Mathematical models for dengue fever epidemiology: A 10-year systematic review

Area of Science:

• Epidemiology
• Mathematical Modeling
• Infectious Disease Dynamics

Background:

• Dengue fever is a significant global public health concern, posing risks to 2.5 billion people.
• The disease involves four distinct serotypes (DENV-1 to DENV-4) and a complex immune response, including antibody-dependent enhancement (ADE).
• Mathematical modeling has been crucial for understanding disease spread, with dengue models dating back to 1970.

Purpose of the Study:

• To conduct a 10-year systematic review of mathematical models for dengue fever epidemiology.
• To analyze multi-strain, vector-host, and within-host models, including their validation and parameter estimation.
• To identify consensus on modeling aspects that can aid public health authorities in dengue control.

Main Methods:

• Systematic literature search across standard scientific databases.
• Review and analysis of diverse mathematical models based on scope, analytical approach, and structural form.
• Evaluation of model validation and parameter estimation techniques using empirical data.

Main Results:

• Detailed description and analysis of various mathematical models for dengue epidemiology.
• Examination of multi-strain frameworks and within-host models.
• Assessment of epidemiological and immunological factors influencing dengue transmission dynamics.

Conclusions:

• The review provides insights into modeling approaches for dengue fever.
• Identifies key features for modeling real-world public health challenges.
• Offers a revised understanding of factors influencing dengue transmission for improved disease control strategies.