中国媒介生物学及控制杂志 ›› 2024, Vol. 35 ›› Issue (1): 32-35.DOI: 10.11853/j.issn.1003.8280.2024.01.006

• 媒介生物监测 • 上一篇    下一篇

南昌市2017-2022年鼠类种群密度与季节消长监测分析

付仁龙, 陈飞, 刘仰青, 陶卉英, 马红梅, 范义兵, 杨树   

  1. 传染病预防控制国家重点实验室研究基地, 江西省卫生健康新发传染病病原学诊断及基因组学重点实验室, 南昌市疾病预防控制中心, 江西 南昌 330038
  • 收稿日期:2023-09-14 出版日期:2024-02-20 发布日期:2024-03-05
  • 通讯作者: 范义兵,E-mail:fan_yibing@163.com;杨树,E-mail:younsoo@163.com
  • 作者简介:付仁龙,男,硕士,副主任技师,主要从事病媒生物控制工作,E-mail:18079167867@qq.com
  • 基金资助:
    南昌市医疗技术支撑计划一般项目(2020-KJZC-018)

Surveillance based characterization of rodent density and seasonal variation in Nanchang, Jiangxi Province, China, 2017-2022

FU Ren-long, CHEN Fei, LIU Yang-qing, TAO Hui-ying, MA Hong-mei, FAN Yi-bing, YANG Shu   

  1. The Collaboration Unit for Field Epidemiology of State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, Jiangxi 330038, China
  • Received:2023-09-14 Online:2024-02-20 Published:2024-03-05
  • Supported by:
    General Project of Nanchang Medical Technology Support Plan (No. 2020-KJZC-018)

摘要: 目的 了解南昌市鼠种构成、鼠密度、不同生境鼠密度变化及季节消长情况,为南昌市科学制定鼠类防控方案提供依据。方法 2017-2022年设置城镇居民区、农村自然村和特殊行业3种监测生境,采用夹夜法进行鼠密度监测,采用描述性统计方法分析南昌市3类不同生境的鼠种构成及鼠密度季节消长等。采用Excel 2021软件整理数据,SPSS 26.0软件用于分析南昌市3类不同生境的鼠种构成及鼠密度季节消长等。描述性方法对监测数据进行统计分析,不同年份和不同生境的鼠密度比较采用χ2检验。结果 2017-2022年南昌市共布放有效鼠夹104 121夹次,捕获鼠类548只,平均鼠密度为0.53%,6年间鼠密度差异有统计学意义(χ2=34.857,P<0.001)。总鼠密度、3种优势鼠种(褐家鼠、小家鼠和黄胸鼠)的全年密度以及城镇居民区和特殊行业生境的鼠密度均随季节变化呈双峰分布,而农村自然村生境的鼠密度呈单峰趋势,峰值在7月。不同生境鼠密度农村自然村(1.56%)>特殊行业(0.45%)>城镇居民区(0.30%)(χ2=304.340,P<0.001)。城镇居民区和农村自然村的优势鼠种为褐家鼠和黄胸鼠,小家鼠在特殊行业占优势(47.47%)。褐家鼠在特殊行业和农村自然村的构成比呈下降趋势,黄胸鼠在城镇居民区的构成比先升后降,而在特殊行业和农村自然村则总体呈上升趋势;小家鼠在3类不同生境的构成比总体均呈上升趋势。结论 2017-2022年南昌市不同年份间鼠密度差异较大,鼠密度随季节变化呈双峰分布,农村自然村鼠密度较高,应针对不同生境鼠种的变化采取针对性的防制措施以降低鼠密度及鼠源疾病风险。

关键词: 鼠类, 密度, 鼠种构成, 季节消长, 监测

Abstract: Objective To investigate the rodent species composition, density, and seasonality in different habitats based on the rodent surveillance program in Nanchang, China, so as to provide a basis for scientifically formulating rodent control strategies in Nanchang. Methods Three types of surveillance habitats including urban residential area, rural natural village, and special industry were chosen from 2017 to 2022. Rodent density was investigated by the night snap-trapping method. Descriptive methods were used to perform a statistical analysis of rodent species composition and seasonal variation of rodent density in three different habitats in Nanchang. With SPSS 26.0 and Excel 2021 softwares, descriptive methods were used to perform a statistical analysis of surveillance data, and the Chi-square test was used for comparison of rodent density across different years and habitats. Results A total of 104 121 effective traps were placed in Nanchang from 2017 to 2022, and 548 rodents were captured, with an average rodent density of 0.53%. The overall rodent density in the six years was statistically significant (χ2=34.857, P<0.001). A bimodal distribution with seasonal variation was found in the overall rodent density, the annual density of three dominant rodent species (Rattus norvegicus, Mus musculus, and R. tanezumi), and the rodent density in residential areas and special industry habitats, while the rodent density in rural natural village habitats showed a unimodal trend, with the peak in July. The rodent density in rural natural villages (1.56%) was significantly higher than that in special industries (0.45%) and than that in urban residential areas (0.30%) (χ2=304.340, P<0.001). The dominant rodent species in urban residential areas and rural natural village habitats were R. norvegicus and R. tanezumi, while M. musculus predominated in special industry habitats (47.47%). The composition ratio of R. norvegicus in special industry and rural natural village habitats was decreasing year by year; the composition ratio of R. tanezumi in urban residential areas showed a decrease after increasing, while it was generally increasing in special industry and rural natural village habitats; the composition ratio of M. musculus in three different habitats showed an overall increasing trend. Conclusions The rodent density varies greatly in Nanchang from 2017 to 2022. The rodent density showed a bimodal distribution with seasonal changes and was high in rural areas. Specific control measures should be taken according to the changes in rodent species in different habitats to reduce the rodent density and the risk of rodent-borne diseases.

Key words: Rodent, Density, Rodent species composition, Seasonal variation, Surveillance

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