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This paper evaluates the impact of tourism on poverty alleviation using a new panel quantile fixed effects method that allows regressors to affect the entire conditional distribution of the dependent variable providing substantial information gains. Our results show statistically significant negative marginal effects of tourism on both absolute poverty measures and Gini income inequality across all quantiles, including the poorest 10%. We also find evidence that international tourism can mitigate the slow improvement in domestic income level for poverty reduction. From a policy perspective, our findings can provide insights into developing targeted tourism policies and strategies to achieve better solutions on poverty alleviation. We also call for special attention to policymakers in developing countries to continue working on tourism product differentiation and targeting a smaller but reachable market in the post COVID-19 recovery era, to prevent the adverse effect of the worldwide income growth stagnation on their poverty rates.
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Purpose This study compares doctor staffing level and the scale of medical education in China with those of other countries and proposes policy recommendations for future adjustments to the scale of China's medical education. Design/Approach/Methods This study employs a literature review and descriptive analysis. Findings China had 1.98 medical doctors per 1,000 people in 2018, ranking 85th out of the 193 member-states of the World Health Organization (WHO). In 2017, China had 1.99 practicing doctors per 1,000 people, only ranking above Turkey (1.88) in Organisation for Economic Co-operation and Development (OECD) countries. China had only 10.28 medical graduates per 100,000 people—placing in the bottom third of OECD countries. China's provision of 1.4 medical schools per 10 million people was also significantly lower than the global average (3.9). However, the average number of students enrolled in medical schools (509) in China was significantly higher than the global average (160). Originality/Value Although the scale of admission in undergraduate medical education must be expanded in China, this needs to be achieved while controlling the average number of medical students per school and reducing enrollment in low-quality medical schools. Furthermore, it is necessary to establish new medical schools while improving the operating level of existing ones.
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The multiple comparison method refers to the hypothesis test of whether there is a significant difference between the means of each sample after the analysis of variance is performed on the samples of each group to be tested. In data analysis, the multiple comparison method can perform a more precise difference analysis based on the analysis of variance. Therefore, this study will select the LSD (Least significant difference) test method in the multiple comparison method to analyze the physical fitness test scores of males and females in the three grades from 2019 to 2021 in the investigated schools. In this way, we can understand the substantial impact of students' home-based learning on students' physical health during the new crown epidemic, so as to make targeted development plans for students' physical health in the current special period, and minimize the adverse impact of the new crown epidemic on students' physical health. © 2023 SPIE.
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This special issue contains 11 s that discuss recent learnings and developments in healthcare financing from a global perspective. The s cover a range of topics such as the impact of mental illness on poverty and catastrophic health expenditure in India, financing challenges in the American healthcare industry, comparative analysis of health system financing in India and Saudi Arabia, and the contribution of the Ghana National Health Insurance Scheme to inequality in healthcare utilisation. Other s explore the influence of socio-economic status on health financing choices in Jambi Province, households' willingness to pay for community-based health insurance in Bangladesh, and changes in household expenditures during the first wave of COVID-19 in India. The issue also includes discussions on managing the provider-purchaser split in India and reconsidering patient value to create better healthcare.
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The 50% plaque reduction neutralization assay (PRNT50) has been previously used to assess the neutralization capacity of donor plasma against wild-type and variant of concern (VOC) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Emerging data suggest that plasma with an anti-SARS-CoV-2 level of ≥2 × 104 binding antibody units/mL (BAU/mL) protects against SARS-CoV-2 Omicron BA.1 infection. Specimens were collected using a cross-sectional random sampling approach. For PRNT50 studies, 63 previously analyzed specimens by PRNT50 versus SARS-CoV-2 wild-type, Alpha, Beta, Gamma, and Delta were analyzed by PRNT50 versus Omicron BA.1. The 63 specimens plus 4,390 specimens (randomly sampled regardless of serological evidence of infection) were also tested using the Abbott SARS-CoV-2 IgG II Quant assay (anti-spike [S]; Abbott, Chicago, IL, USA; Abbott Quant assay). In the vaccinated group, the percentages of specimens with any measurable PRNT50 versus wild-type or VOC were wild type (21/25 [84%]), Alpha (19/25 [76%]), Beta (18/25 [72%]), Gamma (13/25 [52%]), Delta (19/25 [76%]), and Omicron BA.1 (9/25 [36%]). In the unvaccinated group, the percentages of specimens with any measurable PRNT50 versus wild type or VOC were wild-type SARS-CoV-2 (16/39 [41%]), Alpha (16/39 [41%]), Beta (10/39 [26%]), Gamma (9/39 [23%]), Delta (16/39 [41%]), and Omicron BA.1 (0/39) (Fisher's exact tests, vaccinated versus unvaccinated for each variant, P < 0.05). None of the 4,453 specimens tested by the Abbott Quant assay had a binding capacity of ≥2 × 104 BAU/mL. Vaccinated donors were more likely than unvaccinated donors to neutralize Omicron when assessed by a PRNT50 assay. IMPORTANCE SARS-CoV-2 Omicron emergence occurred in Canada during the period from November 2021 to January 2022. This study assessed the ability of donor plasma collected earlier (January to March 2021) to generate any neutralizing capacity against Omicron BA.1 SARS-CoV-2. Vaccinated individuals, regardless of infection status, were more likely to neutralize Omicron BA.1 than unvaccinated individuals. This study then used a semiquantitative binding antibody assay to screen a larger number of specimens (4,453) for individual specimens that might have high-titer neutralizing capacity against Omicron BA.1. None of the 4,453 specimens tested by the semiquantitative SARS-CoV-2 assay had a binding capacity suggestive of a high-titer neutralizing capacity against Omicron BA.1. These data do not imply that Canadians lacked immunity to Omicron BA.1 during the study period. Immunity to SARS-CoV-2 is complex, and there is still no wide consensus on correlation of protection to SARS-CoV-2.
