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).