1
|
Cui T, Zhang X, Wang Q, Yue N, Bao C, Jiang R, Xu S, Yuan Z, Qian Y, Chen L, Hang H, Zhang Z, Sun H, Jin H. Cost-effectiveness analysis of hepatitis E vaccination strategies among patients with chronic hepatitis B in China. Hepatol Res 2024; 54:142-150. [PMID: 37706554 DOI: 10.1111/hepr.13967] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 08/16/2023] [Accepted: 09/05/2023] [Indexed: 09/15/2023]
Abstract
AIM This study aimed to evaluate the cost-effectiveness of hepatitis E vaccination strategies in chronic hepatitis B (CHB) patients. METHODS Based on the societal perspective, the cost-effectiveness of three hepatitis E vaccination strategies-vaccination without screening, screening-based vaccination, and no vaccination-among CHB patients was evaluated using a decision tree-Markov model, and incremental cost-effectiveness ratios (ICERs) were calculated. Values for treatment costs and health utilities were estimated from a prior investigation on disease burden, and values for transition probabilities and vaccination-related costs were obtained from previous studies and government agencies. Sensitivity analyses were undertaken for assessing model uncertainties. RESULTS It was estimated that CHB patients superinfected with hepatitis E virus (HEV) incurred significantly longer disease course, higher economic burden, and more health loss compared to those with HEV infection alone (all p < 0.05). The ICERs of vaccination without screening and screening-based vaccination compared to no vaccination were 41,843.01 yuan/quality-adjusted life year (QALY) and 29,147.32 yuan/QALY, respectively, both lower than China's per-capita gross domestic product (GDP) in 2018. The screening-based vaccination reduced the cost and gained more QALYs than vaccination without screening. One-way sensitivity analyses revealed that vaccine price, vaccine protection rate, and decay rate of vaccine protection had the greatest impact on the cost-effectiveness analysis. Probabilistic sensitivity analyses confirmed the base-case results, and if the willingness-to-pay value reached per-capita GDP, the probability that screening-based vaccination would be cost-effective was approaching 100%. CONCLUSIONS The disease burden in CHB patients superinfected with HEV is relatively heavy in China, and the screening-based hepatitis E vaccination strategy for CHB patients is the most cost-effective option.
Collapse
Affiliation(s)
- Tingting Cui
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Xuefeng Zhang
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Qiang Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, China
| | - Na Yue
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, China
| | - Changjun Bao
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Renjie Jiang
- Yancheng Center for Disease Control and Prevention, Yancheng, China
| | - Shilin Xu
- Yancheng Center for Disease Control and Prevention, Yancheng, China
| | - Zhaohu Yuan
- Zhenjiang Center for Disease Control and Prevention, Zhenjiang, China
| | - Yunke Qian
- Zhenjiang Center for Disease Control and Prevention, Zhenjiang, China
| | - Liling Chen
- Suzhou Center for Disease Control and Prevention, Suzhou, China
| | - Hui Hang
- Suzhou Center for Disease Control and Prevention, Suzhou, China
| | - Zhong Zhang
- Nanjing Center for Disease Control and Prevention, Nanjing, China
| | - Hongmin Sun
- Nanjing Center for Disease Control and Prevention, Nanjing, China
| | - Hui Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, China
| |
Collapse
|
2
|
Han Y, Ji H, Shen W, Duan C, Cui T, Chen L, Hang H, Zhang Z, Sun H, Zhang X, Jin H. Disease burden in patients with severe hand, foot, and mouth disease in Jiangsu Province: a cross-sectional study. Hum Vaccin Immunother 2022; 18:2049168. [PMID: 35476031 PMCID: PMC9196847 DOI: 10.1080/21645515.2022.2049168] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
This study aimed to estimate the disease burden and health-related quality of life (HRQOL) among patients with severe hand, foot, and mouth disease (HFMD) in Jiangsu Province, China. We analyzed the surveillance data of HFMD cases in Jiangsu Province from 2009 to 2020. Moreover, a cross-sectional study was conducted in Nanjing and Suzhou, China, between January 2017 and May 2018. Patients with severe HFMD and their parents were recruited from selected hospitals. Questionnaires and hospital management systems were used to collect data on direct economic burden. The HRQOL of children was assessed using the TNO-AZL Preschool Quality of Life (TAPQOL) scale. A total of 1,348,737 confirmed cases of HFMD were reported to the NNDRS in Jiangsu province during 2009-2020. Of these, 9,622 were severe cases, with 62 (.64%) of these being fatal. From January 2017 to May 2018, data was collected from 362 severe HFMD cases using a structured questionnaire. The median per capita direct economic burden was RMB 16142.88, and was associated with the region and length of hospital stay (P < .05). The direct economic burden for all cases of severe HFMD in Jiangsu province between 2017 and 2018 was approximately RMB 16.64 million. Finally, the median (IQR) of the TAPQOL scale for children with severe HFMD was 69.23 (56.20, 82.27). Severe HFMD infection is a relatively large burden for individuals, and the burden of EV-A71 infection was seen to be even greater for the population. Prevention of severe HFMD should strengthen hygiene habits and targeted measures for EV-A71 vaccination.
