Impact and mechanism of the COVID-19 on the spatio-temporal patterns of Zhangjiajie tourism network attention

Based on the spatial-temporal perspective of geography, this paper quantitatively measures the impact of COVID-19 on the spatial-temporal pattern of tourism network attention in Zhangjiajie, and finally summarizes the influencing factors and mechanisms. The results show as follows. (1) From the perspective of time, the online attention of tourism in Zhangjiajie shows a trend of "decline to rebound, and to stability", which reflects the temporal mobility of the effect of COVID-19 on the tourism. (2) From the spatial dimension, the scale-order of attention to the Zhangjiajie' s tourism network is relatively stable, and the effect of COVID-19 on the tourism shows a trend of "distance decay" on the whole. (3) The adjustment of tourists' perception of tourism risk, destination familiarity and location, tourists' risk tolerance and authority restriction are the influencing factors of tourism net-work attention. These factors interact with each other to drive the spatio-temporal change of tourism network attention.

Analysis of social and psychological factors influencing the treatment of patients with chronic kidney disease under the regular epidemic prevention and control of coronavirus disease 2019.

Objective To explore the sociodemographic and psychological factors influencing the continuity of treatment of patients with chronic kidney disease under the regular epidemic prevention and control of coronavirus disease 2019 (COVID-19). Methods A total of 277 patients with chronic kidney disease who were admitted to Department of Nephrology, The First Affiliated Hospital of Naval Medical University (Second Military Medical University) from Apr. 2020 to Mar. 2021 were enrolled and divided into 3 groups: non-dialysis group (n=102), hemodialysis (HD) group (n=108), and peritoneal dialysis (PD) group (n=67). All patients were investigated by online and offline questionnaires, including self-designed basic situation questionnaire, self-rating anxiety scale (SAS), and self-rating depression scale (SDS). The general sociodemographic data, anxiety and depression of the 3 groups were compared, and the influence of sociodemographic and psychological factors on the interruption or delay of treatment was analyzed by binary logistic regression model. Results There were significant differences in age distribution, marital status, occupation, medical insurance type, caregiver type, whether there was an urgent need for hospitalization and whether treatment was delayed or interrupted among the 3 groups (all P0.05). The average SAS score of 65 PD patients was 38.15+/-15.83, including 53 (81.5%) patients without anxiety, 7 (10.8%) patients with mild anxiety, and 5 (7.7%) patients with moderate to severe anxiety. The average SAS score of 104 patients in the HD group was 36.86+/-14.03, including 81 (77.9%) patients without anxiety, 18 (17.3%) patients with mild anxiety, and 5 (4.8%) patients with moderate to severe anxiety. There were no significant differences in the mean score of SAS or anxiety severity grading between the 2 groups (both P0.05). The mean SDS scores of 65 PD patients were 53.42+/-13.30, including 22 (33.8%) patients without depression, 21 (32.3%) patients with mild depression, and 22 (33.8%) patients with moderate to severe depression. The mean SDS scores of 104 patients in the HD group were 50.79+/-10.76, including 36 (34.6%) patients without depression, 56 (53.8%) patients with mild depression, and 12 (11.6%) patients with moderate to severe depression. There were no significant differences in mean SDS scores or depression severity grading between the 2 groups (both P0.05). The results of intra-group comparison showed that the incidence and severity of depression were higher than those of anxiety in both groups. Multivariate binary logistic regression analysis showed that high school education level (odds ratio OR=5.618, 95% confidence interval CI) 2.136-14.776, P0.01), and unmarried (OR=6.916, 95% CI 1.441-33.185, P=0.016), divorced (OR= 5.588, 95% CI 1.442-21.664, P=0.013), urgent need for hospitalization (OR=8.655, 95% CI 3.847-19.476, P0.01) could positively promote the continuity of treatment in maintenance dialysis patients under the regular epidemic prevention and control of COVID-19. In the non-dialysis group, no sociodemographic and psychological factors were found to be associated with the interruption or delay of treatment (P0.05). Conclusion Education, marital status, and urgent need for hospitalization are correlated with the continuity of treatment in patients with chronic kidney disease on maintenance dialysis.Copyright © 2022, Second Military Medical University Press. All rights reserved.

