Wastewater-based epidemiology framework: Collaborative modeling for sustainable disease surveillance.

Area of Science:

• Environmental microbiology
• Public health surveillance
• Epidemiology

Background:

• Wastewater-based epidemiology (WBE) is crucial for public health monitoring.
• Effective WBE requires integrating modeling with theoretical and institutional frameworks.
• Current frameworks often lack explicit integration of modeling for WBE program design.

Purpose of the Study:

• To develop a collaborative framework integrating modeling for sustainable WBE programs.
• To provide a structured approach for designing WBE plans through stakeholder collaboration.
• To enhance the relevance and decision-making utility of WBE modeling outputs.

Main Methods:

• Building upon an existing theoretical framework to incorporate modeling components.
• Developing a collaborative framework with suggested stakeholder activities.
• Demonstrating the framework using a COVID-19 case study for sampling strategy optimization.

Main Results:

• The framework facilitates the design of WBE programs by integrating modeling.
• Case study analysis revealed distinct sampling needs for different COVID-19 outbreak phases (early, peak, tail).
• Quantified differences in viral event detection likelihood based on sampling time, disease phase, and location.

Conclusions:

• The proposed framework enhances collaboration between researchers and public health authorities.
• It provides a foundation for sustainable WBE, improving disease detection efficiency.
• Optimized sampling strategies are essential for effective wastewater surveillance during outbreaks.