Collapse
Affiliation(s)
- Ying Han
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China.,Key Laboratory of Environmental Medicine Engineering, School of Public Health, Southeast University, Ministry of Education, Nanjing, China
| | - Hong Ji
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Wenqi Shen
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Chunxiao Duan
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Tingting Cui
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China.,Key Laboratory of Environmental Medicine Engineering, School of Public Health, Southeast University, Ministry of Education, Nanjing, China
| | - Liling Chen
- Suzhou Center for Disease Control and Prevention, Suzhou, China
| | - Hui Hang
- Suzhou Center for Disease Control and Prevention, Suzhou, China
| | - Zhong Zhang
- Nanjing Center for Disease Control and Prevention, Nanjing, China
| | - Hongmin Sun
- Nanjing Center for Disease Control and Prevention, Nanjing, China
| | - Xuefeng Zhang
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Hui Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China.,Key Laboratory of Environmental Medicine Engineering, School of Public Health, Southeast University, Ministry of Education, Nanjing, China
| |
Collapse
|
3
|
Wu T, Wang M, Cheng X, Liu W, Zhu S, Zhang X. Predicting incidence of hepatitis E for thirteen cities in Jiangsu Province, China. Front Public Health 2022; 10:942543. [PMID: 36262244 PMCID: PMC9574096 DOI: 10.3389/fpubh.2022.942543] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 09/16/2022] [Indexed: 01/25/2023] Open
Abstract
Hepatitis E has placed a heavy burden on China, especially in Jiangsu Province, so accurately predicting the incidence of hepatitis E benefits to alleviate the medical burden. In this paper, we propose a new attentive bidirectional long short-term memory network (denoted as BiLSTM-Attention) to predict the incidence of hepatitis E for all 13 cities in Jiangsu Province, China. Besides, we also explore the performance of adding meteorological factors and the Baidu (the most widely used Chinese search engine) index as additional training data for the prediction of our BiLSTM-Attention model. SARIMAX, GBDT, LSTM, BiLSTM, and BiLSTM-Attention models are tested in this study, based on the monthly incidence rates of hepatitis E, meteorological factors, and the Baidu index collected from 2011 to 2019 for the 13 cities in Jiangsu province, China. From January 2011 to December 2019, a total of 29,339 cases of hepatitis E were detected in all cities in Jiangsu Province, and the average monthly incidence rate for each city is 0.359 per 100,000 persons. Root mean square error (RMSE) and mean absolute error (MAE) are used for model selection and performance evaluation. The BiLSTM-Attention model considering meteorological factors and the Baidu index has the best performance for hepatitis E prediction in all cities, and it gets at least 10% improvement in RMSE and MAE for all 13 cities in Jiangsu province, which means the model has significantly improved the learning ability, generalizability, and prediction accuracy when comparing with others.
