Cytomegalovirus (CMV) is the most common congenitally acquired infection. It is of major concern due to the long-term neurodevelopmental morbidity in both symptomatic and asymptomatic newborns. While CMV infection is less commonly diagnosed in infancy to adulthood, mostly due to its asymptomatic presentation, it is still an important differential to consider. A missed diagnosis could lead to visual impairments and neurological complications. Infants can acquire CMV by encountering bodily secretions from those who have an active infection. Symptoms of infection include fever, fatigue, pharyngitis, and hepatitis. Laboratory abnormalities include thrombocytopenia, elevated transaminases, and abnormal lymphocyte count. We investigated a clinical case of a previously healthy 5-month-old whose only symptoms were petechial rash and thrombocytopenia. They presented to the ED with a worsening petechial rash for 11 days. The patient’s mother had prenatal care and an uncomplicated pregnancy. In the ED IgM for CMV was positive and platelet count on admission was 35K. The patient was discharged without intervention because platelet count remained above 20K. Outpatient hematology workup ruled out other potential causes of thrombocytopenia. There is no family history of bleeding disorders. The patient was prescribed valganciclovir for 2 months and urine CMV PCR was ordered for the patient and the patient’s mother. The patient’s urine CMV was positive, but the mother’s urine CMV was negative. The patient’s petechiae and thrombocytopenia improved while on valganciclovir treatment. In this case, since the patient’s mother was negative for CMV, it is unlikely that the infection was maternally acquired. Our case illustrates that CMV infection in infancy can be acquired through horizontal transmission and its only presentation can be thrombocytopenia. Since the CMV infection was diagnosed early the patient did not have any neurological symptoms, such as sensorineural hearing loss or delayed developmental milestones.

<p>The main body of this thesis deals with three related concepts pertaining to vaccination strategies for childhood infectious disease. Chapter 2 deals with the implications of reversion in the Oral Polio Vaccine on global polio eradication programs. Chapter 3 explores the phenomenon of contact or secondary vaccination in the use of live-attenuated virus vaccines. Chapter 4 explores the importance of demographic stochasticity in pulse vaccination campaigns. largely focusing on measles dynamics. Abstracts for each chapter are given below.</p><p>Poliomyelitis vaccination via live Oral Polio Vaccine (OPV) suffers from the inherent problem of reversion: the vaccine may, upon replication in the human gut, mutate back to virulence and transmissibility resulting in circulating vaccine derived polio viruses (cVDPVs). We formulate a general mathematical model to assess the impact of cVDPVs on prospects for polio eradication. We find that for OPV coverage levels below a certain threshold, cVDPVs have a small impact in comparison to the expected endemic level of the disease in the absence of reversion. Above this threshold, the model predicts a small but significant endemic level of the disease, even where standard models predict eradication. In light of this, we consider and analyze three alternative eradication strategies involving a transition from continuous OPV vaccination to either continuous Inactivated Polio Vaccine (IPV), pulsed OPV vaccination, or a one-time IPV pulse vaccination. Stochastic modeling shows continuous IPV vaccination is effective at achieving eradication for moderate coverage levels, while pulsed OPV is effective if higher coverage levels are maintained. The one-time pulse IPV method may also be a viable strategy, especially in terms of the number of vaccinations required and time to eradication, provided that a sufficiently large pulse is practically feasible. More investigation is needed rq?;arding the frequency of revertant virus infection resulting directly from vaccination, the ability of IPV to induce gut immunity, and the potential role of spatial transmission dynamics in eradication efforts.</p> <p>Viruses contained in live-attenuated vims vaccines (LAVV) can be transmitted between individuals, resulting in secondary or contact vaccinations. This fact has been exploited successfully in the use of the Oral Polio Vaccine (OPV) to better control wild polio viruses. In this work we analyze general LAVV vaccination models for infections that confer lifelong immunity. We consider both standard (continuous) vaccination strategies and pulse vaccination programs (where mass vaccination is carried out at regular intervals). For continuous vaccination, we provide a complete global analysis of a very general compartmental ordinary differential equation LAVV model. We find that the threshold vaccination level required for eradication of wild virus depends on the basic reproduction numbers of both the wild and vaccine viruses, but is otherwise independent of the distributions of the durations in each of the sequence of stages of disease progression (e.g., latent, infectious, etc.). Furthermore, even for vaccine viruses with reproduction numbers below one. which would naturally fade from the population upon cessation of vaccination, there can be a significant reduction in the threshold vaccination level. The dependence of the threshold vaccination level on the virus reproduction numbers largely generalizes to the pulse vaccination model. For shorter pulsing periods there is negligible difference in threshold vaccination level as compared to continuous vaccination campaigns. Thus, we conclude that current policy in many countries to employ annual pulsed OPV vaccination does not significantly diminish the benefits of contact vaccination.</p><p> In the last two decades, many countries have implemented pulse vaccination for infectious diseases (mass vaccination campaigns repeated annually or at other regular intervals). Based on deterministic mathematical models, previous work has shown that the total expected cost of control or eradication (measured by the number of vaccine doses required) is identical for pulse vaccination (with any pulse interval) and for traditional, continuous vaccination. We reconsider this problem using stochastic epidemic models (both by direct simulation and by employing a moment closure approximation). We focus on measles and show that demographic stochasticity has a large impact on the relative success of pulse and continuous vaccination programs, even for well-mixed populations as large as 10 million.</p> / Thesis / Doctor of Philosophy (PhD)

