- Title
- Can genomics and meteorology predict outbreaks of legionellosis in urban settings?
- Creator
- Timms, Verlaine J.; Sim, Eby; Pey, Keenan; Sintchenko, Vitali
- Relation
- Appl Environ Microbiol Vol. 90, Issue 8, p. 1-12
- Publisher Link
- http://dx.doi.org/10.1128/aem.00658-24
- Publisher
- American Society for Microbiology
- Resource Type
- journal article
- Date
- 2024
- Description
- Legionella pneumophila is ubiquitous and sporadically infects humans causing Legionnaire’s disease (LD). Globally, reported cases of LD have risen fourfold from 2000 to 2014. In 2016, Sydney, Australia was the epicenter of an outbreak caused by L. pneumophila serogroup 1 (Lpsg1). Whole-genome sequencing was instrumental in identifying the causal clone which was found in multiple locations across the city. This study examined the epidemiology of Lpsg1 in an urban environment, assessed typing schemes to classify resident clones, and investigated the association between local climate variables and LD outbreaks. Of 223 local Lpsg1 isolates, we identified dominant clones with one clone isolated from patients in high frequency during outbreak investigations. The core genome multi-locus sequence typing scheme was the most reliable in identifying this Lpsg1 clone. While an increase in humidity and rainfall was found to coincide with a rise in LD cases, the incidence of the major L. pneumophila outbreak clone did not link to weather phenomena. These findings demonstrated the role of high-resolution typing and weather context assessment in determining source attribution for LD outbreaks in urban settings, particularly when clinical isolates remain scarce.
- Subject
- Legionella pneumophila; Legionnaires' disease; surveillance; epidemilogy; bacterial genomics; whole genome sequencing; SDG 3; Sustainable Development Goal
- Identifier
- http://hdl.handle.net/1959.13/1510370
- Identifier
- uon:56395
- Identifier
- ISSN:0099-2240
- Language
- eng
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