Tiger prowling: Distribution modelling for northward-expanding Aedes albopictus (Diptera: Culicidae) in Japan

The Asian tiger mosquito, Aedes albopictus , is a significant public health concern owing to its expanding habitat and vector competence. Disease outbreaks attributed to this species have been reported in areas under its invasion, and its northward expansion in Japan has caused concern because of th...

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Published inPloS one Vol. 19; no. 5; p. e0303137
Main Authors Yang, Chao, Futami, Kyoko, Nihei, Naoko, Fujita, Ryosuke, Ogino, Kazumasa, Hirabayashi, Kimio, Yonejima, Mayuko, Otsuka, Yasushi, Nakamura, Satoshi, Taira, Kensuke, Owhashi, Makoto, Motoki, Mitsugu, Hashimoto, Tomoyuki, Minagawa, Keiko, Kasai, Shinji, Higa, Yukiko
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 09.05.2024
Public Library of Science (PLoS)
Subjects
Aedes - physiology
Aedes - virology
Aedes albopictus
Animal Distribution
Animals
Anthropogenic factors
Aquatic insects
Biology and Life Sciences
Birth rate
Culicidae
Dengue - epidemiology
Dengue - transmission
Dengue fever
Disease control
Distribution
Earth Sciences
Ecology and Environmental Sciences
Ecosystem
Entomology
Habitats
Human influences
Human populations
Introduced species
Japan
Machine Learning
Medical research
Medicine and Health Sciences
Medicine, Experimental
Modelling
Models, Biological
Mosquito Vectors - virology
Mosquitoes
People and Places
Pest outbreaks
Predictions
Public health
Range extension
Social Sciences
Spatial data
Urban areas
Vector-borne diseases
Viral infections
Japan
Asia
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Abstract The Asian tiger mosquito, Aedes albopictus , is a significant public health concern owing to its expanding habitat and vector competence. Disease outbreaks attributed to this species have been reported in areas under its invasion, and its northward expansion in Japan has caused concern because of the potential for dengue virus infection in newly populated areas. Accurate prediction of Ae . albopictus distribution is crucial to prevent the spread of the disease. However, limited studies have focused on the prediction of Ae . albopictus distribution in Japan. Herein, we used the random forest model, a machine learning approach, to predict the current and potential future habitat ranges of Ae . albopictus in Japan. The model revealed that these mosquitoes prefer urban areas over forests in Japan on the current map. Under predictions for the future, the species will expand its range to the surrounding areas and eventually reach many areas of northeastern Kanto, Tohoku District, and Hokkaido, with a few variations in different scenarios. However, the affected human population is predicted to decrease owing to the declining birth rate. Anthropogenic and climatic factors contribute to range expansion, and urban size and population have profound impacts. This prediction map can guide responses to the introduction of this species in new areas, advance the spatial knowledge of diseases vectored by it, and mitigate the possible disease burden. To our knowledge, this is the first distribution-modelling prediction for Ae . albopictus with a focus on Japan.
AbstractList The Asian tiger mosquito, Aedes albopictus, is a significant public health concern owing to its expanding habitat and vector competence. Disease outbreaks attributed to this species have been reported in areas under its invasion, and its northward expansion in Japan has caused concern because of the potential for dengue virus infection in newly populated areas. Accurate prediction of Ae. albopictus distribution is crucial to prevent the spread of the disease. However, limited studies have focused on the prediction of Ae. albopictus distribution in Japan. Herein, we used the random forest model, a machine learning approach, to predict the current and potential future habitat ranges of Ae. albopictus in Japan. The model revealed that these mosquitoes prefer urban areas over forests in Japan on the current map. Under predictions for the future, the species will expand its range to the surrounding areas and eventually reach many areas of northeastern Kanto, Tohoku District, and Hokkaido, with a few variations in different scenarios. However, the affected human population is predicted to decrease owing to the declining birth rate. Anthropogenic and climatic factors contribute to range expansion, and urban size and population have profound impacts. This prediction map can guide responses to the introduction of this species in new areas, advance the spatial knowledge of diseases vectored by it, and mitigate the possible disease burden. To our knowledge, this is the first distribution-modelling prediction for Ae. albopictus with a focus on Japan.
