2017—2022年山东省输入性疟疾流行病学特征

doi:10.12140/j.issn.1000-7423.2024.02.002

中国寄生虫学与寄生虫病杂志 ›› 2024, Vol. 42 ›› Issue (2): 140-146.doi: 10.12140/j.issn.1000-7423.2024.02.002

2017—2022年山东省输入性疟疾流行病学特征

许艳(), 王龙江, 孔祥礼, 李曰进, 卜灿灿, 闫歌, 张本光, 王用斌^*()

山东省寄生虫病防治研究所，山东第一医科大学（山东省医学科学院），济宁 272033

收稿日期:2023-11-01 修回日期:2023-12-22 出版日期:2024-04-30 发布日期:2024-04-18
通讯作者: * 王用斌（1979—），男，硕士，副研究员，从事寄生虫病防控与研究工作。E-mail：aveo226@163.com
作者简介:许艳（1986—），女，硕士，副研究员，从事寄生虫病防控与研究工作。E-mail：betty860927@126.com
基金资助:
山东省自然科学基金(ZR2019PH118);山东省医药卫生科技发展计划(202301050242);山东省医药卫生科技发展计划(202001050530);山东省医药卫生科技发展计划(202112050099);山东省医药卫生科技发展计划(202201050165)

Epidemiological characteristics of imported malaria in Shandong Province in 2017—2022

XU Yan(), WANG Longjiang, KONG Xiangli, LI Yuejin, BU Cancan, YAN Ge, ZHANG Benguang, WANG Yongbin^*()

Shandong Institute of Parasitic Diseases, Shandong First Medical University & Shandong Academy of Medical Sciences, Jining 272033, China

Received:2023-11-01 Revised:2023-12-22 Online:2024-04-30 Published:2024-04-18
Contact: * E-mail: aveo226@163.com
Supported by:
Natural Science Foundation of Shandong Province(ZR2019PH118);Shandong Provincial Medical and Health Science and Technology Development Program(202301050242);Shandong Provincial Medical and Health Science and Technology Development Program(202001050530);Shandong Provincial Medical and Health Science and Technology Development Program(202112050099);Shandong Provincial Medical and Health Science and Technology Development Program(202201050165)

摘要/Abstract

摘要：

目的了解2017—2022年山东省输入性疟疾流行病学特征，为进一步做好防止输入再传播工作提供科学依据。方法从中国疾病预防控制信息系统传染病报告信息管理系统和寄生虫病防治信息管理系统中收集2017—2022年山东省输入性疟疾疫情、病例流行病学个案调查等资料，建立数据库，采用SPSS 26.0软件对疟疾病例分类、感染来源、流行病学特征、病例诊治情况等进行统计分析，率的比较采用χ²检验，时间间隔分布的比较用非参数检验，利用SaTScan v10.1软件对疟疾病例的空间聚集性进行扫描分析，利用GraphPad Prism 8.3.0软件进行绘图。结果 2017—2022年，山东省共报告输入性疟疾820例，均为境外输入性病例。新冠疫情前（2017—2019年）、新冠疫情期间（2020—2022年）分别报告670例、150例。820例均为实验室确诊病例，恶性疟、卵形疟、间日疟、三日疟病例分别占69.5%（570/820）、19.0%（156/820）、7.3%（60/820）和4.1%（34/820），无混合感染和未分型病例。感染来源地以非洲为主（95.9%，786/820）。全省16个市均有病例报告，济宁、烟台、威海、青岛和济南5个市共报告511例，占62.3%（511/820）。空间扫描分析发现7个病例聚集区，其中威海环翠、烟台牟平等13个县（市、区）为一类聚集区（相对危险度 = 3.98，P < 0.01）。按报告地统计，全省共191例跨地区就诊病例，占23.3%（191/820）。全省18所疟疾救治定点医疗机构共报告本市就诊病例421例（55.3%，421/762）。患者发病到初诊、初诊到确诊时间间隔中位数分别为1、0 d。患者初诊单位为省级、市级、县级、县级以下医疗机构的分别占9.9%（81/820）、36.1%（296/820）、31.5%（258/820）和16.6%（136/820），疟疾诊断正确率分别为88.9%（72/81）、84.1%（249/296）、76.4%（197/258）和5.2%（7/136）；初诊单位为其他机构（疾控机构、检验检疫机构等）的占6.0%（49/820），诊断正确率为87.8%（43/49）。不同机构疟疾诊断正确率差异有统计学意义（χ² = 321.959，P < 0.01）。共报告重症疟疾74例，占9.0%（74/820），死亡病例5例。结论 2017—2022年，山东省输入性疟疾病例多、分布广，存在输入再传播的风险。

