1.Spatial temporal distribution of mumps in Gansu, 2009-2013
Dongpeng LIU ; Lei MENG ; Faxiang GOU ; Kongfu WEI ; Xiaoting YANG ; Xinfeng LIU
Chinese Journal of Epidemiology 2015;36(11):1258-1262
Objective To detect the spatial temporal distribution of mumps in Gansu by means of spatial statistics.Methods The county-based incidence of mumps from 2009 to 2013 was used to calculate the global Moran' s I and local G statistics, and analyze its spatial temporal distribution characteristics.Results The incidence of mumps in Gansu were spatial auto-correlated from 2009 to 2013 respectively (P<0.001), and the hot spots were mainly distributed in Hexi area,while the cold spots were distributed in Tianshui, Longnan and Qingyang.Spatial temporal analysis showed that the high incidence of mumps was most likely to be detect in Hexi area (RR=3.05, LLR=4 670.995, P<0.001), and the low incidence was most likely to be detect in Longdong area (RR=0.36,LLR=1 980.686,P<0.001).Conclusion The spatial and spatial temporal clustering of mumps existed in Gansu from 2009 to 2013, the results can be used in the development of mumps prevention and control measure in Gansu.
2. Spatial distribution of Brucellosis in Gansu province, 2013-2018
Kongfu WEI ; Hong ZHANG ; Jian HE ; Faxiang GOU ; Yao CHENG ; Xinfeng LIU
Chinese Journal of Epidemiology 2019;40(9):1099-1105
Objective:
To analyze the spatial distribution and both hot and cold spots of incidence on Brucellosis in Gansu province from 2013 to 2018.
Methods:
Based on data from the Infectious Disease Reporting Information System in China, data related to space-time distribution and both hot and cold spots of Brucellosis in Gansu province from 2013 to 2018 were analyzed, by using the ArcGIS 10.5 software and GeoDa 1.6 software.
Results:
The trend surface analysis showed that the incidence of Brucellosis decreased gradually from the northern to southern parts with slightly higher in the west than in the east of Gansu. Global spatial autocorrelation analysis showed that the Moran’s
3. Epidemiological and spatial-temporal distribution of several natural focus diseases in Gansu province, 2014-2018
Kongfu WEI ; Hong ZHANG ; Jian HE ; Deshan YU ; Xiaoting YANG ; Zhongyi JIANG ; Faxiang GOU ; Yao CHENG ; Haixia LIU ; Yunhe ZHENG ; Xiaojuan JIANG ; Xinfeng LIU
Chinese Journal of Epidemiology 2019;40(8):947-952
Objective:
To analyze the epidemiological and spatial-temporal distribution of Brucellosis, epidemic encephalitis B and hemorrhagic fever with renal syndrome (HFRS) in Gansu province during 2014-2018 so as to provide evidence for the prevention and control of those diseases.
Methods:
A database was established in Gansu province from 2014 to 2018, using the geographical information system. A spatial distribution map was drawn, with trend analysis and space-time clustering used to study the 3-dimention of the diseases, by using both ArcGIS 10.5 and SaTScan 9.6 softwares.
Results:
Results from the trend surface analysis showed that the incidence of Brucellosis decreased gradually from north to south parts while the U type curve could reflect the distribution from the east to the west areas. Incidence of epidemic encephalitis B decreased significantly from south to north areas in the province, with incidence higher in the eastern than in the mid-west region. Difference on the incidence of HFRS was not significantly visible in the eastern and western regions, while the incidence was slightly higher in the southern than the northern parts of the province. Spatial and space-time clustering did exist among the 3 diseases in Gansu from 2014 to 2018. The areas with clusters of Brucellosis appeared in the eastern parts during 2014-2015, including 19 counties. The areas with secondary clusters of Brucellosis were seen in the Hexi district, including 4 counties, during 2017-2018. The areas with high incidence of epidemic encephalitis B were clustered in the middle and southeast areas, including 32 counties, during 2017-2018. Areas with most clusters of HFRS appeared in Min county of Dingxi city in 2018, with the areas of secondary clusters in 8 counties of the eastern areas in 2018.
Conclusions
The overall incidence rates of the 3 natural focus diseases were in a upward trend and showing obvious characteristics on spatial clustering. According to the distributive characteristics, effective measures should be developed accordingly.
4.Spatial-temporal specific incidence of pulmonary tuberculosis in Gansu, 2009-2013.
Xinfeng LIU ; Faxiang GOU ; Xiaowei REN ; Dongpeng LIU ; Yunhe ZHENG ; Kongfu WEI ; Haixia LIU ; Juansheng LI ; Email: LIJSH@LZU.EDU.CN. ; Lei MENG ; Email: CCDCUSC101@163.COM.
Chinese Journal of Epidemiology 2015;36(5):465-469
OBJECTIVETo understand the spatial-temporal specific incidence of pulmonary tuberculosis (TB) in Gansu.
