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Understanding what factors play a role in people's decisions to travel during a pandemic is important to public health officials and to stakeholders in the travel and tourism industry in the United States (US) and worldwide. This study examines factors influencing people's decisions to cancel/postpone recreational travel within the US amidst the COVID-19 pandemic. Our conceptual framework extends the Expected Utility model, commonly used in economics to model decisions under risk and uncertainty, to incorporate subjective norms and perceived behavioral control from the Theory of Planned Behavior. Our results suggest that risk perceptions, subjective norms, and concerns over transmitting COVID-19 to others play a significant role in the decision to cancel and postpone recreational travel. Results also suggest that perceived behavioral control may be less relevant to travel decisions when traveling involves elevated health risks.
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Iron and zinc are important minerals in humans in sub Saharan Africa, whose deficiency is known as "hidden hunger" due to the lack of recognised symptoms in the early stages. Although iron deficiency is the most prevalent, zinc is also involved in inhibition of replication of viruses, including the corona virus (COVID-19). In North Kivu and South Kivu provinces where more than 50% of common bean is produced and consumed in Democratic Republic of Congo, 36% and 47% of preschool children are anemic due to iron deficiency. This paradox is mainly due to insufficiency of iron-rich foods. The aim of this study is to characterise 59 iron and zinc biofortified varieties together with six local varieties of common bean for a potential selection programme in Butembo town in the Democratic Republic of Congo. We focused on 15 qualitative and five quantitative parameters. The qualitative parameters were helpful to distinguish the different morphotypes and for cluster analysis. In addition to the descriptive statistics, the quantitative data were used for Pearson correlation and for principal component analysis, PCA. Qualitative parameters enabled grouping of the study genotypes into 14 morphotypes according to the aspect and colour of the seed coat, the colour around the hilum and the size of seeds. Clustering grouped the 65 genotypes into 12 clusters with the most similar genotypes grouped in the same cluster. Quantitative parameters showed that the study genotypes were dissimilar (P=0.00). A positive correlation was obtained between the days to flowering and the days to maturity (P<0.05) and between the number of pods per plant and the days to flowering. A strong correlation was found between the number of pods per plant and seeds per pod (P<0.01). In contrast, a negative correlation was observed between the 100 seed weight and the number of seeds per pod. The PCA represented on two perpendicular axes showed 64.1% of the total variance of which the 42.3% is explained by the first axis and 21.8% by the second axis. Overall, the study genotypes are morphologically and quantitatively different and thus can be used in a selection programme.
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The onset of COVID- 19 pandemic has resulted in the transition from the conventional face to face health care strategies to computerized approaches, considering distances, the importance of quarantine, and early diagnosis and management. As far as the rapid management of the infection is concerned, telemedicine has been introduced as a beneficial approach. The use of telemedicine is thought to decrease the risk of cross contamination. Moreover, it provides the access to the health care for remote locations. The health care staff can use the computational analyses to get rapid access to the accurate epidemiological and laboratory data. The risk assessment provided by the mathematical models seems beneficial for decision-making in regards to the prognosis and management. We aimed to explore the breakthrough of telemedicine regarding the pandemic, also attempting to describe the related problems and challenges.
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Since the emergence of the Coronavirus disease outbreak, the world has witnessed great changes that have impacted humanity. A study of the pattern of the pandemic would be of great importance to understand the trending behavior for the spreading of the disease within any country. Visualization of the outbreak progression - through accumulated records in the datasets - using statistical tools showed that the initial fast increase rate of the affected cases in the original province in China was followed by a stability period till the end of the reporting date. Hong Kong - which was next to Hubei province in the cases - showed a different surge of slow growth curve with distinct major wave levels. The remaining territories showed a much smaller magnitude of morbidities. However, investigating the similarity levels for the daily kinetics of cases showed a clustering tendency between different political regions suggesting a significant correlation. The technique would be useful for public health authorities work.
