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ECOLOGICAL NICHE MODELING APPLICATIONS TO INFECTIOUS DISEASES.

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This summary is machine-generated.

Ecological niche modeling (ENM) applications in disease systems lack reporting consistency. Improving transparency in ENM components is crucial for robust spatial epidemiology and accurate disease transmission risk mapping.

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Area of Science:

  • Ecology
  • Epidemiology
  • Biogeography

Background:

  • Ecological niche modeling (ENM) is vital for predicting species distributions and has been applied to spatial epidemiology.
  • Limited research evaluates ENM components and assumptions in disease systems, raising concerns about robustness, reproducibility, and transparency.

Purpose of the Study:

  • To systematically review and evaluate articles on ENM applications to infectious diseases between 2020-2022.
  • To identify trends and gaps in reporting ENM protocols for mapping disease transmission risk.

Main Methods:

  • Conducted a systematic review of 78 articles published between 2020 and 2022 on ENM in infectious diseases.
  • Extracted information on ENM components using a standard reporting protocol, including study subject, location, duration, and data selection.

Main Results:

  • Significant variation observed in spatial extent (village to global) and temporal duration (1-101 years).
  • Key components like temporal autocorrelation tests (2.66%), algorithmic uncertainty (28.21%), and model averaging (20.51%) were infrequently reported.
  • Inconsistent reporting of background data selection, coordinate reference systems, and model performance was noted.

Conclusions:

  • Findings highlight a lack of consistency and transparency in disease ecology and biogeography studies using ENM.
  • Inconsistent reporting may lead to misleading ENM applications in spatial epidemiology.
  • Clear reporting of ENM components by researchers and reviewers is essential for biologically sound outputs in disease systems.