Ecological Niche Modeling Applications to Infectious Diseases

• Published in: Biodiversity informatics Vol. 19
• Main Authors: Islam, Shariful, Castaneda-Guzman, Mariana, Soler-Tovar, Diego, Escobar, Luis
• Format: Journal Article
• Language: English
• Published: 23.07.2025
• ISSN: 1546-9735; 1546-9735
• DOI: 10.17161/bi.v19i.23725

Ecological niche modeling (ENM) is a widely used analytical approach for predicting species distributions and has been applied to study 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 (2.7%), algorithmic uncertainty (28.2%), temporal resolution (35.9%), background data selection (44.9%), coordinate reference system (41.0%), model performance from validation data (46.2%), and model averaging (20.5%). 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.