This dissertation is a tale of two emerging human pathogens. The first is a genus of viruses, orthoebolaviruses, which periodically cause outbreaks in humans in central and western Africa following spillover from animal reservoirs. Outbreaks of orthoebolaviruses have high rates of morbidity and mortality and can cause symptoms ranging from vomiting and diarrhea to hemorrhage. Understanding both how the virus evolves to fit its host as well as how the host reacts to viral infection is paramount to understanding what determines whether an infected patient will die or survive orthoebolavirus infection. To understand how orthoebolavirus genomic plasticity allows the virus to optimize itself to its host, I analyzed viral genomic sequencing data from two Orthoebolavirus species during serial passage in tissue culture: Ebola virus and Sudan virus. In low-passage Sudan virus, I discovered a true viral quasispecies in which three to four viral genotypes circulated within the same stock. I then examined how that quasispecies reacted when put into a nonhuman primate model (NHP) of infection; unexpectedly, we saw that the mix of genotypes in the challenge stock matched the mix of genotypes seen at clinical endpoint. To begin to understand what a successful immune response to orthoebolavirus infection entails, I characterized the circulating transcriptomic response in two survival models of Ebola virus disease. In a uniform survival model where NHPs were challenged with Bombali virus, I showed that NHPs have a clear and robust response to infection despite varying symptom severity. In a Taï Forest virus challenge model with ~44% survival, I showed that NHPs that succumb do so in a uniform manner consistent with other models of Ebola virus disease. In contrast, survivors were highly variable in their response to infection: some mimicked the non-survivor response but recovered in time, while others hardly responded at all. After covering orthoebolavirus genomic plasticity and the host response to infection in the first and second sections, respectively, I will then shift to the other focus of my dissertation work: SARS-CoV-2 and molecular epidemiology. SARS-CoV-2 swept the globe in 2020 following spillover into humans from an animal reservoir in late 2019, and surveillance sequencing of viral genomes early in the pandemic showed the virus was rapidly adapting to its new host. I leveraged this high mutation rate to spin up a molecular epidemiology operation for Boston Medical Center (BMC) and Boston University (BU). From mid-2020 through spring 2022, I catalogued, processed, sequenced, and analyzed samples and viral genomes from over 7,000 SARS-CoV-2 patient swabs. I worked with contact tracing teams, physicians, and infection control from BU and BMC to quantify viral introductions, identify transmission chains, and integrate the genetic linkages with traditional epidemiological data. / 2025-01-11T00:00:00Z

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<p>The <em>Streptococcus</em> Milleri Group (SMG) asymptomatically colonize the gastrointestinal, female urogenital, and upper respiratory tract in the healthy population, and are therefore traditionally considered commensals. The SMG, however, are also pathogens that cause pyogenic and pulmonary infections. The factors that differentiate pathogenic from non-pathogenic isolates have proven difficult to identify, and consequently the determinants of SMG pathogenicity remain unknown. Characterization of the immune response to the SMG is important towards advancing the understanding of SMG pathogenicity, however there are limited studies that have done so.</p> <p>Herein, we sought to investigate the cytokine profiles produced by human peripheral blood mononuclear cells in response to 35 clinical isolates of the SMG. Cytokine profiles varied across isolates resulting in a spectrum of responses that separated into three subgroups including a high, intermediate, and low response group. The responses were consistent across three individuals with the exception of several differences, which are discussed and warrant further studies on host susceptibility to SMG infections. The high and intermediate response groups were enriched with clinical isolates from invasive infections, which were found to induce significantly higher cytokine production than airway isolates. Cytokine induction was independent of TLR2 activation, suggesting that other pattern recognition receptors are involved in the recognition of and response to the SMG. Phenotypic characteristics, which are used in the clinical identification of the SMG, did not correlate with cytokine induction; therefore phenotypic tests are not sufficient to identify immunostimulatory isolates. The host response to the SMG characterized in this study provides foundational knowledge for future studies to investigate the mechanism of recognition as well as the function of downstream effector responses in the control of colonization and infection.</p> / Master of Science (MSc)

