Natural grouping behavior of hosts can reduce sample size requirements to estimate disease prevalence at a population scale. The Efficient Sample Size Calculator allows users to consider grouping tendencies of the host species to compute sample sizes needed to have 95% probability that disease prevalence in the population is at or below 1% or 2%. Allowable sampling schemes include simple random sampling, high-harvest sampling and two-stage cluster sampling. Examples cover a wide range of host species, diseases, and sampling schemes, and reveal that a well-designed sampling strategy may dramatically improve scientific efficiency over traditional sample size calculators without jeopardizing scientific rigor. Alternatively, an ill-designed sampling strategy may hamstring the ability for information from samples to reach the population scale. Novel statistical theory in Booth et al. (2024) and Booth et al. (2025).
Booth, J.G., Hanley, B.J., Hodel, F.H. et al. 2024. Sample Size for Estimating Disease Prevalence in Free-Ranging Wildlife Populations: A Bayesian Modeling Approach. Journal of Agricultural, Biological, and Environmental Statistics 29, 438–454. 10.1007/s13253-023-00578-7.
Booth, J.G., Hanley, B.J., Thompson, N.E. et al. 2025. Management Agencies can Leverage Animal Social Structure for Wildlife Disease Surveillance. Journal of Wildlife Diseases. 10.7589/JWD-D-24-00079.