The COVID-19 pandemic has been an ongoing disaster that has devasted millions of lives. With the development of COVID-19 vaccines in late 2020, there was a potential for populations to gain artificial active immunity in order to prevent future outbreaks. However, despite successful clinical trials, millions of citizens have been hesitant to receive the COVID-19 vaccines (Khubchandani et al., 2021). Demographics of the most prominent US vaccine-hesitant populations consist of ethnic/racial minorities and Republicans groups (Khubchandani et al., 2021). Little information is known about COVID-19 vaccine hesitancy in colleges and universities. Colleges provide an elevated risk for infection through their communal residencies, the reemergence of campus activities, and continuous travel to home (Sharma et al., 2021). This study explored COVID-19 vaccine hesitancy in UCF college students and explored potential pathways to achieve higher vaccination rates. Potentially believed COVID-19 misinformation was also studied. A COVID-19 opinion survey was designed and distributed to the UCF college population. Two hypotheses were made for this study: (1) There is a significant effect on vaccination status among people of different political parties, field of study, living conditions, masking frequency, and scores on the knowledge-based questions portion. (2) There will be a significant effect on knowledge-based scores with political party and field of study. The results were analyzed using Chi-square, one-way ANOVA, or two-way ANOVA on SPSS. The results showed a significant effect on vaccination status in political parties, masking frequency in class, and scores on the knowledge-based survey questions. There was no significance with race/ethnicity and field of study. There was a significant effect on the knowledge-based survey questions with political party and field of study. Potential side effects and the vaccines being seen as ineffective were the top two reasons that students choose not to vaccinate.

By reviewing pre-existing academic literature, research, and data (both international and domestic), this report examines information from a variety of sources to contextualize the threat of COVID-19 against the negative consequences of COVID-19 non-pharmaceutical intervention (NPI) response measures. The qualitative and quantitative data in this report highlights costs associated with COVID-19 response measures relative to the threat of COVID-19 and has been collected to inform a Multiple Accounts Cost-Benefit Analysis (CBA). This report emphasizes the costs associated with NPIs as they relate to physical and mental health, as well as human rights and economic concerns. Overall, a review of available evidence did find a relationship between COVID-19 NPI response measure implementation and negative outcomes. In fact, it remains unclear if NPIs are proportionate or even effective against the risk posed by COVID-19. How NPIs might be optimized (i.e., to reduce the negative effects of their implementation) remains unclear as mild to severe NPI implementation can yield similar outcomes. Following the above analysis, this report provides recommendations to the Government of BC to ensure that COVID-19 response measures are optimized and proposes that a Multiple Accounts CBA of NPI implementation be completed. / Graduate

The emergence of coronavirus disease 2019 (COVID-19) has resulted in more than 300 million cases and 5 million deaths worldwide and innumerable economic losses. COVID-19 is acknowledged to transmit via air, but whether it is capable of transmitting via contaminated surfaces, also known as fomites, remains controversial. The overarching goal of this study was to investigate the presence and stability of SARS-CoV-2, the virus that causes COVID-19, on indoor surfaces and masks, and to provide insight into the possibility of fomite transmission. Since most transmission occurs indoors where humans spent 90% of their time, we first focused on quantifying the contamination level of SARS-CoV-2, including both viral RNA and viable virus, on commonly touched surfaces and in the heating, ventilation, and air cleaning (HVAC) systems in two university dormitories. Although we found up to 104 gene copies per ~10×10 cm2 on surfaces, we did not detect any viable virus, suggesting that the possibility of transmission via indoor surfaces is low. As universal masking has been recommended as an effective practice to prevent transmission of SARS-CoV-2, we shifted our focus to masks, both their effectiveness at filtering the virus from the air and their potential to serve as fomites. We evaluated the effectiveness of 11 face coverings for material filtration efficiency, inward protection efficiency on a manikin, and outward protection efficiency on a manikin. Masks made of filter materials, such as vacuum cleaner bag and HVAC filters, achieved a high material filtration efficiency whereas common textiles like cotton and acrylic usually showed the worst performance. The material filtration efficiency was generally positively correlated with either inward or outward protection effectiveness, but stiffer materials were an exception to this relationship as they did not fit as closely to the manikin's face and thus leaked substantially. Subsequently, we analyzed the survival of aerosolized SARS-CoV-2 in saliva on masks. Results suggested that the virus lost infectivity within one hour on an N95 respirator, surgical mask, polyester mask, and two types of cotton masks but not on a nylon/spandex mask. This study also highlighted the importance of applying virus in aerosols of realistic sizes when analyzing the stability of SARS-CoV-2 on surfaces. / Doctor of Philosophy / The emergence of coronavirus disease 2019 (COVID-19) has resulted in more than 300 million cases and 5 million deaths worldwide and innumerable economic losses. Researchers are debating if COVID-19 can transmit via surfaces contaminated with SARS-CoV-2, the virus that causes the disease. The goal of this study was to investigate whether SARS-CoV-2 is present and remains viable on indoor surfaces and masks, and to provide insight into the possibility of transmission via contaminated surfaces. Since most transmission occurs indoors where humans spent 90% of their time, we first focused on quantifying number of SARS-CoV-2 on commonly touched surfaces and in the heating, ventilation, and air cleaning (HVAC) systems in two university dormitories. Although we found a high concentration of SARS-CoV-2 genes on surfaces, we did not detect any viable virus, suggesting that the possibility of transmission via indoor surfaces is low. As universal masking has been recommended as an effective practice to prevent transmission of SARS-CoV-2, we shifted our focus to masks. We evaluated the effectiveness of 11 face coverings regarding their ability to trap viruses, protect wearers from inhaling viruses, and prevent infected individuals from expelling viruses into the surrounding air. Masks made of filter materials, such as a vacuum cleaner bag and HVAC filter, trapped the most viruses whereas common textiles like cotton and acrylic usually performed worst. It is also crucial that masks fit closely to the wearer's face to achieve better protection. Subsequently, we analyzed the ability of SARS-CoV-2 in aerosols, microscopic particles such as those exhaled by an infected person, to survive on different types of masks. Results suggested that the virus died within one hour on a majority of the masks. This study also highlighted the importance of applying aerosols of realistic sizes instead of large droplets when analyzing the survival of SARS-CoV-2 on surfaces.