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We assessed how many US deaths would have been averted each year, 1933-2021, if US age-specific mortality rates had equaled the average of 21 other wealthy nations. We refer to these excess US deaths as "missing Americans." The United States had lower mortality rates than peer countries in the 1930s-1950s and similar mortality in the 1960s and 1970s. Beginning in the 1980s, however, the United States began experiencing a steady increase in the number of missing Americans, reaching 622,534 in 2019 alone. Excess US deaths surged during the COVID-19 pandemic, reaching 1,009,467 in 2020 and 1,090,103 in 2021. Excess US mortality was particularly pronounced for persons under 65 years. In 2020 and 2021, half of all US deaths under 65 years and 90% of the increase in under-65 mortality from 2019 to 2021 would have been avoided if the United States had the mortality rates of its peers. In 2021, there were 26.4 million years of life lost due to excess US mortality relative to peer nations, and 49% of all missing Americans died before age 65. Black and Native Americans made up a disproportionate share of excess US deaths, although the majority of missing Americans were White.
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Background: The main aim of the study was to evaluate the different parameters of the COVID-19 pneumonia in India during the first and second waves. Method: Five hundred RT-PCR positive and HRCT documented COVID-19 pneumonia patients each from first wave (June 2020-December 2020) and second wave (March 2021-May 2021) were selected. The results were evaluated in terms of age groups affected, gender wise distribution, and CT severity score on HRCT. The final conclusion was done by comparing these variables from first wave with the ones during the second wave and inferences drawn upon thereof. Results: During the first wave, majority of the population involved belonged to more than 45 years category whereas during the second wave majority belonged to the 18-45 years category. Further, the severity of the disease was more during the second wave than the first wave with more males being affected than females in both the waves. Conclusion: Second COVID-19 wave in India was more severe than the first wave in terms of the number of patients affected as well as the severity of the pneumonia in the involved patients, likely due to continuously mutating variants of the virus & lifting up of the restrictions.
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In the wake of the COVID-19 pandemic in 2020, older people across Europe have adjusted their daily activities as personal risk avoidance and as an amendment to policy recommendations and restrictions. In this study, we use multilevel logistic regressions to examine to what extent sociodemographic factors are associated with activity reduction among the older population (50+) in Europe and whether these associations are moderated by governmental policy responses to COVID-19. By combining data for~35,000 respondents from the SHARE Corona Survey on reported changes in daily activities and stringency of restrictions at the national level, we find that older age, poorer health and being female versus male were (consistently) associated with greater activity reduction across all activities both in countries with weak and in those with strong restrictions. Associations between education, employment and living situation, on the one hand, and activity reduction, on the other, were weaker and less consistent. We conclude that differences between sociodemographic groups are rather similar for countries with weak and those with strong restrictions and hence argue that group-specific policy recommendation are relevant independent of stringency recommendations.
