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Fang K, Cheng N, Nie C, Song W, Zhao Y, Pan J, Yin Q, Zheng J, Chen Q, Xiang T. Spatial and temporal distribution patterns and factors influencing hepatitis B in China: a geo-epidemiological study. BMC Public Health 2025; 25:1276. [PMID: 40186148 PMCID: PMC11971818 DOI: 10.1186/s12889-025-22452-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2025] [Accepted: 03/24/2025] [Indexed: 04/07/2025] Open
Abstract
BACKGROUND China is a country with an extremely high disease burden of hepatitis B. Spatiotemporal analysis of hepatitis B from a socioeconomic perspective is of great significance for reducing the disease burden, but there is still a relative lack of research. METHODS The age-period-cohort model and spatial distribution maps describe the three-dimensional distribution characteristics of hepatitis B. Spatial autocorrelation analysis and spatiotemporal scanning were used to analyze the spatiotemporal distribution characteristics. The random forest algorithm was used to screen the potential influencing factors. The geographic detector model was used to analyze the interaction patterns of variables. Finally, a geographically and temporally weighted regression model was established to analyze the effects of variables on the incidence rate of hepatitis B at different spatiotemporal scales. RESULTS From 2004 to 2023, a total of 20,376,898 cases of hepatitis B were reported in China. The incidence rate of hepatitis B decreased at a rate of 3.31% per year, and hepatitis B vaccination has led to this downward trend, accompanied by a significant birth cohort effect. And it shows an aggregated characteristic, which highlights the inequality of geographical distribution. Stronger explanations for the incidence of hepatitis B were found for the number of people at the end of each year (q = 0.1949; where q value refers to the explanatory ability of the independent variable for the dependent variable) and the proportion of rural population (q = 0.1895), with an even stronger explanation for the interaction (q = 0.5366). The magnitude and direction of the effect of factors influencing hepatitis B also varied in different regions, and the effect of each factor on the incidence of hepatitis B was not an independent event. CONCLUSIONS The later people are born, the lower the incidence of hepatitis B. The northwest and southwest regions are the main hotspots, but there is a tendency to spread to southern China. The number of beds in medical institutions should be increased in densely populated areas, and economic development should be accelerated in sparsely populated areas. Hepatitis B prevention and control should be prioritized in geographic hotspots, coupled with enhanced awareness campaigns in rural areas and catch-up vaccination programs targeting high-risk populations.
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Affiliation(s)
- Kang Fang
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, 361102, Fujian, China
| | - Na Cheng
- Jiangxi Provincial Key Laboratory of Prevention and Treatment of Infectious Diseases, Jiangxi Medical Center for Critical Public Health Events, the First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330052, Jiangxi, China
| | - Chuang Nie
- Jiangxi Provincial Key Laboratory of Prevention and Treatment of Infectious Diseases, Jiangxi Medical Center for Critical Public Health Events, the First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330052, Jiangxi, China
| | - Wentao Song
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, 361102, Fujian, China
| | - Yunkang Zhao
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, 361102, Fujian, China
| | - Jie Pan
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, 361102, Fujian, China
| | - Qi Yin
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, 361102, Fujian, China
| | - Jiwei Zheng
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, 361102, Fujian, China
| | - Qinglin Chen
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Xiamen, 361102, Fujian, China
| | - Tianxin Xiang
- Jiangxi Provincial Key Laboratory of Prevention and Treatment of Infectious Diseases, Jiangxi Medical Center for Critical Public Health Events, the First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330052, Jiangxi, China.
