Climate seasonality and lower respiratory tract diseases: a predictive model for pediatric hospitalizations

Area of Science:

• Environmental Health
• Pediatric Respiratory Medicine
• Epidemiology

Background:

• Respiratory diseases are a significant cause of childhood illness.
• Climate seasonality is suspected to influence the incidence of pediatric respiratory conditions.
• Predictive models are needed to understand and manage seasonal disease burdens.

Purpose of the Study:

• To analyze the climate seasonality of respiratory diseases in children aged 0-9 years.
• To develop a predictive model for hospital admissions related to these diseases.
• To forecast admissions for the years 2021-2022 based on seasonal patterns.

Main Methods:

• Temporal analysis correlating hospital admissions for pneumonia, bronchitis/bronchiolitis, and asthma with meteorological variables.
• Adjustment of time series models to demonstrate seasonality.
• Verification of correlations to establish seasonal patterns.

Main Results:

• A significant seasonal effect was observed for all studied respiratory diseases.
• The highest incidence of registered cases occurred during autumn and winter months.
• Disease-specific trends were identified: decreasing pneumonia, increasing bronchitis/bronchiolitis, and stable asthma rates.

Conclusions:

• Respiratory disease admissions in children exhibit distinct seasonal patterns, primarily linked to colder months.
• Pneumonia admissions show a decreasing trend, while bronchitis/bronchiolitis admissions tend to increase.
• Asthma occurrence rates remained stable, suggesting other factors may be more influential than seasonality alone.