Analysing dengue fever spread in Kenya using the Zero-Inflated Poisson model

Area of Science:

• Epidemiology
• Environmental Health
• Biostatistics

Background:

• Dengue fever (DF) is a significant public health issue in tropical and subtropical regions, transmitted by Aedes mosquitoes.
• Understanding the link between climate and DF incidence is crucial for effective outbreak prediction and control strategies.

Purpose of the Study:

• To analyze the impact of climatic factors on dengue fever incidence in Kenya.
• To apply a Zero-Inflated Poisson (ZIP) model for analyzing DF data and associated climatic variables.

Main Methods:

• Utilized monthly dengue case data and climatic variables (temperature, rainfall, humidity) from Kenya (2019-2021).
• Employed a Zero-Inflated Poisson (ZIP) model to account for over-dispersion and excess zeros in the data.
• Validated the ZIP model's suitability over a standard Poisson model using statistical tests and AIC.

Main Results:

• Humidity and temperature showed a significant positive association with DF incidence (p < 0.01).
• Rainfall exhibited a significant negative effect on DF cases (p < 0.01).
• The ZIP model demonstrated a superior fit compared to the Poisson model, effectively handling data characteristics.

Conclusions:

• Findings indicate that elevated humidity and temperature favor dengue transmission in Kenya.
• Heavy rainfall may negatively impact mosquito breeding, potentially reducing DF cases.
• The study supports the use of ZIP modeling for enhanced DF surveillance and targeted public health interventions.