Features of the course and medical and social aspects of a new coronavirus infection in the Republic of Tajikistan

The aim - to assess some medical and social aspects of the epidemic process during the first wave of a new coronavirus infectious disease - COVID-19 in the Republic of Tajikistan. Material and methods. The retrospective study was conducted on the basis of an epidemiological analysis of official statistics as part of the epidemiological surveillance of COVID-19 from April 2020 to April 2021. Results and discussion. At the beginning of April 2021, a total of 13 308 cases of COVID-19 were registered, of which the proportion of recovered was 99.3% (13 218 cases), and the number of cases with a fatal outcome was 0.68% (90 cases;the average age of the deceased was 62.3+/-0.07 years). The peak of infection during the first wave occurred in May and June 2020, when the average daily increase was 97 people. For 2 months of the epidemic in the republic, 44.6% of the total number of patients with COVID-19 became infected, and the number of deaths reached 52 people or 57.7%. Among the patients, men prevailed (65%). The largest number of deaths (76.7%;n=69) was among older people with comorbidities (diabetes mellitus, cardiovascular disease, chronic lung disease, metabolic syndrome, etc.). An analysis of the age structure showed that the main proportion of cases fell on the age group of 40-60 years (42.6%). It was found that a significant proportion of patients with COVID-19 was detected in the Sughd region (33.0%) and Dushanbe (30.1%). Conclusion. The COVID-19 pandemic showed that the national healthcare system of the Republic of Tajikistan was not sufficiently prepared for such a development of the COVID-19 epidemic process. There was an acute shortage of medical and preventive specialists in the republic. Given the current situation in the Republic of Tajikistan, within the framework of epidemiological surveillance, the features of the course of the COVID-19 epidemic process were analyzed, adequate emergency measures were developed and proposed to limit the spread of the virus and reduce the negative impact of COVID-19 on public health. The number of beds has been reasonably expanded, the capacity of the laboratory service has been increased, mass vaccination of the population has been started according to epidemic indications.Copyright © 2022 Geotar Media Publishing Group

COVID-19 in Italy: Is the Mortality Analysis a Way to Estimate How the Epidemic Lasts?

When an epidemic breaks out, many health, economic, social, and political problems arise that require a prompt and effective solution. It would be useful to obtain all information about the virus, including epidemiological ones, as soon as possible. In a previous study of our group, the analysis of the positive-alive was proposed to estimate the epidemic duration. It was stated that every epidemic ends when the number of positive-alive (=infected-healed-dead) glides toward zero. In fact, if with the contagion everyone can enter the epidemic phenomenon, only by healing or dying can they get out of it. In this work, a different biomathematical model is proposed. A necessary condition for the epidemic to be resolved is that the mortality reaches the asymptotic value, from there, remains stable. At that time, the number of positive-alive must also be close to zero. This model seems to allow us to interpret the entire development of the epidemic and highlight its phases. It is also more appropriate than the previous one, especially when the spread of the infection is so rapid that the increase in live positives is staggering.

Exposure to COVID-19 Outbreak: A Qualitative Study on Adult People's Experiences

One of the global crises that people are dealing with today is the COVID-19 pandemic. The outbreak of this disease as a social phenomenon has affected all aspects of life. This study aimed to identify adult people's experiences during the COVID-19 outbreak. This qualitative research was performed with a conventional qualitative content analysis approach in Mashhad, Iran, from April to November 2020. twenty-five participants were selected through a purposeful sampling method with maximum diversity until data saturation was reached. Data were collected using semi-structured face-to-face interviews with open-end questions and analyzed with MAXQDA10 software. Two main categories were extracted (1) difficulties in multiple domains (psychological and informational problems, social challenges, spiritual and religious challenges, and economic problems), (2) adaptation to the epidemic (purposive self-care, ignoring the disease and health instructions, faith in God and optimism). The participants faced extensive challenges, which were made worse by the confusion and ambiguity about the information, quarantine, and social isolation. To continue living, the participants tried to adapt to situations. These results provide a guiding framework for policymaking and intervention.Copyright © 2023 Tehran University of Medical Sciences. All rights reserved.