Mathematical and statistical models are widely used in studying infectious disease. They provide important insights – including mechanisms of the spread of infectious disease, forecast epidemic size and duration, and effects of intervention strategies – which are useful in studying and combating infectious disease. Over the last couple of decades, modeling techniques have advanced tremendously due to improvements in computational power, data availability, and data accessibility; this enables researchers to use various modeling approaches to capture more realistic aspects of infectious disease epidemics. Despite having flexible modeling techniques, these approaches use different modeling assumptions to incorporate information and propagate uncertainty, often arriving at inconsistent conclusions. My work focuses on exploring and improving methods for modeling the spread of infectious disease; in particular, exploring the state of the art techniques for disease modeling in real epidemic outbreaks and simulation settings. Motivated by a synthetic forecasting challenge inspired by the 2014 West African Ebola outbreak, I compared simple Markov chain Monte Carlo approaches to simulated epidemics (Chapter 2). Using high-resolution data from an ongoing rabies contact- tracing study, I apply robust techniques to reassess global historical risk estimates of canine rabies (Chapter 3), and show that disease trait correlations bias generation time estimates, with implications for conclusions about control (Chapter 4). In Chapter 5, I developed a method to improve modeling trait relationships while incorporating phylogenetic relationships by reformulating phylogenetic mixed models to improve flexibility and speed. / Dissertation / Doctor of Philosophy (PhD)

Accurate forecasting of infectious disease outbreaks is vital for safeguarding global health and the well-being of individuals. Model-based forecasts enable public health officials to test what-if scenarios, evaluate control strategies, and develop informed policies to allocate resources effectively. Model selection is a pivotal aspect of creating dependable forecasts for infectious diseases. This thesis delves into validating forecasts of simple epidemic models. We use incidence data from the 2015-2016 Zika virus outbreak in Antioquia, Colombia, to assess what model features result in accurate forecasts. We employed the Parametric Bootstrapping and Ensemble Kalman Filter methods to assimilate data and then generated 14-day-ahead forecasts throughout the epidemic across five case studies. We visualized each forecast to show the training/testing split in data and associated prediction intervals. Fore- casting accuracy was evaluated using five statistical performance metrics. Early into the epidemic, phenomenological models - like the generalized logistic model - resulted in more accurate forecasts. However, as the epidemic progressed, the mechanistic model incorporating disease latency outperformed its counterparts. While modeling disease transmission mechanisms is crucial for accurate Zika incidence forecasting, additional data is needed to make these models more reliable and precise. / Master of Science / Accurate forecasting of infectious disease outbreaks is vital for safeguarding global health and the well-being of individuals. Model-based forecasts enable public health officials to test what-if scenarios, evaluate control strategies, and develop informed policies to allocate resources effectively. Model selection is a pivotal aspect of creating dependable forecasts for infectious diseases. This thesis delves into validating forecasts of simple epidemic models. We use data from the 2015-2016 Zika virus outbreak in Antioquia, Colombia, to assess what model features result in accurate forecasts. We considered two techniques to generate 14-day-ahead forecasts throughout the epidemic across five case studies. We visualized each forecast and evaluated model accuracy. Early into the epidemic, simple growth models resulted in more accurate forecasts. However, as the epidemic progressed, the model incorporating disease-specific characteristics outperformed its counterparts. While modeling disease transmission is crucial for accurate epidemic forecasting, additional data is needed to make these models more reliable and precise.

Infectious disease management system area is considered as an emerging field of modern healthcare in the Gulf region. Significant technical and clinical progress and advanced technologies can be utilized to enhance the performance and ubiquity of such systems. Effective infectious disease management (IDM) can be achieved by analysing the disease management issues from the perspectives of healthcare personnel and patients. Hence, it is necessary to identify the needs and requirements of both healthcare personnel and patients for managing the infectious disease. The basic idea behind the proposed mobile IDM system in this thesis is to improve the healthcare processes in managing infectious diseases more effectively. For this purpose, internet and mobile technologies are integrated with social networking, mapping and IDM applications to improve the processes efficiency. Hence, the patients submit their health related data through their devices remotely using our application to our system database (so-called SAIF). The main objective of this PhD project was the design and development of a novel web based architecture of next-generation infectious disease management system embedding the concept of social networking tailored for Saudi patients. Following a detailed literature review which identifies the current status and potential impact of using infectious diseases management system in KSA, this thesis conducts a feasibility user perspective study for identifying the needs and the requirements of healthcare personnel and the patients for managing infectious diseases. Moreover, this thesis proposes a design and development of a novel architecture of next-generation web based infectious disease management system tailored for Saudi patients (i.e., called SAIF – infectious diseases management framework for Saudi Arabia). Further, this thesis introduces a usability study for the SAIF system to validate the acceptability of using mobile technologies amongst infected patient in KSA and Gulf region. The preliminary results of the study indicated general acceptance of the patients in using the system with higher usability rating in high affected patients. In general, the study concluded that the concept of SAIF system is considered acceptable tool in particularly with infected patients.

