Spatial distribution characteristics and risk analysis of rodent density in Zhejiang province, 2021

doi:10.11853/j.issn.1003.8280.2022.04.006

Abstract

Abstract: Objective To investigate temporal and spatial distribution characteristics of rodent density and aggregation areas in Zhejiang province of China in 2021, and to provide a scientific basis for rodent control and deratization and the prevention and treatment of rodent-borne diseases. Methods Statistical description was performed for the data of rodent density monitoring in each county (city/district) from January to November 2021, and the global and local spatial autocorrelation analyses were used to analyze the spatial distribution characteristics of rodent density. Results From January to November in 2021, a total of 380 208 effective rat traps were placed and 1 851 rodents were captured, with a mean rodent density of 0.49 per 100 traps (snap, cages or plates). Rodent density showed an increasing trend from January to November (Z=3.913, P<0.001). Rodent density showed positive spatial autocorrelation within Zhejiang province, and there was a significant difference in Moran's I index among January, May, September, and November (all Z >1.96, P<0.05). The local spatial autocorrelation analysis showed that high-high aggregation areas were distributed in southern Zhejiang from January to November, which was consistent with the spatial distribution of the areas with high rodent density, and low-low aggregation areas were mainly distributed in northern and eastern Zhejiang. Conclusion The overall rodent density is at a relatively low level in Zhejiang province, but with a gradually increasing trend during the whole year of 2021. Rodent density in Zhejiang province shows geographical autocorrelation, and counties with a higher rodent density are mainly distributed in southern Zhejiang, and therefore, the risk of rodent-borne diseases should be concerned seriously in southern Zhejiang.

Key words: Rodent density, Seasonal variation, Spatial distribution characteristics, Spatial autocorrelation

摘要： 目的描述和分析浙江省2021年鼠密度的时空分布特征，分析全省鼠类聚集区，为防鼠灭鼠和鼠传疾病防控提供科学依据。方法对浙江省2021年1－11月各县（市、区）鼠密度监测数据进行统计描述，采用全局和局部空间自相关分析对鼠密度空间分布特征进行分析。结果浙江省2021年1－11月共布放有效鼠夹380 208个，捕鼠1 851只，全年鼠密度为0.49只/100夹（笼、板）。1－11月鼠密度呈升高趋势（Z=3.913，P<0.001）。鼠密度在全省范围内呈空间正相关，1、5、9和11月Moran’s I指数有统计学意义（均Z>1.96，P<0.05）；局部空间自相关分析结果显示，1－11月高-高聚集区均分布在浙南地区，与鼠密度较高地区空间分布一致；低-低聚集区主要分布在浙北、浙东地区。结论浙江省2021年整体鼠密度处于较低水平，但存在逐月升高趋势。浙江省鼠密度存在地理区域自相关性，鼠密度较高的县（市、区）主要集中分布在浙南地区，需要关注浙南地区的鼠传疾病发病风险。

关键词: 鼠密度, 季节消长, 空间分布特征, 空间自相关

CLC Number:

S443

LUO Ming-yu, WANG Jin-na, WU Yu-yan, LIU Qin-mei, LI Tian-qi, GONG Zhen-yu. Spatial distribution characteristics and risk analysis of rodent density in Zhejiang province, 2021[J]. Chinese Journal of Vector Biology and Control, 2022, 33(4): 475-479.

罗明宇, 王金娜, 吴瑜燕, 刘钦梅, 李天奇, 龚震宇. 浙江省2021年鼠类密度空间分布特征与风险分析[J]. 中国媒介生物学及控制杂志, 2022, 33(4): 475-479.

