The nature of co-infection during outbreaks of infectious disease Pubblico
Bixler, Brianna Jeanne (Fall 2023)
Published
Abstract
In light of recent technological advancements that have decreased the cost of sequencing, we have seen a massive increase in publicly available datasets. This increase in quantity has led to new approaches to be implemented when solving epidemiological studies. With this, I have created computational pipelines to process and leverage publicly available datasets from around the world to understand the prevalence and impact of co-infections in the context of this wealth of data.
In my first research project, I focused on an outbreak of H. influenza (Hi), a pathogen that typically causes respiratory infections but in this case, was causing severe septic arthritis in individuals who were also HIV+. It is not clear whether this unusual clinical presentation was from a change introduction into a vulnerable population of HIV+ individuals, or if there is a genetic feature of these particular strains that causes increased virulence. In this study, we performed a comparative genomic analysis of the clinical isolates originally identified in metropolitan Atlanta in the context of the larger pangenome of over 4,000 Hi strains to identify potential features that may suggest enhanced virulence in the cluster strains.
In the second research project, I built a computational pipeline to process over 800 metatranscriptomic samples collected from individuals with COVID-19. After establishing this pipeline, we can ask basic epidemiological questions. With the output of this analysis, we are able to assess if there are any co-infections of viral, bacterial, or fungal pathogens in the nasal cavity at the onset of COVID-19. To understand the effect of co-infection, we looked for a correlation to viral burden and found that none of the pathogens seemed to correlate with an increased COVID-19 viral load.
To conclude, this dissertation will discuss aspects of co-infection in the larger context of thousands of isolates, a scale that is unprecedented for these pathogens. From this scale, we can determine what is unique and what remains common. We generate multiple hypotheses of what co-infections exist and how they may impact public health.
Table of Contents
Table of contents
Distribution Agreement ………………………………………………………………………………. 1
Approval Page ………………………………………………………………………………………... 2
Abstract Cover Page …………………………………………………………………………………. 3
Abstract ………………………………………………………………………………………………… 4
Dissertation Cover Page ……………………………………………………………………………… 6
Acknowledgements ……………………………………………………………………………………. 7
Chapter 1: Introduction ………………………………………………………………………………. 9
Chapter 2: NTHi ………………………………………………………………………………………. 27
Chapter 3: COVID-19 co-infection ………………………………………………………………….. 56
Chapter 4: Conclusion ……………………………………………………………………………….. 84
Appendix ………………………………………………………………………………………………. 86
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