Dataset Information

Epidemiological characteristics and temporal-spatial analysis of overseas imported dengue fever cases in outbreak provinces of China, 2005-2019.

ABSTRACT:

Background

Overseas imported dengue fever is an important factor in local outbreaks of this disease in the mainland of China. To better prevent and control such local outbreaks, the epidemiological characteristics and temporal-spatial distribution of overseas imported dengue fever cases in provincial-level administrative divisions (PLADs) where dengue fever is outbreak in the mainland of China were explored.

Methods

Using the Chinese National Notifiable Infectious Disease Reporting Information System (CNNDS), we identified overseas imported dengue fever cases in dengue fever outbreak areas in the mainland of China from 2005 to 2019 to draw the epidemic curve and population characteristic distribution of overseas imported cases in each PLAD. Based on spatial autocorrelation analysis of ArcGIS 10.5 and temporal-spatial scanning analysis of SaTScan 9.5, we analyzed the temporal-spatial distribution of overseas imported dengue fever in dengue fever outbreak areas in the mainland of China.

Results

A total of 11,407 imported cases, mainly from Southeast Asia, were recorded from 2005 to 2019 in these 13 PLADs. Of which 62.1% were imported into Yunnan and Guangdong Provinces. Among the imported cases, there were more males than females, mainly from the 21-50 age group. The hot spots were concentrated in parts of Yunnan, Guangdong and Fujian Provinces. We found the cluster of infected areas were expanding northward.

Conclusions

Based on the analysis of overseas imported dengue cases in 13 PLADs of the mainland of China from 2005 to 2019, we obtained the epidemiological characteristics and spatial distribution of imported dengue cases. Border controls need to pay attention to key population sectors, such as 21-50 years old men and education of key populations on dengue prevention. There is a need to improve the awareness of the prevention and control of imported cases in border areas. At the same time, northern regions cannot relax their vigilance.

SUBMITTER: Lun X

PROVIDER: S-EPMC8785556 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundDengue poses a large burden on the public health systems worldwide. severe dengue (SD) could lead to more serious clinical symptoms and even death. This study aimed to identify the cause of SD in a clinical trial during the dengue outbreak in Xishuangbanna in 2019, and could provide new insights into the pathogenic mechanisms of SD.MethodsMosquito-borne viral (DENV, JEV, and CHIKV) infections were identified. The epidemiological factors and clinical symptoms of inpatients in Xishuangbanna were recorded. The IgG and IgM levels in the serum of dengue inpatients were evaluated, and secondary infections were identified. Then, the structural proteins (C/PrM/E) were sequenced and compared with those of the same type of DENV in the same area as before, and their structures were predicted by the SWISS-MODEL (expasy.org). The full-length viral genomes were sequenced and aligned with representative strains by BioEidt or MEGA 5.0.ResultsIn this outbreak, the clinical symptoms were more serious in SD. The proportion of SD inpatients of male and Han nationality was larger than that of dengue fever (DF) inpatients (p < 0.05). DENV-2 infection was the majority in DF, with 45 inpatients. However, DENV-1 infection was the most common SD, with 54 inpatients. There were 3 DENV-3-positive inpatients in the DF group and 6 ZIKV-positive inpatients in the SD group. A secondary infection accounted for 76.47% (78 cases) of SD inpatients, but secondary infections were only in 20% (17 cases) of DF inpatients. In the three-dimensional structure of protein analysis, the C/PrM/E of DENV-1 and DENV-2 showed more stability than previous epidemic strains, while DENV-3 in 2019 showed a looser spatial structure. After a complete genome sequencing and analysis, all six DENV-2 strains belonged to cosmopolitan, five of which clustered into one branch. The GC/AT of the five strains decreased from 2014 to 2018. Compared with DF strains, SD strains had no mutations of commonness.ConclusionsSD may related to secondary heteromorphic dengue in Xishuangbanna in 2019. The coinfection of ZIKV could be another related factor for SD. The currently datas were very limited and only suggestive.