References

[1] 姜法春, 董礼艳, 郝毕, 等. 2011-2015年山东省青岛市肾综合征出血热与宿主动物相关性研究[J]. 中华地方病学杂志, 2017, 36(5):365-369. DOI:10.3760/cma.j.issn.2095-4255. 2017.05.013. Jiang FC, Dong LY, Hao B, et al. Correlation between host animal and hemorrhagic fever with renal syndrome in Qingdao city of Shandong province from 2011 to 2015[J]. Chin J Endemiol, 2017, 36(5):365-369. DOI:10.3760/cma.j.issn.2095-4255. 2017.05.013.(in Chinese)
[2] 牛艳芬, 康晓平, 闫东, 等. 河北省2001-2013年长爪沙鼠疫源地长爪沙鼠密度相关因素分析[J]. 中华流行病学杂志, 2016, 37(8):1108-1111. DOI:10.3760/cma.j.issn.0254-6450. 2016.08.011. Niu YF, Kang XP, Yan D, et al. Correlative factors related to the density of Meriones unguiculatus in the M. unguiculatus plague foci of Hebei province, 2001-2013[J]. Chin J Epidemiol, 2016, 37(8):1108-1111. DOI:10.3760/cma.j.issn.0254-6450. 2016.08.011.(in Chinese)
[3] 白雪薇, 陈永明, 牛艳芬, 等. 河北省鼠疫自然疫源地动物鼠疫流行分布特征分析[J]. 中国媒介生物学及控制杂志, 2021, 32(3):324-328. DOI:10.11853/j.issn.1003.8280.2021.03.013. Bai XW, Chen YM, Niu YF, et al. Distribution characteristics of plague epidemics in animals in natural plague foci of Hebei province, China[J]. Chin J Vector Biol Control, 2021, 32(3):324-328. DOI:10.11853/j.issn.1003.8280.2021.03.013.(in Chinese)
[4] Núñez-González S, Gault C, Simancas-Racines D. Spatial analysis of dengue, cysticercosis and Chagas disease mortality in Ecuador, 2011-2016[J]. Trans Roy Soc Trop Med Hyg, 2019, 113(1):44-47. DOI:10.1093/trstmh/try106.
[5] 宋宁娟, 谢昀, 丁晟, 等. 江西省2013-2018年肾综合征出血热空间自相关分析[J]. 中华疾病控制杂志, 2020, 24(8):876-880. DOI:10.16462/j.cnki.zhjbkz.2020.08.003. Song NJ, Xie Y, Ding S, et al. Analysis of spatial autocorrelation of hemorrhagic fever with renal syndrome in Jiangxi province from 2013 to 2018[J]. Chin J Dis Control Prev, 2020, 24(8):876-880. DOI:10.16462/j.cnki.zhjbkz.2020.08.003.(in Chinese)
[6] 中华人民共和国国家质量监督检验检疫总局, 中国国家标准化管理委员会. GB/T 23798-2009病媒生物密度监测方法鼠类[S]. 北京:中国标准出版社, 2009. General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China, Standardization Administration of China. GB/T 23798-2009 Surveillance methods for vector density-Rodent[S]. Beijing:Standards Press of China, 2009. (in Chinese)
[7] 吴建华, 郑艳娟, 虎明明, 等. 2015-2018年宁夏回族自治区银川市鼠疫自然疫源地监测结果分析[J]. 中华地方病学杂志, 2020, 39(6):416-419. DOI:10.3760/cma.j.cn231583-20190617-00172. Wu JH, Zheng YJ, Hu MM, et al. Analysis of monitoring results of plague natural foci in Yinchuan city, Ningxia from 2015 to 2018[J]. Chin J Endemiol, 2020, 39(6):416-419. DOI:10.3760/cma.j.cn231583-20190617-00172.(in Chinese)
[8] 王鼎盛, 席进孝, 格鹏飞, 等. 1962-2018年甘肃省黄鼠鼠疫自然疫源地鼠疫流行病学特征动态变化分析[J]. 中华地方病学杂志, 2020, 39(7):510-515. DOI:10.3760/cma.j.cn231583-20190813-00222. Wang DS, Xi JX, Ge PF, et al. Dynamics of plague epidemic in Spermophilus alaschanicus plague foci of Gansu province from 1962 to 2018[J]. Chin J Endemiol, 2020, 39(7):510-515. DOI:10.3760/cma.j.cn231583-20190813-00222.(in Chinese)
[9] 王宏祥, 李月喜, 李峰, 等. 2018年内蒙古自治区乌兰察布市鼠疫监测结果分析[J]. 中华地方病学杂志, 2019, 38(11):890-893. DOI:10.3760/cma.j.issn.2095-4255.2019.11.006. Wang HX, Li YX, Li F, et al. Analysis of monitoring results on plague in Ulanqab city of Inner Mongolia in 2018[J]. Chin J Endemiol, 2019, 38(11):890-893. DOI:10.3760/cma.j.issn.2095-4255.2019.11.006.(in Chinese)
