Early Detection of Asymptomatic Human Infections in Vector-Borne Diseases: A Programmatic Model for Enhanced...

Area of Science:

• Epidemiology
• Public Health
• Infectious Diseases

Background:

• Current vector-borne disease (VBD) control strategies primarily focus on symptomatic cases.
• A significant proportion of VBD infections, particularly arboviruses, are asymptomatic or minimally symptomatic, potentially sustaining pathogen circulation.
• Symptom-based surveillance alone risks delayed outbreak detection and missed opportunities for intervention.

Purpose of the Study:

• To highlight the limitations of symptom-based surveillance for VBD control.
• To propose a novel model for enhanced VBD surveillance and early detection.
• To advocate for a shift towards anticipatory preparedness in VBD management.

Main Methods:

• Reviewing evidence from various VBDs (dengue, Zika, malaria, etc.) to illustrate challenges posed by asymptomatic infections.
• Proposing the establishment of Enhanced Vector-Borne Disease Vigilance Teams (EVBD-VTs).
• Integrating laboratory networks, sentinel systems, One Health framework, climate-informed risk assessment, and active case detection.

Main Results:

• Asymptomatic infections complicate surveillance and undermine outbreak anticipation across diverse VBDs.
• Reliance on symptomatic cases leads to delayed detection and reactive control measures.
• The proposed EVBD-VT model offers a framework for proactive VBD management.

Conclusions:

• Enhanced surveillance incorporating asymptomatic infections is crucial for effective VBD control.
• The EVBD-VT model provides a structured approach to strengthen early detection and anticipatory preparedness.
• A One Health approach, supported by robust infrastructure and active case detection, is essential for VBD control in changing ecological conditions.