Molecular evolution and genomic surveillance of dengue virus in Africa
Abstract/Contents
- Abstract
- Dengue is an arboviral infection that poses a significant public health risk, particularly in tropical and subtropical developing countries. Recent years have seen an increase in frequency and severity of outbreaks in endemic regions, as well as expansion of the virus to previously naïve areas, resulting in consequential shifts in disease dynamics. Notably several dengue outbreaks have been observed in sub-Saharan Africa, a region in which the burden and severity of dengue is poorly understood. Despite the increasing burden of dengue globally and in sub-Saharan Africa, the virus' continued expansion in this region, as well as the influence of its evolutionary features and their interplay with human and ecological factors in determining spread, have not been examined. In this dissertation, I use newly collected viral sequence data, combined with past sequence data from public databases, along with novel phylogenetic and phylodynamic tools to examine the introduction and expansion of dengue virus in sub-Saharan Africa. In the first chapter I examine the circulating genetic diversity of dengue virus serotype 2 with a focus on outbreaks in coastal and western Kenya, using sequence data collected from a cohort of patients recruited from four clinical sites in Kenya between 2014 and 2022. I use phylogenetic trees to show that dengue circulation in the region is not monophyletic and is characterized by multiple circulating lineages introduced at different times and circulating undetected for varying periods. Phylogeographic models suggest frequent importation of dengue virus into Kenya from East and Southeast Asia via the coastal port of Mombasa. In my second chapter, I further examine the introduction, expansion and circulation dynamics of the additional dengue serotypes 1 and 3, that have been detected in the region. I show that expansion of these additional dengue serotypes follows similar geographic trajectories as the expansion of dengue serotype 2 and thus may be governed by the same drivers. I also identify the increasing frequency of dengue 1 outbreaks in the region suggesting serotype replacement of dengue 2, a phenomenon previously observed in other regions over the course of the expansion of the virus. In my final chapter, I examine the integration of sequencing and case notification data for scaled and effective surveillance of dengue virus. I use global databases of sequencing and case-notification data, as well as recently developed maximum likelihood phylodynamic tools to determine how accurately sequence-based epidemiological metrics of dengue virus outbreak and epidemic activity capture disease dynamics, compared to case-notification data based metrics. I show that sequenced-based measures of outbreak trends do not capture granular outbreak or epidemic patterns but may serve as an important measure of the behavior of outbreaks and epidemics at broad temporal and spatial scales. I also show low concordance between sequence-based metrics and case notification based metrics and conclude that this is due to low data quality, and poorly defined frameworks for the integration of these distinct data types. The expansion of dengue virus is expected to continue, driven primarily by climate change and globalization. As the expansion of the virus continues, it will be imperative to understand pathways of expansion in order to interrupt spread and determine how to effectively use available data to understand dengue disease dynamics. In this dissertation, I examine these pathways in the case of dengue serotype 1, 2 and 3 in Africa using modern tools and methods in genomics and phylogenetics, and further consider how to integrate distinct data types for dengue surveillance. Inferences from these and other modeling and phylogenetic studies can inform disease preparedness measures in advance of dengue outbreaks in Africa, as well as intervention measures during outbreaks.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2023; ©2023 |
| Publication date | 2023; 2023 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Nyathi, Sindiso Victor |
|---|---|
| Degree supervisor | Andrews, Jason |
| Thesis advisor | Andrews, Jason |
| Thesis advisor | Bennett,Shannon |
| Thesis advisor | LaBeaud, Desiree |
| Thesis advisor | Mordecai, Erin |
| Degree committee member | Bennett,Shannon |
| Degree committee member | LaBeaud, Desiree |
| Degree committee member | Mordecai, Erin |
| Associated with | Stanford University, School of Medicine |
| Associated with | Stanford University, Department of Epidemiology |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Sindiso Nyathi. |
|---|---|
| Note | Submitted to the Department of Epidemiology. |
| Thesis | Thesis Ph.D. Stanford University 2023. |
| Location | https://purl.stanford.edu/zj369hh7400 |
Access conditions
- Copyright
- © 2023 by Sindiso Victor Nyathi
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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