A relationship between acute respiratory illnesses and weather

Area of Science:

• Environmental epidemiology
• Biostatistics
• Public health

Background:

• Acute respiratory illnesses (ARIs) pose a significant public health burden.
• Understanding environmental factors influencing ARI incidence is crucial for effective prevention strategies.

Purpose of the Study:

• To develop and validate a statistical model correlating weather variables with ARI incidence.
• To identify specific weather parameters impacting ARI occurrence in primary care settings.

Main Methods:

• Utilized 7 years of weekly primary-care ARI counts and local weather data (2004-2010).
• Employed a multivariate time-series vector error correction model with covariates (VECMX).
• Integrated weather variables using a partial least squares index incorporating temperature, humidity, and rainfall.

Main Results:

• The VECMX model demonstrated statistical significance for trend (P = 0.00) and the weather index (P = 0.00).
• Key weather factors included minimum temperature (coefficient = -0.26), median relative humidity (coefficient = 0.22), and accumulated rainfall (coefficient = 0.5).
• The model explained 76% of the variability in ARI incidence (adjusted R² = 0.76), with seasonality influencing short-term relationships.

Conclusions:

• The developed VECMX model effectively captures the relationship between weather fluctuations and ARI incidence.
• This reproducible methodology can aid researchers in identifying climate-related ARI drivers and understanding disease transmission dynamics.