scholarly journals Meteorological factors and risk of scrub typhus in Guangzhou, southern China, 2006–2012

2014 ◽  
Vol 14 (1) ◽  
Author(s):  
Tiegang Li ◽  
Zhicong Yang ◽  
Zhiqiang Dong ◽  
Ming Wang
2021 ◽  
Vol 8 ◽  
Author(s):  
Jianyun Lu ◽  
Yanhui Liu ◽  
Xiaowei Ma ◽  
Meixia Li ◽  
Zhicong Yang

Background: Scrub typhus was epidemic in the western Pacific Ocean area and East Asia, scrub typhus epidemic in densely populated areas in southern China. To better understand the association between meteorological variables, Southern Oscillation Index (SOI), and scrub typhus incidence in Guangzhou was benefit to the control and prevention.Methodology/Principal Findings: We collected weekly data for scrub typhus cases and meteorological variables in Guangzhou, and Southern Oscillation Index from 2006 to 2018, and used the distributed lag non-linear models to evaluate the relationships between meteorological variables, SOI and scrub typhus. The median value of each variable was set as the reference. The high-risk occupations were farmer (51.10%), house worker (17.51%), and retiree (6.29%). The non-linear relationships were observed with different lag weeks. For example, when the mean temperature was 27.7°C with1-week lag, the relative risk (RR) was highest as 1.08 (95% CI: 1.01–1.17). The risk was the highest when the relative humidity was 92.0% with 9-week lag, with the RR of 1.10 (95% CI: 1.02–1.19). For aggregate rainfall, the highest RR was 1.06 (95% CI: 1.03–1.11), when it was 83.0 mm with 4-week lag. When the SOI was 19 with 11-week lag, the highest RR was 1.06 (95% CI: 1.01–1.12). Most of the extreme effects of SOI and meteorological factors on scrub typical cases were statistically significant.Conclusion/Significance: The high-risk occupations of scrub typhus in Guangzhou were farmer, house worker, and retiree. Meteorological factors and SOI played an important role in scrub typhus occurrence in Guangzhou. Non-linear relationships were observed in almost all the variables in our study. Approximately, mean temperature, and relative humidity positively correlated to the incidence of scrub typhus, on the contrary to atmospheric pressure and weekly temperature range (WTR). Aggregate rainfall and wind velocity showed an inverse-U curve, whereas the SOI appeared the bimodal distribution. These findings can be helpful to facilitate the development of the early warning system to prevent the scrub typhus.


2019 ◽  
Vol 663 ◽  
pp. 227-235 ◽  
Author(s):  
Jian-yun Lu ◽  
Zong-qiu Chen ◽  
Yan-hui Liu ◽  
Wen-hui Liu ◽  
Yu Ma ◽  
...  

2015 ◽  
Vol 12 (7) ◽  
pp. 7254-7273 ◽  
Author(s):  
Jaewon Kwak ◽  
Soojun Kim ◽  
Gilho Kim ◽  
Vijay Singh ◽  
Seungjin Hong ◽  
...  

2019 ◽  
Vol 32 ◽  
pp. 101427 ◽  
Author(s):  
Jiangping Ren ◽  
Jimin Sun ◽  
Zhengting Wang ◽  
Feng Ling ◽  
Xuguang Shi ◽  
...  

2016 ◽  
Vol 145 (3) ◽  
pp. 462-470 ◽  
Author(s):  
J. SETO ◽  
Y. SUZUKI ◽  
R. NAKAO ◽  
K. OTANI ◽  
K. YAHAGI ◽  
...  

SUMMARYClimate change, by its influence on the ecology of vectors might affect the occurrence of vector-borne diseases. This study examines the effects of meteorological factors in Japan on the occurrence of scrub typhus, a mite-borne zoonosis caused byOrientia tsutsugamushi. Using negative binomial regression, we analysed the relationships between meteorological factors (including temperature, rainfall, snowfall) and spring–early summer cases of scrub typhus in Yamagata Prefecture, Japan, during 1984–2014. The average temperature in July and August of the previous year, cumulative rainfall in September of the previous year, snowfall throughout the winter, and maximum depth of snow cover in January and February were positively correlated with the number of scrub typhus cases. By contrast, cumulative rainfall in July of the previous year showed a negative relationship to the number of cases. These associations can be explained by the life-cycle ofLeptotrombidium pallidum, a predominant vector of spring–early summer cases of scrub typhus in northern Japan. Our findings show that several meteorological factors are useful to estimate the number of scrub typhus cases before the endemic period. They are applicable to establish an early warning system for scrub typhus in northern Japan.


2020 ◽  
Vol 70 (1) ◽  
pp. 37-50
Author(s):  
Qin Hong-Yu ◽  
Xin Xiu ◽  
Sha Wanli ◽  
Wang Ben ◽  
Hu Xiansheng ◽  
...  

AbstractSwine erysipelas (SE) is one of the best-known and most serious diseases that affect domestic pigs, which is caused by Erysipelothrix rhusiopathiae. It is endemic in Nanning and has been circulating for decades, causing considerable economic losses. The aim of this study was to investigate the effect of meteorological-related variations on the epidemiology of swine erysipelas in Nanning City, a subtropical city of China. Data on monthly counts of reported swine erysipelas and climate data in Nanning are provided by the authorities over the period from 2006 to 2015. Cross-correlation analysis was applied to identify the lag effects of meteorological variables. A zero-inflated negative binomial (ZINB) regression model was used to evaluate the independent contribution of meteorological factors to SE transmission. After controlling seasonality, autocorrelation and lag effects, the results of the model indicated that Southern Oscillation Index (SOI) has a positive effect on SE transmission. Moreover, there is a positive correlation between monthly mean maximum temperature and relative humidity at 0-1 month lag and the number of cases. Furthermore, there is a positive association between the number of SE incidences and precipitation, with a lagged effect of 2 months. In contrast, monthly mean wind velocity negatively correlated with SE of the current month. These findings indicate that meteorological variables may play a significant role in SE transmission in southern China. Finally, more public health actions should be taken to prevent and control the increase of SE disease with consideration of local weather variations.


2018 ◽  
Vol 12 (6) ◽  
pp. e0006604 ◽  
Author(s):  
Yuehong Wei ◽  
Yang Wang ◽  
Xiaoning Li ◽  
Pengzhe Qin ◽  
Ying Lu ◽  
...  

2018 ◽  
Vol 166 ◽  
pp. 577-587 ◽  
Author(s):  
Guoqi Yu ◽  
Rencong Yang ◽  
Dongmei Yu ◽  
Jiansheng Cai ◽  
Jiexia Tang ◽  
...  

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