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BACKGROUND: During the COVID-19 pandemic, grief and bereavement have been the most prevalent psychological problems experienced. Therefore, the aim of the present study was to compare the effectiveness of grief counseling and God-oriented spiritual counseling on death anxiety and spirituality in people with COVID-19 grief. METHODS: The present quasi-experimental study was conducted with a pretest-posttest design, a control group, and follow-up. The population consisted of all inhabitants of Shahr-e-Rey who had lost a member of their family due to COVID-19 in 2021. Participants (n = 51) were selected through purposive sampling based on their acceptance to participate in the study and the inclusion criteria, and were randomly assigned to 2 experimental groups (n = 34) and 1 control group (n = 17). Data were collected using Templer's Death Anxiety Scale (DAS) and the Spiritual Perspective Scale (SPS) in the pretest, posttest, and follow-up stages. The collected data were analyzed in SPSS software using repeated measures ANOVA. RESULTS: The results showed that both methods of intervention were effective in reducing death anxiety and increasing perceived spirituality. However, God-oriented spiritual counseling was more effective in reducing death anxiety and increasing perceived spirituality compared to grief counseling (P < 0.05). CONCLUSION: The results strongly support the effectiveness of grief counseling and God-oriented spiritual counseling on death anxiety and perceived spirituality. Policymakers and mental health experts can use both counseling approaches (based on cognitive-behavioral therapy and complex bereavement therapy) in designing individual and community-oriented interventions related to bereavement, provided they pay attention to the needs of the target community.
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The coronavirus disease 2019(COVID-19) pandemic spreads across borders with the frequent global population movement. To explore the impact of the COVID-19 pandemic on China's domestic epidemic prevention and control, based on the classical infectious disease dynamics model this paper proposes an infectious disease model that considers oversea imported cases. The model can simulate three situations:national pandemic without imported cases, no domestic cases with only imported cases, and domestic cases with international travellers entering simultaneously. By calculating the peak case number and range of infection spread duration in these situations, as well as the amount of medical resources invested, the model has shown the different results of impact of entry type on the domestic pandemic and different pressures on medical resources. Finally, the paper suggests that testing measures should be taken according to the degree of pandemic risk and resource conditions, that strict prevention and control should be applied to the people not entering through customs, and closed-loop management to the people entering through customs, that entry quarantine measures and quarantine periods should be dynamically adjusted and international exchanges should be gradually resumed in the context of ensuring domestic and overseas epidemic prevention and control in advance, and that it is necessary to integrate medical resources, improve allocation efficiency, and relieve the pressure of resource occupation.
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AIM: The study aimed to assess the effectiveness of the ChAdOx1 nCoV-19 vaccine in preventing laboratory-confirmed COVID-19. METHODS: It was a test-negative, case-control study conducted at Sharda Hospital, Greater Noida, India, between March 2021 and May 2021. An equal number of cases and controls were included in the study after taking proper informed consent. The individuals with positive reverse transcriptase-polymerase chain reaction test reports were taken as cases, whereas those with negative reports were included as controls. Data were analyzed and the groups were compared using multivariable logistic regression to calculate the odds ratio (OR), with adjustment for gender and presence or absence of comorbidities. The effectiveness of vaccine was calculated by the formula (1-adjusted OR) x100%. RESULTS: On analyzing the data from 560 case-control pairs, the vaccine effectiveness was calculated as 57.46% (95% confidence interval [CI]: 53.85-61.02) and 60.09% (95% CI: 56.32-63.77) for single dose and two doses, respectively. The effectiveness of complete and single-dose vaccination against the moderate-to-severe disease was calculated as 63.79% (95% CI: 58.58-68.77) and 56.19% (95% CI: 51.30-61.0), respectively. CONCLUSION: The ChAdOx1 nCoV-19 vaccine was found to be effective against COVID-19, with protection after two doses being a little more than that after a single dose. It also proved effective in protecting against the severe form of the disease.
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An important environmental problem for the Municipality of Burgas is the relatively high levels of PM10 pollution. Particulate matter PM10 is defined as the fraction of particles with an aerodynamic diameter smaller than 10 pm. The article provides statistical processing and evaluation of daily data on the concentration of PM10 in the air by quarters fix Burgas, 2021. A histogram of the frequency distribution of concentrations by quarters was prepared. A regression model for calculating the monthly concentrations in the atmospheric air is derived The tests and inspections performed show that the performed modelling is suitable for evaluation, analysis and forecast. Air pollution harms human health and the environment. Exposure ID air pollution is associated with a wide range of acute and chronic health effects, ranging from irritating effects to death From the end of 2019 until now in the world, Europe and in particular Bulgaria is raging a dangerous respiratory disease known as COVD19. The average monthly new cases of COVD19 for Burgas were assessed, as well as the respective maximum and minimum monthly values. A qualitative assessment of the relationship between the monthly concentrations of PM10 and the incidence of COVID19 was made.
