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Attention Score in Context
| Title |
Epidemiological and spatiotemporal analysis of severe fever with thrombocytopenia syndrome in Eastern China, 2011–2021
|
|---|---|
| Published in |
BMC Public Health, March 2023
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| DOI | 10.1186/s12889-023-15379-3 |
| Pubmed ID | |
| Authors |
Shuyi Liang, Zhifeng Li, Nan Zhang, Xiaochen Wang, Yuanfang Qin, Wei Xie, Changjun Bao, Jianli Hu |
| Abstract |
Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease, which is caused by severe fever with thrombocytopenia syndrome virus (SFTSV) with high fatality. Recently, the incidence of SFTS increased obviously in Jiangsu Province. However, the systematic and complete analysis of spatiotemporal patterns and clusters coupled with epidemiological characteristics of SFTS have not been reported so far. Data on SFTS cases were collected during 2011-2021. The changing epidemiological characteristics of SFTS were analyzed by adopting descriptive statistical methods. GeoDa 1.18 was applied for spatial autocorrelation analysis, and SaTScan 10.0 was used to identify spatio-temporal clustering of cases. The results were visualized in ArcMap. The annual incidence of SFTS increased in Jiangsu Province from 2011 to 2021. Most cases (72.4%) occurred during May and August with the obvious peak months. Elderly farmers accounted for most cases, among which both males and females were susceptible. The spatial autocorrelation and spatio-temporal clustering analysis indicated that the distribution of SFTS was not random but clustered in space and time. The most likely cluster was observed in the western region of Jiangsu Province and covered one county (Xuyi county) (Relative risk = 8.18, Log likelihood ratio = 122.645, P < 0.001) located in southwestern Jiangsu Province from January 1, 2017 to December 31, 2021. The Secondary cluster also covered one county (Lishui county) (Relative risk = 7.70, Log likelihood ratio = 94.938, P < 0.001) from January 1, 2017 to December 31, 2021. The annual number of SFTS cases showed an increasing tendency in Jiangsu Province from 2011 to 2021. Our study elucidated regions with SFTS clusters by means of ArcGIS in combination with spatial analysis. The results demonstrated solid evidences for the orientation of limited sanitary resources, surveillance in high-risk regions and early warning of epidemic seasons in future prevention and control of SFTS in Jiangsu Province. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Lecturer | 1 | 50% |
| Unknown | 1 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 1 | 50% |
| Unknown | 1 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 March 2023.
All research outputs
#16,189,556
of 23,870,022 outputs
Outputs from BMC Public Health
#11,931
of 15,669 outputs
Outputs of similar age
#234,253
of 406,632 outputs
Outputs of similar age from BMC Public Health
#233
of 373 outputs
Altmetric has tracked 23,870,022 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 15,669 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.3. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 406,632 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 373 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.