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We propose a new strategy for analyzing the evolution of random phenomena over time and space simultaneously based on the high-order multivariate Markov chains. We develop a novel Markov model of order r for m chains consisting of s possible states to gather parsimony with realism. It can capture negative and positive associations among the chains with only a reduced number of parameters, rm2s2+2, remarkably lower than msrm+1 required for the full parameterized model. Our model privileges are enhanced by a Monte Carlo simulation experiment, besides application to analyze the spatial-temporal dynamics for the risk level of a recently global pandemic (COVID-19) outbreak in world health organization (WHO) regions for predicting the risk state of epidemiological prevalence and monitoring infection control.
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Officially named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), COVID-19 was first reported in Wuhan, China, at the end of 2019. By February 2020, Mexico had registered its first confirmed case, and by March, its first death. This chapter examines the spatial and temporal patterns of COVID-19 cumulative deaths in Mexico by municipio and analyzes the spatio-temporal distribution and shifting trends of deaths. The analysis was based on a space-time cube with publicly available data from February 3, 2020, through February 8, 2021. The analysis shows the impact of population density and isolation on COVID-19 cumulative deaths in Mexico. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
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Background: Socioeconomic conditions affect the dynamics of the Covid-19 pandemic. We analysed the association between area-level socioeconomic deprivation, proportion of non-nationals, and incidence of Covid-19 infections in Germany. Methods: Using linked nationally representative data at the level of 401 German districts from three waves of infection (January-2020 to May-2021), we fitted Bayesian spatiotemporal models to assess the association between socioeconomic deprivation, and proportion of non-nationals with Covid-19 incidence, controlling for age, sex, vaccination coverage, settlement structure, and spatial and temporal effects. We estimated risk ratios (RR) and corresponding 95% credible intervals (95% CrI). We further examined the deprivation domains (education, income, occupation), interactions between deprivation, sex and the proportion of non-nationals, and explored potential pathways from deprivation to Covid-19 incidence. Findings: Covid-19 incidence risk was 15% higher (RR=1·15, 95%-CrI=1·06-1·24) in areas classified with the highest deprivation quintile (Q5) compared to the least deprived areas (Q1). Medium-low (Q2), medium (Q3), and medium-high (Q4) deprived districts showed 6% (1·06, 1·00-1·12), 8% (1·08, 1·01-1·15), and 5% (1·05, 0·98-1·13) higher risk, respectively, compared to the least deprived. Districts with higher proportion of non-nationals showed higher incidence risk compared to districts with lowest proportion, but the association weakened across the three waves. During the first wave, an inverse association was observed with highest incidence risk in least deprived areas (Q1). Deprivation interacted with sex, but not with the proportion of non-nationals. Interpretation: Socioeconomic deprivation, and proportion of non-nationals are independently associated with the incidence of Covid-19. Regional planning of non-pharmaceutical interventions and vaccination strategies would benefit from consideration of area-level deprivation and non-national residency. Funding: The study was funded by the German Ministry of Health (ZMV I 1 - 25 20 COR 410).
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COVID-19 pandemic which the first outbreak was found on December 2019 in Wuhan, China, has given great impact to tourism industries worldwide. Since then, most countries implemented lockdown and quarantine system, issued tight regulations about travel restriction. In order to survive the COVID-19 pandemic, which the ending has yet to be determined, every tourism industry must be able to work efficiently to maintain the usage of operating costs as low as possible since the revenue could not be optimized. This research aims to measure efficiency score of 41 companies in Tourism and Recreation Industry (code E51) listed on Indonesia Stock Exchange (IDX) from 2018 to 2021. At the first stage, data envelopment analysis (DEA) method with variable-return-to-scale (VRS) input-oriented approach is employed to estimate technical efficiency scores. At the second stage, left-truncated regression estimation with double-bootstrap is employed to test the significance of some explanatory factors. Cost of Sales and Revenue, Operating expenses, Interest expenses, and Fixed Assets are chosen as input variables, while Sales and Revenue, Profit (Loss) from Operation, and Asset Turnover Ratio as output variables of DEA. The result shows that efficiency score dropped by 20.42% in 2020 compared to the score in 2019. A slight increase of 2.39% in 2021 compared to the score in 2020. Another result also denotes that several explanatory factors such as Stock Price positively affected efficiency score of, meanwhile Liability to Asset Ratio gave negative influences. Finally, this research may contribute to the development of operation and management science in hospitality and tourism field as well as to support the business operators to adjust their strategic plans, especially in financial budgeting, to face the long-impact of COVID-19 pandemic. Efficiency measurement using advanced DEA Double Bootstrap method with selected financial parameters that are different from any previous studies in tourism provides novelty to this research. © 2023 WITPress. All rights reserved.