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Background Stratification of patients with post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) would allow precision clinical management strategies. However, long COVID is incompletely understood and characterised by a wide range of manifestations that are difficult to analyse computationally. Additionally, the generalisability of machine learning classification of COVID-19 clinical outcomes has rarely been tested.Methods We present a method for computationally modelling PASC phenotype data based on electronic healthcare records (EHRs) and for assessing pairwise phenotypic similarity between patients using semantic similarity. Our approach defines a nonlinear similarity function that maps from a feature space of phenotypic abnormalities to a matrix of pairwise patient similarity that can be clustered using unsupervised machine learning.Findings We found six clusters of PASC patients, each with distinct profiles of phenotypic abnormalities, including clusters with distinct pulmonary, neuropsychiatric, and cardiovascular abnormalities, and a cluster associated with broad, severe manifestations and increased mortality. There was significant association of cluster membership with a range of pre-existing conditions and measures of severity during acute COVID-19. We assigned new patients from other healthcare centres to clusters by maximum semantic similarity to the original patients, and showed that the clusters were generalisable across different hospital systems. The increased mortality rate originally identified in one cluster was consistently observed in patients assigned to that cluster in other hospital systems. Interpretation Semantic phenotypic clustering provides a foundation for assigning patients to stratified subgroups for natural history or therapy studies on PASC.
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COVID-19 is an unprecedented global pandemic with a serious negative impact on virtually every part of the world. Although much progress has been made in preventing and treating the disease, much remains to be learned about how best to treat the disease while considering patient and disease characteristics. This paper reports a case study of combinatorial treatment selection for COVID-19 based on real-world data from a large hospital in Southern China. In this observational study, 417 confirmed COVID-19 patients were treated with various combinations of drugs and followed for four weeks after discharge (or until death). Treatment failure is defined as death during hospitalization or recurrence of COVID-19 within four weeks of discharge. Using a virtual multiple matching method to adjust for confounding, we estimate and compare the failure rates of different combinatorial treatments, both in the whole study population and in subpopulations defined by baseline characteristics. Our analysis reveals that treatment effects are substantial and heterogeneous, and that the optimal combinatorial treatment may depend on baseline age, systolic blood pressure, and c-reactive protein level. Using these three variables to stratify the study population leads to a stratified treatment strategy that involves several different combinations of drugs (for patients in different strata). Our findings are exploratory and require further validation.
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Purpose - The paper focuses on guest satisfaction and service process improvement, considering the importance of quality elements as an important factor for differentiation in the market. The purpose of this article is to identify the differences in the attitudes of domestic and foreign guests who have stayed in homestay accommodation. As part of the research, an importance-performance analysis was conducted to compare the importance of and satisfaction with quality elements among domestic and foreign guests. Design - Primary research was conducted in September 2020 in 10 counties of the Republic of Croatia. A total of 168 valid questionnaires were collected. The sample consists of guests from 17 countries who were accommodated in homestay accommodation. Methodology - For this article, importance-performance analysis (IPA) was performed and the importance of, and satisfaction with, each quality element was presented in an IPA matrix. By analysing the position of the quality elements in the matrix, it is possible to identify future strategies and improvements that need to be implemented to meet the needs of guests. Approach - The study analyses 20 quality elements in two IPA matrices, one for domestic guests, and one for foreign guests. Each matrix has four quadrants: "Concentrate here", "Keep up the good work", "Low priority" ", and "Possible overkill". Findings - The results show that there are differences between domestic and foreign guests in their perceptions of satisfaction with and importance of quality elements. The results of the conducted IPA provide guidelines for improving certain areas in the service delivery process in accordance with guest preferences. The research has several limitations, mainly the sample size and the fact that the study was conducted during the COVID-19 pandemic. Originality of the research - The results show the peculiarities of guests staying in homestay accommodation and highlight the differences in perception depending on the origin of the guests. The findings provide clear guidance for practitioners by identifying elements of service quality that are important to domestic and international guests. This provides the basis for creating services tailored to guests' needs and expectations.
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Cloud computing is currently one of the prime choices in the computing infrastructure landscape. In addition to advantages such as the pay-per-use bill model and resource elasticity, there are technical benefits regarding heterogeneity and large-scale configuration. Alongside the classical need for performance, for example, time, space, and energy, there is an interest in the financial cost that might come from budget constraints. Based on scalability considerations and the pricing model of traditional public clouds, a reasonable optimization strategy output could be the most suitable configuration of virtual machines to run a specific workload. From the perspective of runtime and monetary cost optimizations, we provide the adaptation of a Hadoop applications execution cost model extracted from the literature aiming at Spark applications modeled with the MapReduce paradigm. We evaluate our optimizer model executing an improved version of the Diff Sequences Spark application to perform SARS-CoV-2 coronavirus pairwise sequence comparisons using the AWS EC2's virtual machine instances. The experimental results with our model outperformed 80% of the random resource selection scenarios. By only employing spot worker nodes exposed to revocation scenarios rather than on-demand workers, we obtained an average monetary cost reduction of 35.66% with a slight runtime increase of 3.36%. © 2023 John Wiley & Sons, Ltd.
