| Background:Typhus group rickettsiosis(TGR)is an acute infectious disease caused by typhus group rickettsia,including epidemic typhus and endemic typhus,caused by Rickettsia prowazekii and Rickettsia typhi,respectively.In recent years,epidemic typhus has rarely been reported worldwide,while endemic typhus is widely distributed around the world.As a Class C notifiable disease in China,TGR cases are reported every year.However,related studies are limited to the analysis of epidemiological characteristics in local areas,and lack of researches on long-term and accurate understanding of TGR epidemic and the related risk factors.Therefore,the aims of this study included to explore the epidemiological characteristics and spatiotemporal patterns of TGR in mainland China,and to provide theoretical basis for TGR prevention and control;to understand the epidemiological characteristics of TGR and relevant meteorological factors in Xishuangbanna Dai autonomous prefecture-the hotspot of TGR in China,in order to provide theoretical basis for the prevention and control strategies and measures.Methods:Daily data of TGR cases from January 2005 to December 2017 were collected from the Chinese Information System for Diseases Control and Prevention.Contemporaneous meteorological data were collected from the China Meteorological Data Sharing Service System.Firstly,a descriptive analysis was used to describe the epidemiological and spatiotemporal characteristics by SPSS 20.0 and R 3.4.1 software,such as age,gender,occupation,seasonal and regional distribution.A spatial autocorrelation analysis and a spatiotemporal scan statistics were used to explore spatiotemporal clusters by ArcGIS 10.2.0 software and SaTScan 9.4.4 software.Then a descriptive analysis was used to explore and compare respective epidemiological characteristics of different regions in Xishuangbanna of Yunnan province,the hotspot of TGR cases.The distributed lag non-linear model(DLNM)was established to analyze the influence of meteorological factors on the TGR incidence in this region.Results:A total of 29211 TGR cases including 7 fatal cases,which were distributed throughout 29 provincial level administration divisions(PLADs)with 795 counties in China,were collected from 2005 to 2017.The annual incidence was the highest in 2015(0.2567/100000),and the lowest in 2017(0.0693/100000).Of all the cases,63.1%occurred from May to October and the male-to-female ratio was 0.97.The age range of the total cases was 0 to 96 years,and 88.4%of the cases occurred in individuals between 0 and 59 years.The occupation distribution showed a higher concentration in farmers and students.The results of the global spatial autocorrelation analysis indicated that there was significant spatial heterogeneity throughout China from 2005 to 2017.The results of the local spatial autocorrelation analysis indicated that the hotspots were not the same each year,and the primary hotspots were located in the southwestern,southern,and circum-Bohai Sea regions of China,including Yunnan,Guangdong,Guangxi,Liaoning,Shandong and Hebei.Eighteen spatiotemporal clusters were observed using Kulldorff s space-time scan statistic,and the primary cluster was located in Xishuangbanna of Yunnan province,including three counties,Jinghong city,Menghai county,and Mengla county.From 2005 to 2017,a total of 9129 cases were reported in Xishuangbanna.Before 2014,Menghai county was the region with the most severe endemic.Since 2015,more cases had been reported in Mengla county than the figure in Menghai county.The epidemiological characteristics of different regions were different.Most cases in Menghai county occurred from July to August,mainly female cases,20-49 years,and farmers.The cases in Mengla county had no obvious age and gender characteristics.The TGR incidence in Jinghong city was lower than the figures in the other two counties,and the epidemiological characteristics were significantly different.The incidence peaked in August.The age distribution was dominated by individuals aged less than 10 years,and the occupation distribution was highest among children living at home.A J-shaped nonlinear association between weekly mean temperature and TGR incidence was found.Taking the median value as the reference within 21 lag weeks,lower temperatures could decrease the risk of TGR incidence without lag effects,while higher temperatures could increase the risk of TGR incidence with long-term lag effects.We also found a reversed U-shaped nonlinear association between weekly mean precipitation and TGR incidence.Precipitation between 5mm and 13mm could increase the risk of TGR incidence.Taking the median value as the reference within 18 lag weeks,no precipitation and lower precipitation could decrease the risk of TGR incidence without lag effects,while higher precipitation could increase the risk of TGR incidence with long-term lag effectsConclusions:From 2005 to 2017,the number of TGR cases showed a decreasing trend,but the hotspots were widely distributed in China.The spatial distribution of TGR cases was significantly correlated,and the hotspots were different across different years,mainly distributed in southwestern,southern and circum-Bohai regions.The epidemiological characteristics of TGR cases were different in different counties of Xishuangbanna-the hotspots of TGR cases.Higher temperature and precipitation had long-term lag effects on TGR incidence. |
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