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Due to the rapid advancement of digital technology and its contribution to sustainable development, digital literacy has become an increasingly significant research topic. However, the uneven distribution of new technologies has caused emerging inequalities, which have been exacerbated by the COVID-19 pandemic, one of the most significant public health crises of the century. This paper aims to conduct an in-depth analysis of scientific production using bibliometric methods to comprehend the current research status of digital literacy studies and evaluate the pandemic's impact on such research. In total, 7523 documents published between 1990 and 2022 were identified and analyzed using bibliometric research methods in the Web of Science database. These methods included growth trend analysis, network analysis, highly cited literature analysis, factor analysis, and time-series-based analysis of frequently discussed topics. Additionally, a word cloud analysis of the keywords in digital literacy literature from 2020 to 2022, during the COVID-19 pandemic, was created. The study's outcomes explore digital literacy research, including current trends, significant publications, and institutions involved in the field. This study emphasizes the importance of digital literacy in today's society, particularly during the COVID-19 pandemic. It also highlights the potential of bibliometric analysis as a tool for identifying research gaps. © 2023 by the authors.
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The Covid-19 epidemic led to loss of the lives of many people in the world and had a very negative impact on the mental and physical health of humans. One of the effective ways to preventive strategies regarding is to study the impact of climatic parameters. This research introduces a new spatiotemporal methodology to explore the association between Covid-19 and hourly data of weather. This methodology developed based on machine learning using unsupervised clustering method. Six counties considered for finding association and the cities that have similar climatic temporal changes clustered and compared with cities that have similar number of Covid-19 cases. For this goal, a new model is developed for finding similarities between clusters, which indicates the association between weather and Covid-19. The result shows similarities are about 57% for wind speed, 63% for temperature, 63% for surface pressure, and 42% for elevation. Then result evaluated sing Kendall's tau_b and Spearman's rho which shows the proposed methodology has an acceptable result. © 2023, The Author(s), under exclusive licence to Korea Spatial Information Society.
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This study aims to present the impact of disasters, such as the COVID-19 pandemic, on the possibility of recovering from and mitigating such impacts. The paper proposes a new emergency planning and disaster recovery management model (EPDRM) which links the ISO 31000:2018 (Risk Management) requirements with the process approach. The model was validated through its application to ISO-certified and ISO-non-certified hotels. The analysis was performed by using an online questionnaire based on the ISO 31000:2018 requirements, where given questions were grouped into 14 categories and presented according to the PDCA (Plan-Do-Check-Act) cycle. The proposed methodology has not been used by other researchers for similar problems. Current results are especially important, because they were collected after the lockdown that had a significant impact on hospitality and tourism in the world. This paper discusses the effect of hotel properties (such as size, certification, and categorization) on the implementation level of the emergency planning and disaster recovery management model. This survey was conducted in 109 hotels in Serbia. The results show that the average level of application was 35.80%. The survey also points to the development possibilities of alternative tourisms in response to COVID-19, and whether the hotel facilities were suitable for such changes in times of increased uncertainty. The results represent the basis of scientific data for improving the national policy, especially during the recovery from a disaster such as COVID-19, as well as emergency planning activities during the pandemic. The study limitations can be identified in the small research sample and insufficient cooperation of contacted hotels as well as the willingness of hotels' managements to participate in the study. The hotels' managers should be aware of the implementation of emergency planning measures, and without their willingness, this cannot be achieved at any level. © 2023 by the authors.
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Many public health organizations worldwide have used E-auctions to monitor, curtail, and improve the transmission of new coronavirus illnesses. However, user population size and acceptance of these technologies significantly impact their effectiveness. The current study's goal was to determine what factors influence customers' intent to use COVID-19 E-auctions by employing the Technology Acceptance Model (TAM) to the Jordanian setting. This study empirically assessed 310 Jordanian respondents using a quantitative approach known as Structural Equation Modeling (SEM). The research findings supported the majority of the proposed hypotheses, showing that behavioral intentions to use electronic bidding are highly influenced by perceived usability, perceived usefulness, trust in the government, social influence, and awareness. This research paper eventually contributes to the field of technology acceptance by developing a context-driven approach to the key pandemic components and features that influence different practices of technology acceptance. © 2023 by the authors.
