Evidence map›Paper›PMID 31269045›Full record

ArticlePloS one2019

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

Carla Ippoliti, Luca Candeloro, Marius Gilbert, Maria Goffredo, Giuseppe Mancini, Gabriele Curci, Serena Falasca, Susanna Tora, Alessio Di Lorenzo, Michela Quaglia and 1 more

Abstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Detection ofFrontiers in veterinary science · 2024
    Article
  5. SpottingFrontiers in veterinary science · 2024
    Article
  6. Review
  7. An Agenda for Research of Uncovered Epidemiological Patterns of Tick-Borne Pathogens Affecting Human Health.International journal of environmental research and public health · 2023
    Article
  8. Article
  9. Eco-Sanitary Regionalization of Wild Boar (Transboundary and emerging diseases · 2023
    Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Carla IppolitiIstituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise G. Caporale, Campo Boario, Teramo, Italy.ORCID 0000-0001-9030-7329
Luca CandeloroIstituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise G. Caporale, Campo Boario, Teramo, Italy.
Marius GilbertSpatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium.
Maria GoffredoIstituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise G. Caporale, Campo Boario, Teramo, Italy.
Giuseppe ManciniIstituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise G. Caporale, Campo Boario, Teramo, Italy.
Gabriele CurciDepartment of Physical and Chemical Sciences, University of L'Aquila, L'Aquila, Italy.
Serena FalascaDepartment of Physical and Chemical Sciences, University of L'Aquila, L'Aquila, Italy.
Susanna ToraIstituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise G. Caporale, Campo Boario, Teramo, Italy.
Alessio Di LorenzoIstituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise G. Caporale, Campo Boario, Teramo, Italy.
Michela QuagliaIstituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise G. Caporale, Campo Boario, Teramo, Italy.
Annamaria ConteIstituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise G. Caporale, Campo Boario, Teramo, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

EcosystemAlgorithmsAnimalsBluetongueCluster AnalysisEpidemiological MonitoringGeographic MappingHumansInsect VectorsItalyMultivariate AnalysisPrincipal Component AnalysisSheepVector Borne DiseasesWest Nile Fever

Identifiers

PMID31269045
PMCPMC6608978

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.