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The aim of the article is to present the financial condition of selected dairy cooperatives using ratio analysis and selected discriminant models. The main objective of the paper is to assess the overall financial condition of dairy cooperatives during the COVID-19 pandemic (2020-2021) and earlier years (2017-2019). The author focused, on the one hand, on the assessment of the financial condition of a selected group and, on the other hand, on the link between the financial situation of selected dairy cooperatives and state aid during the changing economic reality caused by the SARS CoV-2 virus. The financial analysis for dairy cooperatives also reveals a broader comparative context in the time span before and during the COVID-19 pandemic. The research shows that the analysed dairy cooperatives, with the exception of OSM Jasienica Rosielna, did not have a negative financial results.
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The importance of food supply throughout the world has once again shown its significance in the COVID-19 pandemic period. A continuous food supply is possible with correct agricultural programming. An effective agricultural product programming can only be possible by obtaining precise agricultural data. However, it is very difficult to gather accurate agricultural production statistics from all over the world and confirm their accuracy. In this study, the compatibility of the production statistics of six important agricultural products (wheat, rice, potato, onion, banana, apple) which had been collected from local sources, and had published as opensource by the Food and Agriculture Organization of the United Nations, with Benford's law was examined for the first time. Data for the last two decades are used to ignore the impact of annual fluctuations. The compatibility of theoretically expected and observed data was tested by Chi-square (X2) and Mean Absolute Deviation (MAD) tests. Although inconsistencies were found in some data by examining the numbers in the first, second, and first two digits, in general, the MAD test results gave a mostly concordant result.
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In this paper, we construct a hybrid model, consisted of a Bayesian Vector Autoregressive structure with Bayesian stochastic volatility (SVAR-SV), as well as, Fourier Series (FS). We test the model's performance in terms of forecasting ability, comparing it with simple Bayesian stochastic volatility (SV), and also with a classical econometric autoregressive model. By estimating the average prices of the major Food futures in the stock market, and the average prices of the biggest Marine companies' stocks, we test the effect of Covid-19 on these stocks, through the proposed hybrid model, and the impulse-response functions between the aforementioned. Through this approach, we test whether the Covid-19 pandemic hindered the performance of marine companies and affected the food prices, with those two affecting one another. Based on the findings, a shock is apparent from the Food futures to the Marine companies' stocks, and the hybrid model proposed is the best, in terms of forecasting ability.
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Floods are the most commonly occurring natural disaster, with the Centre for Research on the Epidemiology of Disasters 2021 report on "The Non-COVID Year in Disasters" estimating economic losses worth over USD 51 million and more than 6000 fatalities in 2020. The hydrodynamic models which are used for flood forecasting need to be evaluated and constrained using observations of water depth and extent. While remotely sensed estimates of these variables have already facilitated model evaluation, citizen sensing is emerging as a popular technique to complement real-time flood observations. However, its value for hydraulic model evaluation has not yet been demonstrated. This paper tests the use of crowd-sourced flood observations to quantitatively assess model performance for the first time. The observation set used for performance assessment consists of 32 distributed high water marks and wrack marks provided by the Clarence Valley Council for the 2013 flood event, whose timings of acquisition were unknown. Assuming that these provide information on the peak flow, maximum simulated water levels were compared at observation locations, to calibrate the channel roughness for the hydraulic model LISFLOOD-FP. For each realization of the model, absolute and relative simulation errors were quantified through the root mean squared error (RMSE) and the mean percentage difference (MPD), respectively. Similar information was extracted from 11 hydrometric gauges along the Clarence River and used to constrain the roughness parameter. The calibrated parameter values were identical for both data types and a mean RMSE value of ~50 cm for peak flow simulation was obtained across all gauges. Results indicate that integrating uncertain flood observations from crowd-sourcing can indeed generate a useful dataset for hydraulic model calibration in ungauged catchments, despite the lack of associated timing information.
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We all know that the spread of the COVID-19 disease has brought significant restrictions for the whole world, which are also closely related to the business activities of companies. Due to the measures taken by the government of the Slovak Republic, some businesses were limited in the performance of their activities. In order to achieve the goal, in addition to general logical methods, we used hierarchical agglomerative cluster analysis. We chose the ward method as the clustering method. Ward's method of minimum variance is an agglomerative (merging) hierarchical method. Slovak businesses in the field of tourism, the most businesses contained cluster 3, which contained 16 businesses. This most numerous and dominant cluster has an average asset indicator value of 8546978 . In Slovakia, as part of the aid to tourism enterprises at the government level, a call was launched within the framework of the scheme, during which it was possible to draw aid for the months of April to October 2020. This aid was supposed to cover the loss of 10% of their sales to entrepreneurs in the gastronomy and tourism industry.
