Literature DB >> 28905125

Biometeorological forecasts for health surveillance and prevention of meteor-tropic effects.

Luis B Lecha Estela1.   

Abstract

An early method of biometeorological forecasts was developed for Cuba during the late 90s. It was based on the relationship between the daily occurrence of massive health crisis and the magnitude of the 24-h differences of partial density of oxygen in the air (PODA index). Ten years later, applying new technological facilities, a new model was developed in order to offer operational biometeorological forecast to Cuban health institutions. After a satisfactory validation process, the official bioforecast service to health institutions in Villa Clara province began on February of 2012. The effectiveness had different success levels: for the bronchial asthma crisis (94%), in the hypertensive crisis (88%), with the cerebrovascular illnesses (85%), as well as migraines (82%) and in case of cardiovascular diseases (75%) were acceptable. Since 2008, the application of the model was extended to other regions of the world, including some national applications. Furthermore, it allowed the beginning of regional monitoring of meteor-tropic effects, following the occurrence and movement of areas with higher weather contrasts, defined according to the normalized scale of PODA index. The paper describes the main regional results already available, with emphasis in the observed meteor-tropic effects increasing in all regions during recent years. It coincides with the general increase of energy imbalance in the whole climate system. Finally, the paper describes the current development of new global biometeorological forecast services.

Entities:  

Keywords:  Biometeorological forecasts; Health watch and warning systems; Meteor-tropic effects; Partial oxygen density of air; PronBiomet model

Mesh:

Substances:

Year:  2017        PMID: 28905125     DOI: 10.1007/s00484-017-1405-2

Source DB:  PubMed          Journal:  Int J Biometeorol        ISSN: 0020-7128            Impact factor:   3.787


  6 in total

1.  UTCI--why another thermal index?

Authors:  Gerd Jendritzky; Richard de Dear; George Havenith
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2.  Lessons from a very hot summer.

Authors:  L S Kalkstein
Journal:  Lancet       Date:  1995-09-30       Impact factor: 79.321

Review 3.  Meteorotropy and medical-meteorological forecasts.

Authors:  K Bucher; C Haase
Journal:  Experientia       Date:  1993-09-15

4.  [Determination of the oxygen content in the atmosphere based on meteorological parameters (pressure, temperature, humidity) for the purpose of predicting the hypoxic effect of the atmosphere].

Authors:  V F Ovcharova
Journal:  Vopr Kurortol Fizioter Lech Fiz Kult       Date:  1981 Mar-Apr

Review 5.  The atmospheric environment--an introduction.

Authors:  G Jendritzky
Journal:  Experientia       Date:  1993-09-15

6.  Biometeorological classification of daily weather types for the humid tropics.

Authors:  L B Lecha Estela
Journal:  Int J Biometeorol       Date:  1998-12       Impact factor: 3.787

  6 in total
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3.  Heat Balance When Climbing Mount Everest.

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