The complex molecular machinery of the cell controls its response to various signals and environmental conditions. A natural approach to study these molecular mechanisms and cellular processes is with protein interaction networks. Due to the complexity of these networks, sophisticated computational techniques are required to extract biological insights from them. In this thesis, I develop and apply network-based algorithms for three different challenges. 1. I develop a novel, highly-scalable algorithm for network-based label prediction methods that enables the integration of functional annotations and interaction networks across many species in order to predict the functions of genes in newly-sequenced bacteria. 2. To overcome the limitations of experimental approaches to find human proteins and processes that are hijacked by SARS-CoV-2, I adapt network propagation approaches for predicting human interactors of the virus. 3. Large-scale experimental techniques to screen chemicals for toxicity have tested their effects on many individual proteins. I integrate human protein-protein interactions with this data to gain insights into the molecular networks those chemicals affect. For each of these research problems, I perform comprehensive evaluations and downstream analyses to demonstrate both the accuracy of our approaches and their utility in obtaining a broader understanding of the molecular systems in question. / Doctor of Philosophy / The functions of all living cells are governed by complex networks of molecular interactions. A major goal of systems biology is to understand the components of this machinery and how they regulate each other to control the cell's response to various conditions and signals. Advances in experimental techniques to understand these systems over the past couple of decades have led to an explosion of data that probe various aspects of a cell such as genome sequencing, which reads the DNA blueprint, gene expression, which measures the amount of each gene's products in the cell, and the interactions between those products (i.e., proteins). To extract biological insights from these datasets, increasingly sophisticated computational methods are required. A powerful approach is to model the datasets as networks where the individual molecules are the nodes and the interactions between them are the edges. In this thesis, I develop and apply network-based algorithms to utilize molecular systems data for three related problems: (i) predicting the functions of genes in bacterial species, (ii) predicting human proteins and processes that are hijacked by the SARS-CoV-2 virus, and (iii) suggesting cellular signaling pathways affected by exposure to a chemical. Developments such as those presented in these three projects are critical to obtaining a broader understanding of the functions of genes in the cell. Therefore, I make the methods and results for each project easily accessible to aid other researchers in their efforts.

