Evidence map›Paper›PMID 34565466›Full record

ArticleParasites & vectors2021

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

Yibin Zhou, Hongxia Liu, Peien Leng, Jiang Zhu, Shenjun Yao, Yiyi Zhu, Huanyu Wu

Abstract read
In one paragraph

Article in Parasites & vectors, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Review
  4. Article
  5. Insects · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yibin Zhou *Department of Infectious Disease Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, 200336, China.
Hongxia Liu *Department of Infectious Disease Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, 200336, China.
Peien LengDepartment of Infectious Disease Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, 200336, China.
Jiang ZhuDepartment of Infectious Disease Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, 200336, China.
Shenjun YaoKey Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai, 200241, China.
Yiyi ZhuDepartment of Infectious Disease Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, 200336, China. zhuyiyi@scdc.sh.cn.ORCID http://orcid.org/0000-0001-9004-3685
Huanyu WuDepartment of Infectious Disease Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, 200336, China. wuhuanyu@scdc.sh.cn.

Funding

Shanghai Municipal Health Commission 201904350
6 · The paper itself

Abstract

backgroundAedes 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.

methodsThis 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.

resultsA 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.

conclusionsThe 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.

Indexed as

Animal DistributionAedesAnimalsChinaCitiesFemaleGeographic Information SystemsMaleMosquito VectorsOvipositionPopulation DensitySeasonsSpatial AnalysisAedes albopictusBinomial areal kriging modelMosquito oviposition trapSpatial distribution

Identifiers

PMID34565466
PMCPMC8474869

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.