Analysis of pathogen detection results of upper respiratory tract specimens from fever clinic patients

Objective: To explore the pathogen composition and distribution characteristics of pathogens in respiratory samples from patients with fever of unknown origin. Methods: A total of 96 respiratory samples of patients with unknown cause fever with respiratory symptoms were collected from four hospitals above grade II in Shijiazhuang area (Hebei Provincial Hospital of Traditional Chinese Medicine, Luancheng District People's Hospital, Luquan District People's Hospital, Shenze County Hospital) from January to April 2020, and multiplex-fluorescent polymerase chain reaction(PCR)was used to detect influenza A virus, influenza B virus, enterovirus, parainfluenza virus I/II/III/IV, respiratory adenovirus, human metapneumovirus, respiratory syncytial virus, human rhinovirus, human bocavirus, COVID-19, Mycoplasma pneumoniae, Chlamydia pneumoniae, Legionella pneumophila, Pseudomonas aeruginosa, Streptococcus pneumoniae, Klebsiella pneumoniae, Group A streptococcus, Haemophilus influenzae, Staphylococcus aureus nucleic acid detection, the results were analyzed for chi-square. Results: A total of 8 pathogens were detected in the upper respiratory tract samples of 96 fever patients, including 1 kind of virus, 6 kinds of bacterias, and Mycoplasma pneumoniae. There were 12 viruses including influenza virus and parainfluenza virus, Legionella pneumophila and Chlamydia pneumoniae were not detected. The pathogen detection rates in descending order were Streptococcus pneumoniae (58/96, 60.42%), Haemophilus influenzae(38/96, 39.58%), Klebsiella pneumoniae (14/96, 14.58%), Staphylococcus aureus (10/96, 10.42%), Mycoplasma pneumoniae (8/96, 8.33%), Pseudomonas aeruginosa (6/96, 6.25%), Group A streptococcus (4/96, 4.17%) and human rhinovirus (2/96, 2.08%). The proportions of single-pathogen infection and multi-pathogen mixed infection in fever clinic patients were similar, 41.67% (40/96) and 45.83% (44/96), respectively, and 12.50% (12/96)of the cases had no pathogens detected. The infection rate of Mycoplasma pneumoniae in female patients with fever (21.43%) was higher than that in male patients with fever (2.94%) (P < 0.05). There was no statistical difference between the distribution of of other pathogens and gender and age(P > 0.05). Conclusions: The upper respiratory tract pathogens were mainly bacterial infections, and occasional human rhinovirus and Mycoplasma pneumonia infections. In clinical diagnosis and treatment, comprehensive consideration should be given to the pathogen detection.

Implementation and Application of Large-Scale Drug Virtual Screening

The molecular docking-based virtual screening technique evaluates the binding abilities between multiple ligand compounds and receptors to screen for the active compounds. In the context of the global spread of the COVID-19 pandemic, large-scale and rapid drug virtual screening is crucial for identifying potential drug molecules from massive datasets of ligand structures. The powerful computing power of supercomputer provides hardware guarantee for drug virtual screening, but the super large-scale drug virtual screening still faces many challenges that affects the effective execution of the calculation. Based on the analysis of the challenges, this paper proposes a centralized task distribution scheme with a central database, and designs a multi-level task distribution framework. The challenges are effectively solved through multi-level intelligent scheduling, multi-level compression processing of massive small molecule files, dynamic load balancing and high error tolerance management technology. An easy-touse"tree”multi-level task distribution system is implemented. A fast, efficient and stable drug virtual screening task distribution, calculation and result analysis function is realized, and the computing efficiency is nearly linear. Then, heterogeneous computing technology is used to complete the drug virtual screening of more than 2 billion compounds, for two different active sites for COVID-19, on the domestic super computing system, which provides a powerful computing guarantee for the super large-scale rapid virtual screening of explosive malignant infectious diseases. © 2023, Journal of Computer Engineering and Applications Beijing Co., Ltd.;Science Press. All rights reserved.

