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Key elements in a surveillance system Patrick Rolland EPIET / EUPHEM Intro Course 2012

Key elements in a surveillance system Patrick Rolland EPIET / EUPHEM Intro Course 2012. &. Le fil rouge in surveillance?. Surveillance is Information for action!. Good reminder: surveillance?. Langmuir AD., 1963

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Key elements in a surveillance system Patrick Rolland EPIET / EUPHEM Intro Course 2012

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  1. Key elements in a surveillance system Patrick Rolland EPIET / EUPHEM Intro Course 2012 &

  2. Le fil rougein surveillance? Surveillance is Information for action!

  3. Good reminder: surveillance? • Langmuir AD., 1963 “Systematic collection, consolidation, analysis and dissemination of data on specific disease” • Thacker SB., 1996 • “The final link is the application of these data to prevention and control”

  4. Good reminder: surveillance loop Objectives Evaluation Data collection Data analysis Action! Information

  5. Aim and content of the lecture • Aim: To understand key elements in a surveillance system • From a clear understanding of the purpose • To the right dissemination of information • Content • Main objectives of a surveillance system • Checklist of key elements, step by step

  6. Main objectives of a surveillance system

  7. Main objectives • Describe: produce information in terms of TPP • Alert: detect epidemics or emerging events • Evaluate: assess prevention or control measures • And also: • Generate hypotheses for research • Detect changes in health practice • Plan public health actions and resources

  8. But keep in mind the goal! Surveillance is Information for action! By implementation of prevention and control measures In order to reduce morbidityand mortality

  9. Describe: Time = Graph Weekly incidence rate of flu-likesyndromes, 2009-2012, France Source: GP network “Réseau unifié” Incidence (per 100,000) Week

  10. Describe: Place = Map Weekly incidence rate of acute diarrhea (per 100,000) 1 to 7 march 2012, France Source: GP network “Réseau sentinelles”

  11. Describe: Person = Table Characteristicsof persons Severe cases of influenza, winter 2011-2012, France Source: Intensive care units Network Burden

  12. Exceedence Alert: detect an epidemic Weekly incidence of flu-like syndromes, 2007-2012, France Source: GP network “Réseau sentinelles” Incidence Threshold Incidence (per 100,000) Week

  13. Emergence of W135 Alert: detect an emerging phenomena Invasive meningococcal infectionsby serogroup B, C, W135 et Y, 1985-2006, France Source: InVS, NRC for meningococci B Y C W135 Number of cases Year

  14. Vaccination implementation Evaluate: prevention/control measure Cases of Pertussis, England and Wales, 1940-1999 80 40 Number of cases (x 1000) Vaccinate coverage (%) 0 Year

  15. Reinforced surveillanceNew investigation guideUrine antigen testing Evaluate: prevention/control measure Cases of legionellosis, 1988-2011, France Source: Notifiable disease, InVS No cases Incidence Number of cases Incidence (per 100,000) Year

  16. Key elements in a surveillance system

  17. Key elements • Justification of implementation • Objectives of the system • Types of system • Case definition • Population under surveillance • Data providers and data sources • Data elements and data collecting tools • Flow chart and data transmission • Data validation and data analysis • Dissemination and communication data • Human and financial resources • Data security and confidentiality • Evaluation of system

  18. Key elements • Justification of implementation • Objectives of the system • Types of system • Case definition • Population under surveillance • Data providers and data sources • Data elements and data collecting tools • Flow chart and data transmission • Data validation and data analysis • Dissemination and communication data • Human and financial resources • Data security and confidentiality • Evaluation of system

  19. Justification of implementation • Ask yourself two main questions: • Should this event be under surveillance? • High frequency? • High severity? • High socioeconomic cost? • Do some prevention or control measures exist? • And these two additional questions: • Do we have existing data that already answer? • Do we have resources to set up a new system?

  20. Health events under surveillance • Infectious diseases • Notifiable diseases • Health-care associated infections (HCAI) • Vaccine-preventable diseases • Food and waterborne diseases • Sexually transmitted infections (STI) • Zoonoses • Vector-borne diseases • But also?

  21. Health events under surveillance • Chronic diseases and injuries: cancers, accidents, traumas, cardiovascular diseases, etc. • Occupational health: cancers, musculoskeletal disorders, respiratory diseases, mental health, etc. • Environmental hazards: air pollution, ionizing radiations, heat/cool waves, water/soil pollution, etc.

