Developing a spatio-temporal model for banana bunchy top disease: leveraging remote sensing and survey data

Epidemics of Banana Bunchy Top Disease (BBTD) in sub-Saharan Africa are threatening global food security and endangering the livelihoods of smallholder farmers. This study introduces methods for developing data-based models to derive banana production maps and process-based models to assess the potential spread of BBTV at a landscape scale. We introduce two novel aspects: a methodology for deriving probabilistic banana production maps based on high-resolution remote sensing products and parameterization of the epidemiological model for BBTD from limited survey data. We generated a countrywide banana production map for Tanzania and a state-wide map for Ogun State in Nigeria. We used the banana map together with published data from BBTD surveys to parameterize a model for BBTD spread in Tanzania. Our results emphasize the importance of surveys, as having data on the presence and absence of Banana Bunchy Top Virus (BBTV) at different stages of epidemics is crucial not only for effective control of the disease but also for prediction, including making reasonable model assumptions, model parameterization, and model validation that underpin predictions.

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Publication Details

Journal
Frontiers in Plant Science
Published
2025-06-09
DOI
https://doi.org/10.3389/fpls.2025.1521620
Citations
7
Primary Topic
Plant Virus Research Studies
Type
article
Field-Weighted Citation Impact
12.25
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article

Developing a spatio-temporal model for banana bunchy top disease: leveraging remote sensing and survey data

Christopher A. Gilligan, Renata Retkutė
7 citations
Frontiers in Plant Science
Plant Virus Research Studies
12.25
article

Developing a spatio-temporal model for banana bunchy top disease: leveraging remote sensing and survey data

Christopher A. Gilligan, Renata Retkutė
article en
7 citations

Abstract

Epidemics of Banana Bunchy Top Disease (BBTD) in sub-Saharan Africa are threatening global food security and endangering the livelihoods of smallholder farmers. This study introduces methods for developing data-based models to derive banana production maps and process-based models to assess the potential spread of BBTV at a landscape scale. We introduce two novel aspects: a methodology for deriving probabilistic banana production maps based on high-resolution remote sensing products and parameterization of the epidemiological model for BBTD from limited survey data. We generated a countrywide banana production map for Tanzania and a state-wide map for Ogun State in Nigeria. We used the banana map together with published data from BBTD surveys to parameterize a model for BBTD spread in Tanzania. Our results emphasize the importance of surveys, as having data on the presence and absence of Banana Bunchy Top Virus (BBTV) at different stages of epidemics is crucial not only for effective control of the disease but also for prediction, including making reasonable model assumptions, model parameterization, and model validation that underpin predictions.

Frontiers in Plant ScienceVol. 16
University of Cambridge (GB)
Good health and well-being
Openalex Percentile: Top 2%
Plant Virus Research Studies
12.25
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