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This case study paper aims to explore the complexities and challenges of epidemic response and public health surveillance in Native American and Indigenous American communities in the United States and find viable solutions. This paper explores these topics through the emergence and impact of the hantavirus pulmonary syndrome (HPS) within the Navajo Nation in the United States using critical incident analysis and best practices.

This project is a case study paper based on a topical review of the literature. A topical review of the literature is a comprehensive exploration of the current body of knowledge within a particular research field. It is an important tool used by scholars and practitioners to further the development of existing knowledge as well as to identify potential directions for future research (Fourie, 2020). Such a paper can provide a useful insight into the various aspects of the process that the researcher may have overlooked, as well as highlighting potential areas of improvement (Gall et al., 2020). It can also provide a useful source of ideas and inspiration for the researcher as it can provide an overview of the various approaches used by other researchers in the field (Göpferich, 2009). Case study papers using a topical review of the literature have been used to help frame and inform research topics, problems and best practices for some time. They are typically used to explore a topic in greater depth and to provide an overview of the literature to improve the world of practice to provide a foundation for future comprehensive empirical research. Case study papers can provide research value by helping to identify gaps in the literature and by providing a general direction for further research. They can also be used to provide a starting point for research questions and hypotheses and to help identify potential areas of inquiry.

This study explores best practices in public health surveillance and epidemic response that can help strengthen public health infrastructure by informing the development of effective surveillance systems and emergency response plans, as well as improving data collection and analysis capabilities within Native American and Indigenous American communities in the United States that also have the option to include new technologies like artificial intelligence (AI) with similar outbreaks in the future.

The literature review did not include any primary data collection, so the existing available research may have limited the findings. The scope of the study was limited to published literature, which may not have reported all relevant findings. For example, unpublished studies, field studies and industry reports may have provided additional insights not included in the literature review. This research has significant value based on the limited amount of studies on how infectious diseases can severely impact Native American communities in the United States, leading to unnecessary and preventable suffering and death. As a result, research on viable best practices is needed on the best practices in public health surveillance and epidemic response in Native American and Indigenous American communities through historical events and critical incident analysis.

Research on public health surveillance and epidemic response in Native American communities can provide insights into the challenges faced by these communities and help identify potential solutions to improve their capacity to detect, respond to and prevent infectious diseases using innovative approaches and new technologies like AI.

More research on public health surveillance and epidemic response can inform policies and interventions to improve access to healthcare for Native American populations, such as increasing availability of healthcare services, providing culturally appropriate health education and improving communication between providers and patients. By providing better public health surveillance and response capacity, research can help reduce the burden of infectious diseases in Native American communities and ultimately lead to improved public health outcomes.

This paper presents the impact of the COVID-19 pandemic on Vietnam's tourism industry to propose appropriate recovery strategies in the future.

This study uses a combination of research methods. Data were collected from the Ministry of Culture, Sports and Tourism, General Statistics Office, Vietnam National Administration of Tourism and Ministry of Health. Non-parametric statistical methods were applied to analyze the differences between epidemic and non-epidemic periods and find correlations between the number of infections and data related to the performance of the tourism industry. In-depth interviews with 20 people linked to tourism activities were conducted to analyze the impacts and propose strategies for future recovery.

The results demonstrate the severe impact of the pandemic on Vietnam's tourism industry based on a decrease in the number of visitors, business activities, revenue and employment rate. Therefore, to recover tourism – Vietnam's key economic sector in the future – developing reasonable strategies to build a safe tourism environment, building a sustainable tourist market, diversifying and improving tourism high-quality tourism products, marketing, human resources, digital transformation and sustainable tourism are necessary, along with the development trend of the industry after COVID-19.

This paper synchronously and systematically presents the effects of COVID-19 on Vietnam's tourism industry based on official data. Strategies are proposed to handle these effects on a reliable scientific basis. This study can be considered a valuable reference for researchers and managers of tourism in developing countries, such as Vietnam.

Taiwan’s hotel industry was adversely impacted by the COVID-19 pandemic. This study aims to examine the effect of strategic choices by Taiwanese international tourist hotels before and during the pandemic environments.

A data envelopment analysis (DEA)-based Malmquist methodology is used in this study to provide a mechanism to assess Taiwanese hotel strategy performance. Changes in the productivity and performance of Taiwanese international tourist hotels were analyzed in the periods before and during the pandemic to uncover insights useful should a similar crisis occur in the future. Panel data were obtained from the annual report of international tourist hotels published by the Taiwan Tourism Bureau from 2017–2020. Two groups of hotels were analyzed in this study: city hotels and scenic hotels.

The findings of this study reveal that chain hotels tended to perform better than independent hotels in both city and scenic areas during the global pandemic. Specifically, the crisis caused a substantial decline in productivity and profitability for international tourist hotels in Taipei City during the COVID-19 period. Compared to city hotels, findings also indicate that most international tourist hotels in scenic areas were able to maintain better productivity, including larger-sized scenic hotels.

The DEA-based analysis provides unique and valuable insights for hotel firm leaders on how to better identify and make strategic choices when responding to future crises.