METHODSThe county-based incidence of pulmonary TB in Gansu from 2009 to 2013 was used to calculate Moran's I and G statistics, and analyze the spatial-temporal distribution of areas with different pulmonary TB incidences.
RESULTSThe spatial correlation in incidence of pulmonary TB was found in Gansu from 2009 to 2013 (P<0.001), and the hot spot areas were mainly in Hexi area, Linxia, part of Dingxi, while the cold spot areas were in Lanzhou, part of Dingxi, Tianshui, Pingliang and Qingyang. Spatial-temporal analysis showed that the clustering of high pulmonary TB incidence areas were most likely in the Hexi area during 2009-2010 (LLR=3,031.10, RR=2.27, P<0.001), and the clustering of low pulmonary TB incidence areas were most likely in Lanzhou during 2011-2013 (LLR=1,545.52, RR=0.37, P<0.001).
CONCLUSIONThe analysis on spatial and spatial-temporal specific incidences of pulmonary TB in Gansu from 2009 to 2013 indicated that Hexi area is the key area in pulmonary TB prevention and control in Gansu.
Biometry ; China ; epidemiology ; Cluster Analysis ; Humans ; Incidence ; Spatio-Temporal Analysis ; Tuberculosis, Pulmonary ; epidemiology
5.Time-space study on viral hepatitis C in Gansu province, from 2009 to 2013.
Xiaojuan JIANG ; Lei MENG ; Xinfeng LIU ; Email: LXF606@126.COM. ; Dongpeng LIU ; Faxiang GOU ; Kongfu WEI ; Zhiping LI ; Yao CHENG
Chinese Journal of Epidemiology 2015;36(8):867-870
OBJECTIVETo study the time-space distribution of viral hepatitis C in Gansu province during 2009-2013, using the time-space statistics.
METHODSUsing Geoda to analysis the univariate Moran's I and univariate local Moran's I while using SaTScan to detect the time-space gathering areas.
RESULTSThere was spatial autocorrelation on incidence of hepatitis C noticed in Gansu during 2009-2013. The hot spots areas were counties as Jinchang, Wuwei, Zhangye and Lanzhou. Cold spot areas would include counties as Dingxi, Longnan, Pingliang, Gannan, Jiuquan, Qingyang, Baiyin and Tianshui. There were time-space gathering areas nitoced, during 2009-2010. Qinzhou and Maiji counties belonged to high incidence gathering areas. Lintao and Linxia were of low incidence gathering areas. In 2011-2013, high incidence gathering area would include counties as Zhangye, Jinchang, Wuwei Lanzhou and Baiyin while low incidence gathering areas would include counties as Dingxi, Tianshui, Pingliang, Longnan and Qingyang.
CONCLUSIONThere appeared time-space gathering of hepatitis C in Gansu province during 2009-2013. High and low gathering areas varied with time and high incidence gathering area mainly distributed in the western and central areas of Gansu province.
China ; epidemiology ; Hepatitis C ; epidemiology ; Humans ; Incidence ; Spatio-Temporal Analysis
6.Spatial-temporal distribution of hepatitis B in Gansu province, 2009-2014.
Faxiang GOU ; Xinfeng LIU ; Dongpeng LIU ; Xiaowei REN ; Juansheng LI ; Haixia LIU ; Yunhe ZHENG ; Kongfu WEI ; Xiaoting YANG ; Yao CHENG ; Lei MENG
Chinese Journal of Epidemiology 2016;37(1):85-89
OBJECTIVETo understand the hot/cold spots and the spatial-temporal clustering of hepatitis B in Gansu province during 2009-2014 by using spatial statistics, and provide scientific evidence for the prevention and control of hepatitis B.
METHODSThe spatial hot/cold spots and its trend, and the time frame and areas of its spatial-temporal clustering of hepatitis B in Gansu were analyzed by using the county specific incidence of hepatitis B from 2009 to 2014 and spatial statistical software GeoDa and SatScan.
RESULTSThe incidences of hepatitis B from 2009 to 2014 in Gansu were spatial autocorrelated respectively. Local G scan statistics indicated that the number of hot spots was in decline in Hexi area, while the hot spots was in increase in Linxia Hui autonomous prefecture and Gannan Tibetan autonomous prefecture. There was no obvious pattern in cold spots. Temporal-spatial scan statistics showed that the areas with high hepatitis B incidence most likely clustered in Hexi area during 2009-2011, and the areas with low hepatitis B incidence most likely clustered in eastern Gansu during 2012-2014.
CONCLUSIONSThe spatial and temporal clustering of hepatitis B was observed in Gansu from 2009 to 2014. The number of hot spots in Hexi area was in decline, while the numbers of hot spots in Linxia and Gannan were in increase, suggesting that the hepatitis B control and prevention in these areas should be strengthened.
China ; epidemiology ; Cluster Analysis ; Epidemiological Monitoring ; Hepatitis B ; epidemiology ; Humans ; Incidence ; Software ; Spatio-Temporal Analysis