Tuberculosis Situation in Children in 2021 and the Prospects of its Change in 2022

The article analyzes changes in the epidemic tuberculosis situation in children and factors influencing it. Data from tuberculosis statistical surveillance forms and on-line monitoring data for the biggest available peri(xl were studied. It was found that in 2021, tuberculosis incidence increased in children of 0-14 years old. and this increase was statistically significant (p < 0.05) in the group of children of 7-14 years old (from 5.6 to 6.3 per 100,000 children of 7-14 years old), which may be related to the COVID-19 pandemic: increased epidemic risk of tuberculosis infection sources and increased exposure of children primarily of school age, who were switched todistant learning. The increase in tuberculosis incidence among children exposed to tuberculosis patients from 143.8 to 183.0 per 100,000 exposed children may be further attributed to decreased dissociating of contacts by hospitalizing children to tuberculosis sanatoria. The epidemic tuberculosis situation in children is expected to deteriorate due to increased migration from the country with an unfavorable tuberculosis situation, i.e. Ukraine. Tuberculosis mortality in children continued to decline;there were no signs that it would increase in 2022. © 2022 New Terra Publishing House. All rights reserved.

Research on Design Strategy of Mask Recycling Service Based on Behavior Environment

The global novel coronavirus pandemic has caused a surge in the use of masks worldwide. A large number of used masks that have not been properly handled enter the environment, which caused and will cause serious ecological problems. The purpose of this study is to propose a solution to the problem of mask management from the perspective of science of design, and to build a good mask recycling service design strategy through the combination of design and psychology. Firstly, based on the theory of behavioral environment and field investigation, this study analyzes the correlation between the existing mask recycling device and its recycling efficiency, user behavior psychology and environment, and studies the behavioral scene of mask recycling, and then establishes the center of design strategy implementation. Secondly, a visual guidance system is designed, as is a special recycling device for masks by color psychology and product design. Thirdly, combined with the concept of social innovation service design, the design of a mask recycling strategy is conceived, and the optimization and formulation of mask recycling strategy is demonstrated through stakeholders, user journey maps and service flow charts. Finally, the design strategy is hierarchically established, and the feasibility analysis system model of a mask recycling strategy design is constructed. The data collection is carried out through expert interviews and questionnaires, and the weight is calculated by a fuzzy analytic hierarchy process. The final output comprehensive evaluation results show that the mask recycling strategy constructed in this study has public recognition.

Transmission Characteristics and Predictive Model for Recent Epidemic Waves of COVID-19 Associated With OMICRON Variant in Major Cities in China.

Objectives: Waves of epidemics associated with Omicron variant of Coronavirus Disease 2019 (COVID-19) in major cities in China this year have been controlled. It is of great importance to study the transmission characteristics of these cases to support further interventions. Methods: We simulate the transmission trajectory and analyze the intervention influences of waves associated with Omicron variant in major cities in China using the Suspected-Exposed-Infectious-Removed (SEIR) model. In addition, we propose a model using a function between the maximum daily infections and the duration of the epidemic, calibrated with data from Chinese cities. Results: An infection period of 5 days and basic reproduction number R0 between 2 and 8.72 are most appropriate for most cases in China. Control measures show a significant impact on reducing R0, and the earlier control measures are implemented, the shorter the epidemic will last. Our proposed model performs well in predicting the duration of the epidemic with an average error of 2.49 days. Conclusion: Our results show great potential in epidemic model simulation and predicting the end date of the Omicron epidemic effectively and efficiently.

An epidemic-economic model for COVID-19.

In this paper, we propose a new mathematical model to study the epidemic and economic consequences of COVID-19, with a focus on the interaction between the disease transmission, the pandemic management, and the economic growth. We consider both the symptomatic and asymptomatic infections and incorporate the effectiveness of disease control into the respective transmission rates. Meanwhile, the progression of the pandemic and the evolution of the susceptible, infectious and recovered population groups directly impact the mitigation and economic development levels. We fit this model to the reported COVID-19 cases and unemployment rates in the US state of Tennessee, as a demonstration of a real-world application of the modeling framework.

