A systematic review and guide for using multi-response statistical models in co-infection research.

Area of Science:

• Ecology
• Epidemiology
• Infectious Disease Dynamics

Background:

• Co-infections, the simultaneous presence of multiple pathogens, significantly impact infectious disease dynamics in humans and animals.
• Ecologists and epidemiologists use multi-response models to study co-infections, but selecting appropriate models for observational data is challenging.
• Limited cross-disciplinary insights hinder a comprehensive understanding of co-infection patterns and processes.

Purpose of the Study:

• To systematically review the use of multi-response models in co-infection research.
• To assess the diversity of study goals and host-pathogen systems examined.
• To determine the extent of knowledge exchange between different scientific disciplines.

Main Methods:

• Systematic literature review of 69 peer-reviewed primary studies on co-infections in natural environments.
• Analysis of research objectives, host-pathogen systems, and statistical modeling approaches.
• Citation network analysis to evaluate interdisciplinary knowledge exchange.

Main Results:

• Stark divisions observed in research objectives and methodologies across different disciplines.
• Limited crossover of knowledge and insights between ecological and epidemiological studies.
• Identified 69 studies jointly measuring infection patterns of two or more pathogens.

Conclusions:

• Current co-infection research exhibits limited interdisciplinary collaboration and knowledge sharing.
• Greater collaboration between ecology and epidemiology is crucial for advancing disease management strategies.
• Developing standardized approaches for multi-response modeling in co-infection studies is needed.