Evidence map›Paper›PMID 27994156›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2017

Linking parasite populations in hosts to parasite populations in space through Taylor's law and the negative binomial distribution.

Joel E Cohen, Robert Poulin, Clément Lagrue

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Aggregation ofParasite epidemiology and control · 2023
    Review
  3. Distribution of different species of metacercariae in two freshwater fishes:Journal of parasitic diseases : official organ of the Indian Society for Parasitology · 2022
    Article
  4. Article
  5. Article
  6. Chagas disease vector control and Taylor's law.PLoS neglected tropical diseases · 2017
    Article
  7. 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

3 authors.

Joel E CohenLaboratory of Populations, The Rockefeller University, New York, NY 10065; cohen@rockefeller.edu.ORCID 0000-0002-9746-6725
Robert PoulinDepartment of Zoology, University of Otago, Dunedin 9054, New Zealand.
Clément LagrueDepartment of Zoology, University of Otago, Dunedin 9054, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The spatial distribution of individuals of any species is a basic concern of ecology. The spatial distribution of parasites matters to control and conservation of parasites that affect human and nonhuman populations. This paper develops a quantitative theory to predict the spatial distribution of parasites based on the distribution of parasites in hosts and the spatial distribution of hosts. Four models are tested against observations of metazoan hosts and their parasites in littoral zones of four lakes in Otago, New Zealand. These models differ in two dichotomous assumptions, constituting a 2 × 2 theoretical design. One assumption specifies whether the variance function of the number of parasites per host individual is described by Taylor's law (TL) or the negative binomial distribution (NBD). The other assumption specifies whether the numbers of parasite individuals within each host in a square meter of habitat are independent or perfectly correlated among host individuals. We find empirically that the variance-mean relationship of the numbers of parasites per square meter is very well described by TL but is not well described by NBD. Two models that posit perfect correlation of the parasite loads of hosts in a square meter of habitat approximate observations much better than two models that posit independence of parasite loads of hosts in a square meter, regardless of whether the variance-mean relationship of parasites per host individual obeys TL or NBD. We infer that high local interhost correlations in parasite load strongly influence the spatial distribution of parasites. Local hotspots could influence control and conservation of parasites.

Indexed as

Models, BiologicalAnimalsBinomial DistributionDemographyEcologyHost-Parasite InteractionsHumansNew ZealandParasite LoadParasitesPopulation Dynamicsfreshwater communitiesparasite loadspatial distributionsynchronyvariance function

Identifiers

PMID27994156
PMCPMC5224400

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Registered trials

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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.