Spatio-temporal distribution characteristics of Oncomelania hupensis snails spread in Suzhou City of Jiangsu Province from 2016 to 2023
10.16250/j.32.1915.2024155
- VernacularTitle:2016—2023年江苏省苏州市钉螺扩散时空分布特征
- Author:
Qianwen SHI
1
;
Ling’e SHEN
1
;
Jing ZHOU
1
;
Jingzhi WU
1
Author Information
1. Suzhou Center for Disease Prevention and Control, Suzhou, Jiangsu 215000, China
- Publication Type:Journal Article
- Keywords:
Schistosomiasis;
Oncomelania hupensis;
Spatial distribution;
Spatio-temporal clustering;
Spatial autocorrelation;
Spatio-temporal scan;
Suzhou City
- From:
Chinese Journal of Schistosomiasis Control
2024;36(6):577-583
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the Oncomelania hupensis snails spread and its spatio-temporal clustering characteristics in Suzhou City, Jiangsu Province from 2016 to 2023, so as to provide insights into precision control of O. hupensis snails in the City. Methods O. hupensis snail surveillance data in Suzhou City from 2016 to 2023 were collected, and the areas of O. hupensis snail spread and areas of emerging and re-emerging snail habitats were retrieved. The spatial distribution characteristics and clustering types and locations of environments with O. hupensis snail spread were investigated using global and local spatial auto correlation analyses with the software ArcGIS 10.7, and the clustering and cluster areas of O. hupensis snail spread were identified in Suzhou City using spatio-temporal scans with the software SaTScan 10.0.2. Results O. hupensis snail spread covered an area of 677 171 m2 in Suzhou City from 2016 to 2023, including 376 230 m2 emerging snail habitats and 300 941 m2 re-emerging snail habitats. Global spatial autocorrelation analysis showed overall clustering of O. hupensis snail spread in Suzhou City from 2016 to 2023 (Moran’s I = 0.066, P = 0.007), and there were spatial clustering of areas with O. hupensis snail spread in 2019 (Moran’s I = 0.086, P = 0.001) and 2021 (Moran’s I = 0.045, P = 0.003). Local spatial autocorrelation analysis showed clusters of O. hupensis snail spread in Suzhou City from 2016 to 2023, with high-high clusters in Guangfu Township and Dongzhu Street, and the high-high clusters of O. hupensis snail spread were mainly distributed in southwestern Suzhou City. Spatio-temporal scans identified two clusters of areas with O. hupensis snail spread and areas of re-emerging snail habitats in Suzhou City from 2016 to 2023, with large clustering areas found in Guangfu Township, Dongzhu Street, Tong’an Township and Wangting Township [relative risk (RR) = 22.34, log likelihood ratio (LLR) = 163 295.32, P < 0.001] and small clustering areas in Xukou Township, Mudu Township and Xiangshan Street (RR = 2.73, LLR = 921.92, P < 0.001). Conclusions There was spatial clustering of O. hupensis snail spread in Suzhou City from 2016 to 2023. Improved quality of O. hupensis snail control and intensified management of environments at a high risk of O. hupensis snail spread are recommended in Suzhou City.