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In this study, Simple Linear Regression Analysis was carried out to investigate the impact of COVID-19 on Borsa Istanbul Sub-Sectors indices. In the analysis, the number of daily cases of COVID-19 was taken as independent variables, and Borsa Istanbul Sub-Sector (Tourism, Transportation, Textile-Leather, Food-Beverage, Industrial) index data were taken as dependent variables. As the data set, daily data between 11.03.2020-09.04.2021 was preferred. In determining the time interval of the preferred data set, 11 March 2020, when the COVID-19 outbreak was first seen in Turkey, was taken into account. As a result of the analysis, it has been found that the COVID-19 epidemic has a relatively high level of meaningful and negative impact on the Tourism, Textile and Industrial Sector Indices. It has been observed that it has a lower level of meaningful and negative effect on the Food-Beverage and Transportation Indices.
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Sport and physical activity contribute to people's physical, mental, and social health. The state of students' physical ability is an accurate and objective indicator, with the help of which the influence and efficiency of the educational process in physical education and sports can be revealed. The aim of this study was to determine the level of development of the physical ability of students in 5th and 6th grade, through analysis and evaluation, according to the new regulatory system for evaluation. The research was carried out with 75 pupils at a secondary school in the city of Sofia. To realize it, we used a test battery that carries information about the significant indexes of physical fitness. The battery includes five tests: running 30 m., standing long jump with both feet, 3 kg medicine ball throwing with both hands from a standing position, running 200 m., and agility and spatial coordination test. The testing and mathematical-statistical methods (variation analysis comparative analysis with t-criterion of Student and sigma evaluation method) were used in our study. The analysis of the results showed that there was a statistically significant difference between the students from 5th and 6th grade, only in terms of the indicator of agility and spatial coordination. Such a difference was found in the same test, by gender and age, among the boys from the two study groups. Our research showed that the state of physical ability of the students participating in the study was at a good level, which corresponds to the average in the country.
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Background: Robust data of IL-6 is available in bacterial infection, and now it can be utilized in currently ongoing COVID-19 (corona virus disease-19) pneumonia pandemic to guide treatment strategy as marker of inflammation. Methods: Prospective, observational study included 1,000 COVID-19 cases confirmed with RT PCR (reverse transcription polymerase chain reaction). All cases were undergone categorized after clinical details, HRCT (high resolution computerized tomography) thorax, oxygen saturation, IL-6 (interleukin 6) at entry point and follow up. Age, gender, comorbidity and use BIPAP/NIV (bilevel positive airway pressure/non-invasive ventilation), and outcome as with or without lung fibrosis as per HRCT severity were key observations. Statistical analysis is done by using Chi-square test. Results: In study of 1,000 COVID-19 pneumonia cases, age (<50 and >50 years) and gender has significant association with IL-6. HRCT severity score at entry point has significant correlation with IL-6 level (p < 0.00001). IL-6 level has significant association with duration of illness (p < 0.00001). Comorbidities has significant association with IL-6 level (p < 0.00001). IL-6 level has significant association with oxygen saturation (p < 0.00001). BIPAP/NIV requirement has significant association with IL-6 level (p < 0.00001). Timing of BIPAP/NIV requirement during course of hospitalization has significant association with IL-6 level (p < 0.00001). Follow-up IL-6 titer during hospitalization as compared to entry point normal and abnormal IL-6 has significant association with post-COVID-19 lung fibrosis, respectively (p < 0.00001). Conclusion: IL-6 has very crucialrole in COVID-19 pneumonia in predicting severity of illness, progression of illness including 'cytokine storm' and assessing response to treatment during hospitalization and follow-up titers in analyzing post-COVID-19 lung fibrosis.
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In this work we analyze the effectiveness of vaccination strategies for the COVID-19 epidemic in the Brazilian state of Minas Gerais. Firstly we study the effectiveness of general vaccination in the decreasing of the number of infected individuals using a traditional non structured SEIR model. Secondly we consider an age-structured SEIR model with three age classes (youngster, adult and elderly) and we analyze the current strategy in the Brazilian state of Minas Gerais, of focusing the vaccination on the elderly group. We conclude by showing this strategy to be mistaken and that a vaccination focusing on the age group of the adults would be much more efficient in decreasing the total number of infected individuals.
