Objective To retrospectively analyze the prevention and control effect and epidemic characteristics of elderly tuberculosis in Hubei Province from 2016 to 2020, and to provide a scientific basis for the prevention and treatment of elderly tuberculosis in Hubei Province． Methods The data on tuberculosis patients aged 60 and above who registered their current address in Hubei Province from 2016 to 2020 were collected and analyzed. The registration rates and composition ratios were analyzed using χ² test and χ² test for trend. Results A total of 135 976 tuberculosis patients were reported in Hubei from 2016 to 2020. The annual average registration rate of elderly tuberculosis among the elderly registered residence population (referring to the registration rate of elderly registered residence population aged 60 and above as the denominator, and tuberculosis patients aged 60 and above as the numerator) was 263.51/100 000. The highest rate was 300.02/100,000 in 2017, and the lowest was 188.19/100,000 in 2020 (χ²=70,227.603, P<0.001). In terms of composition, the average annual proportion of tuberculosis patients in the 60-70 years old group was 59.60%, which decreased year by year (χ²_trend=40.448，P<0.001 ). The average annual proportion of males was 73.35%, which was significantly higher than that of females (26.65%). The average annual proportion of farmers was 62.03%. From the perspective of case management, the annual average proportion of major epidemic online reports was 85.17%. The classification of cases was mainly based on clinical diagnosis, accounting for 48.33% annually and showing a decreasing trend year by year (χ²_trend=740.911, P<0.001). The proportion of confirmed cases was 25.08%, which showed an increasing trend (χ²_trend=380.557, P<0.001). From 2016 to 2019, the delay rate of diagnosis and treatment of elder tuberculosis patients was 49.42% (67 876/135 967), and the delay rate decreased year by year (χ²_trend=323.764, P<0.001). Conclusion The elderly population with pulmonary tuberculosis in Hubei Province shows a downward trend. It is necessary to focus on the efforts of designated hospitals to proactively identify cases, increase the proportion of confirmed cases, maintain a high tracking in place, reduce medical delays, and ensure the effectiveness of tuberculosis prevention and treatment for the elderly.

Objective:To analyze the epidemic characteristics of brucellosis in China from 2004 to 2018, in order to understand the development trend of brucellosis.Methods:The surveillance data of brucellosis in China from 2004 to 2018 were collected from National Public Health Science Data Center. Joinpoint regression was used to analyze the trend of brucellosis incidence in China and various provinces. Overall trends were estimated by the average annual percentage change (AAPC). Seasonal and trend decomposition using loess (STL) was used to analyze the seasonal characteristics of brucellosis in China and various provinces. The age-related thermodynamic diagram of incidence rate was used to analyze the characteristics of age-onset changes.Results:From 2004 to 2018, a total of 524 980 brucellosis cases and 16 deaths were reported nationwide, with a incidence rate of 2.61/100 000 and a case fatality rate of (3.05 × 10 -3)%. The incidence of brucellosis in China was on the rise (AAPC = 11.58%, 95% CI: 7.91% - 15.25%, P < 0.001). There was no significant trend of change in Inner Mongolia Autonomous Region, Shanxi and Shaanxi provinces ( P > 0.05). Tibet Autonomous Region showed a downward trend (AAPC = - 55.19%, P < 0.001). All other provinces were showing an upward trend (AAPC > 0, P < 0.05). The peak incidence in China occurred from April to June. In terms of provinces, the peak incidence in Hainan, Sichuan, Guizhou, Fujian and Anhui provinces occurred from April to August, the peak incidence in Chongqing and Shanghai cities occurred from June to August, and the peak incidence in other provinces was generally from April to June. There were reports of brucellosis cases in all age groups nationwide, and the age distribution showed an inverted "V" shape. The peak incidence occurred in the 50 - 54 years old (5.43/100 000), followed by the 60 - 64 years old (4.94/100 000). From 2004 to 2018, the top 3 age groups of incidence rate changed from 40 - 44, 50 - 54 and 35 - 39 years old in 2004 to 50 - 54, 60 - 64 and 55 - 59 years old in 2018. Conclusions:The incidence of brucellosis is on the rise nationwide and in most provinces from 2004 to 2018. The high incidence age is gradually changing to the elderly population.

