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Follow-up of patiens after COVID-19 monoclonal antibodies administration
Minaříková, Jiřina ; Zimčíková, Eva (advisor) ; Hendrychová, Tereza (referee)
Follow-up of patients after COVID-19 monoclonal antibodies administration Author: Jiřina Minaříková Supervisor: PharmDr. Eva Zimčíková, Ph.D. Consultant: PharmDr. Petra Rozsívalová Charles University in Prague, Faculty of Pharmacy in Hradec Králové, Department of Social and Clinical Pharmacy Keywords: COVID-19, coronavirus, monoclonal antibodies, casirivimab and imdevimab, REGN-COV2 Introduction: At height of COVID-19 pandemic surge of Delta variant, monoclonal antibodies became a vital treatment option for SARS-CoV-2 positive outpatients at high risk of severe disease progression. Casirivimab and imdevimab (C/I) were used as an unauthorised medicinal product REGN-COV2 under European Medicines Agency emergency use authorisation (EUA). There was paucity of real-world data on safety and effectiveness. Objective: The study aimed to describe REGN-COV2 drug safety, self-reported symptom burden in SARS-CoV-2 positive outpatients within 90 days post C/I infusion. Methods: Prospective multicentric study of SARS-CoV-2 positive outpatients with mild symptoms at high-risk of severe COVID-19 progression (defined criteria under EUA authorization for C/I ambulatory administration) was conducted from September 2021 till April 2022 in three teaching hospitals in Czech Republic and Slovakia. The data collected...
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Economic and financial impacts of the COVID-19 pandemic in a specific company
Zelinka, Matěj ; Oulehla, Jiří (referee) ; Hornungová, Jana (advisor)
This bachelor thesis is focused on the economic and financial impact of the Covid-19 pandemic on the Laskala guesthouse operated by DHZ RAMPA, s.r.o. and subsequent proposals for improving the situation. The thesis is divided into three main parts. The first theoretical part of this thesis contains the literature research necessary for the second analytical part. In the analytical part, the financial statements of the company for the period 2018-2022 are analysed using financial analysis. The last propositional part is focused on the elaboration of proposals that will help DHZ RAMPA, s.r.o. to improve the financial situation of the Laskala guesthouse.
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Statistical analysis of COVID-19
Zapoměl, Jakub ; Popela, Pavel (referee) ; Žák, Libor (advisor)
This thesis deals with the statistical analysis of COVID-19 disease. The thesis focuses on data processing related to the disease, the formulation and verification of statistical hypotheses, the application of piecewise linear regression, the prediction of the further development of the disease, and the verification of predictions presented in the media. Specific analyses are conducted using Python.
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Economic and financial impact of the COVID-19 pandemic in a specific company
Březinová, Barbora ; Gláserová, Jana (referee) ; Hornungová, Jana (advisor)
The bachelor's thesis is devoted to the evaluation of the economic situation of the state company České dráhy, a. s. in the years 2018-2022, when the issue of the COVID-19 pandemic is also included in this period. The first part of the work characterizes terms important to the given topic, which the bachelor's thesis itself deals with. The second part is devoted to the calculation and evaluation of the indicators themselves using the methods mentioned in the theoretical part. The last part of the work is based on the results of the analytical part and its part is the proposal of measures that would lead to the improvement of the current financial situation.
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Sickness insurance benefits and their specifics in the context of the Covid-19 pandemic (theretical thesis)
BAŠTÝŘOVÁ, Kristýna
The bachelor thesis focuses on the analysis of sickness benefits and their specifics in connection with the Covid-19 pandemic. The aim of the thesis is to compare the legal regulation of sickness benefits under normal conditions and during the Covid-19 pandemic. The thesis focuses on analyzing changes in the legislation of sickness insurance in response to the pandemic and assessing the impacts of these changes on employees, employers, and self-employed individuals. It is based on the Act No. 589/1992 Coll., on social security insurance and state policy on employment, Act No. 258/2000 Coll., on the protection of public health, Act No. 187/2006 Coll., on sickness insurance, and several other related laws. In the context of the Covid-19 pandemic, additional measures were continuously issued during the relevant period, which are mentioned in the thesis. The thesis exclusively contains a theoretical delineation of the topic, in which the system of sickness insurance is detailed as a key component of the social security system. This system provides financial support to insured individuals in the event of a social occurrence. The significance of sickness insurance has significantly increased in connection with the Covid-19 pandemic, as the pandemic has notably influenced the rise in the number of temporary incapacity to work cases. The pandemic prevented students from attending schools and educational facilities, leading to a large number of parents applying for sickness benefits. The thesis defines the Covid-19 disease itself and outlines the overall development of sickness insurance during the Covid-19 pandemic in the Czech Republic. In conclusion, the changes to the current legal regulations effective from January 1, 2024, in the area of sickness insurance are summarized. This bachelor's thesis can be utilized as a source of information for social workers or as study material for students in social sciences.
