Overview:

Public health authorities face the critical challenge of accurately identifying infected individuals to implement effective quarantine measures while avoiding unnecessary restrictions on healthy populations. When a diagnostic test returns a positive result, this single data point prompts complex questions about its real-world implications.

Can one reliably conclude an individual is infected based solely on a single positive test result? Similarly, does a negative result definitively indicate someone is infection-free? This session explores the statistical foundations necessary to evaluate diagnostic testing outcomes, addressing whether mass population testing provides meaningful data and how authorities should interpret aggregate results to inform public health decisions.

Why you should Attend:

This webinar provides essential methodology for properly interpreting diagnostic test results through Bayesian statistical inference. Participants will learn to move beyond simplistic interpretations of positive or negative results to understand the actual probability of infection given a specific test outcome.

The session will address critical questions: When can a single test result be considered reliable evidence of infection status? Under what circumstances does a negative test truly indicate someone is safe to release without restrictions? We will examine the public health utility of mass testing initiatives and explore what actions authorities should consider based on population-level testing data, providing a framework for making statistically sound public health decisions.

Areas Covered in the Session:

• Bayesian statistical interpretation of single diagnostic test results

• Analysis of consecutive repeated testing using Bayesian updating

• Calculation and application of positive and negative predictive values

• Comparison of COVID-19 testing methodologies: RT-PCR versus rapid antigen tests

• Understanding test specificity and sensitivity and their impact on result interpretation

• Sequential testing with updated prevalence estimates (priors)

Who Will Benefit:

• Nursing Managers and Supervisors

• Chief Nursing Officers and Nursing Executives

• Healthcare Quality Improvement Directors and Vice Presidents

• Healthcare Operations Leadership

• Public Health Officials and Epidemiologists

• Infection Prevention and Control Specialists