Evidence map›Paper›PMID 40146697›Full record

ArticlePLoS neglected tropical diseases2025

Using iDNA to determine impacts of Amazonian deforestation on Leishmania hosts, vectors, and their interactions.

Aimee L Massey, David José Ferreira da Silva, Carla Julia da Silva Pessoa Vieira, Jennifer M Allen, Gustavo Rodrigues Canale, Christine Steiner São Bernardo, Roberta Vieira de Morais Bronzoni, Carlos A Peres, Taal Levi

Abstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. [Environmental changes and the emergence of zoonoses].Medecine tropicale et sante internationale · 2026
    Review
  3. Article
  4. Article
  5. 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

9 authors.

Aimee L MasseyDepartment of Fisheries, Wildlife, and Conservation Sciences, Oregon State University, Corvallis, Oregon, United States of America.ORCID 0000-0003-2995-3967
David José Ferreira da SilvaInstituto de Ciências da Saúde, Universidade Federal de Mato Grosso, Sinop, Mato Grosso, Brazil.
Carla Julia da Silva Pessoa VieiraInstituto de Ciências da Saúde, Universidade Federal de Mato Grosso, Sinop, Mato Grosso, Brazil.
Jennifer M AllenDepartment of Fisheries, Wildlife, and Conservation Sciences, Oregon State University, Corvallis, Oregon, United States of America.
Gustavo Rodrigues CanaleInstituto de Ciências Naturais, Humanas e Sociais, Universidade Federal de Mato Grosso, Sinop, Mato Grosso, Brazil.
Christine Steiner São BernardoInstituto de Ciências Naturais, Humanas e Sociais, Universidade Federal de Mato Grosso, Sinop, Mato Grosso, Brazil.
Roberta Vieira de Morais BronzoniInstituto de Ciências da Saúde, Universidade Federal de Mato Grosso, Sinop, Mato Grosso, Brazil.
Carlos A PeresInstituto Juruá, Carauari, Brazil.
Taal LeviDepartment of Fisheries, Wildlife, and Conservation Sciences, Oregon State University, Corvallis, Oregon, United States of America.

Funding

Oregon State University (TL)The British CouncilUniversidade Federal de Mato Grosso (RB; GRC)University of East Anglia (CAP)
6 · The paper itself

Abstract

backgroundThere is debate concerning whether there exists a generalizable effect of land-use change on zoonotic disease risk. Strong data informing this debate are sparse because it is challenging to establish direct links between hosts, vectors, and pathogens. However, molecular methods using invertebrate-derived DNA (iDNA) can now measure species composition and interactions from vector samples at landscape scales, which has the potential to improve mechanistic understanding of the effects of land-use change on zoonotic disease risk. METHODOLOGY/PRINCIPAL

findingsWe used iDNA metabarcoding of sandflies to disentangle the relationships between Leishmania parasites, sandfly vectors, and vertebrate hosts. We paired these samples with iDNA metabarcoding of carrion flies to survey vertebrates independent of sandfly feeding preferences. We collected sandflies and carrion flies at forest sites across a deforestation gradient in the southern Amazon 'Arc of Deforestation', which exemplifies global patterns of deforestation due to agricultural expansion. We used a series of models to test whether sandflies and the vertebrate they feed upon were influenced by deforestation, which we measured using percent forest cover, percent pasture cover, and distance to the major urban center. We found that vectors were encountered less frequently in forests surrounded by pasture. We also found that the probability of a Leishmania host/reservoir being detected in sandfly bloodmeals was quadratically related to local forest cover, with the highest probability found at sites with intermediate levels of deforestation. Hosts were also detected most often with carrion flies at sites with intermediate forest cover, suggesting that increased host availability rather than feeding preferences was responsible for this result. Domestic dogs and the nine-banded armadillo, Dasypus novemcinctus, were the most prevalent hosts found in the sandfly iDNA data. CONCLUSIONS/SIGNIFICANCE: Our results did not support the generality of the 'dilution effect' hypothesis. However, important vectors and hosts showed consistent responses to deforestation and our findings suggest that interactions between domestic dogs and sylvatic hosts are a pathway for zoonotic disease transmission in human impacted tropical forests.

Indexed as

Conservation of Natural ResourcesInsect VectorsLeishmaniaLeishmaniasisPsychodidaeAnimalsDNA Barcoding, TaxonomicForestsHumansZoonoses

Identifiers

PMID40146697
PMCPMC11952761

What OpenQuestion holds

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LicenceCC BY
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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.