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Accepted for/Published in: JMIR Public Health and Surveillance

Date Submitted: Jan 29, 2023
Open Peer Review Period: Jan 29, 2023 - Feb 12, 2023
Date Accepted: May 23, 2024
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Factors Associated With the Spatial Distribution of Severe Fever With Thrombocytopenia Syndrome in Zhejiang Province, China: Risk Analysis Based on Maximum Entropy

Tao M, Liu Y, Ling F, Ren J, Zhang R, Shi X, Guo S, Jiang J, Sun J Sr

Factors Associated With the Spatial Distribution of Severe Fever With Thrombocytopenia Syndrome in Zhejiang Province, China: Risk Analysis Based on Maximum Entropy

JMIR Public Health Surveill 2024;10:e46070

DOI: 10.2196/46070

PMID: 39104047

PMCID: 11310739

Factors Associated with the Spatial Distribution of Severe Fever with Thrombocytopenia Syndrome in Zhejiang Province, China: Risk Analysis based on Maximum Entropy

  • Mingyong Tao; 
  • Ying Liu; 
  • Feng Ling; 
  • Jiangping Ren; 
  • Rong Zhang; 
  • Xuguang Shi; 
  • Song Guo; 
  • Jianmin Jiang; 
  • Jimin Sun Sr

ABSTRACT

Background:

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease that was first identified in mainland China in 2009 and has been reported in Zhejiang Province, China since 2011. However, few studies focused on the association between ticks, host animals, and SFTS.

Objective:

To analyze the influence of meteorological and environmental factors as well as the influence of ticks and host animals on SFTS.

Methods:

Data on SFTS incidence, tick density, cattle density, meteorological and environmental factors were collected and analyzed using maximum entropy-based model.

Results:

We found that the density of ticks, precipitation of the wettest month, average temperature, elevation, and normalized difference vegetation index (NDVI) were significantly associated with SFTS spatial distribution. The niche model fitted accurately with good performance in predicting the potential risk areas of SFTS. The risk of SFTS occurrence increased with the increase of tick density, and the response curve indicated that the risk was greater than 0.5 when tick density exceeded 1.4. The risk of SFTS occurrence decreased with the increase of precipitation in the wettest month, and the risk was less than 0.5 when the precipitation exceeded 224.4 mm. The relationship between elevation and SFTS occurrence showed a reverse V shape and the risk peaked at approximately 400 m.

Conclusions:

Tick density, precipitation, and elevation were dominant influencing factors for SFTS and comprehensive intervention measures should be adjusted according to these factors to reduce SFTS incidence in Zhejiang Province.


 Citation

Please cite as:

Tao M, Liu Y, Ling F, Ren J, Zhang R, Shi X, Guo S, Jiang J, Sun J Sr

Factors Associated With the Spatial Distribution of Severe Fever With Thrombocytopenia Syndrome in Zhejiang Province, China: Risk Analysis Based on Maximum Entropy

JMIR Public Health Surveill 2024;10:e46070

DOI: 10.2196/46070

PMID: 39104047

PMCID: 11310739

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