Evidence map›Paper›PMID 37026100›Full record

ArticleFrontiers in veterinary science2023

An integrated system for the management of environmental data to support veterinary epidemiology.

Matteo Mazzucato, Giulio Marchetti, Marco Barbujani, Paolo Mulatti, Diletta Fornasiero, Claudia Casarotto, Francesca Scolamacchia, Grazia Manca, Nicola Ferrè

Open access · goldAbstract read
In one paragraph

Article in Frontiers in veterinary science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.7field-weighted citation impact, top 17% of its field
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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Habitat Suitability ofPathogens (Basel, Switzerland) · 2024
    Article
  3. 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

9 authors at 1 institution in 1 country.

Matteo MazzucatoIstituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy.
Giulio MarchettiIstituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy.
Marco BarbujaniIstituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy.
Paolo MulattiIstituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy.
Diletta FornasieroIstituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy.
Claudia CasarottoIstituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy.
Francesca ScolamacchiaIstituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy.
Grazia MancaIstituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy.
Nicola FerrèIstituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy.
Istituto Zooprofilattico Sperimentale delle Venezie · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Environmental and climatic fluctuations can greatly influence the dynamics of infectious diseases of veterinary concern, or interfere with the implementation of relevant control measures. Including environmental and climatic aspects in epidemiological studies could provide policy makers with new insights to assign resources for measures to prevent or limit the spread of animal diseases, particularly those with zoonotic potential. The ever-increasing number of technologies and tools permits acquiring environmental data from various sources, including ground-based sensors and Satellite Earth Observation (SEO). However, the high heterogeneity of these datasets often requires at least some basic GIS (Geographic Information Systems) and/or coding skills to use them in further analysis. Therefore, the high availability of data does not always correspond to widespread use for research purposes. The development of an integrated data pre-processing system makes it possible to obtain information that could be easily and directly used in subsequent epidemiological analyses, supporting both research activities and the management of disease outbreaks. Indeed, such an approach allows for the reduction of the time spent on searching, downloading, processing and validating environmental data, thereby optimizing available resources and reducing any possible errors directly related to data collection. Although multitudes of free services that allow obtaining SEO data exist nowadays (either raw or pre-processed through a specific coding language), the availability and quality of information can be sub-optimal when dealing with very small scale and local data. In fact, some information sets (e.g., air temperature, rainfall), usually derived from ground-based sensors (e.g., agro-meteo station), are managed, processed and redistributed by agencies operating on a local scale which are often not directly accessible by the most common free SEO services (e.g., Google Earth Engine). The EVE (Environmental data for Veterinary Epidemiology) system has been developed to acquire, pre-process and archive a set of environmental information at various scales, in order to facilitate and speed up access by epidemiologists, researchers and decision-makers, also accounting for the integration of SEO information with locally sensed data.

Indexed as

environmental dataGISSatellite Earth Observationsupport systemveterinary epidemiology

Identifiers

PMID37026100
PMCPMC10070964
OpenAlexW4353076792

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.