ON COVID-19 EPIDEMIC PROCESS SIMULATION: THREE REGRESSION APPROACHES INVESTIGATIONS

An outbreak of a new coronavirus infection was first recorded in Wuhan, China, in December 2019. On January 30, 2020, the World Health Organization declared the outbreak a Public Health Emergency of International Concern and on March 11, it a pandemic. As of January 2022, over 340 million cases have been reported worldwide;more than 5.5 million deaths have been confirmed, making the COVID-19 pandemic one of the deadliest in history. The digitalization of all spheres of society makes it possible to use mathematical and simulation modeling to study the development of the virus. Building adequate models of the epidemic process will make it possible not only to predict its dynamics but also to conduct experimental studies to identify factors affecting the development of a pandemic, determine the behavior of the virus in certain areas, assess the effectiveness of measures aimed at stopping the spread of infection, as well as assess the resources needed to counter the epidemic growth of the disease. This study aims to develop three regression models of the COVID-19 epidemic process in given territories and to investigate the experimental results of the simulation. The research is targeted at the COVID-19 epidemic process. The research subjects are methods and models of epidemic process simulation, which include machine learning methods, particularly linear regression, Ridge regression, and Lasso regression. To achieve the research aim, we have used forecasting methods and have built the COVID-19 epidemic process and regression models. As a result of experiments with the developed model, the predictive dynamics of the epidemic process of COVID-19 in Ukraine, Germany, Japan, and South Korea for 3, 7, 10, 14, 21, and 30 days were obtained. The authorities making decisions on the implementation of anti-epidemic measures can use such predictions to solve the problems of operational analysis of the epidemic situation, an analysis of the effectiveness of already implemented anti-epidemic measures, medium-term planning of resources needed to combat the pandemic, etc. Conclusions. This paper describes experimental research on implementing three regression models of the COVID-19 epidemic process. These are models of linear regression, Ridge regression, and Lasso regression. COVID-19 daily new cases statistics were verified by these models for Ukraine, Germany, Japan, and South Korea, provided by the Johns Hopkins Coronavirus Resource Center. All built models have sufficient accuracy to make decisions on the implementation of anti-epidemic measures to combat the COVID-19 pandemic in the selected area. Depending on the forecast period, regression models can be used to solve different Public Health tasks. © 2022. Dmytro Chumachenko, Ievgen Meniailov, Kseniia Bazilevych, Olha Chub. All Rights Reserved.

Features of the course and medical and social aspects of a new coronavirus infection in the Republic of Tajikistan

The aim - to assess some medical and social aspects of the epidemic process during the first wave of a new coronavirus infectious disease - COVID-19 in the Republic of Tajikistan. Material and methods. The retrospective study was conducted on the basis of an epidemiological analysis of official statistics as part of the epidemiological surveillance of COVID-19 from April 2020 to April 2021. Results and discussion. At the beginning of April 2021, a total of 13 308 cases of COVID-19 were registered, of which the proportion of recovered was 99.3% (13 218 cases), and the number of cases with a fatal outcome was 0.68% (90 cases;the average age of the deceased was 62.3±0.07 years). The peak of infection during the first wave occurred in May and June 2020, when the average daily increase was 97 people. For 2 months of the epidemic in the republic, 44.6% of the total number of patients with COVID-19 became infected, and the number of deaths reached 52 people or 57.7%. Among the patients, men prevailed (65%). The largest number of deaths (76.7%;n=69) was among older people with comorbidities (diabetes mellitus, cardiovascular disease, chronic lung disease, metabolic syndrome, etc.). An analysis of the age structure showed that the main proportion of cases fell on the age group of 40-60 years (42.6%). It was found that a significant proportion of patients with COVID-19 was detected in the Sughd region (33.0%) and Dushanbe (30.1%). Conclusion. The COVID-19 pandemic showed that the national healthcare system of the Republic of Tajikistan was not sufficiently prepared for such a development of the COVID-19 epidemic process. There was an acute shortage of medical and preventive specialists in the republic. Given the current situation in the Republic of Tajikistan, within the framework of epidemiological surveillance, the features of the course of the COVID-19 epidemic process were analyzed, adequate emergency measures were developed and proposed to limit the spread of the virus and reduce the negative impact of COVID-19 on public health. The number of beds has been reasonably expanded, the capacity of the laboratory service has been increased, mass vaccination of the population has been started according to epidemic indications. © 2022 Geotar Media Publishing Group

