Efficient Sample Size Calculator

Author
Hanley, Brenda J.
Booth, James G.
Hodel, Florian H.
Thompson, Noelle E.
Reeder, Ashley A.
Bloodgood, Jennifer C.
Dion, Jean-Philippe
Van de Berg, Sarah
Gonzalez-Crespo, Carlos
Huang, Yitong
Wang, Jue
Miller, Landon A.
Hollingshead, Nicholas A.
Peaslee, Jennifer L.
Schuler, Krysten L.
Abstract

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).

Description
This software is shared under a MIT License:

Copyright 2025

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Sponsorship
This publication was supported by an agreement with Cornell University, under Federal Award Number AP24WSNWRC00C030 from United States Department of Agriculture, Animal and Plant Health Inspection Service. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of Cornell University nor those of Sponsor.
Date Issued
2025-06-06
Keywords
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Related DOI
Related To
Booth, J.G., Hanley, B.J., Hodel, F.H. et al. 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 (2024). https://doi.org/10.1007/s13253-023-00578-7
Booth, J.G., Hanley, B.J., Thompson, N.E. et al. Management Agencies can Leverage Animal Social Structure for Wildlife Disease Surveillance. Journal of Wildlife Diseases (2025). https://doi.org/10.7589/JWD-D-24-00079.
Hanley, B.J., Booth, J.G., Hodel, F.H., et al. Sample size calculator for declaring a population free of infectious disease (Version 1) [Software]. Cornell University Library eCommons (2024). https://doi.org/10.7298/ka5p-bj90.
Type
software