Evidence map›Paper›PMID 42039091›Full record

ArticleBiodiversity informatics2025

ECOLOGICAL NICHE MODELING APPLICATIONS TO INFECTIOUS DISEASES.

Shariful Islam, Mariana Castaneda-Guzman, Diego Soler-Tovar, Luis E Escobar

Abstract read
In one paragraph

Article in Biodiversity informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Shariful IslamDepartment of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, VA, USA.
Mariana Castaneda-GuzmanDepartment of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, VA, USA.
Diego Soler-TovarFaculty of Agricultural Sciences, Universidad de La Salle, Bogotá, Colombia.
Luis E EscobarDepartment of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, VA, USA.ORCID 0000-0001-5735-2750

Funding

Mentored Research (K01) Integrative Spatial Epidemiology Study of Wildlife Rabies SpilloverK01AI168452 · NIAID · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI Luis E Escobar · 2023 to 2026
$502k
NIAID NIH HHS K01 AI168452
6 · The paper itself

Abstract

Ecological niche modeling (ENM) is a widely used analytical approach for predicting species distributions and has been applied to study the spatial epidemiology of infectious diseases. Nevertheless, research evaluating the key components and assumptions of ENM in disease systems remains limited, raising concerns about its robustness, reproducibility, and transparency. To address this limitation, we conducted a systematic review and evaluated articles on ENM applications to infectious diseases between 2020 and 2022. We reviewed 78 articles to extract information following a standard protocol for reporting ENM analysis and summarized the information for each component (e.g., study subject, location, duration). The spatial extent of study areas varied from village to global scales, temporal duration ranged from 1 to 101 years, and the organismal levels ranged from individuals (57.7%) to populations (33.3%). Less frequently reported components included temporal autocorrelation tests (2.66%), algorithmic uncertainty (28.21%), temporal resolution (35.90%), background data selection (44.87%), coordinate reference system (41.02%), model performance from validation data (46.15%), and model averaging (20.51%). Our findings highlight a lack of consistency and transparency in disease ecology and disease biogeography studies, which may lead to misleading ENM applications in spatial epidemiology. Researchers and reviewers applying ENM to disease systems should clearly report key modeling components to ensure biologically sound outputs. This article identified trends and gaps in reporting ENM protocols for mapping disease transmission risk.

Indexed as

BiogeographyDiseaseEcological NicheEpidemiologyReproducibilitySpatial

Identifiers

PMID42039091
PMCPMC13109972

What OpenQuestion holds

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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.