Evidence map›Paper›PMID 34103103›Full record

ArticleParasitology2021

The people

Jean-François Doherty, Antoine Filion, Jerusha Bennett, Upendra Raj Bhattarai, Xuhong Chai, Daniela de Angeli Dutra, Erica Donlon, Fátima Jorge, Marin Milotic, Eunji Park and 3 more

Abstract read
In one paragraph

Article in Parasitology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
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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

13 authors.

Jean-François DohertyDepartment of Zoology, University of Otago, P.O. Box 56, Dunedin, New Zealand.
Antoine FilionDepartment of Zoology, University of Otago, P.O. Box 56, Dunedin, New Zealand.
Jerusha BennettDepartment of Zoology, University of Otago, P.O. Box 56, Dunedin, New Zealand.
Upendra Raj BhattaraiDepartment of Anatomy, University of Otago, P.O. Box 56, Dunedin, New Zealand.
Xuhong ChaiDepartment of Zoology, University of Otago, P.O. Box 56, Dunedin, New Zealand.
Daniela de Angeli DutraDepartment of Zoology, University of Otago, P.O. Box 56, Dunedin, New Zealand.
Erica DonlonDepartment of Zoology, University of Otago, P.O. Box 56, Dunedin, New Zealand.
Fátima JorgeDepartment of Zoology, University of Otago, P.O. Box 56, Dunedin, New Zealand.ORCID 0000-0002-3138-1729
Marin MiloticDepartment of Zoology, University of Otago, P.O. Box 56, Dunedin, New Zealand.
Eunji ParkDepartment of Zoology, University of Otago, P.O. Box 56, Dunedin, New Zealand.ORCID 0000-0002-5087-2398
Amandine J M SabadelDepartment of Zoology, University of Otago, P.O. Box 56, Dunedin, New Zealand.
Leighton J ThomasDepartment of Zoology, University of Otago, P.O. Box 56, Dunedin, New Zealand.
Robert PoulinDepartment of Zoology, University of Otago, P.O. Box 56, Dunedin, New Zealand.ORCID 0000-0003-1390-1206

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Every internet search query made out of curiosity by anyone who observed something in nature, as well as every photo uploaded to the internet, constitutes a data point of potential use to scientists. Researchers have now begun to exploit the vast online data accumulated through passive crowdsourcing for studies in ecology and epidemiology. Here, we demonstrate the usefulness of iParasitology, i.e. the use of internet data for tests of parasitological hypotheses, using hairworms (phylum Nematomorpha) as examples. These large worms are easily noticeable by people in general, and thus likely to generate interest on the internet. First, we show that internet search queries (collated with Google Trends) and photos uploaded to the internet (specifically, to the iNaturalist platform) point to parts of North America with many sightings of hairworms by the public, but few to no records in the scientific literature. Second, we demonstrate that internet searches predict seasonal peaks in hairworm abundance that accurately match scientific data. Finally, photos uploaded to the internet by non-scientists can provide reliable data on the host taxa that hairworms most frequently parasitize, and also identify hosts that appear to have been neglected by scientific studies. Our findings suggest that for any parasite group likely to be noticeable by non-scientists, information accumulating through internet search activity, photo uploads, social media or any other format available online, represents a valuable source of data that can complement traditional scientific data sources in parasitology.

Indexed as

Host-Parasite InteractionsAnimalsCanadaCrowdsourcingDatabases, FactualDemographyFemaleHelminthsHumansInternetMalePhotographyPopulation DensitySeasonsTime FactorsUnited StatesCitizen sciencecrowdsourcingGoogle TrendshairwormsiNaturalistinternet searchiParasitology

Identifiers

PMID34103103
PMCPMC11010187

What OpenQuestion holds

Textmetadata
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.