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COVID-19 disease classification based on analysis of chest X-rays
Šteflík, Dominik ; Kiac, Martin (referee) ; Myška, Vojtěch (advisor)
This diploma thesis addresses the development and evaluation of artificial intelligence algorithms for classifying COVID-19 disease from chest X-ray images. Given the severity and impact of the COVID-19 pandemic on the global population, the ability to rapidly and accurately diagnose diseases from radiographic images has become critical. This study synthesizes current advancements in image processing and deep learning to evaluate the application of several novel classification methods in practice. Using a dataset obtained from a Czech medical environment, these methods are analyzed and validated in order to examine their effectiveness and accuracy in real life scenarios. The methods chosen for this study, COVID-Net, DarkCovidNet, and CoroNet, were selected due to their availability, widespread use and proven effectiveness in the field. The core of the thesis is the design of a convolutional neural network tailored to extract and learn from the subtle features present in X-ray images indicative of COVID-19. This initiative confronted significant challenges posed by variable acquisition parameters of X-ray images, which can substantially affect diagnostic accuracy. The uniformity of these parameters is crucial for reliable analysis, underscoring the importance of rigorous preprocessing techniques. In response, advanced normalization, contrast adjustment, and augmentation procedures were implemented to standardize the input data. The convolutional network itself employs a series of convolutional, pooling, and fully connected layers, optimized to handle the nuanced variations present in medical imaging data. Notably, the network architecture incorporates an attention mechanism, implemented through a Squeeze-and-Excitation block, to dynamically adjust the importance of different channels in the input image. By integrating these elements, the network model is trained to focus on significant features within the X-ray images, allowing it to distinguish subtle indicators of COVID-19 effectively. Furthermore, this work discusses the potential of integrating these AI-driven diagnostic tools into existing healthcare infrastructures to enhance early detection and treatment of COVID-19. The findings indicate that leveraging artificial intelligence in medical imaging can substantially aid in managing and controlling disease outbreaks, ultimately contributing to better health outcomes.
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Bloodstream infection in patients during the COVID-19 pandemic in of General University Hospital in Prague
BAUER, Kristýna
Blood stream infection is one of the serious life-threatening conditions of hospitalized patients with coronavirus disease during the COVID-19 pandemic in the Czech Republic. This is the penetration of microorganisms into the bloodstream, which is accompanied by symptoms of a general infection. The most common consequence is the development of sepsis. The aim of the laboratory examination is to obtain a reliable blood culture result. Such a result can only be achieved if all procedures are followed, from the indication by the doctor to the process of sampling by the medical staff into the bottles directly intended for this purpose. Taking blood cultures confirms or excludes the presence of bacteria in the bloodstream. Blood cultures are the gold standard for diagnosing bloodstream infections. A detection culture is used for hemocultivation of the BacT/Alert 3D system, which is based on the colorimetric detection of CO2 produced by growing microorganisms in blood cultures.
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Impacts of COVID-19 Pandemic on the Mental Health of Pregnant Women in the Czech Republic
Venclů, Viktorie ; Pařízek, Antonín (advisor) ; Richtárová, Adéla (referee)
This bachelor thesis examines the impact that the COVID-19 pandemic had on the mental health of pregnant women in the Czech Republic. The theoretical part includes the fundamental information essential for understanding the context of the topic. It focuses on the disease itself, the emergence and development of its pandemic in the Czech Republic, and its course in pregnant women. Additionally, it delves into the psychology of pregnant women and into mental health in general. The thesis also summarizes the results of some Czech studies investigating the impact of the pandemic on the mental health of the Czech population. The research section investigates the influence of the pandemic on the mental health of pregnant women through regression analysis. The numbers of births among women who required a certain form of psychiatric intervention during pregnancy, or within six months after childbirth are examined. The analysed dataset was obtained from the national registers NRRZ and NRHZS and includes records from January 2015 to December 2021. A regression log- log model was created for analysis, which did not show a statistically significant impact of the pandemic on the number of births for these women. Possible reasons for the different results between this research and mentioned studies are discussed...
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COVID-19 and political preferences through stages of the pandemic: the case of the Czech Republic
Bičáková, Alena ; Jurajda, Štěpán
We track the effects of the COVID-19 pandemic on political preferences through ‘high’ and ‘low’ phases of the pandemic. We ask about the effects of the health and the economic costs of the pandemic measured at both personal and municipality levels. Consistent with the literature, we estimate effects suggestive of political accountability of leaders during ‘high’ pandemic phases. However, we also find that the pandemic political accountability effects are mostly short-lived, and do not extend to the first post-pandemic elections.
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