Abstract

Objective: To explore the spatio-temporal patterns and epidemic characteristics of imported dengue fever cases in six provinces (Yunnan, Guangxi, Guangdong, Hainan, Fujian and Zhejiang) of China from 2016 to 2018. Methods: In this study, we collected the surveillance data of imported dengue fever cases from 2016 to 2018 in six southern provinces of China. The risk intensity, spatio-temporal distribution and epidemiological characteristics of imported dengue fever cases in the six provinces were analyzed from the perspective of space, time and population. Results: Among the imported cases of dengue fever in China from other countries in the world, most of them were from Southeast Asia. In Zhejiang, Fujian and Guangdong provinces, there were greater number of imported cases with wide range of sources. While in Yunnan, Guangxi and Hainan provinces, the imported cases were almost from Southeast Asia. The incidence of imported dengue fever increased during the past three years, and the annual incidence peak was during August-November, but slight differences were observed among provinces. The age of the imported cases in Hainan[(37.0±19.6) years] was higher than that in southeastern coastal provinces[(36.0±11.7) years] and in southwestern provinces[(32.0±16.3) years]. The male-female ratio of the cases in southeastern coastal provinces (2.18∶1) were higher than those in southwestern provinces (1.04∶1) and Hainan (1.38∶1). The occupations of the cases were mainly workers and unemployed people in southeastern coastal provinces and farmers in southwestern provinces, but commercial personnel was the population with high incidence in both southeastern and southwestern provinces. Less imported dengue fever cases were reported in Hainan, the population distribution varied. Conclusions: There were differences in incidence pattern of imported dengue fever between southeastern coastal provinces and southwestern provinces as well as Hainan in China. Different prevention and control measures should be carried out in different areas to implement more precise prevention strategies.

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