This paper aims to promote the higher quality development of high-tech enterprises in China. While science and technology have greatly promoted human civilization, resources have been excessively consumed and the environment has been sharply polluted. Therefore, it is particularly important for current enterprises to make use of scientific and technological innovation to maximize the benefits of mankind, minimize the loss of nature, and promote the sustainable development of our country.

By using DEA-Banker-Charnes-Cooper (BCC) model and DEA-Malmquist model, this paper comprehensively examines the innovation efficiency of high-tech enterprises from both static and dynamic perspectives, and conducts a provincial comparative study with the panel data of ten representative provinces from 2011 to 2020.

The research findings are as follows: the rapid number increase of high-tech enterprises in most provinces (cities) is accompanied by an ineffective input–output efficiency; the quality of high-tech enterprises needs to comprehensively examine both input–output efficiency and total factor productivity; and there is not a positive correlation between element investment and innovation performance.

Because the DEA model used in this paper assumes that the improvement direction of invalid units is to ensure that the input ratio of various production factors remains unchanged but sometimes the proportion of scientific and technological activities personnel and the total research and development investment is not constant. In the future, the nonradial DEA model can be considered for further research. Due to historical data statistics, more provinces, cities and longer panel data are difficult to obtain. The samples studied in this paper mainly refer to the provinces and cities that ranked first in the number of national high-tech enterprises in 2020. Limited by the number of samples, DEA analysis failed to select more input and output indicators. In the future, with the accumulation of statistical data, the existing efficiency analysis will be further optimized.

Aiming at the misunderstanding of emphasizing quantity and neglecting quality in the cultivation of high-tech enterprises, this paper comprehensively uses DEA-BCC model and DEA Malmquist index decomposition method to make a comprehensive comparative study on the development of high-tech enterprises in ten representative provinces (cities) from two aspects of static efficiency evaluation and dynamic efficiency evaluation.

The purpose of this study is to explore the causal relationship between smart transportation technology innovation and green transportation efficiency.

A comprehensive framework is used in this paper to assess the level of green transportation efficiency in China based on the instrumental variable – generalized method of moments model, followed by an examination of the impact of innovation in smart transportation technology on green transportation efficiency. Additionally, their non-linear relationship is explored, as are their important moderating and mediating effects.

The findings indicate that, first, the efficiency of green transportation is significantly enhanced by innovation in smart transportation technology, which means that investing in such technologies contributes to improving green transportation efficiency. Second, in areas where green transportation efficiency is initially low, smart transportation technology innovation exerts a particularly potent influence in driving green transportation efficiency, which underscores the pivotal role of such innovation in bolstering efficiency when it is lacking. Third, the relationship between smart transportation technology innovation and green transportation efficiency is moderated by information and communication technology, and the influence of smart transportation technology innovation on green transportation efficiency is realized through an increase in energy efficiency and carbon emissions efficiency.

Advancing green transportation is essential in establishing a low-carbon trajectory within the transportation sector.

After the identification of a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at Wuhan, China, a pandemic was widely spread worldwide. In Italy, about 240,000 people were infected because of this virus including 34,721 deaths until the end of June 2020. To control this new pandemic, epidemiologists recommend the enforcement of serious mitigation measures like country lockdown, contact tracing or testing, social distancing and self-isolation.

This paper presents the most popular epidemic model of susceptible (S), exposed (E), infected (I) and recovered (R) collectively called SEIR to understand the virus spreading among the Italian population.

Developed SEIR model explains the infection growth across Italy and presents epidemic rates after and before country lockdown. The results demonstrated that follow-up of strict measures such that country lockdown along with high testing is making Italy practically a pandemic-free country.

These models largely help to estimate and understand how an infectious agent spreads in a particular country and how individual factors can affect the dynamics. Further studies like classical SEIR modeling can improve the quality of data and implementation of this modeling could represent a novelty of epidemic models.

As of July 30, 2020, more than 17 million novel coronavirus disease 2019 (COVID-19) cases were registered including 671,500 deaths. Yet, there is no immediate medicine or vaccination for control this dangerous pandemic and researchers are trying to implement mathematical or time series epidemic models to predict the disease severity with national wide data.

In this study, the authors considered COVID-19 daily infection data four most COVID-19 affected nations (such as the USA, Brazil, India and Russia) to conduct 60-day forecasting of total infections. To do that, the authors adopted a machine learning (ML) model called Fb-Prophet and the results confirmed that the total number of confirmed cases in four countries till the end of July were collected and projections were made by employing Prophet logistic growth model.

Results highlighted that by late September, the estimated outbreak can reach 7.56, 4.65, 3.01 and 1.22 million cases in the USA, Brazil, India and Russia, respectively. The authors found some underestimation and overestimation of daily cases, and the linear model of actual vs predicted cases found a p-value (<2.2e-16) lower than the R2 value of 0.995.

In this paper, the authors adopted the Fb-Prophet ML model because it can predict the epidemic trend and derive an epidemic curve.

