A global examination of ecological niche modelling to predict emerging infectious diseases: a systematic review

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As emerging infectious diseases increase, it is necessary to examine their underlying social and environmental drivers.

Ecological niche modelling is increasingly being used to predict disease emergence based on the spatial distribution of biotic conditions and interactions, abiotic conditions, and the mobility or dispersal of vector-host species, as well as social factors that modify the host species’ spatial distribution.

However, the application of ecological niche modelling to emerging infectious diseases is relatively new with varying algorithms and data types.

To explore this issue further, scientists from the International Livestock Research Institute, Saint Louis University, Saint Louis Zoo, Taylor Geospatial Institute and the University of Liverpool carried out a systematic review with the following research question: What is the state of the science and practice of estimating ecological niches via ecological niche modelling to predict the emergence and spread of vector-borne and/or zoonotic diseases?

The team searched five research databases and eight widely recognized One Health journals between 1995 and 2020.

They screened 383 articles at the abstract level (included if study involved vector-borne or zoonotic disease and applied ecological niche modelling) and 237 articles at the full-text level (included if study described ecological niche modelling features and modelling processes).

The objectives were to

  1. describe the growth and distribution of studies across the types of infectious diseases, scientific fields, and geographic regions;
  2. evaluate the likely effectiveness of the studies to represent ecological niches based on the biotic, abiotic, and mobility framework;
  3. explain some potential pitfalls of ecological niche modelling algorithms and techniques; and
  4. provide specific recommendation for future studies on the analysis of ecological niches to predict emerging infectious diseases.

The review found that 99% of studies included mobility factors, 90% modelled abiotic factors with more than half in tropical climate zones, 54% modelled biotic conditions and interactions.

Of the 121 studies, 7% included only biotic and mobility factors, 45% included only abiotic and mobility factors, and 45% fully integrated the biotic, abiotic and mobility data.

Only 13% of studies included modifying social factors such as land use.

A majority of studies (77%) used well-recognized ecological niche modelling algorithms and model selection procedures.

Most studies (90%) reported model validation procedures, but only 7% reported uncertainty analysis.

These findings bolster ecological niche modelling to predict emerging infectious diseases that can help inform the prevention of outbreaks and future epidemics.

Lawrence, T.J., Takenaka, B.P., Garg, A., Tao, D., Deem, S.L., Fèvre, E.M., Gluecks, I., Sagan, V. and Shacham, E. 2023. A global examination of ecological niche modeling to predict emerging infectious diseases: a systematic review. Frontiers in Public Health 11: 1244084.

Photo credit: Landscape in Hoa Binh province, northwest of Vietnam (ILRI/Vu Ngoc Dung)


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