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Surfactant Depletion Combined with Injurious Ventilation Results in a Reproducible Model of the Acute Respiratory Distress Syndrome (ARDS)
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Surfactant Depletion Combined with Injurious Ventilation Results in a Reproducible Model of the Acute Respiratory Distress Syndrome (ARDS)

Published on: April 7, 2021

Are meteorological parameters associated with acute respiratory tract infections?

Jean-Baptist du Prel1, Wolfram Puppe, Britta Gröndahl

  • 1Kinderklinik, Paediatrische Infektiologie & Zentrum Praeventive Paediatrie, Universitaetsmedizin, Johannes-Gutenberg-Universitaet, Mainz, Germany.

Clinical Infectious Diseases : an Official Publication of the Infectious Diseases Society of America
|August 12, 2009
PubMed

Insights

Climate influences acute respiratory infections (ARIs). Temperature affects influenza A and RSV hospitalizations, while humidity impacts rhinovirus. This study shows RSV epidemics are predictable using weather data.

Area of Science:

  • Environmental Science
  • Epidemiology
  • Virology

Background:

  • Understanding the onset of acute respiratory infections (ARIs) aids in timing preventive strategies, such as immunizing high-risk infants against respiratory syncytial virus (RSV).
  • Investigating the impact of climate on ARI hospitalizations can improve predictions of seasonal ARI pathogen activity.

Purpose of the Study:

  • To investigate the influence of climate on hospitalizations for ARIs.
  • To develop a predictive model for seasonal ARI pathogen activity.

Main Methods:

  • Collected samples from 3044 children hospitalized with ARIs in Mainz, Germany (2001-2006).
  • Utilized multiplex reverse-transcriptase polymerase chain reaction enzyme-linked immunosorbent assay to test for pathogens.
  • Correlated ARI hospitalizations with meteorological parameters and employed time series analysis for RSV hospitalization prediction.

Main Results:

  • Influenza A, RSV, and adenovirus showed correlations with temperature.
  • Rhinovirus correlated with relative humidity.
  • A time series model incorporating seasonal and climatic conditions successfully predicted RSV-associated hospitalizations.

Conclusions:

  • Meteorological factors explain the seasonality of specific ARI pathogens.
  • The developed model represents an initial step toward predicting annual RSV epidemics using weather forecast data.
Abstract

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