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Objective To analyze the epidemic characteristics and causes of post-exposure immunization failure of rabies in Hubei Province from 2015 to 2021, and to provide evidence for the prevention and control of rabies in Hubei Province. Methods The investigation data of rabies cases in Hubei Province from 2015 to 2021 were collected, and descriptive epidemiological methods were used for data analysis. Results A total of 127 cases of rabies were reported in Hubei Province from 2015 to 2021, with an average annual incidence of 0.31/million, showing a downward trend. The male to female ratio was 1.70:1. Farmers accounted for 82.67% of the total cases, and the 50-79 years old group accounted for 75.59%. The incidence was mainly concentrated in Xiangyang, Shiyan, Yichang and Jingmen, accounting for 77.17%. Most of the cases were concentrated in summer and autumn. Exposure of grade Ⅱand Ⅲ accounted for 24.79% and 75.21%, respectively. Hands, lower limbs below knee, head, arms and lower limbs above knee accounted for 46.15%, 25.21%, 9.40%, 8.55% and 7.69% of the exposed parts, respectively. Dogs, cats and wild animals accounted for 95.73%, 3.42% and 0.85% of the exposed animals, respectively. Stray animals, domesticated animals, neighbors' animals and wild animals accounted for 41.88%, 37.61%, 19.66% and 0.85% of animal sources, respectively. Neither the neighbors’ animals nor domesticated animals were vaccinated against veterinary rabies virus. After exposure, 8.55% of patients went to medical institutions for standard treatment of wounds, 9.40% were vaccinated with human rabies vaccine, and 4.55% of patients with grade III exposure were injected with rabies virus immunoglobulin. The incubation period within 6 months, from 6 months to 1 year, and over 1 year accounted for 72.22%, 14.74%, and 12.04%, respectively. The exposure degree (Z=-1.98, P 2=10.91, P 2=15.73, P < 0.05) had statistically significant effects on the incubation period. Among the 11 cases of post-exposure immunization failure, all were grade Ⅲ exposure, 63.63% were exposed to the head and face, 81.81% were not fully vaccinated with human rabies virus vaccine, 63.63% were not immunized with immunoglobulin, and 27.27% were inappropriate wound treatment. Conclusion The key to rabies prevention and control is to standardize dog management, strengthen rabies education, standardize post-exposure wound treatment, timely vaccinate against rabies virus, and inject rabies virus immunoglobulin when necessary.
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Objective:To analyze the effects of seasonal autoregressive integrated moving average model (SARIMA), generalized additive model (GAM), and long-short term memory model (LSTM) in fitting and predicting the incidence of hemorrhagic fever with renal syndrome (HFRS), so as to provide references for optimizing the HFRS prediction model.Methods:The monthly incidence data of HFRS from 2004 to 2017 of the whole country and the top 9 provinces with the highest incidence of HFRS (Heilongjiang, Shaanxi, Jilin, Liaoning, Shandong, Hebei, Jiangxi, Zhejiang and Hunan) were collected in the Public Health Science Data Center (https://www.phsciencedata.cn/), of which the data from 2004 to 2016 were used as training data, and the data from January to December 2017 were used as test data. The SARIMA, GAM, and LSTM of HFRS incidence in the whole country and 9 provinces were fitted with the training data; the fitted model was used to predict the incidence of HFRS from January to December 2017, and compared with the test data. The mean absolute percentage error ( MAPE) was used to evaluate the model fitting and prediction accuracy. When MAPE < 20%, the model fitting or prediction effect was good, 20%-50% was acceptable, and > 50% was poor. Results:From the perspective of overall fitting and prediction effect, the optimal model for the whole country and Heilongjiang, Shaanxi, Jilin, Liaoning and Jiangxi was SARIMA ( MAPE was 19.68%, 20.48%, 44.25%, 19.59%, 23.82% and 35.29%, respectively), among which the fitting and prediction effects of the whole country and Jilin were good, and the rest were acceptable. The optimal model for Shandong and Zhejiang was GAM ( MAPE was 18.29% and 21.25%, respectively), the fitting and prediction effect of Shandong was good, and Zhejiang was acceptable. The optimal model for Hebei and Hunan was LSTM ( MAPE was 26.52% and 22.69%, respectively), and the fitting and prediction effects were acceptable. From the perspective of fitting effect, GAM had the highest fitting accuracy in the whole country data, with MAPE = 10.44%. From the perspective of prediction effect, LSTM had the highest prediction accuracy in the whole country data, with MAPE = 12.23%. Conclusions:SARIMA, GAM, and LSTM can all be used as the optimal models for fitting the incidence of HFRS, but the optimal models fitted in different regions show great differences. In the future, in the establishment of HFRS prediction models, as many alternative models as possible should be included for screening to ensure higher fitting and prediction accuracy.