Masks have become an important part of everyday life, protecting both the wearer and individuals nearby from the spread of infectious diseases, most notably severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the coronavirus that causes coronavirus disease 2019 (COVID-19). However, these masks are easily contaminated, whether through continued use or by the wearer touching the mask fabric with contaminated hands, therefore reducing the efficacy and exposing the user to these contagions. When the mask becomes contaminated, it can be discarded, which produces large amounts of waste that will end up in a landfill, or it can be washed, which is costly, wasteful, and time consuming. Our solution to this problem is a mask apparatus that can sanitize itself quickly on demand. The user wears the shell, which contains the fully retracted mask, on a string like they would a necklace. When the mask is required, it is easily pulled out of the shell and can be worn for as long as the user needs it. When it is safe to remove the mask, the user simply pushes a button and the mask retracts back into the shell, where it is then sanitized for the next use. The design of the apparatus features a retractable cloth mask that is sanitized using ultraviolet-C (UVC) radiation while confined safely within an outer shell, minimizing unwanted exposure to the wearer. UVC radiation at wavelength 222 nm has been shown to destroy the outer shell of coronaviruses similar to SARS-CoV-2, inactivating 99.9% of the virus when exposed at a dosage of 2 mJ/cm2. The 28 light-emitting diode (LED) lamps used in this prototype produce this specified wavelength UVC and are separated into 4 strips located in different locations within the shell. Glass rods were used within the shell to guide the mask fabric into a zig-zag shape when fully retracted to maximize exposure to the UVC. To further reduce waste, two lithium-ion rechargeable batteries were used as the power supply for the lamps. The efficacy of this design for inactivating the SARS-CoV-2 coronavirus on the mask was determined indirectly using nano membrane UV sensors placed on the mask fabric, showing that the specified wavelength of UVC radiation can be applied for the required time on all surfaces of the mask. This mask apparatus can directly benefit both front-line healthcare workers as well as individuals going about their daily lives by eliminating pathogens present on their masks, therefore reducing the spread of deadly infectious diseases.

In 1989 the hepatitis C virus was identified as a significant cause of post-transfusion hepatitis. Nearly two decades later there is still no vaccine, inadequate treatment options, and limited understanding of how the virus establishes chronicity in the majority of the people it infects. Recent reports suggest that the interaction of a negative co-stimulatory pathway mediated by PD-1 and PDL-1 is associated with persistent viral infection. The role, if any, that PD-1/PDL-1 has in HCV infection is unknown. In this study we report that PD-1 is upregulated in T-cells from persons with chronic HCV infection when compared to healthy donors. In addition, PD-1 and PDL-1 are upregulated on T-cells from healthy donors when exposed to extracellular HCV core protein (a nucleocapsid protein that is immunosuppressive); upregulation of PD-1 is mediated by core's ability to bind to the complement receptor gC1q. We also report that the observed T-cell function can be restored by blocking the PD-1/PDL-1 interaction. Our results indicate that HCV core can upregulate an important negative T-cell signaling pathway that is associated with viral persistence. This upregulation of PD-1/PDL-1 represents a novel and perhaps shared mechanism that viral pathogens may use to subvert the human immune response. It also represents a potential new treatment option for the millions of people who suffer from chronic hepatitis C infection.