The Asian tiger mosquito, Aedes albopictus, is a significant public health concern owing to its expanding habitat and vector competence. Disease outbreaks attributed to this species have been reported in areas under its invasion, and its northward expansion in Japan has caused concern because of the potential for dengue virus infection in newly populated areas. Accurate prediction of Ae. albopictus distribution is crucial to prevent the spread of the disease. However, limited studies have focused on the prediction of Ae. albopictus distribution in Japan. Herein, we used the random forest model, a machine learning approach, to predict the current and potential future habitat ranges of Ae. albopictus in Japan. The model revealed that these mosquitoes prefer urban areas over forests in Japan on the current map. Under predictions for the future, the species will expand its range to the surrounding areas and eventually reach many areas of northeastern Kanto, Tohoku District, and Hokkaido, with a few variations in different scenarios. However, the affected human population is predicted to decrease owing to the declining birth rate. Anthropogenic and climatic factors contribute to range expansion, and urban size and population have profound impacts. This prediction map can guide responses to the introduction of this species in new areas, advance the spatial knowledge of diseases vectored by it, and mitigate the possible disease burden. To our knowledge, this is the first distribution-modelling prediction for Ae. albopictus with a focus on Japan.The Asian tiger mosquito, Aedes albopictus, is a significant public health concern owing to its expanding habitat and vector competence. Disease outbreaks attributed to this species have been reported in areas under its invasion, and its northward expansion in Japan has caused concern because of the potential for dengue virus infection in newly populated areas. Accurate prediction of Ae. albopictus distribution is crucial to prevent the spread of the disease. However, limited studies have focused on the prediction of Ae. albopictus distribution in Japan. Herein, we used the random forest model, a machine learning approach, to predict the current and potential future habitat ranges of Ae. albopictus in Japan. The model revealed that these mosquitoes prefer urban areas over forests in Japan on the current map. Under predictions for the future, the species will expand its range to the surrounding areas and eventually reach many areas of northeastern Kanto, Tohoku District, and Hokkaido, with a few variations in different scenarios. However, the affected human population is predicted to decrease owing to the declining birth rate. Anthropogenic and climatic factors contribute to range expansion, and urban size and population have profound impacts. This prediction map can guide responses to the introduction of this species in new areas, advance the spatial knowledge of diseases vectored by it, and mitigate the possible disease burden. To our knowledge, this is the first distribution-modelling prediction for Ae. albopictus with a focus on Japan.
The Asian tiger mosquito, Aedes albopictus , is a significant public health concern owing to its expanding habitat and vector competence. Disease outbreaks attributed to this species have been reported in areas under its invasion, and its northward expansion in Japan has caused concern because of the potential for dengue virus infection in newly populated areas. Accurate prediction of Ae . albopictus distribution is crucial to prevent the spread of the disease. However, limited studies have focused on the prediction of Ae . albopictus distribution in Japan. Herein, we used the random forest model, a machine learning approach, to predict the current and potential future habitat ranges of Ae . albopictus in Japan. The model revealed that these mosquitoes prefer urban areas over forests in Japan on the current map. Under predictions for the future, the species will expand its range to the surrounding areas and eventually reach many areas of northeastern Kanto, Tohoku District, and Hokkaido, with a few variations in different scenarios. However, the affected human population is predicted to decrease owing to the declining birth rate. Anthropogenic and climatic factors contribute to range expansion, and urban size and population have profound impacts. This prediction map can guide responses to the introduction of this species in new areas, advance the spatial knowledge of diseases vectored by it, and mitigate the possible disease burden. To our knowledge, this is the first distribution-modelling prediction for Ae . albopictus with a focus on Japan.