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Objective To explore the applicability of the TBATS in predicting the incidence of mumps. Methods The incidence of mumps of Jiangxi Province from 2004 to 2017 was used as the demonstration data. The incidence of mumps in Jiangxi Province from July to December 2017 was used as test data. The training data from January 2004 to June 2017 were used to train the TBATS and the SARIMA, and predict the value from July to December 2017. The fitted and predicted values were compared with the test data. The MAPE, RMSE, MAE and MER were used to evaluate model fitting and prediction effects. Results SARIMA (1,0,0)(1,1,0)12 with drift was the optimal SARIMA. The MAPE, MAE, RMSE and MER fitted by the TBATS and the SARIMA were 15.06%, 0.21, 0.29, 13.57% and 21.93%, 0.29, 0.41, 18.73%, respectively. The MAPE, MAE, RMSE and MER predicted by the TBATS and the SARIMA were 7.95%, 0.08, 0.11, 7.12% and 15.33%, 0.17, 0.18, 14.93%. Conclusion The TBATS has high accuracy in predicting the incidence of mumps and is worthy of popularization and application.
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Objective To explore the optimal combination of parameters for the maximum spatial cluster size and maximum temporal cluster size of scan statistics. Methods The daily incidence data of hand-foot-and-mouth disease (HFMD) in Jingzhou in 2016 was collected as data source. The maximum spatial cluster sizes were set to 50%, 40%, 30%, 20%, and 10% of the population at risk. The maximum temporal cluster sizes were set to 7d, 14d, 30d, and 60d. A total of 20 parameter setting schemes were formed and spatial-temporal scanning was conducted one by one. The areas where the number of towns covered by the scanning area was less than 25 were selected, and the clustered epidemic of hand-foot-mouth disease can be detected at the same time in Xiejiaping Town of Songzi City and Sanzhou Town of Jianli County. The combination of large LLR and RR values was the optimal parameter setting. Results When the spatial windows were set to 20% of the population at risk, and the temporal windows were set to 30d, a total of 6 aggregation areas were detected. The number of covered townships was less than 25, and the clustered epidemic of Xiejiaping Township and Sanzhou Town were successfully detected. The LLR and RR values of the detected aggregation area were relatively large. This combination was the optimal parameter setting. Conclusion The combination of different parameters has a significant impact on the results of spatial-temporal scan statistics. It is recommended that parameters be optimized before applying this method.
