ArticleEpidemiology and infection2020
Short-term associations between Legionnaires' disease incidence and meteorological variables in Belgium, 2011-2019.
Article in Epidemiology and infection, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Impact of Climate Change on Legionnaire's Disease: A Systematic Review.In vivo (Athens, Greece)Pooled it
- Associations between Legionellosis and meteorological variables in Ohio, 2001-2023.Infectious Disease Modelling · 2026Article
- Seasonality and effects of climatic exposures on community-acquired Legionnaires' disease incidence, Italy, 2005 to 2023.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2026Article
- A within-host birth-death and time-dose-response model for Legionnaires' disease.Royal Society open science · 2025Article
- Weather conditions and legionellosis: a nationwide case-crossover study among Medicare recipients.Epidemiology and infection · 2024Article
- Legionellosis on the rise: A scoping review of sporadic, community-acquired incidence in the United States.Epidemiology and infection · 2023Article
- Legionnaires' disease in the EU/EEA*: increasing trend from 2017 to 2019.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2023Article
- Lagged meteorological impacts on COVID-19 incidence among high-risk counties in the United States-a spatiotemporal analysis.Journal of exposure science & environmental epidemiology · 2022Article
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Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The number of reported cases with Legionnaires' disease (LD) is increasing in Belgium. Previous studies have investigated the associations between LD incidence and meteorological factors, but the Belgian data remained unexplored. We investigated data collected between 2011 and 2019. Daily exposure data on temperature, relative humidity, precipitation and wind speed was obtained from the Royal Meteorological Institute for 29 weather stations. Case data were collected from the national reference centre and through mandatory notification. Daily case and exposure data were aggregated by province. We conducted a time-stratified case-crossover study. The 'at risk' period was defined as 10 to 2 days prior to disease onset. The corresponding days in the other study years were selected as referents. We fitted separate conditional Poisson models for each day in the 'at risk' period and a distributed lag non-linear model (DLNM) which fitted all data in one model. LD incidence showed a yearly peak in August and September. A total of 614 cases were included. Given seasonality, a sequence of precipitation, followed by high relative humidity and low wind speed showed a statistically significant association with the number of cases 6 to 4 days later. We discussed the advantages of DLNM in this context.
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