Quantitative Microbial Risk Assessment Applied to Legionella Contamination on Long-Distance Public Transport

Abstract

The quantitative microbial risk assessment (QMRA) framework is used for assessing health risk coming from pathogens in the environment. In this paper, we used QMRA to evaluate the infection risk of L. pneumophila attributable to sink usage in a toilet cabin on Italian long-distance public transportation (LDT). LDT has water distribution systems with risk points for Legionella proliferation, as well as premise plumbing for drinking water, but they are not considered for risk assessment. Monitoring data revealed that approximately 55% of water samples (217/398) were positive for L. pneumophila, and the most frequently isolated was L. pneumophila sg1 (64%, 139/217); therefore, such data were fitted to the best probability distribution function to be used as a stochastic variable in the QMRA model. Then, a sink-specific aerosolization ratio was applied to calculate the inhaled dose, also considering inhalation rate and exposure time, which were used as stochastic parameters based on literature data. At L. pneumophila sg1 concentration ≤100 CFU/L, health risk was approximately 1 infection per 1 million exposures, with an increase of up to 5 infections per 10,000 exposures when the concentrations were ≥10,000 CFU/L. Our QMRA results showed a low Legionella infection risk from faucets on LDT; however, it deserves consideration since LDT can be used by people highly susceptible for the development of a severe form of the disease, owing to their immunological status or other predisposing factors. Further investigations could also evaluate Legionella-laden aerosols from toilet flushing.

Keywords: Legionella pneumophila; bioaerosol; long-distance public transport; monitoring; premise plumbing; public health; risk assessment; train; water distribution system.

Figure 1

Schematics of the QMRA model framework and model input parameters for the modeled exposure scenario of sink usage on LDT.

Figure 2

Annual variability of L. pneumophila concentrations in positive samples. For each year, the distribution of the whole Legionella concentration values is represented by boxplot and the serogroups are identified by different colors. Red dashed lines correspond to Legionella thresholds in water for the application of control measures in healthcare and community settings, according to Italian guidelines [23].

Figure 3

Results of the fitting of a Lognormal distribution to the monitoring dataset. Empirical and theoretical distributions are represented as probability density function (PDF) (a) or as cumulative density function (CDF) (b). Empirical data set plotted against the theoretical lognormal data set are represented as P-P plot (c) and Q-Q plot (d). A straight blue line represents perfect fitting in (c,d).

Figure 3

Results of the fitting of a Lognormal distribution to the monitoring dataset. Empirical and theoretical distributions are represented as probability density function (PDF) (a) or as cumulative density function (CDF) (b). Empirical data set plotted against the theoretical lognormal data set are represented as P-P plot (c) and Q-Q plot (d). A straight blue line represents perfect fitting in (c,d).

Figure 4

Estimated probability of infection for single use of faucet for different concentrations of L. pneumophila sg1 in water, according to concentration categories for water management actions.

Figure 5

Sensitivity analysis results for the QMRA model. The histograms represent the average values of the pairwise differences of P_inf when all the input parameters are fixed and one varying at a time.