Superstorm Sandy Mortality Surveillance in New York City

1. Superstorm Sandy Mortality Surveillancein New York City Elizabeth “Beth” Begier, MD, MPH Assistant Commissioner, Bureau of Vital Statistics NYC Department of Health and Mental Hygiene

2. Overview • Sandy Impact and Public Health Threats • NYC Death Registration System • Mortality Surveillance Activities/Findings • Challenges and Lessons Learned • Next Steps

3. Hurricane Sandy • October 29, 2012 post-tropical cyclone hit 100 miles south of NYC • Record storm surge flooding (4 to 11 ft. predicted vs. 14 actual) • Wind-downed trees and power lines caused fatal drowning and injuries (direct mortality)

4. NYC Sandy Impacts and Hazards • Widespread power and heat outages resultingcold stress and lack of refrigeration (some prolonged building-related issues) • High rise buildings lost elevators and running water • Mobility-impaired stranded • Transit disruption • Total subway/transit shutdown followed by slow phased resumption • Bridge and tunnel closures • Gasoline shortages

5. NYC Sandy Impacts and Hazards • Evacuation of 4 hospitals (1,262 pts.) and 17 nursing homes (2507 residents) • Disruption of ambulatory health care and pharmacy access • Respiratory hazards and concerns • Indoor demolition and flooded building cleanup • Outdoor dust from debris movement • Emissions from temporary generators and boilers • Mental health stress and loss of 300 psychiatric inpatient beds due to evacuations • Injuries relating to rebuilding efforts

6. Routine Death Registration in NYC • NYC Health Code Death Reporting Requirements: • 24 or less hours for certification • Clinician's report of decedent's name, sex, time/date/place of death, and free-text cause of death • Medical providers start “case” in EDRS • 72 hours or less for FD completes and sends for registration • Decedent's address, DOB, and other demographics completed by funeral director • After FD completes, “case” goes electronically to death registration staff for review and registration • 94% of deaths reported fully electronically reported via EDRS

7. Death Registration during/after Sandy • 1 registration staff member stayed at Manhattan office through storm (Steve S relieved him morning after) • Bureau of Vital Statistics’ Office building in lower Manhattan closed for ~1 week due to power and heat outage that began overnight during storm • Relocated Registration Unit morning after hurricane to alternate site in Brooklyn (Thanks Flor Betancourt!) • EDRS up during/after storm; no prolonged outages • A few hospitals initially with internet connectivity issues preventing use of EDRS

8. Tracking: Deaths directly related to Hurricane • Most of such deaths initially registered by MEs with cause pending • ME notified us via email of deaths believed to be Hurricane-related after preliminary investigation • All CODs reviewed in real-time by registration unit for possible ME cases (per routine) • Added pop-up to EDRS cause-of-death page to prompt ME referrals for any deaths related to storm • Conducted free-text searches of DC text fields post-registration for injury deaths as double check

9. Tracking: Indirectly Related Deaths • Health Commissioner very concerned about unrecognized morbidity and mortality increases associated with extensive environmental hazards and stresses in aftermath • Syndromic surveillance for morbidity • Initiated mortality surveillance • Timeframes • Categorized 10 days following hurricane as immediate aftermath (1/1–10) • Rest of time examined as rolling post-aftermath

10. Mortality Surveillance – Approach All-cause mortality counts by date to identify excess mortality of any cause: primary focus post-event • Used pre-registration certified deaths to enhance timeliness of close to complete counts • Concerned about decreased registration timeliness 2° to storm-related disruptions • Adjusted prior year comparison counts for “reporting lag”, i.e., limited to deaths certified by same date in prior years • Had to add certification date to stats file (only had registration date)

11. Mortality Surveillance – Approach • Categorized deaths by age and cause with post-registration data • Cause-of-death routinely ICD-10 coded locally by NYC nosologists 1st business day post-registration • Seemed too complicated to change routine to pre-registration on fly • Date of birth not on certification – provided by FD

12. Mortality Surveillance:Neighborhood Flood Levels • Categorized deaths by decedent residence neighborhood flood levels with post-registration data • Quickly geocoded residence address to census tract level, including quickly resolving manual rejects • Quickly recoded prior years to 2010 census for accurate comparisons • Do not get decedent address until registration (from funeral directors) • Excluded nursing home deaths to focus on deaths occurring in community • Separate analysis done for evacuated nursing homes