Management of the Pre-hospital Emergency Transport Strategy During the Novel Coronavirus Pneumonia Epidemic in Zhuzhou City, China

Objective : Summarize the experience of transporting patients in the pre-hospital emergency center of our hospital from January 20, 2020 to May 2020 during the outbreak of novel coronavirus pneumonia in Zhuzhou City, and formulate a series of transport strategics. Methods: During the novel coronavirus pneumonia epidemic, review the relevant experience of the medical staff and drivers in the pre-hospital emergency center of Zhuzhou Central Hospital to improve the procedures for the transfer of patients during the epidemic. Results: As of the time when patients with novel coronavirus pneumonia in our city are cleared, none of the medical staff in the pre-hospital emergency center of Zhuzhou Central Hospital has been infected, and the city's patients in need of pre-hospital emergency treatment have been treated in an orderly manner. In conjunction with our hospital's epidemic prevention and control expert team, combined with the actual situation in the region, we jointly formulated a series of transfer procedures for Zhuzhou Central Hospital to comply with the region during the epidemic. Conclusion: During the novel coronavirus pneumonia epidemic, all patients received by the pre-hospital emergency center of our hospital were transferred in a timely and safe manner, and a series of transfer procedures were developed.

Comparative Analysis of Work at the Television Archives between the First and Second Wave of the COVID-19 Epidemic

The year 2020 was in many ways an extraordinary year, which applies also to the case of archival work. With the outbreak of the COVID-19 epidemic, various institutions prepared their work procedures according to their own perceptions of working in crises, and the same was in the television archives of Radio-Television Slovenia (RTV Slovenia). In this paper, we will present a comparative analysis of the operation of the television archives of RTV Slovenia in the epidemic, with an emphasis on strategies of measures that directly affected the quality of work. We will present the management of the television archives in the first and second wave and consequently in the third wave, describe the lessons learned from the preparation for work in crises, the problems or shortcomings and their solutions in further work. By analyzing the first and the second wave, we showed big progress in archival processing of archival material. The results of the preliminary analysis show a large gap between work in the first and the second wave. We estimate that different preparation and implementation of lessons learned from the first wave contributed to more successful work results of the television archives in the second wave. © 2021, Maribor Provincial Archives. All rights reserved.

Collective Action of the 'Fandom Girls' in Fighting the Epidemic - - Based on the perspective of social identity theory

The collective action of the 'Fandom Girls' to collect supplies in the fight against the COVID-19 coronavirus pandemic in 2020 demonstrated strong organizational executive skills, changing the public's prejudice and stereotype. Based on the perspective of social identity theory, this paper uses case study and text analysis to explore the identity construction of this collective action. The author finds that 'Fandom Girls' identify with their country, idols, norms, and communities, which function as the motivation of their collective action. The identity mechanism is developed from internal and external identities, which are expressed as self-categorization and evolution through questioning. The social identity theory is validated in this collective action, but it also shows new characteristics. Understanding the group's identity motivations and mechanisms can help to utilize the group's power better. © 2021 IEEE.

How to Reach a Regional Cooperation Mechanism to Deal With the Epidemic: An Analysis From the Game Theory Perspective.