COVID-19: Agent-Based Simulation-Optimization to Vaccine Center Location Vaccine Allocation Problem

This paper presents an agent-based simulation-optimization modeling and algorithmic framework to determine the optimal vaccine center location and vaccine allocation strategies under budget constraints during an epidemic outbreak. Both simulation and optimization models incorporate population health dynamics, such as susceptible (S), vaccinated (V), infected (I) and recovered (R), while their integrated utilization focuses on the COVID-19 vaccine allocation challenges. We first formulate a dynamic location-allocation mixed-integer programming (MIP) model, which determines the optimal vaccination center locations and vaccines allocated to vaccination centers, pharmacies, and health centers in a multi-period setting in each region over a geographical location. We then extend the agent-based epidemiological simulation model of COVID-19 (Covasim) by adding new vaccination compartments representing people who take the first vaccine shot and the first two shots. The Covasim involves complex disease transmission contact networks, including households, schools, and workplaces, and demographics, such as age-based disease transmission parameters. We combine the extended Covasim with the vaccination center location-allocation MIP model into one single simulation-optimization framework, which works iteratively forward and backward in time to determine the optimal vaccine allocation under varying disease dynamics. The agent-based simulation captures the inherent uncertainty in disease progression and forecasts the refined number of susceptible individuals and infections for the current time period to be used as an input into the optimization. We calibrate, validate, and test our simulation-optimization vaccine allocation model using the COVID-19 data and vaccine distribution case study in New Jersey. The resulting insights support ongoing mass vaccination efforts to mitigate the impact of the pandemic on public health, while the simulation-optimization algorithmic framework could be generalized for other epidemics. [ FROM AUTHOR] Copyright of IISE Transactions is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Concept Drift Adaptation Methods under the Deep Learning Framework: A Literature Review

With the advent of the fourth industrial revolution, data-driven decision making has also become an integral part of decision making. At the same time, deep learning is one of the core technologies of the fourth industrial revolution that have become vital in decision making. However, in the era of epidemics and big data, the volume of data has increased dramatically while the sources have become progressively more complex, making data distribution highly susceptible to change. These situations can easily lead to concept drift, which directly affects the effectiveness of prediction models. How to cope with such complex situations and make timely and accurate decisions from multiple perspectives is a challenging research issue. To address this challenge, we summarize concept drift adaptation methods under the deep learning framework, which is beneficial to help decision makers make better decisions and analyze the causes of concept drift. First, we provide an overall introduction to concept drift, including the definition, causes, types, and process of concept drift adaptation methods under the deep learning framework. Second, we summarize concept drift adaptation methods in terms of discriminative learning, generative learning, hybrid learning, and others. For each aspect, we elaborate on the update modes, detection modes, and adaptation drift types of concept drift adaptation methods. In addition, we briefly describe the characteristics and application fields of deep learning algorithms using concept drift adaptation methods. Finally, we summarize common datasets and evaluation metrics and present future directions.

Perspectives towards hotel stay amidst the COVID-19 pandemic recovery stage: a research from Calamba city, Philippines

After the global tourism industry has experienced the impact of the pandemic, it is critical that people gain confidence in traveling and have the impression that staying in hotels is now safe, because only in this way tourism businesses such as hotels can be fully successful in recovering. For this reason, the researchers guided by a descriptive research design and quantitative research approach, aimed to determine what people think about staying in a hotel, particularly in terms of safety and security, price, location, and service quality, in the time of COVID-19 pandemic recovery stage, focused on the local community of Calamba City, Laguna, Philippines, being one of richest cities in the country and the place where the researchers reside. Moreover, a comparative analysis of the perspective of the respondents has been performed in terms of their age, sex, and educational attainment, identifying which age, sex and educational attainment groups have more positive or negative attitude, and a higher or lower level of hotel stay intention compared with other groups. Being the first study that has assessed the tourism market particularly in terms of their perspective on hotel stay as the hospitality industry attempts to recover from the impact of the pandemic, this is expected to provide a clear picture of the need for management of hotels to continuously work on marketing efforts highlighting the information that it is now safe to practice tourism and stay in their establishments, hence, serving as a guide in coming up with promotional strategies and an action plan, as well as a motivation for researchers who wish to determine the same in their locality or country.

