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

TL;DR

SASSE is an interactive tool that helps wildlife professionals design effective disease surveillance systems by building statistical intuition about sampling and diagnostic test performance.

Contribution

SASSE provides a plug-and-play, interactive teaching tool for applying statistical sample size theory to wildlife disease surveillance design.

Findings

SASSE addresses gaps in wildlife surveillance by enabling users to explore sample size and diagnostic test performance.

The tool supports key surveillance objectives like detection, prevalence, and epidemiological dynamics in complex systems.

SASSE is built using open-source software and is accessible to a broad audience for surveillance design.

Abstract

Wildlife disease surveillance helps in protecting public health, agriculture, and biodiversity. Planning effective surveillance involves strategic methods for identifying an effective sampling design for a program's objectives. Gaps in existing standards and complexity for wildlife surveillance justify a need for tools that can build statistically based intuition in wildlife professionals when designing surveillance systems. To address this need, we present the use of plug‐and‐play tools, specifically our surveillance analysis and sample size explorer (SASSE), to allow wildlife professionals to build intuition about the role of sample size vis‐à‐vis sampling design and diagnostic test performance in wildlife systems. SASSE uses open‐source software (R, R Shiny) to design an interactive, module‐based teaching tool to cover key surveillance objectives, including detection, prevalence, and epidemiological dynamics. Our tool fills the following gaps: (1) allows a broad audience to apply statistical sample size theory for designing disease surveillance, and (2) provides a simple statistical tool for addressing challenges with disease surveillance design in wildlife populations. Thus, the tool we present here can be used readily to identify efficient sampling designs for a surveillance objective across a wide variety of settings.

Surveillance of wildlife disease is important and often involves strategic methods to identify an effective design for a program's objectives that accounts for ecological and epidemiological complexities in the system. We present an interactive teaching tool, Surveillance Analysis and Sample Size Explorer (SASSE), to allow wildlife professionals to build statistically based intuition on how to design surveillance for a given objective in complex wildlife systems.

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