Threshold Dynamics of a Temperature-Dependent Stage-Structured Mosquito Population Model with Nested Delays

Area of Science:

• Mathematical Biology
• Epidemiology
• Vector-borne Disease Ecology

Background:

• Mosquito-borne diseases pose significant global public health and economic burdens.
• Rising global temperatures due to climate change are predicted to expand mosquito habitats and increase disease transmission.
• Understanding temperature-dependent mosquito population dynamics is vital for effective disease control strategies.

Purpose of the Study:

• To develop a mathematical model simulating mosquito population dynamics under controlled temperature conditions.
• To analyze the influence of temperature on mosquito population persistence and extinction.
• To estimate model parameters for Aedes aegypti, a key vector for dengue virus.

Main Methods:

• Development of a stage-structured mosquito population model.
• The model is formulated as a system of periodic delay differential equations with periodic delays.
• Analysis of the basic reproduction number as a threshold parameter for population dynamics.
• Parameter estimation for Aedes aegypti using experimental data.
• Numerical simulations incorporating temperature data from Colombo, Sri Lanka (2017 dengue outbreak).

Main Results:

• The basic reproduction number was identified as a critical threshold determining mosquito population viability.
• The model successfully captures mosquito population dynamics influenced by temperature variations.
• Simulations validated the model's predictions using real-world dengue outbreak data.

Conclusions:

• The developed mathematical model provides a valuable tool for understanding temperature-driven mosquito population dynamics.
• The basic reproduction number serves as a key metric for assessing the risk of mosquito-borne disease spread.
• Findings support the development of targeted disease control policies in response to climate change.