Islam, SharifulCastaneda-Guzman, MarianaSoler-Tovar, DiegoEscobar, Luis E.2025-07-102025-07-102025-07-10https://hdl.handle.net/1808/36112This is the dataset that accompanies the recent publication in Biodiversity Informatics, by Islam et al. that can be found at https://journals.ku.edu/jbi/article/view/23725Ecological niche modeling (ENM) is a widely used analytical approach for predicting species distributions and has been applied to study spatial epidemiology of infectious diseases by identifying potential transmission-risk areas. However, research evaluating the fundamental components and assumptions of ENM in disease systems remain limited, raising concerns about its reproducibility and transparency. To address this gap, 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 checklist provided by (Zurell et al. 2020) 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 (44.87%), coordinate reference system (41.02%), model performance of validation data (46.15%), and model averaging (20.51%). Our findings highlight a lack of consistency and transparency in disease ecology and biogeography studies, which may lead to misleading ENM applications in spatial epidemiology. Researchers and reviewers applying ENM to disease systems should clearly report these fundamental modeling components to ensure biologically sound and actionable health. This article outlines the best practices in modeling disease systems and identifies major gaps in the current literature.Copyright 2025 The Authors. This work is licensed under a Creative Commons Attribution Non-Commercial 4.0 license.https://creativecommons.org/licenses/by-nc/4.0/ODMAPEcological niche modelingDatasetDatasethttps://orcid.org/0000-0002-6634-5090https://orcid.org/0000-0001-6106-4284https://orcid.org/0000-0002-0451-6368https://orcid.org/0000-0001-5735-2750openAccess