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The increase in home improvement activity during the COVID-19 pandemic gave rise to concerns of increased asbestos exposure risk. This paper describes high-risk asbestos exposure groups based on current home improvement trends in Australia. A series of quantitative and qualitative studies were commissioned to better understand the attitudes, motivations, and behaviours of home improvers in Australia. In 2021, two in three Australian adults were inclined to undertake home improvement projects—big or small—with or without professional help, underscoring the importance of improving the asbestos safety knowledge and capacity of this cohort. The studies commissioned across 2020 and 2021 provide a deep analysis into this cohort, defining who they are and the segments that make up home improvers, their behaviours, and their asbestos awareness and attitudes. This knowledge enables the development and implementation of a range of targeted campaigns to increase asbestos awareness and prevent potential exposure to asbestos fibres. © 2023 by the authors.
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The pandemic has significantly affected the tourism sector worldwide;however, craftswomen are a vulnerable group that has been affected economically by this crisis. This research evaluated the level of compliance with preventive measures before and after carrying out the virtual educational intervention for craftswomen working with native cotton in the Lambayeque Region, Peru. The methodology applied was a pilot study, quasi-experimental, without a control group. The population consisted of 30 craftswomen from the populated areas of La Raya–Túcume, Pómac III-Pitipo and Jotoro-Jayanca. SPSS Statistics v25 was used for data processing. The χ2 test was used in order to evaluate the variation before and after the intervention. The correlational findings demonstrate that after applying the virtual educational intervention, it is sufficient to apply specific measures in the first (before) and second stage (during) to obtain a higher result in compliance with the general level of the regulations against COVID-19. It is concluded that the virtual educational intervention for the craftswomen has generated awareness, impacting the care of their personal health, their family and their community, as well as being prepared for the reactivation of tourism. © 2023 by the authors.
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CONTEXT: Imperial Valley, California is called ‘America's winter salad bowl' as the agricultural sector produces 2/3 of the winter vegetables eaten in the U.S. However, there is little understanding of the interplay of policy, environmental conditions, and economic components of the agricultural system producers face in the valley. OBJECTIVE: Using a resilience approach, this study asks the research question of how producers in the Imperial Valley perceive and are adapting to changing conditions. METHODS: Through interviews with eight agricultural producers, this paper identifies current challenges and strategies producers employ to navigate a changing agricultural system and build resilience for the future. RESULTS AND CONCLUSIONS: Results highlight the critical role of government policies in the establishment of agriculture in the Valley, while producers see recent policies, such as labor and food safety regulations, as increasing their operation costs. Producers face economic challenges including losing contracts to Mexico, market price fluctuations, land leasing, and the COVID-19 pandemic. Maintaining access to water resources and investing in mechanization and technological innovations are two strategies producers use to maintain resilience and navigate change. SIGNIFICANCE: Understanding how producers remain resilient given ongoing, and often accelerating, political, environmental, and economic change is critical to maintain agricultural systems in California and beyond. © 2023 The Author
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In response to the COVID-19 pandemic in early 2020, Sri Lanka underwent a nationwide lockdown that limited motor vehicle movement, industrial operations, and human activities. This study analyzes the impact of COVID-19 lockdown on carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter (PM10, PM2.5) concentrations in two urban cities (Colombo and Kandy) in Sri Lanka, by comparison of data from the lockdown period (March to May 2020) with its analogous period of 2019 and 2021. The results showed that the percentage change of daytime PM10, PM2.5, CO, and NO2 concentration during the lockdown in Colombo (Kandy) is –42.3% (–39.5%), –46% (–54.2%), –14.7% (–8.8%) and –82.2% (–80.9%), respectively. In both cities, the response of NO2 to the lockdown was the most sensitive. In contrast, daytime O3 concentration in Colombo (Kandy) has increased by 6.7% (27.2%), suggesting that the increase in O3 concentration was mainly due to a reduction in NOx emissions leading to lower O3 titration by NO. In addition, daytime SO2 concentration in Colombo has increased by 22.9%, while daytime SO2 concentration in Kandy has decreased by –40%. During the lockdown period, human activities were significantly reduced, causing significant reductions in industrial operations and transportation activities, further reducing emissions and improving air quality in two cities. The results of this study offer potential for local authorities to better understand the emission sources, assess the effectiveness of current air pollution control strategies, and form a basis for formulating better environmental policies to improve air quality and human health. © The Author(s).
