Chapter 21 Efficient Sample Size Calculator

21.1 What is the Efficient Sample Size Calculator?

The Efficient Sample Size Calculator leverages naturally-occurring biological groupings and group-wise correlation structure to plan a sampling scheme to efficiently investigate whether a free-ranging population is disease free. This calculator allows planning using three different sampling schemes: (1) simple random sampling, (2) high harvest sampling, or (3) two-stage cluster sampling.

21.2 What Question Does it Answer?

Question 1. How many individuals should I test in this next season-year without finding a positive case to make inferences about population-scale disease freedom? The app shows you exactly how many negatives you need to accumulate from your host population in the upcoming year to declare the population free from disease with high confidence.

21.3 Output Details

  • Sample size: The number of samples needed from a population to ensure there is a high probability that disease prevalence is at or below 1% or 2%.

21.4 Abbreviated Tutorial

  1. Click the ‘Run Efficient Sample Size Calculator’ button.
  2. Once the app opens, click through the app to choose your model parameters (see below).
  3. Run the model with those desired population parameters.
  4. Look at the graph to see the number of animals that need to be tested without finding a positive case to ensure there is a high probability that disease prevalence is at or below 1% or 2%.

21.5 Parameters Needed to Execute the Model

  • Model type: Select ‘Efficient Sample Size Calculator’ from the drop-down list, then click the URL link to open and interact with the live software.

  • Population size: Total number of animals in the population of interest. An integer between 100 and 10,000,000.

  • Cluster size: Average cluster size in the population of interest. An integer between 1 (1 animal per cluster) and m (m animals per cluster).

  • Cluster type: Whether cluster sizes are identical across the population (fixed), or vary across the population (random).

  • Sampling scheme: Scheme that you intend to use for sampling.

    • Simple Random Sampling (SRS): Each subject has an equal chance of being sampled.
    • High Harvest Sampling (HHS): Some clusters are randomly sampled more heavily than other clusters.
    • Two-stage Cluster Sampling (2CS): The clusters themselves are first randomly selected, then hosts from those clusters are randomly sampled.

  • Correlation: Correlation in disease status between hosts sharing a cluster. A decimal between 0 (disease status among members is independent) and 0.995 (disease status is nearly perfectly correlated among members).

  • Sensitivity of diagnostic test: The likelihood that the test will declare a true positive. A decimal between 0 (not sensitive) and 0.999 (perfect sensitivity).

  • Number of simulations: Number of simulations you would like to conduct. An integer between 1 (1 simulation) and s (s simulations).

21.6 Details on the Theory

Booth JG, Hanley BJ, Hodel FH, Jennelle CS, Guinness J, Them CE, Mitchell CI, Ahmed MS, Schuler KL. 2024. Sample Size for Estimating Disease Prevalence in Free-Ranging Wildlife Populations: A Bayesian Modeling Approach. Journal of Agricultural, Biological, and Environmental Sciences, 29, 438–454. https://doi.org/10.1007/s13253-023-00578-7.

Booth JG, Hanley BJ, Thompson NE, Gonzalez-Crespo C, Christensen SA, Jennelle CS, Caudell JN, Delisle Z, Guinness J, Hollingshead NA, Them CT, Schuler KL. Management Agencies Can Leverage Animal Social Structure for Wildlife Disease Surveillance. Journal of Wildlife Diseases. Journal of Wildlife Diseases. https://doi.org/10.7589/JWD-D-24-00079.

21.7 Code

The code is publicly available in Hanley BJ, JG Booth, FH Hodel, NE Thompson, AA Reeder, JCG Bloodgood, JP Dion, Van de Berg S, Gonzalez-Crespo C, Huang Y, Wang J, Miller LA, Hollingshead NA, Peaslee JL, Schuler KL. 2025. Efficient Sample Size Calculator [Software]. Cornell University Library eCommons.