Objective:To learn about the age, period, birth cohort characteristics, and incidence trends of hemorrhagic fever with renal syndrome (HFRS) nationwide.Methods:HFRS monitoring data from 2004 to 2018 were collected from the National Public Health Science Data Center (https://www.phsciencedata.cn/). The trend of incidence rate of HFRS was analyzed by joinpoint regression, and the linear trend was estimated by annual percentage change (APC) and average annual percentage change (AAPC). Bayesian Age-Period-Cohort (BAPC) analysis of the effects of age, period, and birth cohort on HFRS cases was conducted, with age, period, and birth cohort used as reference for the 40 - 44 age group, 2011, and 1968, respectively, the RR and 95% CI were calculated. Results:From 2004 to 2018, a total of 190 197 HFRS cases were reported nationwide, with an average annual incidence rate of 0.95/100 000. Among them, the highest incidence rate of HFRS was 1.93/100 000 in 2004. Since 2007, it had continued to fluctuate below 1.00/100 000, ranging from 0.66/100 000 to 0.99/100 000. Joinpoint regression fitting results showed that the overall incidence of HFRS in China was declining (AAPC = - 7.33%, 95% CI: - 8.07% - - 6.58%, P < 0.001); the APCs from 2004 to 2007, 2007 to 2009, and 2012 to 2016 were - 32.00%, - 8.74%, and - 9.02%, respectively, all showed a downward trend( P < 0.05); the APCs from 2009 to 2012 and from 2016 to 2018 were 14.69% and 11.38%, respectively, both showed an upward trend ( P < 0.05). HFRS cases were reported in all age groups, and the reported incidence rate showed a unimodal distribution with age. Among them, the highest incidence rate was in the 50 - 54 age group (1.75/100 000), and the lowest incidence rate was in the 0 - 4 age group (0.03/100 000); the proportion of cases in the age group of 60 years and above increased from 9.75% in 2004 to 25.90% in 2018, showed an increasing trend year by year (χ 2trend = 9 210.90, P<0.001). The analysis results of the BAPC model showed that in the age effect analysis, compared with the reference age group, there was no significant difference in the incidence risk among the age groups of 15 - 79 years old ( P > 0.05), while the incidence risk was lower in the age groups of 14 years old and below, and 80 years old and above ( RR < 1, P < 0.05). In the analysis of period effects, compared with the reference year, the incidence risk was higher from 2004 to 2006 and from 2012 to 2014 ( RR > 1 , P < 0.05), and lower from 2008 to 2010 and from 2017 to 2018 ( RR < 1, P < 0.05); the overall trend was consistent with the descriptive analysis of onset period. In the analysis of birth cohort effect, compared with the reference cohort, the population born between 1920 - 1935 and 1970 - 2018 had lower incidence risk ( RR < 1, P < 0.05); but the risk of disease in the population born after 2003 showed an upward trend. Conclusions:The HFRS epidemic in China has decreased from 2004 to 2018, but the downward trend in recent years is not significant. The incidence risk has increased among people born after 2003. The population aged 60 and above is a key group for further controlling the HFRS epidemic in China.