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Informal settlements house millions of poor urban dwellers in developing countries. Although many studies have been conducted on urban poverty in other developing countries, there has been little research conducted in Myanmar. The country was isolated from the rest of the world for many decades and only reopened its doors in 2011, so there is insufficient data for social policy makers. There have been some studies on the informal settlements in Yangon, but these are qualitative and focus on issues in specific settlements;therefore, there is academic space to explore the Yangon slums in their totality to assess their socio-economic conditions quantitatively. This study aimed to provide quantitative analyses of the socio-economic conditions of Yangon informal settlements, particularly regarding their variations in terms of formation according to the timeline of Myanmar's political regimes. The results indicate that the main socio-economic conditions of Yangon's slums differ depending on the time of settlement. © 2023 Elsevier Ltd
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Exploratory data analysis tools designed to measure global and local spatial autocorrelation (e.g. Moran's (Formula presented.) statistic) have become standard in modern GIS software. However, there has been little development in amending these tools for visualization and analysis of patterns captured in spatio-temporal data. We design and implement an exploratory mapping tool, VASA (Visual Analysis for Spatial Association), that streamlines analytical pipelines in assessing spatio-temporal structure of data and enables enhanced visual display of the patterns captured in data. Specifically, VASA applies a set of cartographic visual variables to map local measures of spatial autocorrelation and helps delineate micro and macro trends in space-time processes. Two visual displays are presented: recency and consistency map and line-scatter plots. The former combines spatial and temporal data view of local clusters, while the latter drills down on the temporal trends of the phenomena. As a case study, we demonstrate the usability of VASA for the investigation of mobility patterns in response to the COVID-19 pandemic throughout 2020 in the United States. Using daily county-level and grid-level mobility metrics obtained from three different sources (SafeGraph, Cuebiq, and Mapbox), we demonstrate cartographic functionality of VASA for a swift exploratory analysis and comparison of mobility trends at different regional scales. © 2023 Cartography and Geographic Information Society.
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The COVID-19 pandemic has negatively affected the tourism and services sector. Using the example of Airbnb's recent layoff of 25% of its workforce, we focused on the role of organizational justice in mitigating the negative psychological impacts of layoffs. Based on a unique survey of Airbnb employees who survived the layoffs, as well as those who left, we employed an ordinary least squares regression to show that employees' perceptions of organizational justice were positively related to their job satisfaction and trust in management, while being negatively related to their emotional exhaustion and cynicism. We discovered the crucial importance of interactional justice (i.e., interpersonal and informational justice). The respect, dignity, and politeness shown by management (i.e., interpersonal justice), as well as truthful and adequate communication about the procedure (i.e., informational justice) were pivotal to successfully conducting layoffs, especially during unprecedented economic uncertainty. © 2023 by the authors.
