Evidence map›Paper›PMID 31311590›Full record

ArticleParasites & vectors2019

Comparative analysis of subsampling methods for large mosquito samples.

Linda Jaworski, Stephanie Jansen, Wolf Peter Pfitzner, Matthias Beck, Norbert Becker, Jonas Schmidt-Chanasit, Ellen Kiel, Renke Lühken

Abstract readComparative Study
In one paragraph

Article in Parasites & vectors, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Linda JaworskiCarl von Ossietzky University, Oldenburg, Germany. linda.jaworski1@uni-oldenburg.de.
Stephanie JansenBernhard Nocht Institute for Tropical Medicine, WHO Collaborating Centre for Arbovirus and Hemorrhagic Fever Reference and Research, Hamburg, Germany.
Wolf Peter PfitznerGerman Mosquito Control Association (KABS), Waldsee, Germany.
Matthias BeckGerman Mosquito Control Association (KABS), Waldsee, Germany.
Norbert BeckerGerman Mosquito Control Association (KABS), Waldsee, Germany.
Jonas Schmidt-ChanasitBernhard Nocht Institute for Tropical Medicine, WHO Collaborating Centre for Arbovirus and Hemorrhagic Fever Reference and Research, Hamburg, Germany.
Ellen KielCarl von Ossietzky University, Oldenburg, Germany.
Renke LühkenBernhard Nocht Institute for Tropical Medicine, WHO Collaborating Centre for Arbovirus and Hemorrhagic Fever Reference and Research, Hamburg, Germany. renkeluhken@gmail.com.

Funding

Bundesanstalt für Landwirtschaft und Ernährung 28-1-91.043-15Bundesanstalt für Landwirtschaft und Ernährung 28-1-91.045-15
6 · The paper itself

Abstract

backgroundThe analysis of large mosquito samples is expensive and time-consuming, delaying the efficient timing of vector control measurements. Processing a fraction of a sample using a subsampling method can significantly reduce the processing effort. However, a comprehensive evaluation of the reliability of different subsampling methods is missing.

methodsA total of 23 large mosquito samples (397-4713 specimens per sample) were compared in order to evaluate five subsampling methods for the estimation of the number of specimens and species: area, volume, weight, selection of 200 random specimens and analyses with an image processing software. Each sample was distributed over a grid paper (21.0 × 29.7 cm; 25 grid cells of 4.2 × 5.9 cm) with 200 randomly distributed points. After taking pictures, mosquito specimens closest to each of the 200 points on the paper were selected. All mosquitoes per grid cell were identified by morphology and transferred to scaled tubes to estimate the volume. Finally, the fresh and dry weights were determined.

resultsThe estimated number of specimens and species did not differ between the area-, volume- and weight-based method. Subsampling 20% of the sample gave an error rate of approximately 12% for the number of specimens, 6% for the proportion of the most abundant species and between 6-40% for the number of species per sample. The error for the estimated number of specimens using the picture processing software ImageJ gave a similar error rate when analyzing 15-20% of the total sample. By using 200 randomly selected specimens it was possible to give a precise estimation of the proportion of the most abundant species (r = 0.97, P < 0.001), but the number of species per sample was underestimated by 28% on average. Selecting adjacent grid cells instead of sampling randomly chosen grid cells and using dry weight instead of wet weight did not increase the accuracy of estimates.

conclusionsDifferent subsampling methods have various advantages and disadvantages. However, the area-based analysis of 20% of the sample is probably the most suitable approach for most kinds of mosquito studies, giving sufficiently precise estimations of the number of specimens and species, which is slightly less laborious compared to the other methods tested.

Indexed as

CulicidaeSampling StudiesAnimalsMosquito VectorsReproducibility of ResultsStatistics as TopicLarge mosquito samplesMosquito surveillanceSubsampling

Identifiers

PMID31311590
PMCPMC6636137

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.