Objective To compare the prediction effect of combined model and single model in HFRS incidence fitting and prediction, and to provide a reference for optimizing HFRS prediction model. Methods The province with the highest incidence in China (Heilongjiang Province) in recent years was selected as the research site. The monthly incidence data of HFRS in Heilongjiang Province from 2004 to 2017 were collected. The data from 2004 to 2016 was used as training data, and the data from January to December 2017 was used as test data. The training data was used to train SARIMA , ETS and NNAR models, respectively. The reciprocal variance method and particle swarm optimization algorithm (PSO) were used to calculate the model coefficients of SARIMA, ETS and NNAR, respectively, to construct combined model A and combined model B. The established models were used to predict the incidence of HFRS from January to December 2017. The fitted and predicted values of the five models were compared with the training data and test data, respectively. Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), Root Mean Standard Deviation (RMSE), and Mean Error Rate (MER) were used to evaluate the model fitting and prediction effects. Results The optimal SARIMA model was SARIMA(1,0,2)(2,1,1)₁₂. The optimal ETS model was ETS(M, N, M), and the smoothing parameter =0.738，=1*10. The optimal NNAR model was NNAR(13,1,7)₁₂. The residuals of the three single models were white noise (P>0.05). The expression of combined model A was ŷ=0.134*y_SARIMA+0.162*y_ETS+0.704*y_NNAR; the expression of combined model B was ŷ=0.246*y_SARIMA+0.435*y_ETS+0.319*y_NNAR. The MAPE, MAE, RMSE, and MER fitted by SARIMA, ETS, NNAR, combined model A and combined model B were 24.10%, 0.11, 0.17, 23.29%; 17.14%, 0.08, 0.14, 17.96%; 6.33%, 0.02, 0.03, 4.25%; 9.03%, 0.03, 0.05, 7.51%; 13.16%, 0.06, 0.09, 12.33%, respectively. The MAPE, MAE, RMSE, and MER predicted by the five models were 18.70%, 0.05, 0.06, 19.62%; 23.83%, 0.06, 0.07, 24.49%; 28.30%, 0.07, 0.10, 29.21%; 21.69%, 0.06, 0.08, 22.63%; 17.39%, 0.05, 0.07, 18.76%, respectively. Conclusion The fitting and prediction effects of the combined models are better than the single models. The combined model based on PSO to calculate the weight of the single model is the optimal model.

Objective:To analyze the epidemic characteristics and periodicity of hemorrhagic fever with renal syndrome (HFRS) in Jingzhou City, Hubei Province, and provide a basis for scientific prevention and control of HFRS in Jingzhou City.Methods:Retrospective analysis was used to collect HFRS case data and population data of Jingzhou City and 8 counties (cities, districts) within its jurisdiction, including Shashi District, Jingzhou District, Gongan County, Jianli City, Jiangling County, Shishou City, Honghu City, and Songzi City from 1962 to 2020, from the Archives of the Jingzhou Center for Disease Control and Prevention and the Infectious Disease Report Information Management System of the China Disease Control and Prevention Information System; and the epidemic characteristics of HFRS was analyzed in Jingzhou City and 8 counties (cities, districts) within its jurisdiction. The periodicity of HFRS onset was determined using wavelet analysis.Results:From 1962 to 2020, 18 936 HFRS cases were reported in Jingzhou City, with an average incidence rate of 5.95/100 000. There were a total of three epidemic peaks, namely from 1972 to 1973 (24.82/100 000, 24.84/100 000), 1983 (60.08/100 000), and 1995 (14.57/100 000). According to different regions, the high incidence areas of HFRS showed a phased transfer trend: from the 1960s to the 1970s, the Jiangbei area (Honghu City, Jianli City) was the highest incidence area; in the 1980s and 1990s, the high incidence areas were transferred to Jiangnan area (Songzi City, Shishou City, and Gongan County); after 2005, high incidence areas were relocated to Jiangbei area (Honghu City, Jianli City, Jiangling County). The wavelet analysis results showed that there were 12.30 and 21.77 years of HFRS epidemic cycles in Jingzhou City before 2000 ( P < 0.05); among them, the periodicity of Shashi District, Gongan County, Jiangling County, Shishou City, and Honghu City was relatively consistent with that of Jingzhou City, with epidemic cycles of about 12 or 22 years ( P < 0.05). Conclusions:Jingzhou City is currently at the peak of a 22-year epidemic cycle of HFRS, with Jiangbei area as the high incidence areas. The 12-year epidemic cycle in Jingzhou City has ended after 2000.

