Linked within-host and between-host models and data for infectious diseases: a systematic review

Area of Science:

• Epidemiology
• Mathematical Biology
• Infectious Disease Dynamics

Background:

• Infectious disease dynamics involve complex processes at both within-host (individual) and between-host (population) scales.
• Understanding the interplay between these scales is crucial for a holistic view of disease spread.
• Mathematical modeling offers a framework to integrate these multi-scale processes.

Purpose of the Study:

• To systematically review the literature on multi-scale mathematical models of infectious disease transmission.
• To assess the extent to which these models link within-host and between-host scales.
• To evaluate the degree to which these integrated models are validated with empirical data.

Main Methods:

• A systematic literature review was conducted following PRISMA guidelines.
• The review focused on published mathematical models combining within-host and between-host scales.
• Papers were screened for data utilization in model parameterization or calibration.

Main Results:

• Out of 197 initially identified papers, 24 met the criteria over a 30-year period.
• A significant proportion of reviewed studies linked within-host and between-host scales in their models.
• The integration of empirical data for model calibration and parameterization was found to be under-utilized.

Conclusions:

• Multi-scale mathematical models are valuable tools for studying infectious disease transmission.
• There is a critical need to increase the use of empirical data in calibrating and validating these models.
• Enhanced collaboration between modelers and empiricists is essential for developing robust, predictive disease transmission models.