Ensemble ecological niche modeling of West Nile virus probability in Florida.

Ecological Niche Modeling is a process by which spatiotemporal, climatic, and environmental data are analyzed to predict the distribution of an organism. Using this process, an ensemble ecological niche model for West Nile virus habitat prediction in the state of Florida was developed. This model wa...

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Autores principales:	Sean P Beeman, Andrea M Morrison, Thomas R Unnasch, Robert S Unnasch
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/85747a57bb7d4776a7c3a581d1a25437
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spelling	oai:doaj.org-article:85747a57bb7d4776a7c3a581d1a254372021-12-02T20:17:10ZEnsemble ecological niche modeling of West Nile virus probability in Florida.1932-620310.1371/journal.pone.0256868https://doaj.org/article/85747a57bb7d4776a7c3a581d1a254372021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0256868https://doaj.org/toc/1932-6203Ecological Niche Modeling is a process by which spatiotemporal, climatic, and environmental data are analyzed to predict the distribution of an organism. Using this process, an ensemble ecological niche model for West Nile virus habitat prediction in the state of Florida was developed. This model was created through the weighted averaging of three separate machine learning models-boosted regression tree, random forest, and maximum entropy-developed for this study using sentinel chicken surveillance and remote sensing data. Variable importance differed among the models. The highest variable permutation value included mean dewpoint temperature for the boosted regression tree model, mean temperature for the random forest model, and wetlands focal statistics for the maximum entropy mode. Model validation resulted in area under the receiver curve predictive values ranging from good [0.8728 (95% CI 0.8422-0.8986)] for the maximum entropy model to excellent [0.9996 (95% CI 0.9988-1.0000)] for random forest model, with the ensemble model predictive value also in the excellent range [0.9939 (95% CI 0.9800-0.9979]. This model should allow mosquito control districts to optimize West Nile virus surveillance, improving detection and allowing for a faster, targeted response to reduce West Nile virus transmission potential.Sean P BeemanAndrea M MorrisonThomas R UnnaschRobert S UnnaschPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 10, p e0256868 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Sean P Beeman Andrea M Morrison Thomas R Unnasch Robert S Unnasch Ensemble ecological niche modeling of West Nile virus probability in Florida.
description	Ecological Niche Modeling is a process by which spatiotemporal, climatic, and environmental data are analyzed to predict the distribution of an organism. Using this process, an ensemble ecological niche model for West Nile virus habitat prediction in the state of Florida was developed. This model was created through the weighted averaging of three separate machine learning models-boosted regression tree, random forest, and maximum entropy-developed for this study using sentinel chicken surveillance and remote sensing data. Variable importance differed among the models. The highest variable permutation value included mean dewpoint temperature for the boosted regression tree model, mean temperature for the random forest model, and wetlands focal statistics for the maximum entropy mode. Model validation resulted in area under the receiver curve predictive values ranging from good [0.8728 (95% CI 0.8422-0.8986)] for the maximum entropy model to excellent [0.9996 (95% CI 0.9988-1.0000)] for random forest model, with the ensemble model predictive value also in the excellent range [0.9939 (95% CI 0.9800-0.9979]. This model should allow mosquito control districts to optimize West Nile virus surveillance, improving detection and allowing for a faster, targeted response to reduce West Nile virus transmission potential.
format	article
author	Sean P Beeman Andrea M Morrison Thomas R Unnasch Robert S Unnasch
author_facet	Sean P Beeman Andrea M Morrison Thomas R Unnasch Robert S Unnasch
author_sort	Sean P Beeman
title	Ensemble ecological niche modeling of West Nile virus probability in Florida.
title_short	Ensemble ecological niche modeling of West Nile virus probability in Florida.
title_full	Ensemble ecological niche modeling of West Nile virus probability in Florida.
title_fullStr	Ensemble ecological niche modeling of West Nile virus probability in Florida.
title_full_unstemmed	Ensemble ecological niche modeling of West Nile virus probability in Florida.
title_sort	ensemble ecological niche modeling of west nile virus probability in florida.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/85747a57bb7d4776a7c3a581d1a25437
work_keys_str_mv	AT seanpbeeman ensembleecologicalnichemodelingofwestnilevirusprobabilityinflorida AT andreammorrison ensembleecologicalnichemodelingofwestnilevirusprobabilityinflorida AT thomasrunnasch ensembleecologicalnichemodelingofwestnilevirusprobabilityinflorida AT robertsunnasch ensembleecologicalnichemodelingofwestnilevirusprobabilityinflorida
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Ensemble ecological niche modeling of West Nile virus probability in Florida.

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