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

doi:10.12140/j.issn.1000-7423.2024.02.002

Abstract

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

CLC Number:

R531.3

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.

Figures/Tables 5

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References 24

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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)