Transmission of broiler egg prices between surplus and deficit areas: exploring the dynamics

Broiler chicken eggs are one of the main and strategic foods for the people of Indonesia and contribute to regional and national inflation. Broiler egg production in Indonesia differs between regions. Areas with a surplus of eggs tend to have lower prices than areas with a deficit. This research is to measure the transmission of broiler egg prices between markets in surplus and deficit areas, using weekly price time series data for the period January 2018-December 2021. Areas of surplus broiler eggs, East Java Province (the highest broiler egg production in Indonesia) which become one of the main suppliers to the Province of East Nusa Tenggara as a deficit area. Using the Johannsen cointegration test it is found that there is no cointegration or there is no relationship between the surplus and deficit regions in the long term but not in the short term. Factors of marketing infrastructure, market information systems, and geographical conditions can be obstacles to the absence of cointegration. The VAR (Vector Auto-Regressive) Vector Error Correction model (VECM) test, found that price transmission occurred between surplus and deficit areas, meaning that between the two regions, there was market integration prior to Covid. The transmission has weakened, and due to the Covid situation, there have been restrictions on the movement of people and goods. The government and other market players need to study the response of the broiler egg market, in the short and long term so that market players can make the right policies.

Pandemi Sürecinde Devletin Geri Dönüşü: Fransa ve Türkiye Örnekleri

Bu çalışmada pandemi sürecinde devletin rolü ve işlevleri Fransa ve Türkiye örnekleri üzerinden karşılaştırmalı olarak ele alınmaktadır. Kovid-19 pandemisinin kamu sağlığı güvenliği açısından yarattığı aciliyet, şok ve kriz ortamı, kamusal otoritelerin önlem alma pratiklerini dönüştürürken her ülkenin, sınırlarını ve güvenlik politikalarını yeniden gözden geçirmesine yol açmıştır. 1980'lerden itibaren refah politikalarından rekabetçi politikalara geçiş, ulusal sınırların esnekleşip uluslararası sermayeye açılması;küreselleşme ve kozmopolitleşme yönünde güçlü bir irade olduğu sanısını yaratmıştır. Ancak pandeminin yarattığı koşullara verilen tepki bunun aksi yönde sonuç vermiştir: Korumacı ekonomi politikalarının, gelir dağıtıcı yaklaşımının yanı sıra ulusal sınırların ve milliyetçi reflekslerin yükselişine şahit olunmuştur. Bu çalışmada bu gelişmelerin pandemi dönemi ile sınırlı ve geçici bir refleks olmayıp post-pandemik toplumsal koşullarda da süreceği iddia edilmekte ve bu süreci anlamak için devletin dönüşümü üzerinden bir okuma önerilmektedir. Çalışmada, hukuki bilgi ve belgelerin yanı sıra aktörlerin açıklamaları ve basına yansıyan haberler incelenmekte ve bahsi geçen dönüşümün sebepleri, mahiyeti ve olası sonuçları betimleyici ve yorumlayıcı yöntemle ele alınmaktadır.Alternate :In this study, the role and functions of the state in the pandemic process are discussed comparatively through the examples of France and Turkey. The urgency, shock, and crisis environment created by the Covid-19 pandemic in terms of public health security have led each country to reconsider its borders and security policies while transforming the precautionary practices of public authorities. Since the 1980s, it has been assumed that there was a strong will for the transition from welfare policies to competitive policies and the flexibility of national borders for strengthening globalization and cosmopolitanism. However, the reaction to the conditions created by the pandemic resulted in the opposite direction: The rise of national borders and nationalist reflexes, as well as the protectionist economic policies and income distribution approach, were witnessed. In this study, it is claimed that these developments will not be a temporary reflex limited to the pandemic period but will continue in post-pandemic social conditions. In addition, it will be suggested that an analysis of the transformation of the state in a historical process is crucial to understand this process. In addition to the legal information and documents, the explanations of the actors and the news will be examined, and the reasons, nature, and possible consequences of the transformation will be discussed with a descriptive and interpretive method.