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Objective@#To analyze the changes of the characteristics of Hemorrhagic fever with renal syndrome (HFRS) in Jingzhou City in different periods.@*Methods@#According to the HFRS epidemic data of Jingzhou City in 2009-2018, based on the incidence rate, the HFRS epidemic situation in Jingzhou City was divided into three periods: 2009-2012 (low), 2013-2016 (middle), and 2017-2018 (high). Descriptive epidemiological methods, standard deviation ellipse and spatio-temporal scanning analysis were used to analyze the time, region, population distribution and temporal and spatial trends of HFRS epidemic in the three periods.@*Results@#The incidence of HFRS in Jingzhou City in the three periods was seasonal and bimodal. The peak incidence included spring and summer peaks (May-July) and autumn-winter peaks (January, November-December). The HFRS cases in Jingzhou City were concentrated in Jianli County, Jiangling County and Honghu City in the three periods. The incidence rates were 0.48/100 000, 1.98/100 000, 0.84/100 000, 0.89/100 000, 1.88/100 000, 1.20/100 000; 4.82/100 000, 13.37/100 000, and 4.58/100 000. The incidence of HFRS in males was higher than that in females in the three periods (χ2=43.38, P < 0.05); the occupations of HFRS in the three periods were mainly farmers, which were 56.26%(69/122), 69.61% (126/181), 74.94% (293/391), respectively. In 116 farmers, growing rice [48.28% (56/116)] and shrimp rice [27.59% (32/116)] were mostly. From the age point of view, the incidence rate in 2009-2017 was 55 to 64 years old; the incidence rate of 2018 was 60 to 69 years old. The results of standard deviation ellipse analysis showed that the expansion trend of HFRS epidemic areas in Jingzhou City was not obvious, and the center of gravity was located in Jianli County or Jiangling County. Spatio-temporal scans revealed that the first-class spatial-temporal clustering areas in the three periods were 2 towns and villages in Jiangling County, and the gathering time was from December 7, 2010 to January 2, 2011; in some townships in Jiangling County and Shacheng District, the gathering time was from December 7, 2016 to February 28, 2017; some townships in Jiangling County and surrounding counties, gathered from April 27, 2018 to July 16, 2018.@*Conclusions@#The HFRS epidemic season in Jingzhou City in different periods is basically the same; the high-incidence areas are basically the same, but there are local fluctuations; the population is mainly male farmers, and the age of high-incidence has shifted back. We should adapt to local conditions and formulate scientific and reasonable comprehensive prevention and control measures.
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Objective To analyze the changes of the characteristics of Hemorrhagic fever with renal syndrome (HFRS) in Jingzhou City in different periods. Methods According to the HFRS epidemic data of Jingzhou City in 2009 - 2018, based on the incidence rate, the HFRS epidemic situation in Jingzhou City was divided into three periods: 2009 - 2012 (low), 2013 - 2016 (middle), and 2017 - 2018 (high). Descriptive epidemiological methods, standard deviation ellipse and spatio-temporal scanning analysis were used to analyze the time, region, population distribution and temporal and spatial trends of HFRS epidemic in the three periods. Results The incidence of HFRS in Jingzhou City in the three periods was seasonal and bimodal. The peak incidence included spring and summer peaks (May - July) and autumn-winter peaks (January, November - December). The HFRS cases in Jingzhou City were concentrated in Jianli County, Jiangling County and Honghu City in the three periods. The incidence rates were 0.48/100000, 1.98/100000, 0.84/100000, 0.89/100000, 1.88/100000, 1.20/100000; 4.82/100000, 13.37/100000, and 4.58/100000. The incidence of HFRS in males was higher than that in females in the three periods (χ2 = 43.38, P < 0.05); the occupations of HFRS in the three periods were mainly farmers, which were 56.26％(69/122), 69.61％ (126/181), 74.94％ (293/391), respectively. In 116 farmers, growing rice [48.28％ (56/116)] and shrimp rice [27.59％ (32/116)] were mostly. From the age point of view, the incidence rate in 2009 - 2017 was 55 to 64 years old; the incidence rate of 2018 was 60 to 69 years old. The results of standard deviation ellipse analysis showed that the expansion trend of HFRS epidemic areas in Jingzhou City was not obvious, and the center of gravity was located in Jianli County or Jiangling County. Spatio-temporal scans revealed that the first-class spatial-temporal clustering areas in the three periods were 2 towns and villages in Jiangling County, and the gathering time was from December 7, 2010 to January 2, 2011; in some townships in Jiangling County and Shacheng District, the gathering time was from December 7, 2016 to February 28, 2017; some townships in Jiangling County and surrounding counties, gathered from April 27, 2018 to July 16, 2018. Conclusions The HFRS epidemic season in Jingzhou City in different periods is basically the same; the high -incidence areas are basically the same, but there are local fluctuations; the population is mainly male farmers, and the age of high-incidence has shifted back. We should adapt to local conditions and formulate scientific and reasonable comprehensive prevention and control measures.
