Surveillance Analysis and Sample Size Explorer (SASSE): Learning How to Plan Disease Surveillance in Wildlife

Area of Science:

• Veterinary Epidemiology
• Wildlife Health Management
• Biostatistics

Background:

• Effective wildlife disease surveillance is vital for safeguarding public health, agriculture, and biodiversity.
• Designing statistically sound surveillance programs requires expertise in sampling methodologies and diagnostic test evaluation.
• Existing tools often lack the accessibility and specific focus needed for wildlife disease surveillance design.

Purpose of the Study:

• To introduce the Surveillance Analysis and Sample Size Explorer (SASSE), an interactive tool for wildlife professionals.
• To enhance statistical intuition regarding sample size, sampling design, and diagnostic test performance in wildlife surveillance.
• To provide a user-friendly solution for designing efficient wildlife disease surveillance systems.

Main Methods:

• Development of an interactive, module-based teaching tool using open-source R and R Shiny software.
• Incorporation of key surveillance objectives: detection, prevalence estimation, and epidemiological dynamics.
• Focus on enabling users to apply statistical sample size theory to practical surveillance design.

Main Results:

• SASSE empowers a broad audience to design statistically robust wildlife disease surveillance.
• The tool simplifies the application of complex statistical concepts for wildlife professionals.
• It facilitates the identification of efficient sampling designs tailored to specific surveillance objectives.

Conclusions:

• SASSE addresses critical gaps in current wildlife surveillance design methodologies.
• The tool enhances the capacity of wildlife professionals to create effective and statistically grounded surveillance programs.
• SASSE promotes better-informed decision-making for wildlife disease management and conservation efforts.