Predicting ectotherm disease vector spread--benefits from multidisciplinary approaches and directions forward

Area of Science:

• Ecology and Epidemiology
• Biostatistics
• Geospatial Analysis

Background:

• Global expansion of ectotherm disease vectors and emergence of vector-borne diseases necessitate interdisciplinary research.
• Understanding the complex causal links and determining factors requires integrating diverse scientific expertise.

Purpose of the Study:

• To evaluate citation behavior and assess scientists' interdisciplinary knowledge integration.
• To review emerging tools and concepts for enhanced vector-borne disease risk assessment.
• To advocate for multidisciplinary approaches in disease surveillance and control.

Main Methods:

• Citation analysis to understand interdisciplinary knowledge sharing.
• Description of correlative models (regression-based, machine learning, profile techniques).
• Explanation of mechanistic models (e.g., basic reproduction number R0) and spatial analysis methods.
• Discussion of advanced integrated approaches like Bayesian geostatistical modeling and geographic profiling.

Main Results:

• Citation patterns suggest scientists are increasingly engaging with results from other disciplines.
• Various modeling techniques, from correlative to mechanistic, are available for risk assessment.
• Data quality for occurrence and predictor variables is crucial for accurate risk identification.

Conclusions:

• Multidisciplinary research is vital for effective surveillance and control of vector-borne diseases.
• Developing interdisciplinary communication networks and sharing methods is essential for new insights.
• Integrating diverse tools and concepts promises improved global public health outcomes.