<abstract xmlns="http://www.w3.org/1999/xhtml"><p>To reach ethically and scientifically valid mean abundance values in parasitological and epidemiological studies this paper considers analytic and simulation approaches for sample size determination. The sample size estimation was carried out by applying mathematical formula with predetermined precision level and parameter of the negative binomial distribution estimated from the empirical data. A simulation approach to optimum sample size determination aimed at the estimation of true value of the mean abundance and its confidence interval (<italic>CI</italic>) was based on the Bag of Little Bootstraps (BLB). The abundance of two species of monogenean parasites <italic>Ligophorus cephali</italic> and <italic>L. mediterraneus</italic> from <italic>Mugil cephalus</italic> across the Azov-Black Seas localities were subjected to the analysis. The dispersion pattern of both helminth species could be characterized as a highly aggregated distribution with the variance being substantially larger than the mean abundance. The holistic approach applied here offers a wide range of appropriate methods in searching for the optimum sample size and the understanding about the expected precision level of the mean. Given the superior performance of the BLB relative to formulae with its few assumptions, the bootstrap procedure is the preferred method. Two important assessments were performed in the present study: i) based on <italic>CI</italic>s width a reasonable precision level for the mean abundance in parasitological surveys of <italic>Ligophorus</italic> spp. could be chosen between 0.8 and 0.5 with 1.6 and 1x mean of the <italic>CI</italic>s width, and ii) the sample size equal 80 or more host individuals allows accurate and precise estimation of mean abundance. Meanwhile for the host sample size in range between 25 and 40 individuals, the median estimates showed minimal bias but the sampling distribution skewed to the low values; a sample size of 10 host individuals yielded to unreliable estimates.</p></abstract>

To reach ethically and scientifically valid mean abundance values in parasitological and epidemiological studies this paper considers analytic and simulation approaches for sample size determination. The sample size estimation was carried out by applying mathematical formula with predetermined precision level and parameter of the negative binomial distribution estimated from the empirical data. A simulation approach to optimum sample size determination aimed at the estimation of true value of the mean abundance and its confidence interval (CI) was based on the Bag of Little Bootstraps (BLB). The abundance of two species of monogenean parasites Ligophorus cephali and L. mediterraneus from Mugil cephalus across the Azov-Black Seas localities were subjected to the analysis. The dispersion pattern of both helminth species could be characterized as a highly aggregated distribution with the variance being substantially larger than the mean abundance. The holistic approach applied here offers a wide range of appropriate methods in searching for the optimum sample size and the understanding about the expected precision level of the mean. Given the superior performance of the BLB relative to formulae with its few assumptions, the bootstrap procedure is the preferred method. Two important assessments were performed in the present study: i) based on CIs width a reasonable precision level for the mean abundance in parasitological surveys of Ligophorus spp. could be chosen between 0.8 and 0.5 with 1.6 and 1x mean of the CIs width, and ii) the sample size equal 80 or more host individuals allows accurate and precise estimation of mean abundance. Meanwhile for the host sample size in range between 25 and 40 individuals, the median estimates showed minimal bias but the sampling distribution skewed to the low values; a sample size of 10 host individuals yielded to unreliable estimates.

Optimum sample size to estimate mean parasite abundance in fish parasite surveys

Research Institute for Integrated Management of Coastal Zones, Department of Applied Mathematics

Unit of Biostatistics, Center for Research in Molecular Medicine and Chronic Diseases (CIMUS)

Helminthologia

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Optimum sample size to estimate mean parasite abundance in fish parasite surveys"}

To reach ethically and scientifically valid mean abundance values in parasitological and epidemiological studies this paper considers analytic and simulation...

Optimum sample size to estimate mean parasite abundance in fish parasite surveys

Published Online: Jan 27, 2018

Page range: 52 - 59

Received: Feb 09, 2017

Accepted: Sep 26, 2017

DOI: https://doi.org/10.1515/helm-2017-0054

Keywords
fish, spp., mean abundance, optimum sample size, precision, Bag of Little Bootstraps

© 2018 S. Shvydka et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Optimum sample size to estimate mean parasite abundance in fish parasite surveys

Published Online: Jan 27, 2018

Page range: 52 - 59

Received: Feb 09, 2017

Accepted: Sep 26, 2017

DOI: https://doi.org/10.1515/helm-2017-0054

Keywordsfish, spp., mean abundance, optimum sample size, precision, Bag of Little Bootstraps

© 2018 S. Shvydka et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
fish, spp., mean abundance, optimum sample size, precision, Bag of Little Bootstraps