Cargando…
Emerging human infectious diseases of aquatic origin: a comparative biogeographic approach using Bayesian spatial modelling
BACKGROUND: With the increase in unprecedented and unpredictable disease outbreaks due to human-driven environmental changes in recent years, we need new analytical tools to map and predict the spatial distribution of emerging infectious diseases and identify the biogeographic drivers underpinning t...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6833193/ https://www.ncbi.nlm.nih.gov/pubmed/31694656 http://dx.doi.org/10.1186/s12942-019-0188-6 |
_version_ | 1783466324599504896 |
---|---|
author | Jagadesh, Soushieta Combe, Marine Couppié, Pierre Le Turnier, Paul Epelboin, Loïc Nacher, Mathieu Gozlan, Rodolphe Elie |
author_facet | Jagadesh, Soushieta Combe, Marine Couppié, Pierre Le Turnier, Paul Epelboin, Loïc Nacher, Mathieu Gozlan, Rodolphe Elie |
author_sort | Jagadesh, Soushieta |
collection | PubMed |
description | BACKGROUND: With the increase in unprecedented and unpredictable disease outbreaks due to human-driven environmental changes in recent years, we need new analytical tools to map and predict the spatial distribution of emerging infectious diseases and identify the biogeographic drivers underpinning their emergence. The aim of the study was to identify and compare the local and global biogeographic predictors such as landscape and climate that determine the spatial structure of leptospirosis and Buruli Ulcer (BU). METHODS: We obtained 232 hospital-confirmed leptospirosis (2007–2017) cases and 236 BU cases (1969–2017) in French Guiana. We performed non-spatial and spatial Bayesian regression modeling with landscape and climate predictor variables to characterize the spatial structure and the environmental drivers influencing the distribution of the two diseases. RESULTS: Our results show that the distribution of both diseases is spatially dependent on environmental predictors such as elevation, topological wetness index, proximity to cropland and increasing minimum temperature at the month of potential infection. However, the spatial structure of the two diseases caused by bacterial pathogens occupying similar aquatic niche was different. Leptospirosis was widely distributed across the territory while BU was restricted to the coastal riverbeds. CONCLUSIONS: Our study shows that a biogeographic approach is an effective tool to identify, compare and predict the geographic distribution of emerging diseases at an ecological scale which are spatially dependent to environmental factors such as topography, land cover and climate. |
format | Online Article Text |
id | pubmed-6833193 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-68331932019-11-08 Emerging human infectious diseases of aquatic origin: a comparative biogeographic approach using Bayesian spatial modelling Jagadesh, Soushieta Combe, Marine Couppié, Pierre Le Turnier, Paul Epelboin, Loïc Nacher, Mathieu Gozlan, Rodolphe Elie Int J Health Geogr Research BACKGROUND: With the increase in unprecedented and unpredictable disease outbreaks due to human-driven environmental changes in recent years, we need new analytical tools to map and predict the spatial distribution of emerging infectious diseases and identify the biogeographic drivers underpinning their emergence. The aim of the study was to identify and compare the local and global biogeographic predictors such as landscape and climate that determine the spatial structure of leptospirosis and Buruli Ulcer (BU). METHODS: We obtained 232 hospital-confirmed leptospirosis (2007–2017) cases and 236 BU cases (1969–2017) in French Guiana. We performed non-spatial and spatial Bayesian regression modeling with landscape and climate predictor variables to characterize the spatial structure and the environmental drivers influencing the distribution of the two diseases. RESULTS: Our results show that the distribution of both diseases is spatially dependent on environmental predictors such as elevation, topological wetness index, proximity to cropland and increasing minimum temperature at the month of potential infection. However, the spatial structure of the two diseases caused by bacterial pathogens occupying similar aquatic niche was different. Leptospirosis was widely distributed across the territory while BU was restricted to the coastal riverbeds. CONCLUSIONS: Our study shows that a biogeographic approach is an effective tool to identify, compare and predict the geographic distribution of emerging diseases at an ecological scale which are spatially dependent to environmental factors such as topography, land cover and climate. BioMed Central 2019-11-06 /pmc/articles/PMC6833193/ /pubmed/31694656 http://dx.doi.org/10.1186/s12942-019-0188-6 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Jagadesh, Soushieta Combe, Marine Couppié, Pierre Le Turnier, Paul Epelboin, Loïc Nacher, Mathieu Gozlan, Rodolphe Elie Emerging human infectious diseases of aquatic origin: a comparative biogeographic approach using Bayesian spatial modelling |
title | Emerging human infectious diseases of aquatic origin: a comparative biogeographic approach using Bayesian spatial modelling |
title_full | Emerging human infectious diseases of aquatic origin: a comparative biogeographic approach using Bayesian spatial modelling |
title_fullStr | Emerging human infectious diseases of aquatic origin: a comparative biogeographic approach using Bayesian spatial modelling |
title_full_unstemmed | Emerging human infectious diseases of aquatic origin: a comparative biogeographic approach using Bayesian spatial modelling |
title_short | Emerging human infectious diseases of aquatic origin: a comparative biogeographic approach using Bayesian spatial modelling |
title_sort | emerging human infectious diseases of aquatic origin: a comparative biogeographic approach using bayesian spatial modelling |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6833193/ https://www.ncbi.nlm.nih.gov/pubmed/31694656 http://dx.doi.org/10.1186/s12942-019-0188-6 |
work_keys_str_mv | AT jagadeshsoushieta emerginghumaninfectiousdiseasesofaquaticoriginacomparativebiogeographicapproachusingbayesianspatialmodelling AT combemarine emerginghumaninfectiousdiseasesofaquaticoriginacomparativebiogeographicapproachusingbayesianspatialmodelling AT couppiepierre emerginghumaninfectiousdiseasesofaquaticoriginacomparativebiogeographicapproachusingbayesianspatialmodelling AT leturnierpaul emerginghumaninfectiousdiseasesofaquaticoriginacomparativebiogeographicapproachusingbayesianspatialmodelling AT epelboinloic emerginghumaninfectiousdiseasesofaquaticoriginacomparativebiogeographicapproachusingbayesianspatialmodelling AT nachermathieu emerginghumaninfectiousdiseasesofaquaticoriginacomparativebiogeographicapproachusingbayesianspatialmodelling AT gozlanrodolpheelie emerginghumaninfectiousdiseasesofaquaticoriginacomparativebiogeographicapproachusingbayesianspatialmodelling |