[10] 刘菁, 陈阳, 林代华, 等. 福建省2016-2018年肾综合征出血热流行特征和宿主动物监测分析[J]. 中国媒介生物学及控制杂志, 2021, 32(3):329-333. DOI:10.11853/j.issn.1003.8280. 2021.03.014. Liu J, Chen Y, Lin DH, et al. Epidemiological characteristics and host animal monitoring of hemorrhagic fever with renal syndrome in Fujian province, China, 2016-2018[J]. Chin J Vector Biol Control, 2021, 32(3):329-333. DOI:10.11853/j.issn.1003.8280. 2021.03.014.(in Chinese)
[11] 涂涛田, 冯绍全, 何亚明, 等. 重庆市2018年国家级监测点鼠类监测结果分析[J]. 中国媒介生物学及控制杂志, 2019, 30(6):711-712. DOI:10.11853/j.issn.1003.8280.2019.06.028. Tu TT, Feng SQ, He YM, et al. An analysis of rodent surveillance results at national-level surveillance sites in Chongqing, China, 2018[J]. Chin J Vector Biol Control, 2019, 30(6):711-712. DOI:10.11853/j.issn.1003.8280.2019.06.028.(in Chinese)
[12] 吴瑜燕, 龚震宇, 侯娟, 等. 浙江省2011-2013年病媒生物监测结果分析[J]. 中国媒介生物学及控制杂志, 2015, 26(4):394-397. DOI:10.11853/j.issn.1003.4692.2015.04.017. Wu YY, Gong ZY, Hou J, et al. Analysis of vector surveillance from 2011 to 2013 in Zhejiang province, China[J]. Chin J Vector Biol Control, 2015, 26(4):394-397. DOI:10.11853/j.issn.1003. 4692.2015.04.017.(in Chinese)
[13] 李贵昌, 王玉姣, 鲁亮, 等. 2019年全国鼠类监测报告[J]. 中国媒介生物学及控制杂志, 2020, 31(4):389-394. DOI:10.11853/j.issn.1003.8280.2020.04.002. Li GC, Wang YJ, Lu L, et al. National surveillance report on rodents in China, 2019[J]. Chin J Vector Biol Control, 2020, 31(4):389-394. DOI:10.11853/j.issn.1003.8280.2020.04.002.(in Chinese)
[14] 顾骏强, 施能, 薛根元. 近40年浙江省降水量、雨日的气候变化[J]. 应用气象学报, 2002, 13(3):322-329. DOI:10.3969/j.issn.1001-7313.2002.03.007. Gu JQ, Shi N, Xue GY. Climatic variation of rainfall and wet days in Zhejiang[J]. J Appl Meteor Sci, 2002, 13(3):322-329. DOI:10.3969/j.issn.1001-7313.2002.03.007.(in Chinese)
[15] 王珂依, 刘园, 刘布春, 等. 1958-2015年长江中下游寒潮时空演变特征[J]. 自然资源学报, 2020, 35(12):3029-3038. DOI:10.31497/zrzyxb.20201217. Wang KY, Liu Y, Liu BC, et al. Spatio-temporal characteristics of cold wave in the middle and lower reaches of the Yangtze River between 1958 and 2015[J]. J Nat Res, 2020, 35(12):3029-3038. DOI:10.31497/zrzyxb.20201217.(in Chinese)
[16] 张蓉, 孙继民, 凌锋, 等. 基于SaTScan的浙江省2010-2014年肾综合征出血热疫情回顾性时空分析[J]. 中国媒介生物学及控制杂志, 2017, 28(3):244-247. DOI:10.11853/j.issn.1003. 8280.2017.03.012. Zhang R, Sun JM, Ling F, et al. Retrospective space-time scan (SaTScan) analysis on epidemic hemorrhagic fever with renal syndrome in Zhejiang province from 2010 to 2014[J]. Chin J Vector Biol Control, 2017, 28(3):244-247. DOI:10.11853/j.issn.1003.8280.2017.03.012.(in Chinese)
[17] 史军, 崔林丽, 田展, 等. 气温变化对华东居住建筑取暖和降温耗能的影响[J]. 自然资源学报, 2011, 26(3):460-467. DOI:10.11849/zrzyxb.2011.03.012. Shi J, Cui LL, Tian Z, et al. Impact of temperature change on heating and cooling energy consumption of residential buildings in east China[J]. J Nat Res, 2011, 26(3):460-467. DOI:10.11849/zrzyxb.2011.03.012.(in Chinese)
[18] 陈化新, 罗成旺. 中国肾综合征出血热监测[J]. 中华流行病学杂志, 2002, 23(1):63-66. DOI:10.3760/j.issn:0254-6450. 2002.01.018. Chen HX, Luo CW. Surveillance of hemorrhagic fever with renal syndrome in China[J]. Chin J Epidemiol, 2002, 23(1):63-66. DOI:10.3760/j.issn:0254-6450.2002.01.018.(in Chinese)
[19] 施旭光, 姜理平, 孙继民, 等. 浙江省钩端螺旋体病10年监测结果分析[J]. 浙江预防医学, 2016, 28(6):550-552, 556. DOI:10.19485/j.cnki.issn1007-0931.2016.06.003. Shi XG, Jiang LP, Sun JM, et al. An analysis on leptospirosis surveillance of ten years in Zhejiang province[J]. Zhejiang Prev Med, 2016, 28(6):550-552, 556. DOI:10.19485/j.cnki.issn 1007-0931.2016.06.003.(in Chinese)