Accurate prediction of severe allergic reactions by a small set of environmental parameters (NDVI, temperature).

Severe allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have b...

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Main Authors: George Notas, Michail Bariotakis, Vaios Kalogrias, Maria Andrianaki, Kalliopi Azariadis, Errika Kampouri, Katerina Theodoropoulou, Katerina Lavrentaki, Stelios Kastrinakis, Marilena Kampa, Panagiotis Agouridakis, Stergios Pirintsos, Elias Castanas
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4368791?pdf=render
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author George Notas
Michail Bariotakis
Vaios Kalogrias
Maria Andrianaki
Kalliopi Azariadis
Errika Kampouri
Katerina Theodoropoulou
Katerina Lavrentaki
Stelios Kastrinakis
Marilena Kampa
Panagiotis Agouridakis
Stergios Pirintsos
Elias Castanas
author_facet George Notas
Michail Bariotakis
Vaios Kalogrias
Maria Andrianaki
Kalliopi Azariadis
Errika Kampouri
Katerina Theodoropoulou
Katerina Lavrentaki
Stelios Kastrinakis
Marilena Kampa
Panagiotis Agouridakis
Stergios Pirintsos
Elias Castanas
author_sort George Notas
collection DOAJ
description Severe allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have been limited by the lack of a well-founded applicable methodology and the wide spatiotemporal distribution of allergic reactions. The valid prediction of severe allergies (and especially those needing hospital treatment) in a region, could alert health authorities and implicated individuals to take appropriate preemptive measures. In the present report we have collecterd visits for serious allergic reactions of unknown etiology from two major hospitals in the island of Crete, for two distinct time periods (validation and test sets). We have used the Normalized Difference Vegetation Index (NDVI), a satellite-based, freely available measurement, which is an indicator of live green vegetation at a given geographic area, and a set of meteorological data to develop a model capable of describing and predicting severe allergic reaction frequency. Our analysis has retained NDVI and temperature as accurate identifiers and predictors of increased hospital severe allergic reactions visits. Our approach may contribute towards the development of satellite-based modules, for the prediction of severe allergic reactions in specific, well-defined geographical areas. It could also probably be used for the prediction of other environment related diseases and conditions.
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spelling doaj.art-eee2d043d63d40b8b8a019ade2648e2a2022-12-22T02:32:48ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01103e012147510.1371/journal.pone.0121475Accurate prediction of severe allergic reactions by a small set of environmental parameters (NDVI, temperature).George NotasMichail BariotakisVaios KalogriasMaria AndrianakiKalliopi AzariadisErrika KampouriKaterina TheodoropoulouKaterina LavrentakiStelios KastrinakisMarilena KampaPanagiotis AgouridakisStergios PirintsosElias CastanasSevere allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have been limited by the lack of a well-founded applicable methodology and the wide spatiotemporal distribution of allergic reactions. The valid prediction of severe allergies (and especially those needing hospital treatment) in a region, could alert health authorities and implicated individuals to take appropriate preemptive measures. In the present report we have collecterd visits for serious allergic reactions of unknown etiology from two major hospitals in the island of Crete, for two distinct time periods (validation and test sets). We have used the Normalized Difference Vegetation Index (NDVI), a satellite-based, freely available measurement, which is an indicator of live green vegetation at a given geographic area, and a set of meteorological data to develop a model capable of describing and predicting severe allergic reaction frequency. Our analysis has retained NDVI and temperature as accurate identifiers and predictors of increased hospital severe allergic reactions visits. Our approach may contribute towards the development of satellite-based modules, for the prediction of severe allergic reactions in specific, well-defined geographical areas. It could also probably be used for the prediction of other environment related diseases and conditions.http://europepmc.org/articles/PMC4368791?pdf=render
spellingShingle George Notas
Michail Bariotakis
Vaios Kalogrias
Maria Andrianaki
Kalliopi Azariadis
Errika Kampouri
Katerina Theodoropoulou
Katerina Lavrentaki
Stelios Kastrinakis
Marilena Kampa
Panagiotis Agouridakis
Stergios Pirintsos
Elias Castanas
Accurate prediction of severe allergic reactions by a small set of environmental parameters (NDVI, temperature).
PLoS ONE
title Accurate prediction of severe allergic reactions by a small set of environmental parameters (NDVI, temperature).
title_full Accurate prediction of severe allergic reactions by a small set of environmental parameters (NDVI, temperature).
title_fullStr Accurate prediction of severe allergic reactions by a small set of environmental parameters (NDVI, temperature).
title_full_unstemmed Accurate prediction of severe allergic reactions by a small set of environmental parameters (NDVI, temperature).
title_short Accurate prediction of severe allergic reactions by a small set of environmental parameters (NDVI, temperature).
title_sort accurate prediction of severe allergic reactions by a small set of environmental parameters ndvi temperature
url http://europepmc.org/articles/PMC4368791?pdf=render
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