Skip to main content Accessibility help
×
×
Home

A system dynamics modelling simulation based on a cohort of hepatitis B epidemic research in east China community

  • Zhixin Yu (a1), Min Deng (a1), Chunting Peng (a1), Xue Song (a1), Yi Chen (a1), Xue Zhang (a1), Qiuxia Liu (a1), Yuchuan Li (a1), Haiyin Jiang (a1), Xiaolan Xu (a1), Liya Pan (a1), Jing Yuan (a2) and Bing Ruan (a1)...

Abstract

Hepatitis B constitutes a severe public health challenge in China. The Community-based Collaborative Innovation hepatitis B (CCI-HBV) project is a national epidemiological study of hepatitis B and has been conducting a comprehensive intervention in southern Zhejiang since 2009.

The comprehensive intervention in CCI-HBV areas includes the dynamic hepatitis B screening in local residents, the normalised treatment for hepatitis B infections and the upcoming full-aged hepatitis B vaccination. After two rounds of screening (each round taking for 4 years), the initial epidemiological baseline of hepatitis B in Qinggang was obtained, a coastal community in east China. By combining key data and system dynamics modelling, the regional hepatitis B epidemic in 20 years was predicted.

There were 1041 HBsAg positive cases out of 12 228 people in Round 1 indicating HBV prevalence of 8.5%. Of the 13 146 people tested in Round 2, 1171 people were HBsAg positive, with a prevalence of 8.9%. By comparing the two rounds of screening, the HBV incidence rate of 0.192 per 100 person-years was observed. By consulting electronic medical records, the HBV onset rate of 0.533 per 100 person-years was obtained. We generated a simulated model to replicate the real-world situation for the next two decades. To evaluate the effect of interventions on regional HBV prevalence, three comparative experiments were conducted.

In this study, the regional hepatitis B epidemic in 20 years was predicted and compared with HBV prevalence under different interventions. Owing to the existing challenges in research methodology, this study combined HBV field research and simulation to provide a system dynamics model with close-to-real key data to improve prediction accuracy. The simulation also provided a prompt guidance for the field implementation.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

      Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      A system dynamics modelling simulation based on a cohort of hepatitis B epidemic research in east China community
      Available formats
      ×

      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

      A system dynamics modelling simulation based on a cohort of hepatitis B epidemic research in east China community
      Available formats
      ×

      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

      A system dynamics modelling simulation based on a cohort of hepatitis B epidemic research in east China community
      Available formats
      ×

Copyright

This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.

Corresponding author

Author for correspondence: Bing Ruan, E-mail: ruanbing@zju.edu.cn

References

Hide All
1.Ott, JJ et al. (2012) Global epidemiology of hepatitis B virus infection: new estimates of age-specific HBsAg seroprevalence and endemicity. Vaccine 30, 22122219.
2.Chen, YS, Wang, XX and Shang, PH (2007) The study of tendency of hepatitis B virus surface antigen in Chinese population. Chinese Journal of Experimental and Clinical Infectious Diseases 1, 3640.
3.Trépo, C, Chan, HLY and Lok, A (2014) Hepatitis B virus infection. The Lancet 384, 20532063.
4.Howell, J et al. (2014) Overview of hepatitis B prevalence, prevention, and management in the Pacific Islands and Territories. Journal of Gastroenterology and Hepatology 29, 18541866.
5.Liang, X et al. (2009) Epidemiological serosurvey of hepatitis B in China–declining HBV prevalence due to hepatitis B vaccination. Vaccine 27, 65506557.
6.Razavi-Shearer, D et al. (2018) Global prevalence, treatment, and prevention of hepatitis B virus infection in 2016: a modelling study. The Lancet Gastroenterology & Hepatology 3, 383403.
7.Yang, S et al. (2015) Protective immune barrier against hepatitis B is needed in individuals born before infant HBV vaccination program in China. Scientific Report 5, 18334.
8.Yang, S et al. (2017) Prevalence and influencing factors of hepatitis B among a rural residential population in Zhejiang Province, China: a cross-sectional study. BMJ Open 7, e014947.
9.Ogata, K et al. (2013) New computer model for prediction of individual 10-year mortality on the basis of conventional atherosclerotic risk factors. Atherosclerosis 227, 159164.
10.Kaul, H and Ventikos, Y (2015) Investigating biocomplexity through the agent-based paradigm. Brief Bioinform 16, 137152.
11.Jones, AP et al. (2006) Understanding diabetes population dynamics through simulation modeling and experimentation. American Journal of Public Health 96, 488494.
12.Li, LJ and Li, L (ed.) (2012) Standard Operation Procedure for major Projects of National Science and Technology of Infectious Disease: The Community Comprehensive Prevention and Control of major Infectious Diseases, vol 89 Beijing: Science Press,.
13.Fattovich, G, Bortolotti, F and Donato, F (2008) Natural history of chronic hepatitis B: special emphasis on disease progression and prognostic factors. Journal of Hepatology 48, 335352.
14.Honeycutt, AA et al. (2003) A dynamic Markov model for forecasting diabetes prevalence in the United States through 2050. Health Care Management Science 6, 155164.
15.Yu, R, Fan, R and Hou, J (2014) Chronic hepatitis B virus infection: epidemiology, prevention, and treatment in China. Frontiers of Medicine 8, 135144.
16.National Bureau of Statistics of China Web site. Population by region in 1–1. Available at http://www.stats.gov.cn/tjsj/pcsj/rkpc/6rp/indexch.htm. Accessed in 2010.
17.Torpy, JM, Burke, AE and Golub, RM (2011) Hepatitis b. JAMA 305, 15001500.
18.Yim, HJ and Lok, AS-F (2006) Natural history of chronic hepatitis B virus infection: what we knew in 1981 and what we know in 2005. Hepatology (baltimore, Md ) 43, S173S181.
19.Caley, M et al. (2012) Differences in hepatitis B infection rate between ethnic groups in antenatal women in Birmingham, United Kingdom, May 2004 to December 2008. Eurosurveillance 17, 2631.
20.Chinese Centre for Disease Control and Prevention. National Data of Notifiable Diseases in2014.http://www.moh.gov.cn/jkj/s3578/201502/847c041a3bac4c3e844f17309be0cabd.shtml. Accessed 2016.
21.Yang, SG et al. (2012) Effectiveness of HBV vaccination in infants and prediction of HBV prevalence trend under new vaccination plan: findings of a large-scale investigation. PLoS One 7, e47808.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Epidemiology & Infection
  • ISSN: 0950-2688
  • EISSN: 1469-4409
  • URL: /core/journals/epidemiology-and-infection
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Keywords

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed