What s New in Surveillance Dona Schneider Ph D

What’s New in Surveillance Dona Schneider, Ph. D, MPH

§ Surveillance is the ongoing, systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice, closely integrated with the timely feedback of these data to those who need to know. Centers for Disease Control Examples: Morbidity and Mortality Weekly Report (MMWR) Disease Registries

Surveillance for communicable diseases remains important… § The world population is highly mobile § International travel and troop movements increase the risk of communicable disease transmission § Migration for war and famine, and voluntary immigration increase communicable disease risk § Naturally occurring disease is not our only threat

Types of Surveillance § Passive § Inexpensive, provider-initiated § Good for monitoring large numbers of typical health events § Under-reporting is a problem § Active § More expensive, Health Department-initiated § Good for detecting small numbers of unusual health events § Enhanced § Rapid reporting and communication between surveillance agencies and stakeholders § Best for detecting outbreaks and potentially severe public health problems

New and complex disease entities must also be monitored… § New syndromes may emerge that present in an atypical manner § Syndromic surveillance uses health-related data that precede diagnosis and signal a sufficient probability of a case or an outbreak to warrant further public health response

Example of Passive Surveillance § § § § § Day 1 - feels fine Day 2 - headaches, fever - buys Tylenol Day 3 - develops cough - calls nurse hotline Day 4 - Sees private doctor – dx with “flu” Day 5 - Worsens - calls ambulance seen in ED Day 6 - Admitted - “pneumonia” Day 7 - Critically ill - ICU Day 8 - Expires - “respiratory failure” Case enters surveillance system through an EDC

Example of Syndromic Surveillance § § § § § Day 1 - feels fine Pharmaceutical Sales Day 2 - headaches, fever - buys Tylenol Day 3 - develops cough - calls nurse hotline Nurse’s Hotline Day 4 - Sees private doctor - dx “flu” Managed Care Org Absenteeism records Day 5 - Worsens - calls ambulance - seen in ED Ambulance Dispatch (EMS) Day 6 - Admitted - “pneumonia” Day 7 - Critically ill - ICU ED Logs Day 8 - Expires - “respiratory failure” Case is under immediate investigation by the LHD because of the pre-diagnostic information gathered

We also watch for sentinel events… § Sentinel surveillance identifies preventable disease, disability, or deaths that warn that known methods of prevention, treatment or safety need to be improved § Sentinel events may have catastrophic outcomes – they may indicate the “tip of the iceberg”

Sentinel Surveillance § Monitors § Sites § Events § Providers § Vectors/animals

SENTINEL EVENT Nov 12, 2001 - 9: 17 am Flight AA 587 Crashes in Rockaways 7 -Zip Surveillance showed: 27 Obs / 10 Exp Resp Emergencies p<0. 001 31 Obs / 16 Exp Hospital Events p<0. 05

Investigation § Key Questions § True increase or natural variability? § Bioterrorism or self-limited illness? § Available Methods § § § Response team assigned Response team “Drills down” Query clinicians / laboratories Chart reviews Patient follow-up Increased diagnostic testing

Investigation § Chart review in one hospital (9 cases) § § § Smoke Inhalation (1 case) Atypical Chest Pain / Anxious (2 cases) Shortness of Breath - Psychiatric (1 case) Asthma Exacerbation (3 cases) URI/LRI (2 cases) § Checked same-day logs at 2 hospitals Increase not sustained

Surveillance can… § § § § Estimate the magnitude of a problem Determine geographic distribution of illness Detect epidemics/outbreaks Generate hypotheses, stimulate research Evaluate control measures Monitor changes in infectious agents Detect changes in health practices

Data Sources § § § § Notifiable diseases Laboratory specimens Vital records Sentinel surveillance Registries and surveys Administrative data systems Other data sources

Reported Cases of Food borne Botulism, United States, 1981 -2001 *Data from annual survey of State Epidemiologists and Directors of State Public Health Laboratories. Source: CDC. Summary of notifiable diseases. 2001.

Cases of Measles United States, 1966 -2001 Source: CDC. Summary of notifiable diseases. 2001.

Blood Lead Measurements 1975 -1981 110 18 Predicted blood lead 100 Lead used in gasoline 90 (thousands of tons) 80 16 Mean blood lead 14 levels g/dl Gasoline lead 70 Observed blood lead 12 60 50 10 40 30 1975 1976 1977 1978 1979 1980 1981 8 Year Source: Pirkle et al JAMA 272: 284 -91, 1994

Reported Salmonella Isolates, * United States, 1976 -2001 *Data from Public Health Laboratory Information System (PHLIS). Source: CDC. Summary of notifiable diseases. 2001.

National Notifiable Diseases Surveillance System (NNDSS) – produces the data in the MMWR § The reportable diseases list is revised periodically by the CSTE/CDC § States report diseases to the CDC voluntarily § Reporting is mandated at the state level § All states report the internationally quarantinable diseases (i. e. , cholera, plague, SARS, smallpox and yellow fever) in compliance with WHO International Health Regulations and a varied list of other diseases

In New Jersey § Reporting mandated by state law/regulation § Health care providers, laboratories report to the LHD (county) § LHD submits reports to the State § Reports transmitted by State to CDC primarily through National Electronic Telecommunications System for Surveillance (NETSS)

Other NCHS Data Systems for Surveillance Vital Statistics § National Infant Mortality Surveillance (NIMS) § Linked: • birth records • death records

SENSOR Sentinel Event Notification System for Occupational Risks

Recent Occupational Monitoring Efforts for Sentinel Events Include… § Biodetection Systems (BDS) in NJ post offices to detect anthrax and soon, ricin § Biowatch, an air monitoring system in New York City and 30 other cities

Weekly Communicable Disease Reporting System (CDRS) Alerts § Comparison of current 4 -week reporting period to previous reporting periods; generated at NJDHSS every Monday § by disease § by county § Increase over baseline (3 SD) triggers an alert for further investigation § Limitation: timeliness of reporting into CDRS

County Disease Amebiasis (Entamoeba histolytica) Campylobacteriosis (Campylobacter spp) Cum Reports Baseline 4 -wk Av SD Last 4 wk Period 211 5. 5 4. 6 8 1, 296 40. 6 17. 6 28 Flag √ √ Creutzfeld-Jakob disease 21 1. 0 0. 0 1 Cryptosporidiosis (Cryptosporidium spp. ) 52 1. 8 0. 8 1 Encephalitis, West Nile 42 5. 6 4. 3 2 171 7. 1 4. 5 3 1, 427 51. 9 9. 9 21 167 4. 3 1. 9 1 Enterohemorrhagic E. coli O 157: H 7 Giardiasis (Giardia lamblia) Haemophilus influenzae - invasive disease √ √ √

New Jersey Real Time Outbreak and Disease Surveillance OTC Surveillance Reports Through March 15, 2003 County ZIP Category Sale Base Mean Date 1 Sales in Date 1 Base Mean Date 2 (RODS) Sales in Date 2 Base Mean Date 3 Sales in Date 3 Diarrhea N 3. 9 8 (03/11/03) 3. 6 4 (03/12/03) 5. 3 11 (03/13/03) Antifever N 12. 4 6 (03/11/03) 11. 4 9 (03/12/03) 10. 0 20 (03/13/03) Diarrhea N 2. 7 3 (03/11/03) 3. 5 3 (03/12/03) 3. 6 8 (03/13/03) Cough/Cold N 35. 7 30 (03/10/03) 37. 8 30 (03/11/03) 18. 6 53 (03/12/03) Cough/Cold N 44. 0 42 (03/10/03) 52. 7 45 (03/11/03) 27. 0 72 (03/12/03) Cough/Cold N 192. 6 178 (03/11/03) 193. 3 181 (03/12/03) 167. 3 191 (03/13/03) Hydrocortisones N 2. 5 1 (03/10/03) 2. 1 2 (03/11/03) 1. 7 6 (03/12/03) Cough N 11. 3 14 (03/11/03) 7. 7 13 (03/12/03) 11. 3 15 (03/13/03) Antifever Y 9. 3 9 (03/11/03) 5. 1 4 (03/12/03) 3. 9 13 (03/13/03) Antifever Y 8. 8 11 (03/11/03) 7. 7 8 (03/12/03) 5. 7 20 (03/13/03)

Cipro and Doxycycline Prescriptions

National Electronic Disease Surveillance System (NEDSS) § Will replace NETSS, HIV/AIDS, TB, STD, vaccine-preventable and infectious disease reporting systems § Goal is to standardize health reporting and link laboratory, hospital and managed care data

Enhanced and Syndromic Surveillance § Costs § Implementation costs are modest § Operational costs = time of public health staff, investigations § Benefits § Possibily huge if early detection results § Strengthens traditional surveillance § Sets high standards for all data collection agencies

Good surveillance does not necessarily ensure the making of right decisions, but it reduces the chances of wrong ones. Alexander D. Langmuir NEJM 1963; 268: 182 -191

Free Resources World Health Organization DISMOD Software Centers for Disease Control Epi Info