This web application has been designed to estimate the apparent prevalence of Bursaphelenchus mucronatus in individually tested wood samples and Monochamus adults, or pooled wood or Monochamus samples. In addition to B. mucronatus the application can also be used to estimate the prevalence of other organisms.
The application can be used to calculate:
The application is written with R version 4.2.1 (R Core Team 2022) and its package ‘shiny’ (Chang et al. 2022) . The apparent prevalence of B. mucronatus in individually tested samples is estimated with exact binomial test using the binom.test function from the R package ‘stats’ (R Core Team 2022) . The apparent prevalence of B. mucronatus in pooled samples is estimated with maximum likelihood estimation test using the PoolPrev function from the R package ‘PoolTestR’ (McLure et al. 2021) . Comparisons of prevalences of the pooled data are calculated with the pooledBinDiff function from the ‘binGroup’ package using Firth's Correction method to compute the point estimation, and Skew-Corrected Score method to compute the confidence interval estimation (Zhang et al. 2010) .
Data must be uploaded to the application as comma separated csv files in which
The application was developed in the Risk Assessment Unit of the Finnish Food Authority in 2022 as part of a project 'Assessing the confidence in pest freedom gained in the past pine wood nematode surveys'. The project is a co-operation between the Finnish Food Authority, the Estonian Agriculture and Food Board (EAFB), the State Plant Service under the Ministry of Agriculture of the Republic of Lithuania (SPSMoA), the Norwegian Scientific Committee for Food and Environment (VKM), and the Swedish University of Agricultural Sciences (SLU). The project is co-funded by the European Food Safety Authority (EFSA) Partnering grant (GP/EFSA/ENCO/2020/03), yet EFSA is not responsible for any use that may be made of the information contained in the app.
Chang W, Cheng J, Allaire J, Sievert C, Schloerke B, Xie Y, Allen J, McPherson J, Dipert A and Borges B (2022) shiny: Web Application Framework for R. R package version 1.7.2, https://CRAN.R-project.org/package=shiny
McLure A, O’Neill B, Mayfield H, Lau C and McPherson B (2021) PoolTestR: An R package for estimating prevalence and regression modelling for molecular xenomonitoring and other applications with pooled samples Environmental Modelling and Software, 145, 105158. doi:10.1016/j.envsoft.2021.105158
R Core Team (2022) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
Zhang B, Bilder C, Biggerstaff B, Schaarschmidt F and Hitt B (2018) binGroup: Evaluation and Experimental Design for Binomial Group Testing. R package version 2.2-1, https://CRAN.R-project.org/package=binGroup
The source code for the application is available at Zenodo under the GNU General Public License version 3.
Please cite the application as:
Marinova-Todorova M, Tuomola J and Hannunen S (2023) A web application for estimating the apparent prevalence of Bursaphelenchus mucronatus in wood and Monochamus samples. Finnish Food Authority, Helsinki, Finland. Available at: https://b-mucronatus-prevalence-estimation.rahtiapp.fi/