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Purpose: The paper provides a summary of the findings from GOOD Awaits - The Regenerative Tourism New Zealand (NZ) Podcast and envisions a regenerative future for tourism in Aotearoa. Design/methodology/approach: This paper is based on the findings from the GOOD Awaits Podcast, a series of interviews with pioneers and practitioners of regenerative tourism. The podcast was created as a platform for the collective discovery of a new way forward for tourism in the wake of COVID-19, and the series provides a detailed summary of the regenerative tourism movement in NZ. Findings: Through these interviews, a vision for a regenerative visitor economy in Aotearoa emerged. This new model is rooted in indigenous knowledge and living systems theory. It is a paradigm shift that allows us to see tourism as a living ecosystem and requires innovative economic models, such as social entrepreneurship, systems level changes to the way tourism operates and is governed, local tourism solutions with community thriving as the primary aim and much more collaboration both within tourism and across sectors. Originality/value: Regenerative tourism is an emerging model and one that is rapidly gaining traction in NZ and globally. The GOOD Awaits podcast is a unique, thoughtful and practical demonstration of what this model could look like in Aotearoa. It demonstrates the potential and feasibility of regenerative tourism practice, and the response has shown the desire for these conversations at a national and international scale. This paper is an accessible summary of the podcast's first season and has value for anyone interested in the regenerative tourism movement in Aotearoa.
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Food supply chains (FSCs) have long been exposed to environmental variability and shock events caused by various economic, political, and infrastructural factors. The outbreak of the COVID-19 pandemic has further exposed and identified the vulnerability of FSCs, and promoted integrated optimization approaches for building resilience. However, existing works focusing on general supply chains (SCs) and FSCs have not been fully aware of the distinct characteristics of FSCs in green logistics, i.e., the expiration of fresh products. In reality, perishable food materials can be processed into products of different processing levels (i.e., multi-level processing) for longer shelf lives, which can serve as a timely and economic strategy to increase safety stocks for mitigating disruption risks. Motivated by this fact, we study the problem of enhancing FSC with a multi-level processing strategy. An integrated location, inventory, and distribution planning model for a multi-echelon FSC under COVID-19-related disruptions is formulated to maximize the total profit over a finite planning horizon. Specifically, a two-stage stochastic programming model is presented to hedge against disruption risks, where scenarios are generated to characterize geographical impact induced by source-region disruptions. For small-scale problems, the model can be solved with commercial solvers. To exactly and efficiently solve the large-scale instances, we design an integer L-shaped method. Numerical experiments are conducted on a case study and randomly generated instances to show the efficiency of our model and solution method. Based on the case study, managerial insights are drawn.
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Lake eutrophication has become a critical environmental issue due to the global effects of anthropogenic activities and climate change, and has been comprehensively studied for many years. A series of models and indicators have been proposed to assess the trophic state of lakes. The trophic state index (TSI) is a synthetic index that integrates chlorophyll-a, water clarity, and total phosphorus and is widely used to evaluate the trophic state of aquatic environments. In this study, we collected in situ lake samples (N = 431) from typical lakes to match Sentinel-2 MultiSpectral Instrument (MSI) imagery data using the Case 2 Regional Coast Color processor. Then we developed a new empirical model, TSI = -34.04 x (band 4/band 5) - 1.114 x (band 1/band 4) + 97.376. This model is valid for all of China, with good performance and few errors (RMSE = 7.36;MAE = 6.25) for the validation dataset. Recognizing that over 94% of the Chinese population located along eastern watersheds and large lakes have competing water uses, and given the TSI model on the seasonal scales, we further estimated the mean TSI and trophic state in eastern Chinese lakes (> 100 km2) from 2019 to 2020. The results revealed that more lakes were eutrophic in autumn (94.28%) than in spring (> 77.14%), indicating a serious eutrophication of eastern lakes. Although the eastern lakes have been studied in more detail, this study found that eutrophication still has markedly negative impacts on lake ecosystems. In addition, no significant improvement was observed in spring, most likely due to the months of curfew/lockdown from January 2020 onwards due to COVID-19. This may be due to the enrichment of nutrients deposited in sediment or watershed soil, which can be characterized as "autochthonous sources" of lake eutrophication, over decades with high rates of economic development. This study demonstrates the applicability of Sentinel-2 MSI data to monitor lake eutrophication as well as the feasibility of blue/red and red/red edge combinations. The framework and TSI model used bands available on MSI sensors to develop a novel approach for generating historical eutrophication data for large-scale evaluation of and decision-making related aquatic environmental changes, even in poorly studied areas.