1. 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
2.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.
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.Analysis on the characteristics of natural foci of hemorrhagic fever with renal syndrome in Gansu Province, 2012-2022
Kongfu WEI ; Xinfeng LIU ; Faxiang GOU ; Xuxia WANG ; Zhongyi JIANG ; Zhiping LI ; Xiaoshu ZHANG
Chinese Journal of Epidemiology 2024;45(1):117-122
Objective:To explore the characteristics of natural foci of hemorrhagic fever with renal syndrome (HFRS) in Gansu Province.Methods:The information of HFRS case data and rodent density monitoring data from 2012 to 2022 in Gansu Province were collected and epidemiological methods were used to analyze and investigate the characteristics of the epidemic focus.Results:A total of 869 cases of HFRS were reported, and four patients died from 2012 to 2022. The annual incidence rate is between 0.05 per 100 000 and 1.21 per 100 000. The cases were mainly distributed in the eastern, southeast, southern, and south of the central region of Gansu Province. Most cases were distributed between age 20-60, and the sex ratio was 1.85∶1 (564∶305). Most cases were farmers (61.80%, 537/869), herdsmen (19.79%,172/869) and students (6.33%, 55/869). In a wild rat-type epidemic focus,the incidence peak was from November to January of the following year. The natural rodent hosts of HFRS were Rattus norvegicus, Apodemus agrarius, and Mus musculus. The hantaan virus carriage rates were 2.79% (21/754), 0.42% (5/1 179) and 0.31% (2/643),respectively. Three epidemic foci were defined: two derived from the Pingliang and Gannan prefecture new outbreaks epidemic foci, respectively, while the other was the residue of the Dingxi epidemic focus. Conclusions:The southern, south of the central region and eastern part of Gansu Province are current key HFRS epidemic foci dominated by Rattus norvegicus, Apodemus agrarius, and Mus musculus, respectively. The virus genotype is hantaan virus. Case reporting areas should strengthen epidemic monitoring; the key epidemic areas should strengthen and implement various prevention and control measures to reduce the harm caused by HFRS.
5.Epidemiological characteristics of COVID-19 in Gansu province
Faxiang GOU ; Xiaoshu ZHANG ; Jinxi YAO ; Deshan YU ; Kongfu WEI ; Hong ZHANG ; Xiaoting YANG ; Jianjun YANG ; Haixia LIU ; Yao CHENG ; Xiaojuan JIANG ; Yunhe ZHENG ; Bin WU ; Xinfeng LIU ; Hui LI
Chinese Journal of Epidemiology 2020;41(9):1415-1419
Objective:To understand the epidemiological characteristics of COVID-19 cases in different epidemic stages in Gansu province.Methods:Epidemiological investigation was conducted to collect the information of confirmed COVID-19 cases, including demographic, epidemiological and clinical information.Results:As of 25 February 2020, a total of 91 confirmed COVID-19 cases had been reported in Gansu. The epidemic of COVID-19 in Gansu can be divided as three different stages, i.e. imported case stage, imported-case plus indigenous case stage, and indigenous case stage. A total of 63 cases were clustered cases (69.23%), 3 cases were medical staff infected with non-occupational exposure.The initial symptoms included fever (54.95%, 50/91), cough (52.75%, 48/91), or fatigue (28.57%, 26/91), the proportion of each symptom showed a decreasing trend along with the three epidemic stages, but only the differences in proportions of fever (trend χ2=2.20, P<0.05) and fatigue (trend χ2=3.18, P<0.05) among the three epidemic stages were statistically significant. The cases with critical severe symptoms accounted for 42.85% (6/14), 23.73% (14/59) and 16.67% (3/18), respectively, in three epidemic stages, showed a decreasing trend ( H=6.45, P<0.05). Also, the incubation period prolonged along with the epidemic stage ( F=51.65, P<0.01), but the intervals between disease onset and hospital visit ( F=5.32, P<0.01), disease onset and diagnosis ( F=5.25, P<0.01) became shorter along with the epidemic stage. Additionally, the basic reproduction number ( R0) had decreased from 2.61 in imported case stage to 0.66 in indigenous case stage. Conclusions:The COVID-19 epidemic in Gansu was caused by the imported cases, and about 2/3 cases were clustered ones. No medical worker was observed to be infected by occupational exposure. With the progression of COVID-19 epidemic in Gansu, the change in initial symptom and incubation period suggests. the early screening cannot only depend on body temperature monitoring.
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