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.

Objective To analyze the global status of COVID-19 epidemics, so as to preliminarily forecast the epidemic trend. Methods The epidemiological data of 208 countries and the prevention and control policies implemented by typical countries from December 31, 2019 to December 14, 2020 were collected. We use the cumulative incidence rate, cumulative mortality, cumulative fatality and real-time dependent reproduction number (R_t) to analyze the epidemic status. We use the provenance package to group different countries and discuss the effect of prevention and control measures. Results As of December 14, 2020, a cumulative incidence of 93.49 per 10000, a cumulative mortality rate of 0.21‰, and a cumulative fatality rate of 3.1‰ had been reported globally.112 of the 208 countries still had R_t ≥ 1.0, and 96 countries had R_t <1.0. The grouping of 208 countries showed that countries from the same continent often gather together and were geographically adjacent. Countries that were geographically adjacent could easily be grouped together. Conclusion As of December 14, 2020, the epidemic situation in most countries had not been effectively controlled, and epidemic prevention and control are facing greater pressure. Sub-Saharan countries currently had a high R_t , and the government had adopted more relaxed epidemic prevention measures. The epidemic situation in this region may continue to deteriorate, and needs to be focused in the later period.

Objective:To analyze the molecular characteristics of Echovirus 11 (Echo11) strains isolated in Xiangyang, Hubei Province from 2016 to 2017 based on the sequences of VP1 gene.Methods:Rectal and throat swab specimens were collected from children with hand, foot and mouth disease (HFMD) in Xiangyang from 2016 to 2017. Echo11 strains were detected by real-time reverse transcriptase PCR (RT-PCR) and isolated after cultured in human rhabdosarcoma (RD) cells. The VP1 regions of Echo11 strains isolated from RD cells and the whole genomes of three representative Echo11 strains were amplified by conventional RT-PCR and the sequences were analyzed. DNAStar7.0 (MegAlign) and MEGA6.0 (Data) were used to analyze the homology and mutation sites in nucleotide and amino acid sequences. Neighbor-joining method was used to construct phylogenetic trees. Recombination analysis was performed with SimPlot software (BootScanning).Results:A total of 11 Echo11 strains were isolated from 3 494 HFMD cases, accounting for 0.31%. They were highly homologous in the VP1 gene. These strains shared 98.4%-100.0% homology in nucleotide sequences and 98.3%-100.0% homology in amino acid sequences. The homology between the 11 Echo11 strains and the prototype strain (Echo11/Gregory, X80059) was 73.9%-74.8% in nucleotide sequences and 87.7%-88.7% in amino acid sequences. All of the Echo11 strains circulating in Xiangyang were classified into lineage D, having a similarity to the strains circulating in some regions of mainland China since 2013. In multiple regions of the genome, the Echo11 strains isolated in Xiangyang were highly similar to the Henan Echo1 strains in 2010 and the Hubei Echo6 strains in 2015, suggesting there was recombination within the genome of Echo11 strains in Xiangyang.Conclusions:The Echo11 strains circulating in Xiangyang from 2016 to 2017 belonged to lineage D and were recombinant strains.

