Evidence map›Paper›PMID 27935638›Full record

ArticleEcology2017

When can we infer mechanism from parasite aggregation? A constraint-based approach to disease ecology.

Mark Q Wilber, Pieter T J Johnson, Cheryl J Briggs

Abstract read
In one paragraph

Article in Ecology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Journal of parasitic diseases : official organ of the Indian Society for Parasitology · 2021
    Article
  6. Article
  7. Measuring aggregation in parasite populations.Journal of the Royal Society, Interface · 2020
    Article
  8. Article
  9. Article
  10. Article
  11. 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.

Mark Q WilberUniversity of California, Santa Barbara, Santa Barbara, California, 93106, USA.ORCID http://orcid.org/0000-0002-8274-8025
Pieter T J JohnsonUniversity of Colorado, Boulder, Colorado, 80309, USA.
Cheryl J BriggsUniversity of California, Santa Barbara, Santa Barbara, California, 93106, USA.

Funding

EID disease in complex communities: multi-host multi-pathogen interactionsR01GM109499 · NIGMS · UNIVERSITY OF CALIFORNIA SANTA BARBARA · PI BRIGGS, CHERYL J · 2013 to 2016
$1.7M
NIGMS NIH HHS R01 GM109499
6 · The paper itself

Abstract

Few hosts have many parasites while many hosts have few parasites. This axiom of macroparasite aggregation is so pervasive it is considered a general law in disease ecology, with important implications for the dynamics of host-parasite systems. Because of these dynamical implications, a significant amount of work has explored both the various mechanisms leading to parasite aggregation patterns and how to infer mechanism from these patterns. However, as many disease mechanisms can produce similar aggregation patterns, it is not clear whether aggregation itself provides any additional information about mechanism. Here we apply a "constraint-based" approach developed in macroecology that allows us to explore whether parasite aggregation contains any additional information beyond what is provided by mean parasite load. We tested two constraint-based null models, both of which were constrained on the total number of parasites P and hosts H found in a sample, using data from 842 observed amphibian host-trematode parasite distributions. We found that constraint-based models captured ~85% of the observed variation in host-parasite distributions, suggesting that the constraints P and H contain much of the information about the shape of the host-parasite distribution. However, we also found that extending the constraint-based null models can identify the potential role of known aggregating mechanisms (such as host heterogeneity) and disaggregating mechanisms (such as parasite-induced host mortality) in constraining host-parasite distributions. Thus, by providing robust null models, constraint-based approaches can help guide investigations aimed at detecting biological processes that directly affect parasite aggregation above and beyond those that indirectly affect aggregation through P and H.

Indexed as

EcologyHost-Parasite InteractionsAmphibiansAnimalsParasitesTrematodaamphibiansfeasible setshost-heterogeneitymacroparasitesmaximum entropynegative binomialparasite-induced host mortalitytrematodes

Identifiers

PMID27935638
PMCPMC12463491

What OpenQuestion holds

Textmetadata
LicenceTDM
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.