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Shan Q, Ma X, Chen Y, Zhou G, Gao S, Sun J, Guo F, Zhang F, Ma D, Sun G, Zhu W, Meng X, Ruan G, Zhang Y, Tan X, Liu D, Wang Y, Yin C, Zhou X, On behalf of Children Hepatitis in China, China National Critical Care Quality Control Center Group and National Quality Control Center for Medical Record Management. Health economic analysis and medical cost analysis of children with severe hepatitis B in China: A retrospective study from 2016 to 2022. Chin Med J (Engl) 2024; 138:00029330-990000000-00944. [PMID: 38291587 PMCID: PMC11882285 DOI: 10.1097/cm9.0000000000002987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Indexed: 02/01/2024] Open
Abstract
BACKGROUND Hepatitis B poses a heavy burden for children in China, however, the national studies on the distributional characteristics and health care costs of children with severe hepatitis B is still lacking. This study aimed to analyze the disease characteristics, health economic effects, and medical cost for children with severe hepatitis B in China. METHODS Based on patient information in the Hospital Quality Monitoring System, cases with severe hepatitis B were divided into four groups according to age, and the etiology and symptoms of each group were quantified. The cost of hospitalization was calculated for cases with different disease processes, and severity of disease. The spatial aggregation of cases and the relationship with health economic factors were analyzed by Moran's I analysis. RESULTS The total number of children discharged with hepatitis B from January 2016 to April 2022 was 1603, with an average age of 10.5 years. Liver failure cases accounted for 43.48% (697/1603,) of total cases and cirrhosis cases accounted for 11.23% (180/1603,). According to the grouping of disease progression, there were 1292 cases without associated complications, and the median hospitalization cost was $818.12. According to the spatial analysis, the aggregation of cases was statistically significant at the prefectural and provincial levels in 2019, 2020, and 2021 (all P <0.05). The number of severe cases was negatively correlated with gross domestic product (GDP, Moran's I <0) and percentage of urban population (Moran's I <0), and positively correlated with the number of pediatric beds per million population (Moran's I >0). CONCLUSION The number of severe hepatitis B cases is low in areas with high GDP levels and high urban population ratios, and health care costs have been declining over the years.
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Affiliation(s)
- Qijun Shan
- Information Center Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Xudong Ma
- Department of Medical Administration, National Health Commission of the People’s Republic of China, Beijing 100044, China
| | - Yujie Chen
- Department of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Guanghua Zhou
- Department of Information Technology, Center of Statistics and Health Informatics, National Health Commission of People’s Republic of China, Beijing 100044, China
| | - Sifa Gao
- Department of Medical Administration, National Health Commission of the People’s Republic of China, Beijing 100044, China
| | - Jialu Sun
- National Institute of Hospital Administration, National Health Commission of the People’s Republic of China, Beijing 100044, China
| | - Fuping Guo
- Department of Infectious Diseases, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Feng Zhang
- Information Center Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Dandan Ma
- Information Center Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Guoqiang Sun
- Information Center Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Wen Zhu
- Information Center Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Xiaoyang Meng
- Information Center Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Guiren Ruan
- Department of Infectious Diseases, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Yuelun Zhang
- Medical Research Center, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Xutong Tan
- Medical Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Dawei Liu
- Department of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Yi Wang
- Department of Medical Records and Collaborating Center for the WHO Family of International Classifications in China, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Chang Yin
- National Institute of Hospital Administration, National Health Commission of the People’s Republic of China, Beijing 100044, China
| | - Xiang Zhou
- Information Center Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China
- Department of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China
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Wang X, Du Z, Wang Y, Wang J, Huang S, Wang Y, Gu J, Deng W, Gilmour S, Li J, Hao Y. Impact and Cost-Effectiveness of Biomedical Interventions on Adult Hepatitis B Elimination in China: A Mathematical Modelling Study. J Epidemiol Glob Health 2023; 13:517-527. [PMID: 37349664 PMCID: PMC10469118 DOI: 10.1007/s44197-023-00132-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 05/30/2023] [Indexed: 06/24/2023] Open
Abstract
BACKGROUND China has one of the highest hepatitis B virus (HBV) disease burdens worldwide and tracking progress toward the 2030 HBV elimination targets is essential. This study aimed to assess the impact of biomedical interventions (i.e., adult vaccination, screening and treatment) on the adult HBV epidemic, estimate the time for HBV elimination, and evaluate the cost-effectiveness of the interventions in China. METHODS A deterministic compartmental model was developed to project the HBV epidemic from 2022 to 2050 and estimate the time to meet elimination targets under four intervention scenarios. Cost-effectiveness was calculated using incremental cost per quality-adjusted life year (QALY) gained, i.e., average cost-effectiveness ratio (CER). RESULTS Under the status quo, there will be 42.09-45.42 million adults living with HBV in 2050 and 11.04-14.36 million HBV-related deaths cumulatively from 2022 to 2050. Universal vaccination would cumulatively avert 3.44-3.95 million new cases at a cost of US$1027-1261/QALY gained. The comprehensive strategy would cumulatively avert 4.67-5.24 million new chronic cases and 1.39-1.85 million deaths, expediting the realization of the elimination targets forward to 2049. This strategy was also cost-effective with an average CER of US$20,796-26,685/QALY and a saved healthcare cost of US$16.10-26.84 per person. CONCLUSION China is not on track to meet the elimination targets but comprehensive biomedical interventions can accelerate the realization of the targets. A comprehensive strategy is cost-effective and cost-saving, which should be promoted in primary care infrastructures. Universal adult vaccination may be appropriate in the near future considering practical feasibility.