  22. Key elements • Justification of implementation • Objectives of the system • Types of system • Case definition • Population under surveillance • Data providers and data sources • Data elements and data collecting tools • Flow chart and data transmission • Data validation and data analysis • Dissemination and communication data • Human and financial resources • Data security and confidentiality • Evaluation of system

  23. Objectives of the system • Primary objective: To describe a health-related event in population-based or in a specific population • With two possible aims (sometimes both): • To alertby early detection of epidemics or emerging pathologies that need timely action • To evaluatethe efficiency of prevention orcontrol measures

  24. Key elements • Justification of implementation • Objectives of the system • Types of system • Case definition • Population under surveillance • Data providers and data sources • Data elements and data collecting tools • Flow chart and data transmission • Data validation and data analysis • Dissemination and communication data • Human and financial resources • Data security and confidentiality • Evaluation of system

  25. Passive and active system • Consideration useful for discussion • Passive: “The data come to you” • Data collection based on existing information • Simple, not burdensome but could be incomplete • E.g.: notifiable diseases, deaths, emergency data • Active: “You go towards the data” • Data collection specially set up • Good quality of data but required resources • E.g. : injuries, non-notifiable infectious diseases, etc.

  26. E.g. of passive system % of gastroenteritis among emergency consultations, seasons 2010-2011 and 2011-2012, Aquitaine, France Proportion of cases Week

  27. E.g. of active system Cases of envenomation by Physalia Physalis reported bylifeguards, Aquitaine Atlantic Coast, Summer 2011, France Number of cases Day

  28. Exhaustive vs. sentinel system • Important consideration for data analysis • Severe diseases or low-frequency diseases requiring timely action • Exhaustive system (= all providers) • E.g.: cancers registries, notifiable diseases • High-frequency diseases or less-severe diseases • Sentinel system (= selected providers) • E.g.: seasonal flu, occupational diseases (except cancers)

  29. 3. Skin cancer 2. Colorectal cancer 1. Breast cancer E.g. of exhaustive system Cancers among women, Year 2005, Gironde, France Source: Cancerregistry of Gironde Cancer causes Number of cases

  30. E.g. of sentinel system Prevalence of occupational diseases (except cancers),Year 2010, Region of Aquitaine, France Source: Sentinel Network of occupational physicians (n=92)

  31. Case vs. syndromic system • Case system (traditional system) • Targets a defined health-related event • E.g.: mesothelioma, Lyme disease, diabetes, etc.. • Syndromic system (“before diagnosis”) • For early detection, evaluation of event impact • Based on existing activity data, real-time collection, analysis and interpretation data • E.g.: emergency services, virology labs, deaths certificates, medicine sales, absence in schools, etc.

  32. E.g. of case system Occupations at risk for mesothelioma, France Source: Program of Mesothelioma Surveillance (1998-2012), InVS Occupations Odds-ratio (95% CI)

  33. E.g. of syndromic system % of gastroenteritis among emergency consultations, seasons 2010-2011 and 2011-2012, Aquitaine, France Proportion of cases Week

  34. Key elements • Justification of implementation • Objectives of the system • Types of system • Case definition • Population under surveillance • Data providers and data sources • Data elements and data collecting tools • Flow chart and data transmission • Data validation and data analysis • Dissemination and communication data • Human and financial resources • Data security and confidentiality • Evaluation of system

  35. Case definition • The “heart” of the system! • Must be clear and simple • Based on criteria:clinical, biological, epidemiological • May include: • Classification (possible, probable, confirmed) • TPP (Time-Place-Person) information

  36. Clinical criteria E.g. for measles definition as notifiable disease Laboratory criteria Source: Case definitions of notifiable diseases Commission Decision 2008/426/EC – 28-IV-2008 Epidemiological criteria Case classification

  37. Key elements • Justification of implementation • Objectives of the system • Types of system • Case definition • Population under surveillance • Data providers and data sources • Data elements and data collecting tools • Flow chart of data and data transmission • Data validation and data analysis • Dissemination and communication data • Human and financial resources • Data security and confidentiality • Evaluation of system

  38. Population under surveillance • Depends on characteristics of health-event • E.g.: Hemolytic Uremic Syndrome (HUS) • Rare disease that predominantly affects children, needs timely action in outbreak • Population under surveillance (France): children (< 15 years) hosted in pediatric and nephrology hospital services (N=31)

  39. Key elements • Justification of implementation • Objectives of the system • Types of system • Case definition • Population under surveillance • Data providers and data sources • Data elements and data collecting tools • Flow chart and data transmission • Data validation and data analysis • Dissemination and communication data • Human and financial resources • Data security and confidentiality • Evaluation of system

  40. Data providers and data sources • Data providers: health professionals, laboratories, health insurance funds, civil status offices, etc. • Data sources • Administrative: death certificates, hospital systems, etc. • Medical: patients folders, notifiable diseases, etc. • Biological: virology, bacteriology, toxicology samples • Environmental: air pollution sensors, individual ionizing radiations card for exposed workers, etc.