关键词: 疟疾, 流行病学特征, 空间聚集性, 跨地区就诊, 山东省

Abstract:

Objective To understand the epidemiological characteristics of imported malaria in Shandong Province and provide scientific basis for the prevention of re-transmission of imported malaria. Methods Data of the imported malaria epidemiological situation and case investigation in Shandong Province from 2017 to 2022 were collected from the Infectious Disease Reporting Information Management System and the Parasitic Disease Prevention and Control Information Management System of China Disease Prevention and Control Information System. A database for analysis was established. SPSS 26.0 software was use to analyze the case classification, source of infection, epidemiological characteristics, and the diagnosis and treatment records of the malaria cases. The χ² test was used to compare the rates, and the nonparametric test was used to compare the time interval distribution. The spatial clustering of malaria cases was analyzed by scanning with SaTScan v10.1 software. Figures were generated using GraphPad Prism 8.3.0 software. Results From 2017 to 2022, a total of 820 imported malaria cases were reported in Shandong Province, all of which were imported from abroad. A total of 670 cases were reported before the corona virus disease 2019 （COVID-19） pandemic and 150 cases during the COVID-19 pandemic. All the 820 cases were laboratory-diagnosed. falciparum malaria, ovale malaria,vivax malaria and malariae malaria accounted for 69.5% (570/820), 19.0% (156/820), 7.3% (60/820) and 4.1% (34/820), respectively. There were no mixed infections and unclassified cases. The main source of the infections was Africa (95.9%, 786/820). All 16 cities in Shandong Province had cases reported, while 511 cases were reported in five cities, including Jining, Yantai, Weihai, Qingdao and Jinan, accounting for 62.3% (511/820). Spatial scanning analysis found 7 case clusters, among which 13 counties, such as Huancui in Weihai and Muping in Yantai were the primary clusters (relative risk = 3.98, P < 0.01). According to the city where the case was reported, 191 cases had been treated in a different region within the province, accounting for 23.3% (191/820). A total of 421 local cases (55.3%, 421/762) were reported by 18 medical facilities designated for malaria treatment in the province. The median time interval from onset of symptoms to initial diagnosis and from initial diagnosis to final diagnosis was 1 and 0 days, respectively. The proportion of patients who were initially diagnosed in the provincial, municipal, county, and below-county medical facilities was 9.9% (81/820), 36.1% (296/820), 31.5% (258/820) and 16.6% (136/820), respectively. The malaria diagnosis accuracy was 88.9% (72/81), 84.1% (249/296), 76.4% (197/258) and 5.2% (7/136), respectively, with 6.0% (49/820) of the patients initially diagnosed in other institutions, such as centres for disease control, inspection and quarantine organizations, and the malaria diagnosis accuracy was 87.8% (43/49). There was a significant difference in the malaria diagnosis accuracy in different institutions (χ² = 321.959, P < 0.01). A total of 74 severe malaria cases were reported, accounting for 9.0% (74/820), and 5 cases decesed. Conclusion There are high number of imported malaria cases in Shandong Province, which are widely distributed. The risk of re-transmission exists.

Key words: Malaria, Epidemiological characteristics, Spatial clustering, Cross-regional medical treatment, Shandong Province

中图分类号:

R531.3

许艳, 王龙江, 孔祥礼, 李曰进, 卜灿灿, 闫歌, 张本光, 王用斌. 2017—2022年山东省输入性疟疾流行病学特征[J]. 中国寄生虫学与寄生虫病杂志, 2024, 42(2): 140-146.

XU Yan, WANG Longjiang, KONG Xiangli, LI Yuejin, BU Cancan, YAN Ge, ZHANG Benguang, WANG Yongbin. Epidemiological characteristics of imported malaria in Shandong Province in 2017—2022[J]. Chinese Journal of Parasitology and Parasitic Diseases, 2024, 42(2): 140-146.

