Cargando…

Analysis of the spatial distribution of Aedes albopictus in an urban area of Shanghai, China

BACKGROUND: Aedes albopictus is a vector of major arboviral diseases and a primary pest in tropical and temperate regions of China. In most cities of China, the current monitoring system for the spread of Ae. albopictus is based on the subdistrict scale and does not consider spatial distribution for...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhou, Yibin, Liu, Hongxia, Leng, Peien, Zhu, Jiang, Yao, Shenjun, Zhu, Yiyi, Wu, Huanyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8474869/
https://www.ncbi.nlm.nih.gov/pubmed/34565466
http://dx.doi.org/10.1186/s13071-021-05022-8
_version_ 1784575316766752768
author Zhou, Yibin
Liu, Hongxia
Leng, Peien
Zhu, Jiang
Yao, Shenjun
Zhu, Yiyi
Wu, Huanyu
author_facet Zhou, Yibin
Liu, Hongxia
Leng, Peien
Zhu, Jiang
Yao, Shenjun
Zhu, Yiyi
Wu, Huanyu
author_sort Zhou, Yibin
collection PubMed
description BACKGROUND: Aedes albopictus is a vector of major arboviral diseases and a primary pest in tropical and temperate regions of China. In most cities of China, the current monitoring system for the spread of Ae. albopictus is based on the subdistrict scale and does not consider spatial distribution for analysis of species density. Thus, the system is not sufficiently accurate for epidemic investigations, especially in large cities. METHODS: This study used an improved surveillance program, with the mosquito oviposition trap (MOT) method, integrating the actual monitoring locations to investigate the temporal and spatial distribution of Ae. albopictus abundance in an urban area of Shanghai, China from 2018 to 2019. A total of 133 monitoring units were selected for surveillance of Ae. albopictus density in the study area, which was composed of 14 subdistricts. The vector abundance and spatial structure of Ae. albopictus were predicted using a binomial areal kriging model based on eight MOTs in each unit. Results were compared to the light trap (LT) method of the traditional monitoring scheme. RESULTS: A total of 8,192 MOTs were placed in the study area in 2018, and 7917 (96.6%) were retrieved, with a positive rate of 6.45%. In 2019, 22,715 (97.0%) of 23,408 MOTs were recovered, with a positive rate of 5.44%. Using the LT method, 273 (93.5%) and 312 (94.5%) adult female Ae. albopictus were gathered in 2018 and 2019, respectively. The Ae. albopictus populations increased slowly from May, reached a peak in July, and declined gradually from September. The MOT positivity index (MPI) showed significant positive spatial autocorrelation across the study area, whereas LT collections indicated a nonsignificant spatial autocorrelation. The MPI was suitable for spatial interpolation using the binomial areal kriging model and showed different hot spots in different years. CONCLUSIONS: The improved surveillance system integrated with a geographical information system (GIS) can improve our understanding of the spatial and temporal distribution of Ae. albopictus in urban areas and provide a practical method for decision-makers to implement vector control and mosquito management. GRAPHICAL ABSTRACT: [Image: see text]
format Online
Article
Text
id pubmed-8474869
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-84748692021-09-28 Analysis of the spatial distribution of Aedes albopictus in an urban area of Shanghai, China Zhou, Yibin Liu, Hongxia Leng, Peien Zhu, Jiang Yao, Shenjun Zhu, Yiyi Wu, Huanyu Parasit Vectors Research BACKGROUND: Aedes albopictus is a vector of major arboviral diseases and a primary pest in tropical and temperate regions of China. In most cities of China, the current monitoring system for the spread of Ae. albopictus is based on the subdistrict scale and does not consider spatial distribution for analysis of species density. Thus, the system is not sufficiently accurate for epidemic investigations, especially in large cities. METHODS: This study used an improved surveillance program, with the mosquito oviposition trap (MOT) method, integrating the actual monitoring locations to investigate the temporal and spatial distribution of Ae. albopictus abundance in an urban area of Shanghai, China from 2018 to 2019. A total of 133 monitoring units were selected for surveillance of Ae. albopictus density in the study area, which was composed of 14 subdistricts. The vector abundance and spatial structure of Ae. albopictus were predicted using a binomial areal kriging model based on eight MOTs in each unit. Results were compared to the light trap (LT) method of the traditional monitoring scheme. RESULTS: A total of 8,192 MOTs were placed in the study area in 2018, and 7917 (96.6%) were retrieved, with a positive rate of 6.45%. In 2019, 22,715 (97.0%) of 23,408 MOTs were recovered, with a positive rate of 5.44%. Using the LT method, 273 (93.5%) and 312 (94.5%) adult female Ae. albopictus were gathered in 2018 and 2019, respectively. The Ae. albopictus populations increased slowly from May, reached a peak in July, and declined gradually from September. The MOT positivity index (MPI) showed significant positive spatial autocorrelation across the study area, whereas LT collections indicated a nonsignificant spatial autocorrelation. The MPI was suitable for spatial interpolation using the binomial areal kriging model and showed different hot spots in different years. CONCLUSIONS: The improved surveillance system integrated with a geographical information system (GIS) can improve our understanding of the spatial and temporal distribution of Ae. albopictus in urban areas and provide a practical method for decision-makers to implement vector control and mosquito management. GRAPHICAL ABSTRACT: [Image: see text] BioMed Central 2021-09-26 /pmc/articles/PMC8474869/ /pubmed/34565466 http://dx.doi.org/10.1186/s13071-021-05022-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zhou, Yibin
Liu, Hongxia
Leng, Peien
Zhu, Jiang
Yao, Shenjun
Zhu, Yiyi
Wu, Huanyu
Analysis of the spatial distribution of Aedes albopictus in an urban area of Shanghai, China
title Analysis of the spatial distribution of Aedes albopictus in an urban area of Shanghai, China
title_full Analysis of the spatial distribution of Aedes albopictus in an urban area of Shanghai, China
title_fullStr Analysis of the spatial distribution of Aedes albopictus in an urban area of Shanghai, China
title_full_unstemmed Analysis of the spatial distribution of Aedes albopictus in an urban area of Shanghai, China
title_short Analysis of the spatial distribution of Aedes albopictus in an urban area of Shanghai, China
title_sort analysis of the spatial distribution of aedes albopictus in an urban area of shanghai, china
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8474869/
https://www.ncbi.nlm.nih.gov/pubmed/34565466
http://dx.doi.org/10.1186/s13071-021-05022-8
work_keys_str_mv AT zhouyibin analysisofthespatialdistributionofaedesalbopictusinanurbanareaofshanghaichina
AT liuhongxia analysisofthespatialdistributionofaedesalbopictusinanurbanareaofshanghaichina
AT lengpeien analysisofthespatialdistributionofaedesalbopictusinanurbanareaofshanghaichina
AT zhujiang analysisofthespatialdistributionofaedesalbopictusinanurbanareaofshanghaichina
AT yaoshenjun analysisofthespatialdistributionofaedesalbopictusinanurbanareaofshanghaichina
AT zhuyiyi analysisofthespatialdistributionofaedesalbopictusinanurbanareaofshanghaichina
AT wuhuanyu analysisofthespatialdistributionofaedesalbopictusinanurbanareaofshanghaichina