  41. One NRC perinfectious disease E.g. data provider: NRC (France) 47 National Reference Centers and 34 Associated Laboratories Anaérobies et Botulisme (LA) Arbovirus (LA) ATNC Brucella Borrelia (LA) Campylobacter & Helicobacter Charbon (LA) Chlamydiae Cytomégalovirus Enterovirus Escherichiacoli & Shigella (LA) Francisellatularensis Gonocoques Haemophilusinfluenzae Legionella Leishmania Mycobactéries et résistance des mycobactéries Paludisme (2 co-responsables) Pneumocoques Résistance aux antibiotiques (LA) Rickettsia, Coxellia & Bartonella Virus de la rougeole Staphylocoques VIH StreptocoquesVirus Influenza Syphilis Virus entériques Trichinella Virus des hépatites A et E Toxoplasmose Virus des hépatites B, C et Delta Arbovirus Arbovirus & influenza virus en AG Charbon Borrelia Anaérobies et Botulisme Chimiorésistance du paludisme en Antilles Guyane Coqueluche et autres bordetelloses Corynebactéries toxinogènes Escherichiacoli & Shigella Fièvres hémorragiques virales Leptospires Listeria Méningocoques Mycologie et antifongiques Peste et autres yersinioses Rage Salmonella Résistance aux antibiotiques Streptocoques (LA) Virus des Hépatites B & C (LA) Vibrions et cholera Virus Influenza 15 NRC and 3 AL Pasteur Institute (Paris) 32 NRC and 31 AL Within hospitals, universities, other research institutes

  42. E.g. data source: ND (France) 27 notifiable diseases (ND) require surveillance and timely action Frequent ND (n=14) Infrequent ND (n=10) • Botulisme • Brucellose • Chikungunya • Dengue • Fièvres typhoïdes et paratyphoïdes • Hépatite aiguë A • Infections invasives à méningocoques • Légionellose • Listériose • Rougeole • Saturnisme de l’enfant mineur • MCJ et ESST • Toxi-infection alimentaire collective • Tuberculose • Choléra (RSI) • Diphtérie • Fièvres hémorragiques africaines • Fièvre jaune (RSI) • Paludisme autochtone et paludisme importés dans DOM • Peste (RSI) • Poliomyélite • Rage • Typhus exanthématique Bioterrorism-related ND (n=3) • Charbon, Tularémie, Variole 4 ND require surveillance only • Infection à VIH quel qu’en soit le stade • Hépatite aiguë B • Tétanos • Mésothéliome • (entrée en 2012)

  43. Key elements • Justification of implementation • Objectives of the system • Types of system • Case definition • Population under surveillance • Data providers and data sources • Data elements and data collecting tools • Flow chart of data and data transmission • Data validation and data analysis • Dissemination and communication data • Human and financial resources • Data security and confidentiality • Evaluation of system

  44. Nominative data on patient and provider E.g. French form for mesothelioma notiable disease Anonymous data on patient diagnosis (by clinician&pathologist) Dates and signatures of provider and sanitary authority

  45. Key elements • Justification of implementation • Objectives of the system • Types of system • Case definition • Population under surveillance • Data providers and data sources • Data elements and data collecting tools • Flow chart and data transmission • Data validation and data analysis • Dissemination and communication data • Human and financial resources • Data security and confidentiality • Evaluation of system

  46. E.g. of flow chart: ND (France) Politic of Health Public Health High Council HealthRegional Agencies Declaration Patient Ministry of Health Alert Health professionals, laboratories, etc. ReferenceCenters Alert Partners National/International Experts Networks Clinicians/Pathologists

  47. Data transmission • Reliable and fast • Electronic: e-mails, websites • And: phone, fax and mail • Low frequency • Daily • Weekly • Monthly • Secure • Regularity, punctuality, exhaustiveness • And don’t forget the “Zero reporting”

  48. Key elements • Justification of implementation • Objectives of the system • Types of system • Case definition • Population under surveillance • Data providers and data sources • Data elements and data collecting tools • Flow chart and data transmission • Data validation and data analysis • Dissemination and communication data • Human and financial resources • Data security and confidentiality • Evaluation of system

  49. Data validation and data analysis • Data validation • Missing data • Duplicates • Data quality • Data analysis • Indicators: frequency, severity • Methods: descriptive, analytical • Illustrations: tables, graphs and maps • Keep in mind: Time-Place-Person!

  50. Temperature 2003 1999-2002 2003 Deaths 1999-2002 E.g. of data analysis: time series Daily deaths, summers 1999-2002 vs. 2003, France Source: Syndromic Program, InVS Number of deaths Temperature (°C) Day (25 June to 19 august)

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