Impacts of meteorological factors on the risk of scrub typhus in China, from 2006 to 2020: A multicenter retrospective study

被引:5
|
作者
Han, Ling [1 ]
Sun, Zhaobin [2 ,3 ]
Li, Ziming [2 ]
Zhang, Yunfei [1 ]
Tong, Shilu [4 ,5 ,6 ,7 ]
Qin, Tian [1 ]
机构
[1] Natl Inst Communicable Dis Control & Prevent, Chinese Ctr Dis Control & Prevent, State Key Lab Infect Dis Prevent & Control, Beijing, Peoples R China
[2] China Meteorol Adm, Inst Urban Meteorol, Beijing, Peoples R China
[3] China Meteorol Adm Urban Meteorol Key Lab, Beijing, Peoples R China
[4] Shanghai Jiao Tong Univ, Shanghai Childrens Med Ctr, Sch Med, Shanghai, Peoples R China
[5] Anhui Med Univ, Inst Environm & Populat Hlth, Sch Publ Hlth, Hefei, Peoples R China
[6] Nanjing Med Univ, Ctr Global Hlth, Nanjing, Peoples R China
[7] Queensland Univ Technol, Sch Publ Hlth & Social Work, Brisbane, Qld, Australia
基金
中国国家自然科学基金;
关键词
scrub typhus; rickettsiosis; vector-borne diseases; climatic factors; risk window; regional heterogeneity; CLIMATE-CHANGE; INFECTIOUS-DISEASES; JAPAN;
D O I
10.3389/fmicb.2023.1118001
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Scrub typhus is emerging as a global public health threat owing to its increased prevalence and remarkable geographic expansion. However, it remains a neglected disease, and possible influences of meteorological factors on its risk are poorly understood. We conducted the largest-scale research to assess the impact of meteorological factors on scrub typhus in China. Weekly data on scrub typhus cases and meteorological factors were collected across 59 prefecture-level administrative regions from 2006 to 2020. First, we divided these regions into 3 regions and analyzed the epidemiological characteristics of scrub typhus. We then applied the distributed lag nonlinear model, combined with multivariate meta-analysis, to examine the associations between meteorological factors and scrub typhus incidence at the total and regional levels. Subsequently, we identified the critical meteorological predictors of scrub typhus incidence and extracted climate risk windows. We observed distinct epidemiological characteristics across regions, featuring obvious clustering in the East and Southwest with more even distribution and longer epidemic duration in the South. The mean temperature and relative humidity had profound effects on scrub typhus with initial-elevated-descendent patterns. Weather conditions of weekly mean temperatures of 25-33 degrees C and weekly relative humidity of 60-95% were risk windows for scrub typhus. Additionally, the heavy rainfall was associated with sharp increase in scrub typhus incidence. We identified specific climatic signals to detect the epidemic of scrub typhus, which were easily monitored to generalize. Regional heterogeneity should be considered for targeted monitoring and disease control strategies.
引用
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页数:9
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