Collapse
Affiliation(s)
- Tianxing Wu
- School of Computer Science and Engineering, Southeast University, Nanjing, China
| | - Minghao Wang
- School of Computer Science and Engineering, Southeast University, Nanjing, China,*Correspondence: Minghao Wang
| | - Xiaoqing Cheng
- Jiangsu Provincial Centre for Disease Control and Prevention, Jiangsu Institution of Public Health, Nanjing, China,Chinese Field Epidemiology Training Program, Chinese Center for Disease Control and Prevention, Beijing, China,Xiaoqing Cheng
| | - Wendong Liu
- Jiangsu Provincial Centre for Disease Control and Prevention, Jiangsu Institution of Public Health, Nanjing, China
| | - Shutong Zhu
- School of Computer Science and Engineering, Southeast University, Nanjing, China
| | - Xuefeng Zhang
- Jiangsu Provincial Centre for Disease Control and Prevention, Jiangsu Institution of Public Health, Nanjing, China,Xuefeng Zhang
| |
Collapse
|
4
|
Tan J, Tang X, He Y, Xu X, Qiu D, Chen J, Zhang Q, Zhang L. In-patient Expenditure Between 2012 and 2020 Concerning Patients With Liver Cirrhosis in Chongqing: A Hospital-Based Multicenter Retrospective Study. Front Public Health 2022; 10:780704. [PMID: 35350474 PMCID: PMC8957842 DOI: 10.3389/fpubh.2022.780704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 02/11/2022] [Indexed: 11/13/2022] Open
Abstract
Background Liver cirrhosis is a major global health and economic challenge, placing a heavy economic burden on patients, families, and society. This study aimed to investigate medical expenditure trends in patients with liver cirrhosis and assess the drivers for such medical expenditure among patients with liver cirrhosis. Methods Medical expenditure data concerning patients with liver cirrhosis was collected in six tertiary hospitals in Chongqing, China, from 2012 to 2020. Trends in medical expenses over time and trends according to subgroups were described, and medical expenditure compositions were analyzed. A multiple linear regression model was constructed to evaluate the factors influencing medical expenditure. All expenditure data were reported in Chinese Yuan (CNY), based on the 2020 value, and adjusted using the year-specific health care consumer price index for Chongqing. Results Medical expenditure for 7,095 patients was assessed. The average medical expenditure per patient was 16,177 CNY. An upward trend in medical expenditure was observed in almost all patient subgroups. Drug expenses were the largest contributor to medical expenditure in 2020. A multiple linear regression model showed that insurance type, sex, age at diagnosis, marital status, length of stay, smoking status, drinking status, number of complications, autoimmune liver disease, and the age-adjusted Charlson comorbidity index score were significantly related to medical expenditure. Conclusion Conservative estimates suggest that the medical expenditure of patients with liver cirrhosis increased significantly from 2012 to 2020. Therefore, it is necessary to formulate targeted measures to reduce the personal burden on patients with liver cirrhosis.
Collapse
Affiliation(s)
- Juntao Tan
- Medical Records and Statistics Room, People's Hospital of Chongqing Banan District, Chongqing, China
| | - Xuewen Tang
- Department of Cardiology, People's Hospital of Chongqing Banan District, Chongqing, China
| | - Yuxin He
- Department of Medical Administration, People's Hospital of Chongqing Banan District, Chongqing, China
| | - Xiaomei Xu
- Department of Gastroenterology, The Fifth People's Hospital of Chengdu, Chengdu, China.,Department of Infectious Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Daoping Qiu
- Medical Records and Statistics Room, People's Hospital of Chongqing Banan District, Chongqing, China
| | - Jianfei Chen
- Department of Cardiology, People's Hospital of Chongqing Banan District, Chongqing, China
| | - Qinghua Zhang
- Department of Science and Education, People's Hospital of Chongqing Banan District, Chongqing, China
| | - Lingqin Zhang
- Department of Biomedical Equipment, People's Hospital of Chongqing Bishan District, Chongqing, China
| |
Collapse
|
5
|
Yu S, Rui J, Cheng X, Zhao Z, Liu C, Lin S, Zhu Y, Wang Y, Xu J, Yang M, Liu X, Wang M, Lei Z, Zhao B, Zhao Q, Zhang X, Chen T. Hepatitis E in 24 Chinese Cities, 2008-2018: A New Analysis Method for the Disease's Occupational Characteristics. Front Public Health 2021; 9:720953. [PMID: 34650949 PMCID: PMC8506125 DOI: 10.3389/fpubh.2021.720953] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Accepted: 08/30/2021] [Indexed: 12/27/2022] Open
Abstract
