Hackman, JN; (2023) Application of pathogen genomics to infer the transmission direction of respiratory infection. PhD thesis, London School of Hygiene & Tropical Medicine. DOI: https://doi.org/10.17037/PUBS.04671561
Permanent Identifier
Use this Digital Object Identifier when citing or linking to this resource.
Abstract
Understanding transmission direction is important for the epidemiological assessment of infectious diseases to identify sources and risks for infection and thus implement preventative measurements against disease acquisition. Thus, phylogenetic reconstruction methods, which infer transmission direction using genomic data of sampled individuals, are well suited for these investigations. Recent developments in sequencing technologies and bioinformatic tools have streamlined phylogenetic inference in the transmission direction of human pathogens with reduced cost and required resources. Previous approaches to infer transmission direction have mostly relied on epidemiological data which are time and cost intensive to follow and can lead to unreliable self-reported data from the study participants. In outbreak settings where the transmission involves multiple individuals such as hospital, household, and school settings, determining the source of the infection can be difficult to disentangle in the absence of genomic data. This PhD focuses on the capacity at which we can infer the transmission direction of Streptococcus pneumoniae and SARS-CoV-2 using whole-genome next-generation sequencing data from household settings with “known” transmission direction according to the epidemiological records. In addition to highlighting the potential role of within-host genetic diversity, in the context of Streptococcus pneumoniae co-carriage, in transmission events. In summary, the context of Streptococcus pneumoniae, increased sequencing read lengths and intra-host diversity, in the form of single nucleotide polymorphisms, increased our ability to infer the correct direction of transmission. Moreover, the presence of a transmission bottleneck can aid in identifying the source of infection. While for the SARS-CoV-2 study, the transmission direction inferred from the genomic data suggests reclassification of the household index case. Findings from this PhD show promising results that we can infer the linkage and transmission direction of respiratory pathogens, Streptococcus pneumoniae and SARS-CoV-2.
Item Type | Thesis |
---|---|
Thesis Type | Doctoral |
Thesis Name | PhD |
Contributors | Hue, S; Flasche, S; Toizumi, M and Lay-Myint, Y |
Faculty and Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology (-2023) |
Research Centre | Centre for the Mathematical Modelling of Infectious Diseases |
Funder Name | Nagasaki University |
Copyright Holders | Jada Hackman |
Download
Filename: 2023_IDE_PhD_Hackman_J.pdf
Licence: Creative Commons: Attribution-Noncommercial-No Derivative Works 4.0
Download