To pool or not to pool? Guidelines for pooling samples for use in surveillance testing of infectious diseases in aquatic animals

Abstract

Samples from multiple animals may be pooled and tested to reduce costs of surveillance for infectious agents in aquatic animal populations. The primary advantage of pooling is increased population‐level coverage when prevalence is low (<10%) and the number of tests is fixed, because of increased likelihood of including target analyte from at least one infected animal in a tested pool. Important questions and a priori design considerations need to be addressed. Unfortunately, pooling recommendations in disease‐specific chapters of the 2018 OIE Aquatic Manual are incomplete and, except for amphibian chytrid fungus, are not supported by peer‐reviewed research. A systematic review identified only 12 peer‐reviewed aquatic diagnostic accuracy and surveillance studies using pooled samples. No clear patterns for pooling methods and characteristics were evident across reviewed studies, although most authors agreed there is a negative effect on detection. Therefore, our purpose was to review pooling procedures used in published aquatic infectious disease research, present evidence‐based guidelines, and provide simulated data examples for white spot syndrome virus in shrimp. A decision tree of pooling guidelines was developed for use by peer‐reviewed journals and research institutions for the design, statistical analysis and reporting of comparative accuracy studies of individual and pooled tests for surveillance purposes.

Pooled samples and eDNA-based detection can facilitate the “clean trade” of aquatic animals

“…(6)). The results are largely intuitive: when n individual-level samples are divided into m = n/k pools of size k, the number of pools that need be screened is reduced up to k-fold, assuming low prevalence of infection and high diagnostic sensitivity 24,74 . The gains in efficiency from pooling are reduced somewhat for less sensitive tests when infections are more common, but not markedly so.…”

“…On the other hand, the formula assumes that the analyte is not overwhelmed or inhibited by non-target materials (e.g., PCR inhibitors in skin secretions, microbial DNA) nor diluted below a detection threshold (e.g., as was observed with pools of fish screened for a Megalocytivirus 75 ). This later assumption is unlikely to hold with very large pools of samples (see Laurin et al 74 for a review), but may be reasonable for small pools. It is an important assumption to test under realistic conditions, but one could simply use lower values of diagnostic sensitivity (Se in Eq.…”

Counting and identification of molds and yeasts in dry salted shrimp commercialized in Rio Branco, Acre, Brazil

“…Adherence to these procedures guarantees the periodic evaluation of the product's microbiological quality, as well as safety to the consumer's health. (Laurin et al, 2019). However, the search for fungi and potential mycotoxins in shrimp is scarce in the literature.…”

Sample pooling methods for efficient pathogen screening: Practical implications

“…Because the positive samples are indistinguishable from negative samples, a test must be performed on a sample or a group of samples in order to determine their status. The test is typically assumed to always be accurate, even when many samples are tested together (in practice, this is often not the case and approaches that consider test error and constraints on the number of samples per pool have been examined [16,17]). In the worst case, all of the samples would need to be tested individually requiring N tests.…”

“…To accomplish this, some of the pooling schemes required additional steps and tests that are accounted for in the simulation. The simulation code is available at https://github.com/FofanovLab/sample_pooling_sims.DNA Sudoku SimulationsFor the DNA Sudoku experiments, we tested different weights ranging from 2 to the highest value that did not exceed the number of tests required for individual testing.For example, with a sample size of 96, the maximum weight we used was 6 with window sizes of10,11,13,17,19, and 23; this testing design required 93 tests, in the unambiguous case, and including any additional testing windows would cause the number of tests to exceed individual testing. The window sizes at the maximum weight were 20, 21, 23, 29, 31, 37, 41, 43, 47, and 53 for 384 samples; and 40, 41, 43, 47, 49, 51, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97, 101, 103, 107, 109, and 113 for 1,536 samples.…”