Utilizing big data to determine the temperature dependency of Legionella in hot water systems

Abstract

ABSTRACT Domestic hot water installations provide an ideal habitat for Legionella spp. and pose a potential risk of human infection. Heating the water is considered the major preventive measure against Legionella contamination. Our study aimed to understand better the relationships between hot water temperatures and Legionella spp. occurrence within such systems. We utilized routine monitoring data from public and apartment buildings, comprising 292,937 data sets. We employed the analysis of variance, receiver operating characteristic analysis, and relative probability of occurrence to quantitatively assess statistical relationships. In the case of supply flow (SF) and return flow (RF), i.e. near the water heater, water temperature strongly regulates Legionella spp. growth. Below calculated tipping points (SF: 56 °C, RF: 53 °C), the relative probability of Legionella spp. occurrence is 18.7 and 7.5 times higher, respectively. For peripheral samples, the relationship between temperature and Legionella spp. occurrence is less pronounced. Additionally, statistical relationships between central and peripheral temperatures, as well as between central temperatures and peripheral Legionella spp. concentrations within one system, were weak or zero, respectively. Thus, the central temperature regime of hot water systems alone is insufficient to control the occurrence of Legionella spp. in the periphery.