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Integration of Epidemiological and Laboratory Data

Integration of Epidemiological and Laboratory Data. -- Challenges and Perspectives in China. Dr. Zhen XU Branch of Respiratory Disease Prevention and Control Division for Disease Control and Emergency Response Chinese Center for Disease Control and Prevention June, 2011.

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Integration of Epidemiological and Laboratory Data

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  1. Integration of Epidemiological and Laboratory Data --Challenges and Perspectives in China Dr. Zhen XU Branch of Respiratory Disease Prevention and Control Division for Disease Control and Emergency Response Chinese Center for Disease Control and Prevention June, 2011

  2. Influenza Surveillance

  3. Influenza related surveillance currently in China

  4. Influenza information system • Integration of ILI sentinel surveillance system and ILI outbreak event report system • Data input, query and auto analysis • Lab info management • Surveillance quality monitoring

  5. National ILI sentinel surveillance 5 • Epidemiology Surveillance • Diagnosis and Registry: daily • Reporting of ILI case: weekly • Collect and analyze the surveillance data • Laboratory Surveillance • Specimen collection: 5-15 nose ＆ throat swabs from ILI cases per week per hospital • Lab detection: PCR test or virus isolation, antigenic and genetic analysis, antiviral resistance

  6. ILI surveillance information reporting ILI reporting ILI sentinel hospitals Specimens collection Send specimens to labs Specimens info & results Network laboratories Detection Isolates to CCDC Re-identification CCDC

  7. Real-time Database- ILI epi data • Input data of ILI counts and ILI% by week • and age group; • Data query by date, by week, by age group, • by hospital and by area ;

  8. Real-time Database- ILI lab data • Input data of PCR and virus isolation results • by specimen within 48h; • Data query by patient, by date, by week, by • hospital and by area ;

  9. Real-time Database- ILI outbreak • event-based report • basic info of ILI outbreak: major symptoms, case number, lab results, duration and location of the outbreak • progress report of outbreak response;

  10. Automatic data analysis ILI analysis Virus typing Surveillance quality monitoring

  11. Real-time Database Information System for serological surveillance of Occupational exposure population and environment surveillance environment surveillance data Serological surveillance data

  12. Information dissemination: Weekly Report Influenza Weekly Report www.cnic.org.cn/eng www.cnic.org.cn

  13. Report Weekly Surveillance Data to FluNet Information Sharing FluID

  14. SARIsentinel surveillance • To monitor the severity of Pandemic H1N1 and understand the characteristics of SARI cases caused by pdm H1N1 • Following WHO case definition • Support by MOH and EID program • Data source: • Epi data by case: Respiratory, Internal ICU, and Infectious Departments from 10 hospitals • Lab data: 10 network Labs where the hospitals located • Data report: EPI Database weekly sent from hospitals and labs by email • Data sharing: Brief report sent to hospitals and labs regularly

  15. Notifiable disease reporting system • Most are clinical cases; • No virological info; • Limited use for flu surveillance

  16. Research of pandemic H1N1 Case patients hospitalized with 2009 pandemic influenza A (H1N1) virus infection, by date of onset, China, Sep 2009–Feb 2010. ICU,

  17. Challenges • Still lack of a comprehensive surveillance system to oversee the virus and diseases caused by flu virus • Characteristics and burden of mild, severe and fatal case • Maintain the current giant ILI network—cost, willingness and enthusiasm • Translating data into practice is much more important than collecting data • Surveillance data, research data • Risk assessment of surveillance data • Quality monitoring didn’t followed by in time quality improvement action • SARI surveillance info is independent from ILI system. Mild and severe case caused by flu virus cannot be linked well

  18. Challenges • Vaccine gap • Supply: 30m doses VS 570m population • Capacity: 126m doses VS 570m population • Vaccination strategy • Annual technical recommendations for target population only • Flu vaccination not covered by national government or medical insurance • Beijing is the only city to provide the free vaccination service to local population: ﹥65yrs, primary and middle school students

  19. Future plans Use the data for vaccination policy making • Improve the sentinel SARI surveillance • Internet-based reporting of epi and lab data • Integration with HIS and LIS in hospitals • Publication and sharing of SARI findings • Modeling the ILI seasonal pattern • Application of early warning based on long-term and good-quality flu data in pilot areas • Describe the burden of severe and fatal cases caused by flu virus • Population-based inpatients surveillance • DSP site: ICD code-based deaths analysis

  20. Integrated information system Submission Data Entry Search Surveillance Information System Sequence Database Result feedback Download Analysis&Report Share Information Platform Security check Receipt Lab Data Management Website Public propaganda Take&Return Technical support Result Entry New Security check

  21. Thank you! 谢 谢！

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