[Analysis on the characteristics of natural foci of hemorrhagic fever with renal syndrome in Gansu Province, 2012-2022].

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.

[Epidemiological characteristics of 2019-nCoV Delta variant in Gansu province].

Objective: To analyze the epidemiological characteristics of COVID-19 caused by 2019-nCoV Delta variant (B.1.617.2) in Gansu province, and provide evidence for the prevention and control of COVID-19. Methods: The information of COVID-19 cases, including demographic characteristics, epidemiological history, onset date, diagnosis date, exposure place, detection way and infection source, in Gansu from 17 October to 25 November, 2021 were collected. Software Excel 2016,SPSS 22 and ArcGIS 10.7 were used for data process and analysis. Results: As of November 25, 2021, a total of 146 COVID-19 cases had been reported in Gansu and the epidemic affected 10 counties (districts) in 5 cities. The epidemic of COVID-19 in Gansu had three stages: imported case stage,imported-local case stage and local case stage. The age of cases ranged from 1 to 87 years,and the cases in age group 18-59 years accounted for 59.59% (87/146). The male to female ratio of the cases was 1∶1.12 (69∶77). The cases were mainly people engaged in business services (17.12%, 25/146),retirees (15.75%, 23/146),students (13.70%, 20/146),the jobless and unemployed (12.33%, 18/146). In 3 epidemic stages, the cases aged 18-59 years accounted for 44.44%,54.41% and 70.00% respectively,showing an upward trend,and there were differences among different populations (trend χ2=23.24, P<0.001). Also, the incubation period of the cases tended to decrease, and severe cases accounted for 33.33% (6/18), 19.12% (13/68) and 3.33% (2/60) respectively, showing a downward trend. Community screening (25.34%, 37/146) and close contact screening were the main ways to detect cases,the cases detected by close contact screening in 3 epidemic stages accounted for 50.00% (9/18), 66.18% (45/68) and 86.67% (52/60) respectively. The epidemic had obvious case clustering in confined places,and the main exposure modes were living together (24.66%), working/studying together (11.64%), taking same transportation (9.59%) and dining together (9.59%). Conclusions: The COVID-19 epidemic in Gansu was caused by 2019-nCoV Delta variant from imported cases. The virus was mainly transmitted through travel, sharing transportation, dining together and home contact. The characteristics of COVID-19 epidemic in Gansu changed with time, the case's clinical symptoms were not obvious and the incubation period became shorter. The infections mainly occurred in group aged 18 years and above.

[Epidemiological characteristics of COVID-19 in Gansu province].

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.

[Spatial distribution of Brucellosis in Gansu province, 2013-2018].

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 I of Brucellosis in Gansu province from 2013 to 2018 were 0.242, 0.487, 0.424, 0.460, 0.427 and 0.468 (P<0.01), suggesting that the incidence of Brucellosis had spatial clustering features in Gansu province. Local global spatial autocorrelation analysis showed that the number of hot spots were declining in the eastern and north-central regions while the hot spots were increasing in the Hexi area (Wuwei, Zhangye, Jinchang and Jiuquan cities). The cold spots areas were mainly seen in the eastern, southeastern and south of central regions in Gansu province. Conclusions: The incidence of Brucellosis showed obviously spatial clustering characteristics in Gansu province. The number of hot spots were decreasing in the eastern and north of central regions while the hot spots were increasing in the Hexi area, suggesting that the prevention and control measures for Brucellosis should be further strengthened in these areas.

[Epidemiological and spatial-temporal distribution of several natural focus diseases in Gansu province, 2014-2018].

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.

[Study on early warning threshold values for 7 common communicable diseases in Gansu province, 2016].

Objective: To optimize the warning threshold values of common communicable diseases in Gansu province, and improve the early warning effect. Method: An early warning model was set up for influenza, scarlet fever, other infectious diarrheal diseases, dysentery, typhoid and paratyphoid, viral hepatitis type E and hand foot and mouth disease (HFMD) respectively in Gansu by using the moving percentile method and cumulative sum method. By calculating the sensitivity, specificity, predictive value of positive test, predictive value of negative test, Youden' index and receiver-operating characteristic curve, the optimum early warning threshold values for communicable diseases in Gansu were selected. Results: The optimum early warning boundary values of influenza, scarlet fever, other infectious diarrheal diseases, dysentery, typhoid and paratyphoid, and viral hepatitis type E were P(90), P(80), P(95), P(90), P(80) and P(90) respectively. The optimum early warning parameters of HFMD were k=1.2, H=5σ. Under the optimum early warning boundary values/parameters, the early warning sensitivities of influenza, scarlet fever, other infectious diarrheal diseases, dysentery, typhoid and paratyphoid, viral hepatitis type E and HFMD were 86.67%, 100.00%, 91.67%, 100.00%, 100.00%, 100.00% and 100.00%, the specificities were 86.49%, 62.22%, 75.00%, 100.00%, 97.92%, 89.13% and 74.47%. The predictive values of positive test were 72.22%, 29.17%, 52.38%, 100.00%, 80.00%, 54.55% and 29.41%, and the predictive values of negative test were 94.12%, 100.00%, 96.77%, 100.00%, 100.00%, 100.00% and 100.00%, and the Youden' indexes were 0.73, 0.62, 0.67, 1.00, 0.98,0.89 and 0.74. Receiver-operating characteristic curve showed that the values/parameters of this warning boundary were the points closest to the upper left of the coordinate diagram. Conclusion: The early warning thresholds of influenza, other infectious diarrheal diseases, dysentery and hepatitis E in Gansu may be raised appropriately and the early warning parameters of HFMD need to be adjusted to improve the effectiveness of early warning.