Background: The disease burden of hepatitis E remains high. We used a new method (richness, diversity, evenness, and similarity analyses) to classify cities according to the occupational classification of hepatitis E patients across regions in China and compared the results of cluster analysis. Methods: Data on reported hepatitis E cases from 2008 to 2018 were collected from 24 cities (9 in Jilin Province, 13 in Jiangsu Province, Xiamen City, and Chuxiong Yi Autonomous Prefecture). Traditional statistical methods were used to describe the epidemiological characteristics of hepatitis E patients, while the new method and cluster analysis were used to classify the cities by analyzing the occupational composition across regions. Results: The prevalence of hepatitis E in eastern China (Jiangsu Province) was similar to that in the south (Xiamen City) and southwest of China (Chuxiong Yi Autonomous Prefecture), but higher than that in the north (Jilin Province). The age of hepatitis E patients was concentrated between 41 and 60 years, and the sex ratio ranged from 1:1.6 to 1:3.4. Farming was the most highly prevalent occupation; other sub-prevalent occupations included retirement, housework and unemployment. The incidence of occupations among migrant workers, medical staff, teachers, and students was moderate. There were several occupational types with few or no records, such as catering industry, caregivers and babysitters, diaspora children, childcare, herders, and fishing (boat) people. The occupational similarity of hepatitis E was high among economically developed cities, such as Nanjing, Wuxi, Baicheng, and Xiamen, while the similarity was small among cities with large economic disparities, such as Nanjing and Chuxiong Yi Autonomous Prefecture. A comparison of the classification results revealed more similarities and some differences when using these two methods. Conclusion: In China, the factors with the greatest influence on the prevalence of hepatitis E are living in the south, farming as an occupation, being middle-aged or elderly, and being male. The 24 cities we studied were highly diverse and moderately similar in terms of the occupational distribution of patients with hepatitis E. We confirmed the validity of the new method on in classifying cities according to their occupational composition by comparing it with the clustering method.
Collapse
Affiliation(s)
- Shanshan Yu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Jia Rui
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Xiaoqing Cheng
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Zeyu Zhao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Chan Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Shengnan Lin
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Yuanzhao Zhu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Yao Wang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Jingwen Xu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Meng Yang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Xingchun Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Mingzhai Wang
- Xiamen City Center for Disease Control, Xiamen, China
| | - Zhao Lei
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Benhua Zhao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| | - Qinglong Zhao
- Jilin Provincial Center for Disease Control and Prevention, Changchun, China
| | - Xuefeng Zhang
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Tianmu Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China
| |
Collapse
|
6
|
Song X, Lan L, Zhou T, Yin J, Meng Q. Economic Burden of Major Diseases in China in 2013. Front Public Health 2021; 9:649624. [PMID: 34095056 PMCID: PMC8170047 DOI: 10.3389/fpubh.2021.649624] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 04/26/2021] [Indexed: 02/05/2023] Open
Abstract
Studies on the economic burden of disease (EBD) can estimate the social benefits of preventing or curing disease. The majority of studies focus on the economic burden of a single or regional disease; however, holistic or national research is rare in China. Estimating the national EBD can provide evidence for policy makers. We used the top-down method to assess the economic burden of 30 types of diseases between urban and rural areas in China. The two-step model was used to evaluate the direct economic burden of disease (DEBD), while the human capital method was used to assess the indirect economic burden of disease (IEBD). The total economic burden of 30 types of diseases in China was between $13.39 and 803.00 billion in 2013. The average total economic burden of disease (TEBD) in cities was $81.39 billion, while diseases in villages accounted for $50.26 billion. The range of direct and indirect EBD was $5.77-494.52 billion, and the range in urban areas was $0.61-20.34 billion. The direct and indirect EBD in rural areas accounted for $5.88-277.76 billion and $0.59-11.39 billion, respectively. There was a large difference between the economic burden of different diseases. The economic burden of urban diseases was more significant than the burden for the rural. The top five most economically burdensome diseases were myocardial infarction coronary artery bypass, acute myocardial infarction, cerebral hemorrhage, acute upper gastrointestinal bleeding and acute appendicitis.