Pandemics are periodic events characterized by rapid and widespread transmission of infectious disease affecting a significant proportion of the population over a large geographical area. Zoonotic strains of influenza viruses and coronaviruses have both caused pandemics in the recent past. Although vaccination is the often the most effective way to prevent infection or serious outcomes of infection, vaccine development, production, distribution, and deployment are all time- consuming and logistically challenges processes. Alternative readily deployed approaches must be quickly executed to mitigate the toll of future pandemics, especially during the early phases. The work described in this thesis describes some of these approaches. Firstly, I describe the process by which I performed genome-wide CRISPR-Cas9 knockout screens using SARS-CoV-2 variants of concern to discover crucial host factors as targets for broad-acting antivirals. I found that all variants rely on similar host pathways to replicate in the glial cell line used for the screen. I identified BCL-xL, a regulator of apoptosis, as a potential target for a broad- acting antiviral. I show that chemical inhibition of BCL-xL results in accelerated cell death in infected cells in vitro, but improved clinical signs and disease mortality of SARS-CoV-2 in our murine infection model. Secondly, I describe a unique mechanism for cooperative antiviral combination therapy. I demonstrate that chemical inhibition of neuraminidase by oseltamivir improved immune effector cell activation by hemagglutinin stalk-binding antibodies. Combination therapy of oseltamivir and stalk-binding antibodies also improved clinical signs and disease mortality of influenza in our murine infection model compared to monotherapy in both prophylactic and therapeutic contexts. Finally, I show that non-pharmaceutical public health interventions used to restrict the spread of COVID-19 were also effective against several other infectious diseases. I used an interrupted time- series analysis on Ontario public health administrative data during the early COVID-19 pandemic period and found a drastic and sustained decline in outpatient visits for diseases that are typically caused by viruses that transmit by droplet or aerosol. The three projects described in this thesis outlines broadly-protective and distinct strategies to curb the spread of novel respiratory viruses. These new tools may be leveraged to improve the response and to mitigate the burden of future pandemics. / Thesis / Doctor of Philosophy (PhD) / Most pandemics in recent history have been caused by viruses that infect the respiratory tract. Vaccination is often the best way to prevent the spread of these pandemic viruses, but making these vaccines takes time. Vaccines also work less well in the very young, the elderly, and those with a compromised immune system. These people are often also the most vulnerable to severe disease. My work describes three novel approaches to help combat the next pandemic, especially during the early phases when vaccines are still being developed, or for the segments of the population that respond poorly to vaccination. These include discovering and using new drugs that work against a wide range of viruses, using combinations of previously-discovered antiviral drugs, and using non-pharmaceutical methods such as physical distancing and wearing masks.