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Introduction: To statistically compare the trends of epidemiological indicators of COVID-19 in India with Italy, the UK, and the US. Methodology: In this descriptive analysis, epidemiological indicators were calculated and their trends were plotted and compared statistically. Regression analysis was done to predict the fatalities. Results: The trends of total and active cases per million populations are rising in India and US, while Italy has achieved the plateau in the total cases per million populations, and active cases have been sharply declining with time. The UK is about to achieve the same. India has remained far behind the other three countries in the number of tests per million populations (p < 0.05). In the initial phase, the test positivity rate of India was quite lower but has overtaken Italy and UK. India has always reported a higher recovery rate than US and lower than Italy. CFRs have achieved a plateau in Italy and UK, in US it is declining, while it remained almost constant in India throughout the pandemic. Testing was a significant covariate in predicting the fatalities. Conclusions: India was able to manage the initial phase of this pandemic due to early and strict government interventions and strong public health responses.
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The COVID-19 virus pandemic has led to huge changes in the business of many companies. Managers and owners of companies were most affected, so in one segment of this paper, certain psychological ways that are available to people when it comes to overcoming various crises. Considering that profitable business is a condition for the survival of companies, in this paper, a comparison of profitability in the production of organic and conventional food was performed. ROA and ROE were calculated on a sample of 150 food producers in our country for the period from 2016 to 2020. The results showed that ROA is higher in conventional food producers, while ROE is higher in organic food producers. During the COVID-19 pandemic, the profitability of food producers is higher than in the period before its outbreak. Also, there is a tendency to increase profitability in both types of production.
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The phenomenon of cryptocurrencies still requires systematic and in-depth scientific research, because the literature lacks a concentrate and systematic analysis on issue of private, decentralized digital money (cryptocurrencies) in relation to the future of traditional money, as well as the stability of the financial system. Moreover, the is lack of research based on the opinions of participants of the financial system, which includes users – current and potential – as subjects relevant to the future of the financial system, based on the historically well-known principle of universal acceptance and trust in traditional monetary system. In particular, comparative and international research has received limited attention. In response to the identified research gap, this article refers to the results of research on the perception of cryptocurrencies by young financial market participants. We try to answer to the following research questions: 1) are there international differences in perceptions and attitudes toward the traditional monetary system and cryptocurrencies? 2) are cryptocurrencies constructed on the basis of blockchain a valid alternative to current fiat money? 3) do cryptocurrencies have characteristics that make them successors to fiat money? Our work is based on the research material collected during surveys conducted before the outbreak of the COVID-19 pandemic – in December 2019 and January 2020 – in Germany and Poland. The survey was conducted among 281 respondents – 143 from Germany and 128 from Poland. They were students of economics and finance majors of studies. The survey was conducted in the form of an auditorium questionnaire. The paper questionnaire used in the survey consisted of 26 questions related to virtual money and 5 questions of socio-demographic characteristics. In addition, the article used statistical methods – correlation and variance analysis – to characterize the distributions of responses and the relationships between questions. Our findings lead to the conclusion that there are significant differences in perception, the traditional monetary system, and cryptocurrencies due to a variety of factors, which include the level of development of the economy, the innovation of financial markets, historical warranty and being their derivative the so-called collective consciousness (mentality). The obtained research results can be a starting point for further in-depth analysis of the studied phenomenon at the international level, not only in the sphere of economics and finance, but also behavioral finance, sociology and psychology. © 2022 Narodowy Bank Polski. All rights reserved.
