Evidence map›Paper›PMID 38850367›Full record

ArticleEcoHealth2024

Evaluating the Risk Landscape of Hawaiian Monk Seal Exposure to Toxoplasma gondii.

Stacie Robinson, Kim Falinski, Devin Johnson, Elizabeth VanWormer, Karen Shapiro, Angela Amlin, Michelle Barbieri

Abstract read
In one paragraph

Article in EcoHealth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  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

7 authors.

Stacie RobinsonNOAA, Hawaiian Monk Seal Research Program, Honolulu, USA. stacie.j.robinson@gmail.com.ORCID 0000-0002-0539-0306
Kim FalinskiUH, Water Resources Research Center, Honolulu, USA.
Devin JohnsonNOAA, Protected Species Division, Honolulu, USA.
Elizabeth VanWormerUniversity of Nebraska-Lincoln, Lincoln, USA.
Karen ShapiroUniversity of California Davis, Davis, USA.
Angela AmlinNOAA, Pacific Islands Regional Office, Honolulu, USA.
Michelle BarbieriNOAA, Hawaiian Monk Seal Research Program, Honolulu, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Toxoplasmosis is a disease of primary concern for Hawaiian monk seals (Neomonachus schauinslandi), due to its apparently acute lethality and especially heavy impacts on breeding female seals. The disease-causing parasite, Toxoplasma gondii, depends on cats to complete its life cycle; thus, in order to understand how this pathogen infects marine mammals, it is essential to understand aspects of the terrestrial ecosystem and land-to-sea transport. In this study, we constructed a three-tiered model to assess risk of Hawaiian monk seal exposure to T. gondii oocysts: (1) oocyst contamination as a function of cat population characteristics; (2) land-to-sea transport of oocysts as a function of island hydrology, and (3) seal exposure as a function of habitat and space use. We were able to generate risk maps highlighting watersheds contributing the most to oocyst contamination of Hawaiian monk seal habitat. Further, the model showed that free-roaming cats most associated with humans (pets or strays often supplementally fed by people) were able to achieve high densities leading to high levels of oocyst contamination and elevated risk of T. gondii exposure.

Indexed as

Seals, EarlessToxoplasmaToxoplasmosis, AnimalAnimalsCatsEcosystemFemaleHawaiiHumansOocystsRisk AssessmentDisease ecologyHawaiian monk sealHydrologyRisk modelToxoplasmosis

Identifiers

PMID38850367
PMCPMC11649717

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.