicates that both natural environment and human factors integratedly affect the spread pattern of COVID-19 in China.

Lian Hua Qing Wen Capsules, a Potent Epithelial Protector in Acute Lung Injury Model, Block Proapoptotic Communication Between Macrophages, and Alveolar Epithelial Cells.

Besides pathogen evading, Acute Lung Injury (ALI), featuring the systematic inflammation and severe epithelial damages, is widely believed to be the central non-infectious factor controlling the progression of infectious diseases. ALI is partly caused by host immune responses. Under the inspiration of unsuccessful treatment in COVID-19, recent insights into pathogen-host interactions are leading to identification and development of a wide range of host-directed therapies with different mechanisms of action. The interaction unit consisting of macrophages and the alveolar epithelial cells has recently revealed as the therapeutic basis targeting ALI. Lian Hua Qing Wen capsule is the most effective and commonly-used clinical formula in treating respiratory infection for thousands of years in China. However, little is known about its relevance with ALI, especially its protective role against ALI-induced alveolar tissue damages. Aiming to evaluate its contribution in antibiotics-integrating therapies, this study pharmacologically verified whether LHQW could alleviate lipopolysaccharide (LPS)-induced ALI and explore its potential mechanisms in maintaining the physiology of macrophage-epithelial unit. In ALI mouse model, the pathological parameters, including the anal temperature, inflammation condition, lung edema, histopathological structures, have all been systematically analyzed. Results consistently supported the effectiveness of the combined strategy for LHQW and low-dose antibiotics. Furthermore, we established the macrophages-alveolar epithelial cells co-culture model and firstly proved that LHQW inhibited LPS-induced ER stress and TRAIL secretion in macrophages, thereby efficiently protected epithelial cells against TRAIL-induced apoptosis. Mechanistically, results showed that LHQW significantly deactivated NF-κB and reversed the SOCS3 expression in inflammatory macrophages. Furthermore, we proved that the therapeutic effects of LHQW were highly dependent on JNK-AP1 regulation. In conclusion, our data proved that LHQW is an epithelial protector in ALI, implying its promising potential in antibiotic alternative therapy.

Critically ill patients with COVID-19 with ECMO and artificial liver plasma exchange: A retrospective study.

COVID-19 is an emerging infectious disease capable of causing severe pneumonia. We aimed to characterize a group of critically ill patients in a single-center study.This was a retrospective case series of 23 patients with confirmed COVID-19-related critical illness in the intensive care unit (ICU) of a hospital in Hangzhou Zhejiang Province between January 22 and March 20, 2020.Of the 23 critically ill patients, the median age was 66 years (interquartile range [IQR] 59-80 years). The median time from disease onset to ICU admission was 10 days (IQR 6-11 days), to mechanical ventilation (MV) was 11 days (IQR 7.75-13 days), to artificial liver plasma exchange was 12 days (IQR 9.75-14.75 days), and to extracorporeal membrane oxygenation (ECMO) was 22 days (IQR 17.5-30 days). Nine patients required high flow oxygen. Fourteen patients received MV. Six required ECMO. Nine received artificial liver plasma exchange. Mortality was 0 at day 28.Mortality was 0 at day 28 in our single-center study. Extracorporeal membrane oxygenation reduced the requirements for ventilator support. Artificial liver plasma exchange significantly reduced inflammatory cytokine levels. These supportive therapies helped to extend the patients' survival times and increase the chance of follow-up treatments.