Viral infection stimulates the immune response to produce many cytokines and chemokines, the proteins imperative to fight a brewing infection. This response begins through recognition of pathogen-associated molecular patterns (PAMPs) from the virus, or from other signatures characteristic of tissue damage, damage-associated molecular patterns (DAMPs), by pattern recognition receptors (PRRs) that in turn stimulate pro-inflammatory signaling cascades. The results of these signaling pathways include the release of cytokines and chemokines that work to further upregulate immune responses and attract immune cells to the site of infection, respectively. In the case of SARS-CoV-2 infection, these responses can become problematic if they go unmitigated or unresolved, resulting in the severe COVID-19 manifestation of the 'cytokine storm,' or multisystem inflammatory syndrome in children (MIS-C). One classically increased protein in cytokine storm of COVID-19 patients is C-X-C motif chemokine 10 (CXCL10), which has been explored as a prognostic marker as it is shown to be predictive of disease outcome in hospitalized patients. To prevent severe outcomes like cytokine storm, a delicate balance must be struck, to ensure that this inflammation does not result in high levels of diffuse tissue damage. To achieve this, anti-inflammatory pathways exist within the immune system and help dampen the signals being induced. One such unique anti-inflammatory protein is a pattern recognition receptor known as NLRX1 (Nucleotide binding oligomerization domain, leucine rich repeat containing X1), that can interact with two main pathways involved with anti-viral immunity, the NFB and interferon pathways, downregulating them to keep off-target tissue damage at bay. NLRX1 is also involved in several other cellular processes, including modulating cell death processes and cellular metabolism which can also impact viral replication and clearance indirectly. In this work, we investigated both the pro- and anti-inflammatory arms of the anti-SARS-CoV-2 response focusing on two key proteins – pro-inflammatory chemokine CXCL10 and immunoregulatory PRR NLRX1. The roles of these two proteins were explored utilizing transcriptomic analysis of both human and mouse RNA samples, immortalized cell culture work, humanized mouse models of SARS-CoV-2 infection, and mouse-adapted virus models to be able to utilize deficient mouse models. In this work we better characterize the immune response to SARS-CoV-2 and its related immune-driven pathobiology of disease. The data presented in this work continues to elucidate CXCL10's role as an important driver of viral clearance of SARS-CoV-2, translating data from human patient nasal swabs to the animal model of disease, exploring differential inflammation and immune responses in the absence of CXCL10. Additionally, the work shown here provides further understanding of NLRX1 and its role in antiviral immunity with the context of SARS-CoV-2 infection. The interactions between this protein and the virus remains to be fully characterized, however, it appears they have some degree of mutual inhibition as determined by animal and cell culture models. The culmination of work here emphasizes the importance for both the pro- and anti-inflammatory responses in SARS-CoV-2 infection and offers insight into two possible related targets for future drug development. / Doctor of Philosophy / When a virus invades the body, the immune system kicks off many signaling cascades to keep the virus from replicating, clear virus already established in cells, and clean up the tissues surrounding the infected area of the remnants of cells that already succumbed to the virus. While this immune response is important to fight off the virus that has made its way into the body, overactive immune responses can result in hospital stays requiring supportive care to aid recovery from possible off-target tissue damage. One such case of this happening is when SARS-CoV-2 induces such a strong response, the immune system becomes overzealous and results in overproduction of pro-inflammatory cytokines and chemokines, signaling proteins in the immune system, which can lead to the characteristic 'cytokine storm' of severe COVID-19 disease. One of the proteins most often overproduced is the chemokine CXCL10, and this protein has been used as a biomarker in clinical practice to successfully predict severe disease outcomes in COVID-19 patients. To help combat severe disease outcomes and high levels of tissue damage, the immune system has inborn checks and balances to ensure that proteins like CXCL10 do not reach the level of overproduction as in the cytokine storm of COVID-19. One of these natural checkpoints is a protein called NLRX1, which interacts with two of the main pathways that can lead to the overproduction of cytokines seen overproduced in the case of cytokine storm. NLRX1 also has other roles in other interesting facets important for viral infections, including the metabolism of the cell and cellular death processes. The culmination of these roles could offer up NLRX1 as a possible target for treatments in the future. The work put together here explores both sides of the immune response, turning it 'on' with pro-inflammatory signaling, and turning it 'off' with anti-inflammatory signaling, trying to find just the right amount of inflammation to clear a viral invader while also impeding off target and diffuse tissue damage as the body fights the virus. This work focuses on two key proteins, CXCL10 to represent pro-inflammatory responses, and NLRX1 to represent the anti-inflammatory signaling. Understanding both arms of the immune response to SARS-CoV-2 infection is crucial to being able to identify potential targets for future treatments to help combat severe outcomes of SARS-CoV-2 infection. Using multiple levels across the translational spectrum, including cell culture, animal models, and human patient RNA from COVID test swabs, we explore both facets of SARS-CoV-2 immunity, focusing on these two proteins. Utilizing mouse models bearing deletions of the genes required to make these proteins and a mouse-adapted strain of SARS-CoV-2, this work characterizes how important these individual proteins are in the immune response to SARS-CoV-2, and work as proxies to understand the broader impacts of either the positive or negative regulation of immune signaling. Because of the work culminated here, these two tangentially related proteins are also offered up as possible future drug targets for the development of treatments in severe COVID-19 disease with cytokine storm presentation.

COVID-19 Patientinnen und Patienten haben ein hohes thrombotisches Risiko. Die Sicherheit und Wirksamkeit verschiedener Antikoagulationsschemata bei COVID-19 Patientinnen und Patienten sind unklar. Acht RCTs mit 5580 Patientinnen und Patienten wurden identifiziert, wovon zwei RCTs Antikoagulation in halbtherapeutischer und sechs RCTs Antikoagulation in therapeutischer Dosierung mit der Standard Thromboembolieprophylaxe verglichen haben. Die halbtherapeutische Antikoagulation kann wenig oder gar keinen Einfluss auf thrombotische Ereignisse oder Todesfälle haben (RR 1,03, 95% KI 0,86-1,24), kann aber schwere Blutungen (RR 1,48, 95% KI 0,53-4,15) bei mittelschweren bis schweren COVID-19 Patientinnen und Patienten verstärken. Therapeutische Antikoagulation kann thrombotische Ereignisse oder den Tod bei Patientinnen und Patienten mit mittelschwerem COVID-19 (RR 0,64, 95% KI 0,38-1,07) verringern, kann aber bei Patientinnen und Patienten mit schwerer Erkrankung (RR 0,98, 95% KI 0,86-1,12) wenig oder keine Wirkung haben. Das Risiko schwerer Blutungen kann unabhängig vom Schweregrad der Erkrankung zunehmen (RR 1,78, 95% KI 1,15-2,74). Die Evidenzsicherheit ist immer noch gering. Mäßig betroffene COVID-19 Patientinnen und Patienten können von einer therapeutischen Antikoagulation profitieren, jedoch ist das Blutungsrisiko erhöht. / COVID-19 patients have a high risk of thrombotic disease. The safety and efficacy of various anticoagulation regimens in COVID-19 patients remains unclear. Eight RCTs with 5580 patients were identified, with two comparing anticoagulation in intermediate doses and six comparing therapeutic doses to standard thromboembolism prophylaxis. Intermediate anticoagulation may have little or no effect on thrombotic events or deaths (RR 1.03, 95% CI 0.86-1.24), but may increase major bleeding (RR 1.48, 95% CI 0.53-4.15) in moderate to severe COVID-19 patients. Therapeutic anticoagulation may reduce thrombotic events or death in patients with moderate COVID-19 (RR 0.64, 95% CI 0.38-1.07), but may have little or no effect in patients with severe disease (RR 0.98, 95% CI 0.86-1.12). The risk of major bleeding may increase regardless of the severity of the disease (RR 1.78, 95% CI 1.15-2.74). The certainty of evidence is still low. Moderately affected COVID-19 patients may benefit from therapeutic anticoagulation, but the risk of bleeding is increased.