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Understanding the observation process is key to effective use of opportunistic biodiversity data from low-structure citizen science. We investigated how observer characteristics, including activity level (enthusiastic, moderate, or short-term) and primary location (resident or visitor), influenced spatial and taxonomic patterns of iNaturalist participation in the Hawaiian Islands from 2008 to 2021. We found that visitors represented nearly two-thirds of all observers and 96% of the enthusiastic group. Sampling bias toward developed areas, sites near roads or trails, and areas with fewer protections was relatively stronger for residents, most of whom were short-term participants. However, observations by enthusiastic residents had the greatest taxonomic diversity. Participation grew exponentially through 2019, then decreased in spring 2020. Though resident participation was comparatively steady during COVID-19 travel restrictions, it did not compensate for the decline in visitor activity. Once restrictions ended in 2021, participation recovered quickly among enthusiastic visitors but continued to be lower than expected for residents. Our results indicate that the majority and diversity of sampling relies on a small group of highly active observers, most of whom are unlikely to live in the region. Fostering sustained, local participation could improve the consistency and quality of iNaturalist observations and thus their utility in biodiversity conservation. © 2023 The Authors
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Until the outbreak of the COVID-19 pandemic, virtual tourism was not as popular as during its duration in 2021, when traveling in the real world was not possible due to social isolation and forced quarantine. In response to the lockdown and the lack of freedom of movement around the world, tourists decided to travel in cyberspace during the COVID-19 pandemic. In this way only, and without leaving home, could they visit tourist attractions, watch museum exhibitions, participate in various media events and take virtual walks. After the "unfreezing” of tourism, the time has now come to adapt tourism to the post-pandemic normality. The aim of the paper is to discover whether the new trend of online tourism that developed during the pandemic will stay with us forever and how it will evolve, especially for Generation Z, who are just entering the labor market but who, at the same time, will determine the future of tourism soon. The research results show that as the pandemic restrictions disappear, the need to experience various forms of tourism in places previously viewed in cyberspace (virtually), occurs among the representatives of Generation Z. Thus, virtual tourism is a form that precedes and complements a real journey. The qualitative method was chosen for the research conducted in Poland. The research was carried out in 2022. A total of 40 focus groups of 7 people each (N = 280) participated in the research. They consisted of Generation Z representatives born after 1995;the oldest of them will be 27 in 2022. In parallel, the method of in-depth individual interviews was used in the research. In order to reach the participants, a non-random sample was chosen using the "snowball” method. In total, 100 people took part in the in-depth individual interview. The two-track research allowed to obtain a total sample of N = 380. © 2023 by the authors.
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COVID-19 has had far-reaching economic, social and health consequences, with vulnerable groups disproportionally affected. Even before the COVID-19 pandemic, concern was expressed about university students' mental health, with global data suggesting students are more vulnerable than the general population to mental disorders. Yet, it is unclear what the pandemic's impact has been on the mental health of students in South Africa. We examined the impact of COVID-19 on first-year students at two universities in South Africa by analysing changes in the prevalence and age-of-onset of three common mental disorders (namely major depressive episode, generalised anxiety disorder, and suicidal ideation) before and during the pandemic, and comparing these to changes between 2015 and 2017. Our analysis of cross-sectional survey data collected in 2015, 2017 and 2020 shows no clear or consistent pattern of increases in prevalence of common mental disorders following the start of the pandemic. Lifetime prevalence rates of common mental disorders among students have been steadily increasing since 2015, and where increases before and during COVID-19 were observed, they are not consistently larger than increases between 2015 and 2020. No significant changes were observed in the 12-month prevalence of common mental disorders before and during COVID-19, except for an increase in prevalence of depression at one institution, and a decrease in suicidal ideation at the other. Findings suggest that in the context of ongoing adversity and disruptions on South African university campuses in recent years, COVID-19 may be just one more stressor local students face and that its impact on student mental health may not have been as marked in South Africa compared to other regions. © 2023. The Author(s). Published under a Creative Commons Attribution Licence.
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With the long-lasting impact of the COVID-19 pandemic, online learning has gradually become one of the mainstream learning methods in Chinese universities. The effectiveness of online learning is significantly influenced by learning engagement, and studies into this topic can help learners by providing them with process-based learning support and focused teaching interventions. Based on the online learning environment, this research constructs an online learning engagement analysis model. Additionally, this study explores the relationship between students' online learning engagement and their online learning performance by taking the Secondary School Geography Curriculum Standards and Textbooks Research, a small-scale private online course (SPOC) of the geography education undergraduate course at Nanjing Normal University, as an example. The findings are as follows: In the cognitive engagement dimension, only "analyze” is significantly positively correlated with learning performance;in the behavioral engagement dimension, the "number of question and answer (Q&A) topic posts,” the "replies to others,” and the "teachers' replies” are all significantly positively correlated with learning performance. In terms of the emotional engagement dimension, "curiosity” and "pleasure” are positively correlated with learning performance;as for the social engagement dimension, "point centrality” and "intermediary centrality” are positively correlated with learning performance. The findings of this case study reveal that the student's engagement in higher-order cognitive learning is obviously insufficient. Students' online learning performance can be enhanced both by behavioral engagement in knowledge reprocessing and positive emotional engagement. Further research should be focused on finding ways to increase students' enthusiasm for social engagement. © 2023 by the authors.