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The better-than-average effect (BTAE) is a mechanism where people perceive oneself as better than others. The BTAE could be one of the phenomena explaining why people follow-in the moment of a global health crisis-guidelines ("I am superior to others, and I [will]) take extra precautions, e.g., a vaccine shot"). In this paper, we investigate the BTAE with 3,066 respondents. In Study 1, in all countries, across two measurements in time, the BTAE was present: Participants rated their involvement in self-protection as greater in comparison to others. Study 2 replicated this effect, proving its robustness. Participants estimated their willingness to vaccinate as higher than others. The BTAE was a significant predictor of willingness to vaccinate. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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OBJECTIVES: To compare the values of the hematological and inflammatory markers in 1st and 4th waves to predict the outcome of COVID-19 in a hospital-based study. METHODOLOGY: This comparative study was conducted in the Department of Hematology, Hayatabad Medical Complex Peshawar, from April 2020 to 20 August 2021. Tests of significance (Independent t-test/Mann Whitney U test) and Chi-square test were used. Relevant information was recorded on a pre-designed proforma prepared following the study's objectives. RESULTS: A total of 178 patients, 71 from (the 1st wave) and 107 from (the 4th wave) with known outcomes, were studied. A statistically significant difference exists between the groups (1st vs 4th wave) regarding hematological markers;neutrophil to lymphocyte ratio (NLR) (p=0.02), Absolute Neutrophilic count (ANC) (p=0.01) and platelet count (p=0.001). Similarly, significantly higher inflammatory markers values were recorded in the 1st wave compared with the 4th wave regarding inflammatory markers;CRP (p=0.002) and D-dimer (p=0.001). During the 1st wave, Total Leukocyte Count (TLC), ANC and d-dimer were the leading prognostic indicators to predict mortality/worst outcome in COVID-19 with an Area Under Curve (AUC) of 0.74, 0.70 and 0.7 on receiver operating characteristics (ROC) respectively. In 4th, the Area under the curve (AUC) of d-dimer was 0.84 to predict mortality. CONCLUSION: TLC, ANC, NLR, and low platelet count were the worst hematological markers in COVID-19 in the first wave, while d-dimer and CRP were the primary prognostic inflammatory markers. Unlikely in the 4th wave, the prognostic values of hematological markers were merely significant. The d-dimer values in both the waves proved to be reliable for predicting the severity and mortality of COVID-19.
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Introduction: throughout history, several diseases have put mankind "in stress" and due to the accelerated and extensive spread have been labeled as pandemics. Background: to assess similarities and differences between COVID-19 and the Spanish influenza. Method: a literature review was carried out in December 2021. Using several Academic search engines, like (Pubmed, Google and Google Scholar). It was assessed several Articles published in Spanish;those that did not meet these conditions were excluded;89 bibliographic references were studied, of which 25 were cited in this article. Development: COVID-19 and Spanish flu are similar for arising respiratory symptoms at first, clinical characteristic of a common cold. The earliest documented case of Spanish flu was in the United States of America and it was caused by the H1N1 influenza A virus and it's not identified as a zoonosis, however, COVID-19 first cases were documented in China and it was caused by the virus of SARS-CoV-2, virus identified as a zoonosis that affect most commonly older adults, whereas the Spanish flu affected more young adults. It has been attributed some protective immunity to those who became ill with the Spanish flu, however, the coronavirus does not leave person with immunization levels after been infected. Conclusion: Spanish flu and coronavirus are the two great pandemics of history which have many similarities and differences from clinical, epidemiological and social point of view.
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The severe impact of global crises, such as COVID-19 and climate change, is plausibly reshaping the way in which people perceive risks. In this paper, we examine and compare how global crises and local disasters influence public perceptions of multiple hazards in Italy and Sweden. To this end, we integrate information about the occurrence of hazardous events with the results of two nationwide surveys. These included more than 4000 participants and were conducted in two different phases of the COVID-19 pandemic corresponding to low (August 2020) and high (November 2020) levels of infection rates. We found that, in both countries, people are more worried about risks related to experienced events. This is in line with the cognitive process known as the availability heuristic: individuals assess the risk associated with a given hazard based on how easily it comes to their mind. Epidemics, for example, are perceived as less likely and more impactful in Italy compared to Sweden. This outcome can be explained by cross-country differences in the impact of, as well as governmental responses to, COVID-19. Notwithstanding the ongoing pandemic, people in both Italy and Sweden are highly concerned about climate change, and they rank it as the most likely threat.
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Data is an important production factor in the era of digital economy. Privacy computing can ensure that data providers do not disclose sensitive data, carry out multi-party joint analysis and computation, securely and privately complete the full excavation of data value in the process of circulation, sharing, fusion, and calculation, which has become a popular research topic. String comparison is one of the common operations in data processing. To address the string comparison problem in multi-party scenarios, we propose an algorithm for secure string comparison based on outsourced computation. The algorithm encodes the strings with one hot encoding scheme and encrypts the encoded strings using an XOR homomorphic encryption scheme. The proposed algorithm achieves efficient and secure string comparison and counts the number of different characters with the help of a cloud-assisted server. The proposed scheme is implemented and verified using the new coronavirus gene sequence as the comparison string, and the performance is compared with that of a state-of-the-art security framework. Experiments show that the proposed algorithm can effectively improve the string comparison speed and obtain correct comparison results without compromising data privacy. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.