Collapse
Affiliation(s)
- Xianyan Song
- Institute of Hospital Management, West China Hospital, Sichuan University, Chengdu, China
| | - Lan Lan
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
| | - Ting Zhou
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jin Yin
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
| | - Qiong Meng
- Department of Epidemiology and Health Statistics, School of Public Health, Kunming Medical University, Kunming, China
| |
Collapse
|
7
|
Wu J, Guo N, Zhu L, Zhang X, Xiong C, Liu J, Xu Y, Fan J, Yu J, Pan Q, Yang J, Liang H, Jin X, Ye S, Wang W, Liu C, Zhang J, Li G, Jiang B, Cao H, Li L. Seroprevalence of AIH-related autoantibodies in patients with acute hepatitis E viral infection: a prospective case-control study in China. Emerg Microbes Infect 2020; 9:332-340. [PMID: 32037983 PMCID: PMC7033704 DOI: 10.1080/22221751.2020.1722759] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The seroprevalenc of autoimmune hepatitis (AIH)-related antibodies in patients, particularly Asians, with acute hepatitis E (AHE) is unclear. In this study, we investigated whether acute hepatitis E virus (HEV) infection is associated with the seroprevalence of AIH-related autoantibodies and assessed their impact on the disease characteristics. AIH-related autoantibodies were detected by indirect immunofluorescence in 198 AHE patients and 50 type 1 AIH patients. The positivity rates of against nuclear antigen (ANA) and smooth muscles antibody (SMA) in AHE patients were 37.4% and 22.7%, and the total positivity rate was 50%. Compared to those in AIH patients, the positivity rates of ANA-H and SMA-AA were significantly lower (35.1% vs. 82.1% and 4.4% vs. 88.4%). Female gender and the ALT level, but not immunosuppressive or antiviral drugs, were independently predictive of the presence of AIH-related autoantibodies in AHE patients. Fifty-two patients positive for AIH-related autoantibodies were followed up for 12 months. During this period, 33 of them became negative and 19 remained positive, albeit with significantly decreased titres. In conclusions, the seroprevalence of AIH-related autoantibodies in AHE patients was elevated, particularly in females, but their subspecificities and titres differed from those of type 1 AIH. Acute HEV infection may be related to AIH. Abbreviations: AIH: autoimmune hepatitis; AHE: acute hepatitis E; ANA: against nuclear antigen; SMA: smooth muscles antibody; ANA-H: ANA with homogeneous pattern; SMA-AA: SMA with anti-actin pattern; Anti-LKM1: anti- liver-kidney microsomes-1 antibody; ANCA: anti-neutrophil cytoplasmic antibody; AMA: anti-mitochondrial antibody; Anti-SLA: anti-soluble liver antigen; Anti-LC1: anti-liver cytoplasmic type 1 antibody; pANCA: perinuclear antineutrophil cytoplasmic antibody
Collapse
Affiliation(s)
- Jian Wu
- State Key Laboratory for the Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People's Republic of China.,Department of Laboratory Medicine, The First People's Hospital of Yancheng City, Yancheng, People's Republic of China
| | - Naizhou Guo
- Department of Laboratory Medicine, The First People's Hospital of Yancheng City, Yancheng, People's Republic of China
| | - Lifei Zhu
- State Key Laboratory for the Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - Xueyan Zhang
- Department of Public Health, Jiangsu Vocational College of Medicine, Yancheng, People's Republic of China
| | - Cunquan Xiong
- Department of Public Health, Jiangsu Vocational College of Medicine, Yancheng, People's Republic of China
| | - Jun Liu
- Department of Laboratory Medicine, The Fifth People's Hospital of Wuxi, Affiliated to Jiangnan University, Wuxi, People's Republic of China
| | - Yanping Xu
- State Key Laboratory for the Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - Jun Fan
- State Key Laboratory for the Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - Jiong Yu
- State Key Laboratory for the Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - Qiaoling Pan
- State Key Laboratory for the Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - Jinfeng Yang
- State Key Laboratory for the Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - Hanying Liang
- State Key Laboratory for the Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - Xiuyuan Jin
- State Key Laboratory for the Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - Sunyi Ye
- State Key Laboratory for the Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - Wei Wang
- Department of Laboratory Medicine, The First People's Hospital of Yancheng City, Yancheng, People's Republic of China
| | - Chengyuan Liu
- Department of Laboratory Medicine, The First People's Hospital of Yancheng City, Yancheng, People's Republic of China
| | - Jinrong Zhang
- Department of Laboratory Medicine, The People's Hospital of Dafeng City, Yancheng, People's Republic of China
| | - Gongqi Li
- Department of Clinical Laboratory, Linyi Traditional Hospital, Linyi, People's Republic of China
| | - Bin Jiang
- Department of Laboratory Medicine, The Central Blood Station of Yancheng City, Yancheng, People's Republic of China
| | - Hongcui Cao
- State Key Laboratory for the Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People's Republic of China.,Zhejiang Provincial Key Laboratory for Diagnosis and Treatment of Aging and Physic-chemical Injury Diseases, Hangzhou, People's Republic of China
| | - Lanjuan Li
- State Key Laboratory for the Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| |
Collapse
|