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Defining ecological regions in Italy based on a multivariate clustering approach: A first step towards a targeted vector borne disease surveillance

Ecoregionalization is the process by which a territory is classified in similar areas according to specific environmental and climatic factors. The climate and the environment strongly influence the presence and distribution of vectors responsible for significant human and animal diseases worldwide....

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Autores principales: Ippoliti, Carla, Candeloro, Luca, Gilbert, Marius, Goffredo, Maria, Mancini, Giuseppe, Curci, Gabriele, Falasca, Serena, Tora, Susanna, Di Lorenzo, Alessio, Quaglia, Michela, Conte, Annamaria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6608978/
https://www.ncbi.nlm.nih.gov/pubmed/31269045
http://dx.doi.org/10.1371/journal.pone.0219072
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author Ippoliti, Carla
Candeloro, Luca
Gilbert, Marius
Goffredo, Maria
Mancini, Giuseppe
Curci, Gabriele
Falasca, Serena
Tora, Susanna
Di Lorenzo, Alessio
Quaglia, Michela
Conte, Annamaria
author_facet Ippoliti, Carla
Candeloro, Luca
Gilbert, Marius
Goffredo, Maria
Mancini, Giuseppe
Curci, Gabriele
Falasca, Serena
Tora, Susanna
Di Lorenzo, Alessio
Quaglia, Michela
Conte, Annamaria
author_sort Ippoliti, Carla
collection PubMed
description Ecoregionalization is the process by which a territory is classified in similar areas according to specific environmental and climatic factors. The climate and the environment strongly influence the presence and distribution of vectors responsible for significant human and animal diseases worldwide. In this paper, we developed a map of the eco-climatic regions of Italy adopting a data-driven spatial clustering approach using recent and detailed spatial data on climatic and environmental factors. We selected seven variables, relevant for a broad set of human and animal vector-borne diseases (VBDs): standard deviation of altitude, mean daytime land surface temperature, mean amplitude and peak timing of the annual cycle of land surface temperature, mean and amplitude of the annual cycle of greenness value, and daily mean amount of rainfall. Principal Component Analysis followed by multivariate geographic clustering using the k-medoids technique were used to group the pixels with similar characteristics into different ecoregions, and at different spatial resolutions (250 m, 1 km and 2 km). We showed that the spatial structure of ecoregions is generally maintained at different spatial resolutions and we compared the resulting ecoregion maps with two datasets related to Bluetongue vectors and West Nile Disease (WND) outbreaks in Italy. The known characteristics of Culicoides imicola habitat were well captured by 2/22 specific ecoregions (at 250 m resolution). Culicoides obsoletus/scoticus occupy all sampled ecoregions, according to its known widespread distribution across the peninsula. WND outbreak locations strongly cluster in 4/22 ecoregions, dominated by human influenced landscape, with intense cultivations and complex irrigation network. This approach could be a supportive tool in case of VBDs, defining pixel-based areas that are conducive environment for VBD spread, indicating where surveillance and prevention measures could be prioritized in Italy. Also, ecoregions suitable to specific VBDs vectors could inform entomological surveillance strategies.
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spelling pubmed-66089782019-07-12 Defining ecological regions in Italy based on a multivariate clustering approach: A first step towards a targeted vector borne disease surveillance Ippoliti, Carla Candeloro, Luca Gilbert, Marius Goffredo, Maria Mancini, Giuseppe Curci, Gabriele Falasca, Serena Tora, Susanna Di Lorenzo, Alessio Quaglia, Michela Conte, Annamaria PLoS One Research Article Ecoregionalization is the process by which a territory is classified in similar areas according to specific environmental and climatic factors. The climate and the environment strongly influence the presence and distribution of vectors responsible for significant human and animal diseases worldwide. In this paper, we developed a map of the eco-climatic regions of Italy adopting a data-driven spatial clustering approach using recent and detailed spatial data on climatic and environmental factors. We selected seven variables, relevant for a broad set of human and animal vector-borne diseases (VBDs): standard deviation of altitude, mean daytime land surface temperature, mean amplitude and peak timing of the annual cycle of land surface temperature, mean and amplitude of the annual cycle of greenness value, and daily mean amount of rainfall. Principal Component Analysis followed by multivariate geographic clustering using the k-medoids technique were used to group the pixels with similar characteristics into different ecoregions, and at different spatial resolutions (250 m, 1 km and 2 km). We showed that the spatial structure of ecoregions is generally maintained at different spatial resolutions and we compared the resulting ecoregion maps with two datasets related to Bluetongue vectors and West Nile Disease (WND) outbreaks in Italy. The known characteristics of Culicoides imicola habitat were well captured by 2/22 specific ecoregions (at 250 m resolution). Culicoides obsoletus/scoticus occupy all sampled ecoregions, according to its known widespread distribution across the peninsula. WND outbreak locations strongly cluster in 4/22 ecoregions, dominated by human influenced landscape, with intense cultivations and complex irrigation network. This approach could be a supportive tool in case of VBDs, defining pixel-based areas that are conducive environment for VBD spread, indicating where surveillance and prevention measures could be prioritized in Italy. Also, ecoregions suitable to specific VBDs vectors could inform entomological surveillance strategies. Public Library of Science 2019-07-03 /pmc/articles/PMC6608978/ /pubmed/31269045 http://dx.doi.org/10.1371/journal.pone.0219072 Text en © 2019 Ippoliti et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ippoliti, Carla
Candeloro, Luca
Gilbert, Marius
Goffredo, Maria
Mancini, Giuseppe
Curci, Gabriele
Falasca, Serena
Tora, Susanna
Di Lorenzo, Alessio
Quaglia, Michela
Conte, Annamaria
Defining ecological regions in Italy based on a multivariate clustering approach: A first step towards a targeted vector borne disease surveillance
title Defining ecological regions in Italy based on a multivariate clustering approach: A first step towards a targeted vector borne disease surveillance
title_full Defining ecological regions in Italy based on a multivariate clustering approach: A first step towards a targeted vector borne disease surveillance
title_fullStr Defining ecological regions in Italy based on a multivariate clustering approach: A first step towards a targeted vector borne disease surveillance
title_full_unstemmed Defining ecological regions in Italy based on a multivariate clustering approach: A first step towards a targeted vector borne disease surveillance
title_short Defining ecological regions in Italy based on a multivariate clustering approach: A first step towards a targeted vector borne disease surveillance
title_sort defining ecological regions in italy based on a multivariate clustering approach: a first step towards a targeted vector borne disease surveillance
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6608978/
https://www.ncbi.nlm.nih.gov/pubmed/31269045
http://dx.doi.org/10.1371/journal.pone.0219072
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