Can genomics and meteorology predict outbreaks of legionellosis in urban settings?

Abstract

Legionella pneumophila is ubiquitous and sporadically infects humans causing Legionnaires disease (LD). Globally, reported cases of LD has risen four-fold from 2000-2014. In 2016, Sydney, Australia was the epicentre 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 cgMLST 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.