Human immunodeficiency virus (HIV) has become a global pandemic over the past few decades, with new infections and related deaths in the millions each year. There is no cure in sight for HIV-1 infection, and there has been little progress in developing an efficacious vaccine. Heterosexual transmission of HIV-1 remains the principal mode of transmission throughout the world and thus measures, such as topical vaginal microbicides, to prevent infection of the female reproductive tract are actively being explored. Recent trials of topical vaginal microbicides have shown that their interaction with the mucosal surfaces of the female reproductive tract as well as semen can hinder microbicide effectiveness against HIV-1 infection. Therefore, understanding the role these fluids play in HIV transmission would be critical towards developing effective antiviral prophylaxes. A recent study from our group demonstrated that human cervicovaginal secretions contained numerous cationic antimicrobial peptides and proteins, which collectively inhibited HIV-1 infection of target cells and tissues. To ascertain if human seminal plasma (SP), the main vector responsible for transmitting HIV-1, exhibited antiviral activity we utilized several antiHIV assays in the presence or absence of minimally manipulated SP. The majority of the intrinsic anti-HIV-1 activity of SP resided in the cationic polypeptide fraction. Antiviral assays utilizing luciferase reporter cells and lymphocytic cells revealed the ability of whole SP to prevent HIV-1 infection, even when SP was diluted 3200-fold. Subsequent fractionation by continuous flow acid-urea (AU)-PAGE and antiviral testing revealed that cationic polypeptides within SP were responsible for the majority of anti-HIV-1 activity. A proteomic approach was utilized to resolve and identify 52 individual cationic polypeptides that contribute to the aggregate anti-HIV-1 activity of SP. One peptide fragment of semenogelin I, termed SG-1, was purified from SP by a multi-step chromatographic approach, protein sequenced, and determined to exhibit anti-HIV-1 activity against HIV-1. Anti-HIV-1 activity was transient, as whole SP incubated for prolonged time intervals exhibited a proportional decrease in anti-HIV-1 activity that was directly attributed to the degradation of semenogelin I peptides. Collectively, these results indicate that the cationic polypeptide fraction of SP is active against HIV-1, and that semenogelin-derived peptides contribute to the intrinsic anti-HIV-1 activity of SP. Conversely, naturally occurring peptidic fragments from the SP-derived prostatic acid phosphatase (PAP) have been reported to form amyloid fibrils called "SEVI" capable of enhancing HIV-1 infection in vitro. In order to understand the biological consequence of this proviral effect, we extended these studies in the presence of human SP. PAP-derived peptides were agitated to form SEVI and incubated in the presence or absence of SP. While PAP-derived peptides and SEVI alone were proviral, the presence of 1% SP ablated their proviral activity in several different anti-HIV-1 assays. The anti-HIV-1 activity of SP was concentration dependent and was reduced following filtration. Supraphysiological concentrations of PAP peptides and SEVI incubated with diluted SP were degraded within hours, with SP exhibiting proteolytic activity at dilutions as high as 1:200. Sub-physiological concentrations of two prominent proteases of SP, prostate-specific antigen (PSA) and matriptase, could degrade physiological and supraphysiological concentrations of PAP peptides and SEVI. While human SP is a complex biological fluid, containing both antiviral and proviral factors, our results suggest that PAP peptides and SEVI may be subject to naturally occurring proteolytic components capable of reducing their proviral activity. Our studies demonstrate the overall antiviral activity of human SP, but there is still a critical need for effective topical vaginal microbicides that can prevent HIV-1 transmission. The synthetic human retrocyclins are cyclic antimicrobial peptides that are remarkably active against HIV-1, and are being developed as topical vaginal microbicides. Herein, we assessed whether the putative proviral SEVI was able to adversely affect the anti-HIV-1 activity of the retrocyclin analog RC-101. While SEVI alone enhanced viral infection, this effect was completely negated in the presence of RC-101. Retrocyclins such as RC-101 are inhibitors of HIV-1 entry, by preventing gp41-mediated viral fusion. Interestingly, using an HIV-1 reverse transcriptase (RT) specific assay, we also determined that RC-101 directly inhibited the activity of RT in a dose dependent manner, suggesting a secondary mechanism of viral inhibition. Our group has determined that RC-101 induces only a modest level of resistance in HIV, which may be due in part to RC-101's dual mechanisms of viral inhibition.

<p>Antibiotic use is generally regarded as the major driver for resistance. Many studies reporting an association between antibiotic use and the emergence of resistance have been published. However, most studies have significant limitations such as single center data with comparably low number of cases, using retrospective designs with limited data availability, ecological studies with lack of assessing the individual level and risk for ecological fallacy, and inappropriate selection of controls in case-control studies.</p> <p>A cohort study in adult patients hospitalized in 15 participating acute care hospital sites in Ontario, Canada, was conducted from April 1 2005 to June 30 2006. Antibiotic use on the unit level in defined daily doses (DDD) was only available for 3 sites. In order to assess antibiotic use on both the individual as well as on the unit level as a risk factor for resistance, days of therapy (DOT) could be calculated. However, it was unclear whether this approach would results in similar findings as when using DDD. Thus, the impact of using either DDD or DOT on the risk estimates for resistance was assessed for three antimicrobial-bacteria combinations, i.e. fluoroquinolone use and fluoroquinolone resistance in enterobacteriaceae an in <em>Pseudomonas aeruginosa</em>, and the use of betalactams and resistance to third generation cephalosporins in enterobacteriaceae.</p> <p>The risk estimates for resistance were very similar for all three antimicrobial-bacteria combinations on acute care units, there were some discrepancies on the unit level on intensive care units, and discrepancies on both levels for step down and rehabilitation units.</p> <p>In conclusion, the approach to use DOT instead of DDD to measure antibiotic utilization revealed similar results. However, the lack of comprehensive information on patient transfers when calculating DOT may bias the findings on units with frequent patient transfers such as intensive care units and step down and rehabilitation units.</p> / Master of Science (MSc)