Poverty and income distribution incidence of the COVID-19 outbreak: investigating socially responsible policy alternatives for Turkey

To counterbalance the deep systemic global crisis triggered by the COVID-19, many countries introduced a vast arsenal of fiscal policy instruments coupled with monetary accommodation. Yet, Turkey's response had almost exclusively relied on credit expansion and loan guarantees while minimizing the role of fiscal policy. Within that context, this article has three interrelated objectives. Firstly, we evaluate the effects of the crisis and the implemented policies on poverty and income distribution. Second, we measure the macroeconomic impacts of COVID-19 on the Turkish economy through a general equilibrium model. We find that these policies had a limited impact on reducing crisis-induced poverty. Finally, we propose alternatives to mitigate the effects of the COVID-19 crisis, which are compatible with fiscal constraints. Our results suggest that by pursuing a targeted fiscal income transfer programme covering wage earners and small-sized enterprises, Turkey could have achieved a more egalitarian and effective response to the Covid-19 crisis. [ FROM AUTHOR] Copyright of Journal of Southeast European & Black Sea Studies is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Building Geographic Information System Story Maps for Jakarta's Local Community Health Infrastructures Awareness

COVID-19 is caused by the novel coronavirus SARS-CoV-2. First started in Wuhan, COVID-19 has spread everywhere, including Indonesia. COVID-19 can cause severe pneumonia, severe acute respiratory distress syndrome (ARDS) symptoms, and multiple organ failure. According to the WHO, COVID-19 generally has an incubation period of 5-6 days, ranging from 1 to 14 days. However, in Jakarta, the cases have decreased significantly since the implementation of PPKM (Restrictions of Activity), running since early July 2021. The government claimed that the PPKM rule has significantly impacted COVID-19 cases, decreasing every day, especially in Jawa-Bali Region. In addition, the Vaccination rate in Indonesia also played a significant part in decreasing COVID-19 cases, with Jakarta currently standing with 9 million people fully vaccinated per December 2021. To monitor the development of COVID-19 in Jakarta and provide information to the public about health facilities, especially hospitals in Jakarta, in this study, the distribution area of COVID-19 cases will be mapped with CHIME using ArcGIS Online tools. The analysis results obtained based on the mapping results that most cases were in the Cengkareng area, and the area with the most hospitals werein East Jakarta. © 2022 IEEE.

Impact of COVID-19, Lockdowns and Economic Slowdown on Food and Nutrition Security in India

The two waves of the COVID-19 pandemic in India have resulted in widespread food insecurity and hunger in the country as a result of the burden of health expenditure and illness, economic slowdown and loss of livelihoods. Given the context of high levels of malnutrition and some reversal in the gains made in the last decade, this could have serious long-term implications. The response of the government in the form of additional benefits for PDS beneficiaries and some continuation of school meals and supplementary nutrition under ICDS scheme has been inadequate. This paper argues that there is a need to use the pandemic as an opportunity to expand and strengthen these schemes with a view of making the food system more equitable. As immediate measures, universalisation of the PDS including pulses and oil and strengthening of direct nutrition programmes for children and women are imperative. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

Unraveling the Impact of COVID-19 Pandemic Dynamics on Commercial Water-Use Variation

