The analysis of real-world data and the development of mathematical models played a fundamental role in understanding the epidemiology of COVID-19 and informing public policies throughout the recent pandemic. This thesis presents a collection of modeling approaches and results addressing key questions that arose during the COVID-19 crisis, with a specific focus on the emergence and epidemiological features of SARS-CoV-2 variants of concern (VOC) in Italy and related public health implications. In the first chapter, conducted analyses suggest that the Alpha variant was approximately 50% more transmissible than historical lineages of SARS-CoV-2, and that this transmissibility advantage was enough to outcompete a variant associated with immune escape phenomena and circulating in central Italy in February 2021 (i.e., the Gamma variant). In the second chapter, by investigating the potential impact of new hypothetical VOCs in Italy in late 2021, modeling results highlighted that the emergence of variants associated with significant immune escape (i.e., with a rate at which vaccinated or recovered individuals from infection with pre-circulating lineages become infected being at least one-fifth that of unvaccinated individuals who never experienced SARS-CoV-2 infection) would have been able to replace pre-circulating lineages in a couple of weeks. Strict restrictions would have been required to prevent a new large epidemic wave. In the third chapter, the analysis of genomic and epidemiological data associated with the expansion of the Omicron variant over the Italian territory revealed that this variant was able to become dominant at the national level in less than a month, increasing the net reproduction number from 1.15 to 1.83. Despite the marked growth advantage of Omicron compared to the previously circulating Delta variant, a moderate impact on the number of severe cases was observed, likely due to the high proportion of vaccinated individuals in the country by the end of 2021. In the fourth chapter, the estimation of the intrinsic generation time of the Omicron variant (mean: 6.84 days) was found to be similar to that of previous lineages. Such estimates have been key to define adequate isolation, quarantine, surveillance, and contact tracing protocols in 2022. The prevention of SARS-CoV-2 transmission in educational settings represented a key challenge during the pandemic, due to the large proportion of asymptomatic carriers in young individuals. The last chapter presented in this thesis shows that, when the Alpha variant was circulating in Italy, almost half of positive students and school personnel ascertained during in-person education were likely infected by school contacts. The mean number of secondary cases caused at schools was found to be 0.33, with high heterogeneity in the chance of onward transmission. Provided estimates suggest that the timely identification of cases combined with reactive quarantine policies had the potential of reducing SARS-CoV-2 transmission in schools by at least 30%.

Die COVID-19 Pandemie ist die bisher verheerendste Pandemie des 21. Jahrhunderts. Durch die Einführung neuer mRNA-basierter Impfstoffe sowie der hohen Rate natürlicher Infektionen konnte die weltweite SARS-CoV-2-Immunität gesteigert werden. Trotz aller Erfolge zur Eindämmung der Pandemie kann eine Infektion auch heute noch zu schweren Verläufen und Tod führen. Eine adäquate COVID-19-Therapie ist folglich auf potente Virostatika angewiesen. Eine durch Umgehung zeitaufwändiger klinischer Studien schnell verfügbare Alternative zu neu entwickelten Arzneimitteln ist die Anwendung etablierter Medikamente. Wir isolierten und charakterisierten ein von einem Patienten stammendes SARS-CoV-2-Virus. Dieses Virusisolat wurde bisher in elf Publikationen verwendet. Mittels quantitativer Echtzeit-Polymerasekettenreaktion untersuchten wir eine Substanzbibliothek mit mehr als 300 neuen und bereits zugelassenen Wirkstoffen auf ihre Wirksamkeit gegen SARS-CoV-2. Dabei konnten wir zeigen, dass der selektive Serotonin-Wiederaufnahmehemmer Fluoxetin die SARS-CoV-2-Replikation ab einer Dosis von 0,8 μg/ml signifikant inhibiert, einer bei der Behandlung von Depressionen häufig angewandten Dosierung. Der EC50-Wert lag bei 387 ng/ml. Die Behandlung mit Fluoxetin resultierte in einer reduzierten Zahl an Virusprotein-produzierenden Zellen, was darauf hindeutet, dass es die virale Reinfektion und/oder Proteinexpression inhibiert. Fluoxetin ist ein racemisches Gemisch, wobei das (S)-Enantiomer der potentere Serotonin-Wiederaufnahmehemmer ist. Wir konnten zeigen, dass beide Enantiomere einen vergleichbaren antiviralen Effekt gegen SARS-CoV-2 aufweisen, wodurch das (R)-Enantiomer bei virologischer Indikation gegebenenfalls präferiert werden sollte. Fluoxetin hat keinen Einfluss auf die Replikation des Tollwut-Virus und des Humanen Respiratorischen Synzytial-Virus, was auf eine Virusspezifität hindeutet. Weitere aus der Bibliothek stammende signifikante Inhibitoren der SARS-CoV-2-Replikation sind die am Institut für Organische Chemie Würzburg entwickelten Substanzen AKS 232 und AKS 128. Neben der medikamentösen Therapie ist die akkurate Bestimmung neutralisierender Antikörper gegen SARS-CoV-2 zur Quantifizierung des bestehenden (Re-) Infektionsschutzes sowie zur Planung zukünftiger Impfstrategien von großer Bedeutung. Im Rahmen dieser Arbeit entwickelten wir unter Verwendung der quantitativen Echtzeit-Polymerasekettenreaktion erfolgreich ein zuverlässiges Testverfahren zur Detektion neutralisierender anti-SARS-CoV-2 Antikörper. / The COVID-19 pandemic is the most fatal pandemic of the 21st century. The introduction of new mRNA-based vaccines and the high rate of natural infections have increased global SARS-CoV-2 immunity. Despite the successes in containing the pandemic, infection can still lead to severe courses and death. COVID-19 treatment is therefore dependent on potent antivirals. The development of new antivirals is a prolonged process. By bypassing time-consuming clinical trials, repurposing established medication offers a quickly available alternative to newly developed drugs. We isolated and characterized a patient-derived SARS-CoV-2 virus. This virus isolate has been used in 11 publications so far. Using quantitative real-time polymerase chain reaction, we investigated a compound library with more than 300 new and already approved substances against SARS-CoV-2. We showed that the selective serotonin reuptake inhibitor Fluoxetine significantly inhibits SARS-CoV-2 replication at a concentration of 0.8 µg/ml, a dosage frequently used in the treatment of depression. The EC50 was determined with 387 ng/ml. Treatment with Fluoxetine resulted in a decrease in viral protein-expressing cells, indicating that it inhibits viral reinfection and/or protein expression. Fluoxetine is a racemate with the (S)-enantiomer being the dominant serotonin reuptake inhibitor. We have shown that both stereoisomers have a comparable antiviral effect against SARS-CoV-2, suggesting the (R)-enantiomer might be the preferred option for virological indications. Fluoxetine suppressed neither Rabies virus nor human Respiratory Syncytial Virus replication, indicating it is virus specific. Other significant inhibitors of SARS-CoV-2 replication originating in the compound library are AKS 232 and AKS 128, developed with the Institute of Organic Chemistry Würzburg. In addition to drug therapy, the accurate determination of neutralising antibodies against SARS-CoV-2 is of great importance for quantifying the existing (re)infection protection and for planning future vaccination strategies. In this work, we successfully developed a reliable test procedure for the detection of neutralising anti-SARS-CoV-2 antibodies using the quantitative real-time polymerase chain reaction.

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.

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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.