This paper aims to describe the unique health challenges facing female commercial sex workers (FSWs), including issues related to their marginalisation and difficulty accessing health care. It proposes solutions to some of these problems.

This paper addresses this sensitive subject through the methodology of a literature review, drawing on a variety of relevant published literature to inform a modern understanding of the current health challenges faced by this population.

This paper discusses issues around criminalisation of commercial sex workers, complexities of family planning, sexually transmitted infection prevention, mental health and substance abuse and how increasing health-care worker awareness of the health needs of this vulnerable population can be a positive step in building trust within this relationship. Although adoption of the proposed recommendations put forth in this paper may help to eliminate some of the barriers encountered by female sex workers, further research is recommended.

The subject of commercial sex worker health care is neglected in the academic literature. This review explores the topic in an open and balanced manner and presents a broad and updated overview of the current health-care challenges faced by FSWs as well as opportunities for optimising access and quality of sex worker health care.

The pandemic has enhanced the global phenomenon of disinformation. This paper aims to study the false news concerning COVID-19, spread through social media in Spain, by using the LatamChequea database for a duration from 01/22/2020, when the first false information has been detected, up to 03/09/2021.

A quantitative analysis has been conducted with regard to the correlation between fake news stories and the pandemic state, the motive to share them, their dissemination in other countries and the effectiveness of fact checking. This study is complemented by a qualitative method: a focus group conducted with representatives of different groups within the society.

Fake news has been primarily disseminated through several social networks at the same time, with two peaks taking place in over a half of the said false stories. The first took place from March to April of 2020 during complete lockdown, and we were informed of prevention measures, the country’s situation and the origin of the virus, whereas the second was related to news revolving around the coming vaccines, which occurred between October and November. The audience tends to neither cross-check the information received nor report fake news to competent authorities, and fact-checking methods fail to stop their spread. Further awareness and digital literacy campaigns are thus required in addition to more involvement from governments and technological platforms.

The main limitation of the research is the fact that it was only possible to conduct a focus group of five individuals who do not belong to generation Z due to the restrictions imposed by the pandemic, although a clear contribution to the analysis of the impact of fake news on social networks during the COVID-19 pandemic in Spain can be seen from the privileged experiences in each of the fields of work that were identified. In this sense, the results of the study are not generalizable to a larger population. On the other hand, and with a view to future research, it would be advisable to carry out a more specific study of how fake news affects generation Z.

This research is original in nature, and the findings of this study are valuable for business practitioners and scholars, brand marketers, social media platform owners, opinion leaders and policymakers.

There is little knowledge to date regarding the influence of the COVID-19 health crisis on tourists' intention to travel differently in the future. This paper addresses this and explores its determinants. The objective of the present study is to determine to what extent the Spanish tourists affected by COVID-19 may change the way they travel in the future, according to the perceived risk of travel in a pandemic context.

Between May and June 2020, the authors conducted a survey with a sample population of Spanish tourists who were resident in Spain during the COVID-19 pandemic, for the purposes of studying the role of attitudes and risk in the intention to change the way they want to travel in the future. Cluster analysis and one-way ANOVA were conducted to assess differences among the respondents. Finally, some models were built using the linear regression technique in order to evaluate the role of attitudes in the tourists' adaptive response to the perceived risk of travel.

Results confirm the formation of a new way of life influencing tourists' intentions to travel more sustainably. Accordingly, tourists with a previous environmental attitude are less interested in visiting mass tourism beach destinations in the future. However, changes in the way some tourists travel can also be read as an adaptive and temporary response to the perceived risk of contracting the disease, and do not point to a reduction of the vital importance of tourism in their lives.

The exploratory nature of the study and the lack of similar international analyses does not allow the authors to contrast its results at a global level, though it offers a starting point for future research in other countries. There are also methodological limitations, since the field work was carried out between the first and second waves of the disease, at a time when the pandemic was in remission, possibly affecting the orientation of some responses, given the desire to recover normalcy and “normal” travel, and this may have influenced the priority given to tourism.

This study gives new insights into the debate on the social transformation of the collective consciousness. Despite some signs of change, part of the Spanish tourists are still anchored in traditional tourism practices embedded in cultural factors, which can hinder sustainability in the Spanish tourism industry. The experience of the COVID-19 crisis has not been sufficient to change the declared travel habits of Spanish tourists. Therefore, progress towards the definition of a new tourism system that implies the effective transformation of demand will require applying policies and promoting institutional innovation and education to create paths that facilitate transformative experiences.

The study is focused on the analysis of the relationship between attitudes and risk perception, including novel elements that enrich the academic debate on social progress in the transformation of tourism and the possibilities of promoting a reset from the demand side. Moreover, it incorporates, for the first time, the COVID-19 as it was experienced as an explanatory variable to analyse the changing travel attitudes in a post-COVID-19 era. The analysis of the psychosocial mechanisms of risk offers a good opportunity for a better assessment of post-pandemic demand risk perception. Finally, the study offers empirical evidence on how Spanish tourists are reimagining their next and future holidays, which can be highly valuable for destination managers.