Water use was impacted significantly by the COVID-19 pandemic. Although previous studies quantitatively investigated the effects of COVID-19 on water use, the relationship between water-use variation and COVID-19 dynamics (i.e., the spatial-temporal characteristics of COVID-19 cases) has received less attention. This study developed a two-step methodology to unravel the impact of COVID-19 pandemic dynamics on water-use variation. First, using a water-use prediction model, the water-use change percentage (WUCP) indicator, which was calculated as the relative difference between modeled and observed water use, i.e., water-use variation, was used to quantify the COVID-19 effects on water use. Second, two indicators, i.e., the number of existing confirmed cases (NECC) and the spatial risk index (SRI), were applied to characterize pandemic dynamics, and the quantitative relationship between WUCP and pandemic dynamics was examined by means of regression analysis. We collected and analyzed 6-year commercial water-use data from smart meters of Zhongshan District in Dalian City, Northeast China. The results indicate that commercial water use decreased significantly, with an average WUCP of 59.4%, 54.4%, and 45.7%during the three pandemic waves, respectively, in Dalian. Regression analysis showed that there was a positive linear relationship between water-use changes (i.e., WUCP) and pandemic dynamics (i.e., NECC and SRI). Both the number of COVID-19 cases and their spatial distribution impacted commercial water use, and the effects were weakened by restriction strategy improvement, and the accumulation of experience and knowledge about COVID-19. This study provides an in-depth understanding of the impact of COVID-19 dynamics on commercial water use. The results can be used to help predict water demand under during future pandemic periods or other types of natural and human-made disturbance.

Food commerce upshots with their former locus in the economy with respect to the pandemic 2020 - a drawback or an aid in South Kolkata, West Bengal

Background: The Food Commerce industry has flourished massively during the past decade in South Kolkata in West Bengal, with new outlets opening every now and then, so much so that this region is known as 'Food Street'. Regardless of their scale of operations, each of these outlets had well established themselves, catering to their respective target markets and earning decent amount of revenue over the years. However, this growth suffered a setback owing to the origin of novel Coronavirus SARS-n-CoV-2. The growth rate declined to a great extent over the span of two years, with recent studies showing an overall stunted growth rate. Even though online marketing of these outlets and selling the food through delivery apps have aided the entrepreneurs, the cost to revenue ratio is not at par with that of the times before the pandemic hit. Overall, the pandemic has impacted the eateries in more way than initially imagined. Objectives: (a) To reveal the various problems and scenarios of managing food business during the Covid-19 pandemic in South Kolkata region;(b) To compare the present scenario of the food industry with how things were before prior to the pandemic to understand the nature of change during this time frame;and, (c) To describe the challenges and methods implemented by the food retail business entrepreneurs and managers of the randomly selected establishments to hold a steady business flow during the Covid-19 pandemic. Methodology: The study follows a descriptive research design. Therefore, the research will describe the characteristics of the sample under study. The food outlets of South Kolkata have been chosen as the study location. 100 respondents were selected. The respondents are those who consume food from these outlets such that they represent the wider target market of the 'Food Street'. Both Primary Data and Secondary Data were used. Primary Data was collected through sample survey. Random Sampling technique was used to choose the respondents. The study used quantitative data, therefore, only Quantitative analysis was performed. Results: The Research was able to depict the comparison between the present scenario and the situation prior to the pandemic. The study was able to reveal the challenges and problems that the food outlets had to suffer from. Also, the methods or strategies taken up by the entrepreneurs of these outlets to overcome the pandemic were discovered. 46% of the respondents opted for "Mobile Food Delivery" as their strategy to revive from losses. Conclusion: With COVID-19 having altered - and still in the process of altering - the definition of "normal" across the world, most industries are still scrambling to adjust. The effect on the restaurant industry has been particularly dramatic. With restaurants and pubs closed for sit-down service, many establishments are struggling to keep their heads above water. The food outlets located in South Kolkata shares the same fate and the research is able to highlight this effectively.

Cardiac manifestations of post-COVID syndrome in children and adolescents.