The outbreak and persistence of COVID-19 have posed a great threat to global public health and economic development. The continuous economic deterioration has been intensified due to the continuous prevention and control measures, such as closed management. Insisting on the prevention of the epidemic or economic restart has become a dilemma for all countries. Epidemic prevention is not only the main behavior of a single country but also a common problem faced by all countries in the region. Continuous prevention measures will affect economic development, but an early restart of the economy is faced with the recurrence of the epidemic. To avoid the emergence of prisoner's dilemma in the governance of the epidemic, each country cannot make decisions with its optimization, and so it is necessary to build a regional cooperation mechanism to achieve the overall optimization of the economy and prevent the epidemic. Based on the game theory, we analyzed the behavior of countries when carrying out regional cooperation to govern the epidemic and put forward specific cooperative income distribution schemes according to the different attributes of the countries. Our results showed that in the presence of population mobility, regional cooperation to govern the epidemic can minimize the total number of infected people and maximize the overall utility of the region, which was significantly better than the overall benefits of the region in the case of non-cooperation. However, in detail, the smaller the difference of preference for preventing and controlling the epidemic between the two, the more likely it is to lead to a win-win situation. Otherwise, there will be one with damaged interests. When damaged interests appear, the appropriate distribution of cooperative income to the country with a small economic scale and low preference in preventing the epidemic is more conducive to the achievement of cooperative mechanisms and the realization of a win-win situation in the region.

Customized treatment protocols for patients with closed fracture in hospitals at varying coronavirus disease 2019 (COVID-19) risk.

BACKGROUND: To determine an optimized treatment protocol during the COVID-19 epidemic for patients with closed fracture and delayed surgery. METHODS: The epidemic data of three hospitals, randomly selected from different administrative regions of Wuhan, were analyzed retrospectively from 23 January to 31 March 2020. Changes in the number of confirmed cases per day (cumulative and new) of each region were tracked as a reflection of changing epidemic risk levels. The risk level map was drawn. The epidemic status, treatment protocols, and treatment efficiencies for patients with closed fracture in the three hospitals were compared. RESULTS: Overall, 138 patients with closed fracture were admitted. Each hospital had established its own protocol, according to the initial perceived risk. Based on the risk level map, over the study period, the risk levels of the three regions changed independently and were not in sync. All patients recovered and were timely discharged. No staff member was detected with COVID-19. CONCLUSIONS: The COVID-19 risk level of each area is dynamic. To optimize medical resources, avoid cross-infection, and improve efficiency, changes in epidemic risk should be monitored. For patients with closed fracture, treatment protocols should be adjusted according to changes in epidemic risk.

Self-organization of oscillation in an epidemic model for COVID-19.

On the basis of a compartment model, the epidemic curve is investigated when the net rate λ of change of the number of infected individuals I is given by an ellipse in the λ - I plane which is supported in [ I ℓ , I h ] . With a ≡ ( I h - I ℓ ) ∕ ( I h + I ℓ ) , it is shown that (1) when a < 1 , oscillation of the infection curve is self-organized and the period of the oscillation is in proportion to the ratio of the difference ( I h - I ℓ ) and the geometric mean I h I ℓ of I h and I ℓ , (2) when a = 1 , the infection curve shows a critical behavior where it decays obeying a power law function with exponent - 2 in the long time limit after a peak, and (3) when a > 1 , the infection curve decays exponentially in the long time limit after a peak. The present result indicates that the pandemic can be controlled by a measure which makes I ℓ < 0 .

On forecasting the spread of the COVID-19 in Iran: The second wave.

One of the common misconceptions about COVID-19 disease is to assume that we will not see a recurrence after the first wave of the disease has subsided. This completely wrong perception causes people to disregard the necessary protocols and engage in some misbehavior, such as routine socializing or holiday travel. These conditions will put double pressure on the medical staff and endanger the lives of many people around the world. In this research, we are interested in analyzing the existing data to predict the number of infected people in the second wave of out-breaking COVID-19 in Iran. For this purpose, a model is proposed. The mathematical analysis corresponded to the model is also included in this paper. Based on proposed numerical simulations, several scenarios of progress of COVID-19 corresponding to the second wave of the disease in the coming months, will be discussed. We predict that the second wave of will be most severe than the first one. From the results, improving the recovery rate of people with weak immune systems via appropriate medical incentives is resulted as one of the most effective prescriptions to prevent the widespread unbridled outbreak of the second wave of COVID-19.