ArticlePloS one2017
Environmental risk of leptospirosis infections in the Netherlands: Spatial modelling of environmental risk factors of leptospirosis in the Netherlands.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Ecological Niche Modeling of PathogenicPathogens (Basel, Switzerland) · 2026Article
- Unraveling the drivers of leptospirosis risk in Thailand using machine learning.PLoS neglected tropical diseases · 2025Article
- Seroprevalence ofVeterinary world · 2025Article
- Spatio-temporal risk prediction of leptospirosis: A machine-learning-based approach.PLoS neglected tropical diseases · 2025Article
- Epidemiology of reported cases of leptospirosis in the EU/EEA, 2010 to 2021.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2024Article
- Leptospirosis and the Environment: A Review and Future Directions.Pathogens (Basel, Switzerland) · 2023Review
- A predictive risk map for human leptospirosis guiding further investigations in brown rats and surface water.Infection ecology & epidemiology · 2023Article
- Occurrence ofMicroorganisms · 2022Article
- Agro-Environmental Determinants of Leptospirosis: A Retrospective Spatiotemporal Analysis (2004-2014) in Mahasarakham Province (Thailand).Tropical medicine and infectious disease · 2021Article
- Spatial autocorrelation and co-occurrence of six serovarieties of Leptospira in goat herds of the State of Guanajuato, Mexico.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2021Article
- Ecological and Socio-Economic Determinants of Livestock Animal Leptospirosis in the Russian Arctic.Frontiers in veterinary science · 2021Article
- Mapping the Geographic Distribution of Tungiasis in Sub-Saharan Africa.Tropical medicine and infectious disease · 2020Article
- Environmental Risk of Leptospirosis in Animals: The Case of The Republic of Sakha (Yakutia), Russian Federation.Pathogens (Basel, Switzerland) · 2020Article
- Spatial analysis and factors associated with leptospirosis in Santa Catarina, Brazil, 2001-2015.Revista da Sociedade Brasileira de Medicina Tropical · 2020Article
- A systematic literature review of leptospirosis outbreaks worldwide, 1970-2012.Revista panamericana de salud publica = Pan American journal of public health · 2020Review
- Prediction mapping of human leptospirosis using ANN, GWR, SVM and GLM approaches.BMC infectious diseases · 2019Article
- Emerging human infectious diseases of aquatic origin: a comparative biogeographic approach using Bayesian spatial modelling.International journal of health geographics · 2019Article
- Geographical and temporal distribution of the residual clusters of human leptospirosis in China, 2005-2016.Scientific reports · 2018Article
- Spatiotemporal dynamics and risk factors for human Leptospirosis in Brazil.Scientific reports · 2018Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Leptospirosis is a globally emerging zoonotic disease, associated with various climatic, biotic and abiotic factors. Mapping and quantifying geographical variations in the occurrence of leptospirosis and the surrounding environment offer innovative methods to study disease transmission and to identify associations between the disease and the environment. This study aims to investigate geographic variations in leptospirosis incidence in the Netherlands and to identify associations with environmental factors driving the emergence of the disease. Individual case data derived over the period 1995-2012 in the Netherlands were geocoded and aggregated by municipality. Environmental covariate data were extracted for each municipality and stored in a spatial database. Spatial clusters were identified using kernel density estimations and quantified using local autocorrelation statistics. Associations between the incidence of leptospirosis and the local environment were determined using Simultaneous Autoregressive Models (SAR) explicitly modelling spatial dependence of the model residuals. Leptospirosis incidence rates were found to be spatially clustered, showing a marked spatial pattern. Fitting a spatial autoregressive model significantly improved model fit and revealed significant association between leptospirosis and the coverage of arable land, built up area, grassland and sabulous clay soils. The incidence of leptospirosis in the Netherlands could effectively be modelled using a combination of soil and land-use variables accounting for spatial dependence of incidence rates per municipality. The resulting spatially explicit risk predictions provide an important source of information which will benefit clinical awareness on potential leptospirosis infections in endemic areas.
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