Interpretations and pitfalls in modelling vector-transmitted infections.

Area of Science:

• Epidemiology
• Mathematical Biology
• Public Health

Background:

• Mathematical models are increasingly used to evaluate control strategies for vector-borne infections.
• The complexity of these models must align with their intended purpose, whether for intuition checking or future prediction.
• Potential pitfalls exist in the application and interpretation of these models.

Purpose of the Study:

• To debate the role and appropriate complexity of mathematical models in evaluating vector-borne infection control.
• To examine potential pitfalls associated with different classes of mathematical models.
• To discuss the limitations of specific models, including those with inappropriate biological assumptions for diseases like dengue.

Main Methods:

• Analysis and critique of two distinct classes of mathematical models: those for intuition checking and those for prediction.
• Simplification of complex mathematical models for vector-borne infections.
• Examination of a predictive model from recent literature to highlight dangers of unconsidered limitations.
• Review of an intuition-checking model with potentially inappropriate biological assumptions for dengue.

Main Results:

• Models intended for prediction require significant complexity and carry risks if their limitations are ignored.
• Models designed to check intuition may contain biological assumptions unsuitable for specific diseases, such as dengue.
• Simplifying complex models is essential for clear communication and application.

Conclusions:

• Mathematical models are valuable tools but require careful consideration of their complexity, limitations, and biological relevance.
• Misgivings regarding the application of mathematical modeling in public health decision-making are presented for further debate.
• The choice of model must be carefully matched to the research question and the specific disease context.