Yes / Since December 2019, a new type of coronavirus called novel coronavirus (2019-nCoV, or COVID-19) was identified in Wuhan, China and on March 11, 2020, the World Health Organization (WHO) has declared the novel coronavirus (COVID-19) outbreak a global pandemic. With more than 101,797,158 confirmed cases, resulting in 3,451,354 deaths as of May 21, 2021, the world faces an unprecedented economic, social, and health impact. The clinical spectrum of COVID-19 has a wide range of manifestations, ranging from an asymptomatic state or mild respiratory symptoms to severe viral pneumonia and acute respiratory distress syndrome. Several diagnostic methods are currently available for detecting the coronavirus in clinical, research, and public health laboratories. Some tests detect the infection directly by detecting the viral RNA using real time reverse transcriptase polymerase chain reaction (RT-PCR) and other tests detect the infection indirectly by detecting the host antibodies. Additional techniques are using medical imaging diagnostic tools such as X-ray and computed tomography (CT). Various approaches have been employed in the development of COVID-19 therapies. Some of these approaches use drug repurposing (eg Remdesivir and Dexamethasone) and combinational therapy (eg Lopinavir/Ritonavir), whilst others aim to develop anti-viral vaccines (eg mRNA and antibody). Additionally, health experts integrate data sharing, provide with guidelines and advice to minimize the effects of the pandemic. These guidelines include wearing masks, avoiding direct contact with infectious people, respiratory and personal hygiene.

The aim of this diploma thesis was to describe information about SARS-CoV-2 virus and coronavirus disease (COVID-19), to evaluate the course of the disease in the Home with a special regime in Břevnice, in which the epidemic took place at the beginning of the first wave of COVID-19 pandemic in spring 2020. Another goal was to perform an antibody analysis and evaluate the obtained data. I divided the diploma thesis into three main parts: theoretical, experimental and discussion. In the theoretical part, I worked with the literature and described information related not only to COVID-19, but also to other serious infections caused by human coronaviruses. In the experimental part, which I performed in the immunological laboratory of the Department of Joint Laboratories at Havlíčkův Brod Hospital, I dealt with the issue of the clinical course of the disease, the severity of the disease and possible consequences after the infection. I also dealt with methods for the determination of antibodies, the principles of which are described in Chapter 4.5. The diagnostic methods and procedures used are described in Chapter 5.3 Laboratory Assays. From the obtained data, I prepared graphs and tables and processed data on the clinical course of the infection in the Břevnice Home, both for the clients and the...

Se validó y evaluó un método de RT-PCR en tiempo real usando cebadores y sondas específicas para los genes RdRP de SARS-CoV-2 y GAPDH de humanos; este último fue usado como control endógeno. Se evaluó la especificidad y sensibilidad; además, se evaluó otros parámetros como la robustez, la repetibilidad, reproducibilidad, comparabilidad y el límite de detección. La sensibilidad, especificidad, los valores predictivos positivo y negativo, la robustez, comparabilidad y la repetibilidad-reproducibilidad de la prueba de RT-PCR en tiempo real dúplex fue de 100%, con un límite de detección de 100 copias/μL, de acuerdo con los criterios de aceptación establecidos para validación del protocolo. Esta prueba estandarizada es una buena alternativa para el diagnóstico de COVID-19; además, la prueba fue aplicada de manera exitosa en personas sospechosas de la enfermedad permitiendo controlar el número de falsos negativos.