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Objective To investigate the spatial correlation and spatial cluster pattern of hemorrhagic fever with renal syndrome (HFRS) in Jingzhou City,Hubei Province from 2013 to 2017.Methods The HFRS surveillance data during 2013-2017 were collected from China Disease Prevention and Control Information System.Software ArcGIS 10.3 was used to analyze the spatial distribution,and global autocorrelation analysis (Moran'sI) and hot spot analysis (Getis-Ord Gi) were used to analyze the spatial autocorrelation.Spatial cluster pattern was explored by trend surface analysis and directional distribution.Results In 2013-2017,the global Moran's I was 0.117 6 (P ＞ 0.05),0.349 8 (P ＜ 0.05),0.102 1 (P ＞ 0.05),0.276 3 (P ＜ 0.05),and 0.394 8 (P ＜ 0.05),respectively.The Getis-Ord Gi analysis showed that there were 7,8,8,8,15 hot areas with high incidence of HFRS during this period,respectively,which were part of townships in Jiangling County,Shashi District,Jianli County,and Honghu City.The cold spot area with low incidence of HFRS was only detected in 2015,and it was part of the township in Shashi District and Jingzhou District.The trend surface analysis showed that the inverted-U type curve could reflect the HFRS distribution from northern to southern,and it was also from eastern to western.The directional distribution showed that the HFRS cases were distributed in the north-central part of Jingzhou in 2013-2017,and they were inconsistent with the distribution of the Yangtze River system.Conclusions The incidence of HFRS has an obvious spatial clustering characteristic,and the areas at high risk are mainly in the north-central part of Jingzhou City.The spatial cluster pattern of HFRS has nothing to do with the Yangtze River system.
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<p><b>OBJECTIVE</b>To estimate the hospitalization rate of severe acute respiratory infection (SARI) cases attributable to influenza in Jingzhou city, Hubei province from 2010 to 2012.</p><p><b>METHODS</b>SARI surveillance was conducted at four hospitals in Jingzhou city, Hubei province from 2010 to 2012. Inpatients meeting the SARI case definition and with informed consent were enrolled to collect their demographic information, clinical features, treatment, and disease outcomes, with their respiratory tract specimens collected for PCR test of influenza virus.</p><p><b>RESULTS</b>From April, 2010 to September, 2012, 19 679 SARI cases enrolled were residents of Jingzhou, and nasopharyngeal swab was collected from 18 412 (93.6%) cases of them to test influenza virus and 13.3% were positive for influenza. During the three consecutive 2010-2012 flu seasons, laboratory-confirmed influenza was associated with 102 per 100 000, 132 per 100 000 and 244 per 100 000, respectively. As for the hospitalization rate attributable to specific type/subtype of influenza virus, 48 per 100 000, 30 per 100 000 and 24 per 100 000 were attributable to A (H3N2), A (H1N1) pdm2009, and influenza B, respectively in 2010-2011 season; 42 per 100 000 [A (H3N2)] and 90 per 100 000 (influenza B) in 2011-2012 season; 90 per 100 000 [A (H3N2)] and one per 100 000 [influenza B] from April, 2010 to September, 2012. SARI hospitalization caused by influenza A or B occurred both mainly among children younger than five years old, with the peak in children aged 0.5 year old.</p><p><b>CONCLUSION</b>Influenza could cause a substantial number of hospitalizations and different viral type/subtype result in different hospitalizations over influenza seasons in Jingzhou city, Hubei province. Children less than five years old should be prioritized for influenza vaccination in China.</p>