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年份 Year	恶性疟 Falciparum malaria		间日疟 Vivax malaria		卵形疟 Ovale malaria		三日疟 Malariae malaria		合计 Total
年份 Year	病例数/例 No. case/case	构成比/% Constituent ratio/%	病例数/例 No. case/casee	构成比/% Constituent ratio/%	病例数/例 No. case/case	构成比/% Constituent ratio/%	病例数/例 No. case/case	构成比/% Constituent ratio/%	病例数/例 No. case/case	构成比/% Constituent ratio/%
2017	155	74.2	17	8.1	31	14.8	6	2.9	209	100
2018	175	75.1	7	3.0	44	18.9	7	3.0	233	100
2019	167	73.2	15	6.6	35	15.4	11	4.8	228	100
2020	48	64.0	9	12.0	17	22.7	1	1.3	75	100
2021	9	27.3	6	18.2	16	48.5	2	6.1	33	100
2022	16	38.1	6	14.3	13	31.0	7	16.7	42	100
合计 Total	570	69.5	60	7.3	156	19.0	34	4.1	820	100

聚集序列 Cluster sequence	聚集区分类 Cluster classification	主要包含县（市、区） Covering counties (City, District)	对数似然比 Log likelihood ratio	相对危险度 Relative risk	P值 P value
1	一类聚集区 Primary	威海的环翠、文登、荣成、乳山，烟台的牟平、莱山、芝罘、福山、海阳、栖霞、蓬莱、莱阳、长岛 Huancui, Wendeng, Rongcheng and Rushan in Weihai; Muping, Laishan, Zhifu, Fushan, Haiyang, Qixia, Penglai, Laiyang and Changdao in Yantai	97.07	3.98	< 0.01
2	二类聚集区A Secondary A	泰安的岱岳、泰山、肥城 Daiyue, Taishan and Feichang in Tai’an	59.38	59.38	< 0.01
3	二类聚集区B Secondary B	威海的环翠、文登、荣成；烟台的牟平、莱山 Huancui, Wendeng and Rongcheng in Weihai; Muping and Laishan in Yantai	49.95	4.03	< 0.01
4	二类聚集区C Secondary C	烟台的栖霞、福山、蓬莱、招远、芝罘 Qixia, Fushan, Penglai, Zhaoyuan and Zhifu in Yantai	30.55	3.46	< 0.01
5	二类聚集区D Secondary D	德州的德城 Decheng in Dezhou	22.92	5.13	< 0.01
6	二类聚集区E Secondary E	济宁的嘉祥 Jiaxiang in Jining	14.76	3.81	< 0.01
7	二类聚集区F Secondary F	烟台的海阳、莱阳、莱州 Haiyang, Laiyang and Laizhou in Yantai	8.89	2.27	< 0.05

市City	按报告地统计 Statistics according to the report city		按现住地统计 Statistics according to the present address
市City	病例数/例 No. case/case	外地就诊病例数（占比/%） No. case of cross-regional treatment (Ratio/%)	病例数/例 No. case/case	外地就诊病例数（占比/%） No. case of cross-regional treatment (Ratio/%)	定点医疗机构报告本市就诊病例数（占比/%） No. case of local treatment reported by designated medical institutions (Ratio/%)
济南 Jinan	80	39 (48.8)	42	1 (2.4)	35 (83.3)
青岛 Qingdao	81	19 (23.5)	65	3 (4.6)	58 (89.2)
淄博 Zibo	19	2 (2/19)	21	4 (19.0)	10 (47.6)
枣庄 Zaozhuang	5	0 (0)	11	6 (6/11)	3 (3/11)
东营 Dongying	11	0 (0)	13	2 (2/13)	9 (9/13)
烟台 Yantai	101	4 (4.0)	101	4 (4.0)	75 (74.3)
潍坊 Weifang	27	1 (3.7)	41	15 (36.6)	14 (34.1)
济宁 Jining	163	80 (49.1)	86	3 (3.5)	79 (91.9)
泰安 Tai’an	73	0 (0)	102	29 (28.4)	35 (34.3)
威海 Weihai	86	4 (4.7)	84	2 (2.4)	33 (39.3)
日照 Rizhao	29	1 (3.4)	34	6 (17.6)	9 (26.5)
临沂 Linyi	58	3 (5.2)	78	23 (29.5)	25 (32.1)
德州 Dezhou	68	36 (52.9)	36	4 (11.1)	32 (88.9)
聊城 Liaocheng	4	0 (0)	10	6 (6/10)	3 (3/10)
滨州 Binzhou	3	2 (2/3)	2	1 (1/2)	1 (1/2)
菏泽 Heze	12	0 (0)	36	24 (66.7)	0 (0)
合计 Total	820	191 (23.3)	762	133 (17.5)	421 (55.2)

2017—2022年山东省输入性疟疾流行病学特征

Epidemiological characteristics of imported malaria in Shandong Province in 2017—2022

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