The aim of the research. To study the features of cardiovascular system disorders in post-covid syndrome (PCS) in children and adolescents after a mild form of coronavirus infection (COVID-19). Material and methods. From 260 children and adolescents after a mild form of COVID-19, a total of 30 patients aged 7-17 years with cardiac manifestations of PCS were selected. Therewith, 32 patients with an uncomplicated form of the disease were selected to form a comparison group. In 3 and 6 months after disease onset, a comprehensive examination of patients was performed with a questionnaire on the subjective scale for MFI-20 assessment asthenia (Multidimensional Fatigue Inventory-20), electrocardiography (ECG), echocardiography;daily monitoring of ECG and blood pressure. The biochemical blood test included assay of creatine phosphokinase-MB (CPK-MB), troponin I and lactate dehydrogenase (LDH). Results. The incidence of PCS with cardiac manifestations amounted to 11.5 %. After 3 months from the disease onset, complaints of pain and discomfort in the chest, palpitations, fatigue, and poor exercise tolerance persisted. Asthenic syndrome was diagnosed in 70 % of patients. The "general asthenia" indicator totalled14 [12;16] points (p<0.001) and was associated with the age of patients (r=+0.5;p<0.05). Arrhythmic syndrome and conduction disorders were detected in 67% of children. Labile arterial hypertension and hypotension occurred in 23 % of the adolescents. The increase in CPK-MB remained in 17% of the children, LDH - in 10%. In the sixth month after the onset of the disease, there were no significant differences in the results of the examination in the observation groups. However, a decrease in the level of resistance within 6 months was recorded in 43.3% of the schoolchildren with PCS (p<0.001). Conclusion. The data obtained indicate the need for early verification of cardiopathies in children with COVID-19, determination of a set of therapeutic and rehabilitation measures as well as ECG monitoring.Copyright © 2022, Krasnoyarsk State Medical University. All rights reserved.

Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly Intractable Bayesian Inference

In this article, a multivariate count distribution with Conway-Maxwell (COM)-Poisson marginals is proposed. To do this, we develop a modification of the Sarmanov method for constructing multivariate distributions. Our multivariate COM-Poisson (MultCOMP) model has desirable features such as (i) it admits a flexible covariance matrix allowing for both negative and positive nondiagonal entries;(ii) it overcomes the limitation of the existing bivariate COM-Poisson distributions in the literature that do not have COM-Poisson marginals;(iii) it allows for the analysis of multivariate counts and is not just limited to bivariate counts. Inferential challenges are presented by the likelihood specification as it depends on a number of intractable normalizing constants involving the model parameters. These obstacles motivate us to propose Bayesian inferential approaches where the resulting doubly intractable posterior is handled with via the noisy exchange algorithm or the Grouped Independence Metropolis–Hastings algorithm. Numerical experiments based on simulations are presented to illustrate the proposed Bayesian approach. We demonstrate the potential of the MultCOMP model through a real data application on the numbers of goals scored by the home and away teams in the English Premier League from 2018 to 2021. Here, our interest is to assess the effect of a lack of crowds during the COVID-19 pandemic on the well-known home team advantage. A MultCOMP model fit shows that there is evidence of a decreased number of goals scored by the home team, not accompanied by a reduced score from the opponent. Hence, our analysis suggests a smaller home team advantage in the absence of crowds, which agrees with the opinion of several football experts. Supplementary materials for this article are available online.

Proximity tourism: an observational analysis of the use of Instagram to promote the northeast of Brazil. (Special Issue: Tourism in the northeast.)

