A Compartmental Model for Zika Virus with Dynamic Human and Vector Populations

Area of Science:

• Epidemiology
• Mathematical Biology
• Public Health

Background:

• The Zika virus (ZIKV) outbreak caused a Public Health Emergency of International Concern due to its association with microcephaly and Guillain-Barré Syndrome.
• Understanding ZIKV transmission dynamics is critical for effective public health interventions.

Purpose of the Study:

• To develop a compartmental vector-host model for ZIKV to analyze disease dynamics.
• To evaluate the effectiveness of various containment strategies and their combined effects.
• To identify key parameters influencing ZIKV spread and inform decision-making for epidemic control.

Main Methods:

• A compartmental model incorporating logistic human population growth and dynamic vector population growth was developed.
• The basic reproduction number (R0) was derived to assess disease transmissibility.
• Simulations were performed to contrast parameter impacts and evaluate containment strategy efficacy.

Main Results:

• The model provides insights into ZIKV transmission dynamics and the influence of different parameters on outbreak spread.
• Different containment strategies were evaluated for their effectiveness in minimizing total infections.
• The study highlights the importance of "digital disease surveillance" for timely epidemic response.

Conclusions:

• The developed model serves as a decision-support tool for selecting effective ZIKV containment strategies.
• Early containment can be achieved by optimizing interventions based on model predictions.
• Digital disease surveillance is a vital component in managing outbreaks of ZIKV and other infectious diseases.