Objective:To investigate the etiology of necrotizing pneumonia (NP) in children and the clinical characteristics of NP caused by different pathogens in China.Methods:A retrospective, case-control study was performed in children with NP who were admitted to 13 hospitals in China from January 2008 to December 2019. The demographic and clinical information, laboratory data, etiological and radiological findings were analyzed. The data were divided into three groups based on the following years: 2008-2011, 2012-2015 and 2016-2019, and the distribution characteristics of the pathogens in different period were compared. Meanwhile, the pathogens of pediatric NP in the southern and northern China were compared. And the clinical characteristics of the Mycoplasma pneumoniae (MP) NP and the bacterial NP were also compared. T-test or Mann-Whitney nonparametric test was used for comparison of numerical variables, and χ 2 test was used for categorical variables. Results:A total of 494 children with NP were enrolled, the median ages were 4.7 (0.1-15.3) years, including 272 boys and 222 girls. Among these patients, pathogens were identified in 347 cases and the pathogen was unclear in the remaining 147 cases. The main pathogens were MP (238 cases), Streptococcus pneumoniae (SP) (61 cases), Staphylococcus aureus (SA) (51 cases), Pseudomonas aeruginosa (13 cases), Haemophilus influenzae (10 cases), adenovirus (10 cases), and influenza virus A (7 cases), respectively. MP was the most common pathogen in all three periods and the proportion increased yearly. The proportion of MP in 2016-2019 was significantly higher than that in 2012-2015 (52.1% (197/378) vs. 36.8% (32/87), χ 2= 6.654, P=0.010), while there was no significant difference in the proportion of MP in 2012-2015 and that in 2008-2011 (36.8% (32/87) vs. 31.0% (9/29), χ2=0.314, P=0.575).Regarding the regional distribution, 342 cases were in the southern China and 152 in the northern China. Also, MP was the most common pathogen in both regions, but the proportion of MP was higher and the proportion of SP was lower in the north than those in the south (60.5% (92/152) vs. 42.7% (146/342), χ 2=13.409, P<0.010; 7.9% (12/152) vs. 14.3% (49/342), χ 2= 4.023, P=0.045). Comparing the clinical characteristics of different pathogens, we found that fever and cough were the common symptoms in both single MP and single bacterial groups, but chest pain was more common (17.0% (34/200) vs. 6.1% (6/98), χ 2=6.697, P=0.010) while shortness of breath and wheezing were less common in MP group (16.0% (32/200) vs. 60.2% (59/98), χ 2=60.688, P<0.01; 4.5% (9/200) vs. 21.4% (21/98), χ 2=20.819, P<0.01, respectively). The white blood cell count, C-reactive protein and procalcitonin in the bacterial group were significantly higher than those in the MP group (14.7 (1.0-67.1)×10 9/L vs. 10.5 (2.5-32.2)×10 9/L, 122.5 (0.5-277.3) mg/L vs. 51.4 (0.5-200.0) g/L, 2.13 (0.05-100.00) μg/L vs. 0.24 (0.01-18.85) μg/L, Z=-3.719, -5.901 and -7.765, all P<0.01). Conclusions:The prevalence of pediatric NP in China shows an increasing trend during the past years. MP, SP and SA are the main pathogens of NP, and the most common clinical symptoms are fever and cough. The WBC count, C-reactive protein and procalcitonin in bacterial NP are significantly higher than those caused by MP.

Since the outbreak of the COVID-19 at the end of December 2019, Hubei province has actively adopted a series of prevention and control measures such as ^“quarantine, treatment, testing, and containment^”, and have basically blocked the spread of COVID-19. However, with the development of overseas epidemics and the occurrence of case clusters in local areas, we not only face the threat of imported cases, but also face the urgent need to resume normal work and daily life. This puts forward higher requirements for regular prevention and control of COVID-19. Therefore, we should more deeply understand the significance of regular prevention and control as well as the epidemic situation in our province, summarize experience and lessons, and adhere to the prevention and control strategy of ^“government-led, group-specialist combination, and specialized-oriented^”. Meanwhile, it is necessary to implement the working requirement that combines regular prevention and control surveillance with rapid emergency response to local COVID-19 outbreaks. Furthermore, we should establish a regular multi-point trigger early warning mechanism for COVID-19, strengthen the reserve of emergency supplies and carry out training and drills on epidemic prevention and control across the province to make full preparations for the coming autumn and winter epidemics. The most important is to reform the system of disease prevention and control and public health, comprehensively improve the ability of prevention and treatment, and promote the modernization of public health governance.