With the changes in consumer profile, especially in tourism activity, facing the issues brought by globalization, greater access to and use of Technologies, and more recently, the restrictions imposed by the protocols to prevent contamination by the Covid-19 virus and its consequences, it has been necessary to change the way of experiencing tourism, leading the market to adapt to the new reality. Thus, the incentive to implement so-called Proximity Tourism has gathered strength, prompting the following research question: how has this type of tourism been addressed and how have the cities of the Brazilian Northeast have been working with this theme to promote their potential on the social network platform Instagram? The main objective of this study was to perform an observational analysis of what is being posted on this social network concerning proximity tourism, by investigating the use of the hashtag #turismodeproximity, and whether the cities of the Northeast of Brazil are using this Instagram tool. As the result of this research, it was found that of the total posts indexed with this hashtag, only a small number are directly related to this region, indicating a lack of dissemination, and consequently, failure to generate greater visibility for this tourism modality.

COVID-19 impacts on United States crawfish. (Special Issue: COVID-19 impacts on selected commodities.)

This research determines the impacts of COVID-19 US on crawfish production and consumption for 2020 and 2021 using an Equilibrium Displacement Model. In the US, crawfish is one of the seafood commodities where most production is consumed by domestic consumers (7% of domestic consumption is from imports). Crawfish and rice are complementary. Therefore, the impacts of COVID-19 on crawfish consumption simultaneously influence rice production and crawfish producers and consumers. In the first year of COVID-19 (2020), the reduction in crawfish retail demand caused negative effects on final consumers and producers. However, crawfish consumption recovered significantly in the second year (2021), which could compensate for the loss in 2020. Overall, consumer and producer gains ranged from $549 to $626 million if the COVID-19 pandemic only impacted retail consumption. However, in 2021, the increase in production costs due to higher oil/diesel prices and other input prices caused the farm supply to decrease. As a result, total welfare gains ranged from $200 to $228 million. If the demand in 2021 did not increase, but the crawfish farm supply decreased, consumer and producer losses ranged from $929 to $1045 million. Overall, the total effects of COVID-19 on consumers and producers for 2020 and 2021 depend on its effects in 2021. If the demand in 2021 increased following the decrease in farm supply, consumers and producers would benefit from the shocks of COVID-19 due to higher post-COVID-19 demand.

The Markov Bernoulli Lomax with Applications Censored and COVID-19 Drought Mortality Rate Data

In this article, we present a Markov Bernoulli Lomax (MB-L) model, which is obtained by a countable mixture of Markov Bernoulli and Lomax distributions, with decreasing and unimodal hazard rate function (HRF). The new model contains Marshall- Olkin Lomax and Lomax distributions as a special case. The mathematical properties, as behavior of probability density function (PDF), HRF, rth moments, moment generating function (MGF) and minimum (maximum) Markov-Bernoulli Geometric (MBG) stable are studied. Moreover, the estimates of the model parameters by maximum likelihood are obtained. The maximum likelihood estimation (MLE), bias and mean squared error (MSE) of MB-L parameters are inspected by simulation study. Finally, a MB-L distribution was fitted to the randomly censored and COVID-19 (complete) data. © 2023 by the authors.

Arbovirus and its potential to lead the next global pandemic from sub-Saharan Africa: What lessons have we learned from COVID-19?

Risk and predisposing factors for viral zoonoses abound in the sub-Saharan Africa (SSA) region with significant public health implications. For several decades, there have been several reports on the emergence and re-emergence of arbovirus infections. The lifetime burden of arboviral diseases in developing countries is still poorly understood. Studies indicate significant healthcare disruptions and economic losses attributed to the viruses in resource-poor communities marked by impairment in the performance of daily activities. Arboviruses have reportedly evolved survival strategies to aid their proliferation in favorable niches, further magnifying their public health relevance. However, there is poor knowledge about the viruses in the region. Thus, this review presents a survey of zoonotic arboviruses in SSA, the burden associated with their diseases, management of diseases as well as their prevention and control, mobility and determinants of infections, their vectors, and co-infection with various microorganisms. Lessons learned from the ongoing coronavirus disease 2019 (COVID-19) pandemic coupled with routine surveillance of zoonotic hosts for these viruses will improve our understanding of their evolution, their potential to cause a pandemic, control and prevention measures, and vaccine development.Copyright © GERMS 2022.