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Affiliation(s)
- Xinran Wang
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
- Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, 510080, China
- Key Laboratory of Health Informatics of Guangdong Province, Sun Yat-sen University, Guangzhou, 510080, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
- Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, 510080, China
- Key Laboratory of Health Informatics of Guangdong Province, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yijing Wang
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
- Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, 510080, China
- Key Laboratory of Health Informatics of Guangdong Province, Sun Yat-sen University, Guangzhou, 510080, China
| | - Junren Wang
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Shanshan Huang
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Ying Wang
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
- Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, 510080, China
- Key Laboratory of Health Informatics of Guangdong Province, Sun Yat-sen University, Guangzhou, 510080, China
| | - Jing Gu
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
- Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, 510080, China
- Key Laboratory of Health Informatics of Guangdong Province, Sun Yat-sen University, Guangzhou, 510080, China
- Guangzhou Joint Research Center for Disease Surveillance, Early Warning and Risk Assessment, Guangzhou, 510080, China
| | - Wanyu Deng
- College of Life Science, Shangrao Normal University, Shangrao, 334001, China
| | - Stuart Gilmour
- Graduate School of Public Health, St. Luke's International University, Tokyo, Japan
| | - Jinghua Li
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
- Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, 510080, China.
- Key Laboratory of Health Informatics of Guangdong Province, Sun Yat-sen University, Guangzhou, 510080, China.
- Guangzhou Joint Research Center for Disease Surveillance, Early Warning and Risk Assessment, Guangzhou, 510080, China.
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, 100191, China.
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China.
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Effect of a Community-Based Hepatitis B Virus Infection Detection Combined with Vaccination Program in China. Vaccines (Basel) 2021; 10:vaccines10010019. [PMID: 35062680 PMCID: PMC8777927 DOI: 10.3390/vaccines10010019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 12/16/2021] [Accepted: 12/21/2021] [Indexed: 12/26/2022] Open
Abstract
Evidence on the effectiveness of hepatitis B virus (HBV) infection screening and vaccination programs remains rare in China. We used a quasi-experimental method, propensity score matching, to evaluate the effects of a community-based HBV infection detection combined with vaccination (HBVIDV) program in a pilot. Data were retrieved from the HBVIDV program implemented between July 2019 and June 2020. Outcomes were the difference between the treatment and control groups in hepatitis B vaccination (≥1 dose), hepatitis B vaccine series completion (≥3 doses), and serologic evidence of vaccine-mediated immunity. Altogether, 26,180 individuals were included, where 6160 (23.5%) individuals were assigned to the treatment group, and 20,020 (76.5%) individuals were assigned to the control group. After propensity score matching, 5793 individuals were matched. The rates of hepatitis B vaccination, hepatitis B vaccine series completion, and prevalence of vaccine-mediated immunity in the treatment and control groups were 29.0% vs. 17.8%, 22.1% vs. 13.1%, and 38.2% vs. 27.6%, respectively. The HBVIDV program was significantly associated with increased hepatitis B vaccination rate (OR, 1.884, 95% CI 1.725-2.057), hepatitis B vaccine series completion rate (OR, 1.872, 95% CI 1.696-2.065), and prevalence of vaccine-mediated immunity (OR, 1.623, 95% CI 1.501-1.755). The greater magnitude of association between HBVIDV program and outcomes was observed among adults aged 35-54 years and adults who live in rural areas. The HBVIDV program was effective in increasing the hepatitis B vaccination rate, hepatitis B vaccine series completion rate, and prevalence of vaccine-mediated immunity among adults in the pilot. Further focusing the program on special populations and regions may produce more effective results.
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