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Updated: May 24, 2026

A Murine Model of Dengue Virus-induced Acute Viral Encephalitis-like Disease
04:23

A Murine Model of Dengue Virus-induced Acute Viral Encephalitis-like Disease

Published on: April 28, 2019

Climate-based models for understanding and forecasting dengue epidemics.

Elodie Descloux1, Morgan Mangeas, Christophe Eugène Menkes

  • 1UMR190, Emergence of Viral Pathologies, Institute of Research for the Development, Aix-Marseille University, Marseille, France. elodie.descloux@hotmail.com

Plos Neglected Tropical Diseases
|February 21, 2012
PubMed
Summary
This summary is machine-generated.

Climate significantly influences dengue outbreaks in Noumea, New Caledonia. Specific temperature and humidity thresholds, identified through climate-based models, can predict future dengue epidemics, enabling early warning systems.

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Protocol for Dengue Infections in Mosquitoes (A. aegypti) and Infection Phenotype Determination
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Last Updated: May 24, 2026

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Published on: April 28, 2019

Protocol for Dengue Infections in Mosquitoes (A. aegypti) and Infection Phenotype Determination
15:25

Protocol for Dengue Infections in Mosquitoes (A. aegypti) and Infection Phenotype Determination

Published on: July 4, 2007

Area of Science:

  • Environmental Science
  • Epidemiology
  • Vector-borne Diseases

Background:

  • Dengue fever dynamics are influenced by complex interactions between humans, Aedes aegypti mosquitoes, viruses, and environmental/climatic factors.
  • Understanding these relationships is crucial for predicting and managing dengue outbreaks.

Purpose of the Study:

  • To analyze and model the relationships between climate, Aedes aegypti vector indices, and dengue outbreaks in Noumea, New Caledonia.
  • To develop an early warning system for dengue epidemics.

Main Methods:

  • Analysis of epidemiological, meteorological, and entomological data from 1971 to 2010.
  • Development of multivariate non-linear climate-based models to estimate dengue outbreak risk.

Main Results:

  • Dengue outbreaks showed a strong seasonal pattern, peaking 1-2 months after the warmest temperatures.
  • Key meteorological predictors included days with temperatures >32°C (Jan-Mar) and relative humidity >95% (Jan).
  • Predictive models using previous year's climate data achieved 79% accuracy in identifying epidemic years.

Conclusions:

  • Climate, particularly temperature and relative humidity, is a primary driver of dengue epidemic dynamics in Noumea.
  • Specific climate thresholds and their persistence are critical for outbreak occurrence.
  • A successful operational model was developed to anticipate dengue outbreak risk, with potential applications in other regions.