Background: ​Infectious disease outbreaks are amongst the most threatening of disasters, capable of affecting the health and economies of millions of people around the world in a single occurrence. Mathematical models are a tool that can be used to synthesize information from different disciplines into a comprehensive model, which can further be used to guide public health in making appropriate economic and social decisions. However, the integration of modelling within public health is not maximized. This study aims to explore perceptions of key stakeholders in planning, producing and applying infectious disease mathematical models in public health. Methodology: ​Data was collected using semi-structured key informant interviews with key stakeholder groups (n=19), academic modellers (n=6), government modellers (n=5), government end-users (n=5) and professionals and practitioners who are end-users (n=4). Data was analyzed with thematic analysis with NVivo 11 (QSR International). A stakeholder analysis was used to map out the interrelatedness of key stakeholder issues, and a thematic analysis was used to abstract themes of collaboration between stakeholders, challenges with data and perceptions of predictive modelling. Results and Conclusion:​ The findings of this study identify and organize important insights and recommendations required to optimize the utilization of infectious disease mathematical models in public health decision-making. The findings suggest that models that are most applicable to public health problems often go through iterative collaborations between end-users and modellers. The findings also suggest that there are growing challenges when it comes to the collection and interpretation of sources of infectious disease data and that mathematical models are valuable when used for understanding infectious disease outbreaks and/or interventions, rather than projecting the course of a specific outbreak. This study recommends actions be taken in education, practice and research to minimize the existing gap between mathematical models of infectious disease and their application for public health decision-making. / Thesis / Master of Science (MSc)

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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

No description available.

<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.

Human T lymphotropic virus type -1 (HTLV-1) infections are important causes of mortality and morbidity in endemic areas worldwide. There is neither a vaccine specific for the virus nor satisfactory treatment for the associated malignancy or inflammatory syndromes. HTLV-1 associated infective dermatitis (IDH) is a chronic dermatitis that has been observed in a variable proportion of HTLV-1 infected children. IDH may serve as an early clinical marker for HTLV-1 and an indicator of increased risk for developing other HTLV-1 associated conditions such as adult T cell leukaemia/lymphoma (ATLL) and HTLV-1-associated myelopathy or transient spastic paraparesis (HAM/TSP). However the mechanisms underlying IDH and the relationships with HAM/TSP and ATLL are poorly understood. We undertook skin biopsies from 14 cases with IDH, and controls which included five asymptomatic carriers (ACs) and 18 healthy uninfected individuals from South Africa. We conducted clinical assessments, proviral load, allergen-specific IgE, peripheral blood and cutaneous T cell and virological analyses. We obtained relevant clinical history and examined all cases and controls based on a pre-formed questionnaire. Despite the partial clinical similarities with atopic dermatitis, the individuals with IDH did not have an increased incidence of atopic disease including asthma or rhinitis. Furthermore house dust mite-specific IgE levels were not elevated in the cases compared to the controls, suggesting that atopy is not a predisposing factor for the development of IDH in HTLV-1 infected individuals. Circulating proviral load was significantly higher in those with IDH compared to asymptomatic carriers and skin biopsy revealed acanthosis, and lymphocytic epidermotropism associated with a superficial perivascular and periadnexal lymphocytic infiltration of CD8+, and CD4+ T cells. Furthermore IDH associated with an infiltrate of epidermal and dermal FoxP3+ T cells and lesional down-regulation of filaggrin expression compared to non-lesional skin. We did not observe an elevation of pro-inflammatory cytokines in the sera of individuals with IDH compared to the controls. We investigated integration patterns in the skin and blood of 10 cases with IDH, and two asymptomatic carrier (AC) individuals from South Africa. We first showed that the virus is present in the skin at high levels (total mean levels of 47.09 proviral copies per 1000 cells) as comparable to that which has been observed in blood (total mean levels 137 proviral copies per 1000 cells). Using a high throughput Illumina sequencing system in collaboration with Professor Bangham, we mapped and quantified the relationship between oligoclonal proliferation of HTLV-1 infected T cells in the skin and blood of IDH patients. It was found that in IDH, a selective outgrowth of certain clones is favoured, supporting the possibility of skin-specific factors exerting positive selection on proliferation. In IDH, there was not a preferential integration of the provirus in transcriptionally active regions of the gene sites, as had been observed in other HTLV-1 associated conditions. These observations imply that the selection forces that favour oligoclonal proliferation of HTLV-1+ T cells differ fundamentally between simple HTLV-1 infection and other events associated with the dermatitis. In conclusion, these data show that HTLV-1 is not associated with an atopic diathesis. Given the lack of elevated pro-inflammatory cytokines and presence of a cutaneous infiltrate of FoxP3+ T cells, the findings suggest that high levels of HTLV-1 replication promotes a regulatory environment leading to filaggrin down-regulation, cutaneous susceptibility to infection, and secondary inflammatory skin disease. Viral integration patterns would support the presence of skin-specific positive selection, perhaps eventually leading to expansion of particular clones with the potential to develop towards ATLL. It remains to be explained whether the high viral load in IDH changes over time, more specifically in the steps leading to ATLL.