Audience Academic
Author Nakamura, Satoshi
Hashimoto, Tomoyuki
Minagawa, Keiko
Futami, Kyoko
Otsuka, Yasushi
Motoki, Mitsugu
Kasai, Shinji
Higa, Yukiko
Fujita, Ryosuke
Yang, Chao
Hirabayashi, Kimio
Ogino, Kazumasa
Taira, Kensuke
Owhashi, Makoto
Nihei, Naoko
Yonejima, Mayuko
AuthorAffiliation 7 International Center for Island Studies, Kagoshima University, Kagoshima, Kagoshima, Japan
4 Department of Immunology and Parasitology, University of Occupational and Environmental Health, Kitakyushu, Fukuoka, Japan
1 Department of Medical Entomology, National Institute of Infectious Diseases, Shinjuku, Tokyo, Japan
10 Tokushima University, Tokushima, Tokushima, Japan
6 Faculty of Humanities and Social Sciences, Kumamoto University, Kumamoto, Kumamoto, Japan
8 Faculty of Nursing, Hiroshima Bunka Gakuen University, Kure, Hiroshima, Japan
12 Environmental Biology & Living Environment Department, Japan Environmental Sanitation Center, Kawasaki, Kanagawa, Japan
5 Institution of Textile Science and Technology, Academic Assembly, Shinshu University, Matsumoto, Nagano, Japan
University of Pécs: Pecsi Tudomanyegyetem, HUNGARY
11 Apex Pest Control Co. Ltd., Minato, Tokyo, Japan
2 Institute of Tropical Medicine, Nagasaki University, Nagasaki, Nagasaki, Japan
3 Laboratory of Sanitary Entomology, Faculty o
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/38722911$$D View this record in MEDLINE/PubMed
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Copyright Copyright: © 2024 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
COPYRIGHT 2024 Public Library of Science
2024 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
2024 Yang et al 2024 Yang et al
2024 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright_xml – notice: Copyright: © 2024 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
– notice: COPYRIGHT 2024 Public Library of Science
– notice: 2024 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
– notice: 2024 Yang et al 2024 Yang et al
– notice: 2024 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
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Snippet The Asian tiger mosquito, Aedes albopictus , is a significant public health concern owing to its expanding habitat and vector competence. Disease outbreaks...
The Asian tiger mosquito, Aedes albopictus, is a significant public health concern owing to its expanding habitat and vector competence. Disease outbreaks...
The Asian tiger mosquito, Aedes albopictus , is a significant public health concern owing to its expanding habitat and vector competence. Disease outbreaks...
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StartPage e0303137
SubjectTerms Aedes - physiology
Aedes - virology
Aedes albopictus
Animal Distribution
Animals
Anthropogenic factors
Aquatic insects
Biology and Life Sciences
Birth rate
Culicidae
Dengue - epidemiology
Dengue - transmission
Dengue fever
Disease control
Distribution
Earth Sciences
Ecology and Environmental Sciences
Ecosystem
Entomology
Habitats
Human influences
Human populations
Introduced species
Japan
Machine Learning
Medical research
Medicine and Health Sciences
Medicine, Experimental
Modelling
Models, Biological
Mosquito Vectors - virology
Mosquitoes
People and Places
Pest outbreaks
Predictions
Public health
Range extension
Social Sciences
Spatial data
Urban areas
Vector-borne diseases
Viral infections
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Title Tiger prowling: Distribution modelling for northward-expanding Aedes albopictus (Diptera: Culicidae) in Japan
URI https://www.ncbi.nlm.nih.gov/pubmed/38722911
https://www.proquest.com/docview/3069285029
https://www.proquest.com/docview/3053975086
https://pubmed.ncbi.nlm.nih.gov/PMC11081387
https://doaj.org/article/ba0e9a53d7d84a4c8b23d4aa834678b8
http://dx.doi.org/10.1371/journal.pone.0303137
Volume 19
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