Legionella is the pathogen that causes Legionnaires’ disease, an increasingly prevalent and sometimes fatal disease worldwide. In 2021, 97% of cases in Europe were caused by Legionella pneumophila. We present a mathematical model that can be used by public health officials to assess the effectiveness and efficiency of different Legionella monitoring and control strategies to inform government requirements to prevent community-acquired Legionnaires’ disease in non-hospital buildings. This simulation model was built using comprehensive data from multiple scientific and field-based sources. It is a tool for estimating the relative economic and human costs of monitoring and control efforts targeting either L. pneumophila or Legionella species and was designed to analyze the potential application of each approach to specific building classes across Italy. The model results consistently showed that targeting L. pneumophila is not only sufficient but preferable in optimizing total cost (direct and economic) for similar human health benefits, even when stress-tested with extreme inputs. This cost–benefit analytical tool allows the user to run different real-life scenarios with a broad range of epidemiological and prevalence assumptions across different geographies in Italy. With appropriate modifications, this tool can be localized and applied to other countries, states, or provinces.

Legionnaires’ Disease Surveillance and Public Health Policies in Italy: A Mathematical Model for Assessing Prevention Strategies

Montagna M. T.;De Giglio O.;
2024-01-01

Abstract

Legionella is the pathogen that causes Legionnaires’ disease, an increasingly prevalent and sometimes fatal disease worldwide. In 2021, 97% of cases in Europe were caused by Legionella pneumophila. We present a mathematical model that can be used by public health officials to assess the effectiveness and efficiency of different Legionella monitoring and control strategies to inform government requirements to prevent community-acquired Legionnaires’ disease in non-hospital buildings. This simulation model was built using comprehensive data from multiple scientific and field-based sources. It is a tool for estimating the relative economic and human costs of monitoring and control efforts targeting either L. pneumophila or Legionella species and was designed to analyze the potential application of each approach to specific building classes across Italy. The model results consistently showed that targeting L. pneumophila is not only sufficient but preferable in optimizing total cost (direct and economic) for similar human health benefits, even when stress-tested with extreme inputs. This cost–benefit analytical tool allows the user to run different real-life scenarios with a broad range of epidemiological and prevalence assumptions across different geographies in Italy. With appropriate modifications, this tool can be localized and applied to other countries, states, or provinces.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/506741
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