13. Mortality – Other investigations • Initial assessment of Hospital evacuations • Calculated mortality counts at receiving hospitals in 10 days following storm • Added expected death counts for evacuated hospitals to receiving hospitals’ baselines based on count of evacuees received to improve comparability • Did not have names or acuity of transferees (ICU, etc) • Initial look at nursing home evacuations • Identified decadents with evacuated nursing homes as their residence address • Compared counts for 4 weeks post-sandy to 2 prior years

14. RESults

15. Results: Timeliness • Time to certification & registration increased during/after storm compared to current and prior year baselines

16. Timeliness by Date– Certification:Deaths Certified in <24 hours in Blue Percent of Registrations

17. Timeliness by Date– Registration:Day 1 Blue, Day 2 Red, Day 3 Green Percent of Registrations

18. Median Days to Registration from Death by Percent of Census Tract Flooded and Year: Oct 29–Nov 10

19. Mortality Surveillance - Findings • Relied on ME email notification to BVS for timely notification of preliminary Sandy-related deaths • N=43; Major causes drowning (81%), blunt trauma (16%) • >50% on Staten Island, nearly half aged 65+ • No Sandy-related deaths found through free-text search of post-registration data for injury terms that had not already sent by ME

20. Sample Early Table: Number of Certified Daily Deaths from All Causes, Nov 1–19, 2010-2012, NYC, Reported As of 21NOV2012 (Deaths Certified Through 11/20 of Each Year)

21. Sample Early Table: T Number of Certified Daily Deaths from All Causes, Nov 1–19, 2010-2012, NYC, Reported As of 21NOV2012 (Deaths Certified Through 11/20 of Each Year) • 11/19/2012 on 11/21 report: • Deaths certified by 11/20: 111 • Adjusted baseline 101 and 111 deaths • indicated not beyond historical norms • That day would eventually get to 138 deaths

23. Sample Table: Analysis by Flooding Level

24. Sample Table: Analysis by Flooding Level November 1–10, 2010-2012 • Overall results: • 0% flooded: 111% of baseline • >0-10%: 109% of baseline • >10-75%: 105% of baseline • >75%: 101% of baseline

25. Investigating Death Increase in Immediate post-Sandy Period • Up 11% (156 deaths) • Not concentrated in flooded areas • Not concentrated in any specific age/cause group • Resolved after about 10 days as most of city operations returned to normal outside of flooded areas • No increase with past subway shutdowns seen • Later second rise in deaths found to related to onset of influenza season

26. Investigating Death Increase in Immediate Post-Sandy Period: Healthcare Facility Evacuations • Deaths among evacuated nursing home residents up only 5-6 over prior years (preliminary) • Deaths at receiving hospitals up ~20-25 deaths after adjustment of baselines (preliminary) • No adjustment made for medical acuity of transferees • Unable to examine by transferring hospital • No deaths reported to ME as transfer-related (would be reportable in NYC)

27. Challenges I • Time-consuming ad hoc SQL queries required to extract needed mortality data from EDRS to get certified data and additional data elements needed • Needed to quickly resolve current year geocoding rejects and recode prior years to 2010 census • SAS programs needed to be urgently developed for reports, delaying results despite timely data transfer from death reporters (ideally have canned reports/programs ready) • De-duplicating pre-registration death certifications for analysis added extra step to analysis • Difficult to account for evacuation impact

28. Lessons Learned • EDRS effectively adapted to provide disaster-related mortality surveillance • Pre-registration records increase timeliness but require staff with SQL programming skills • Local MMDS software and nosologists essential to timely cause of death coding • Zip code proved too coarse a measure in urban area to accurately categorize areas by flood levels • Few zip codes with majority flooded and many with just small area affected • Need to restricting comparison data by certification/registration date 2°reporting lag • Post-registration free-text in injury searches not helpful in our setting

29. Next Steps I • Planned investigation for potential excess all-cause mortality (some pending grant-related resources) • Time-series analysis of deaths counts to better account for known environmental factors that influence daily death counts (EH) • Use of hospital discharge data to characterize death increase • More detailed analysis of possible transfer related mortality using linked hospital discharge data and mortality data (account for medical acuity) • More detailed analysis of possible nursing home related death transfers with IJE data and possibly chart reviews given small counts

30. Next Steps II • Consider adding DOB and address to DC certification screens to allow for age and neighborhood analyses on more timely certified only data • Consider operationalizing reports for expected emergencies (applied for staff as part syndromic surveillance program request) • Advocate to NCHS for access to updated MMDS software to allow this kind of work for emergency response

31. Food for Thought • Most post-disaster mortality analyses not based on Vital Statistics • Recent MMWR used red cross data • Stand alone mortality reporting systems have been used in US for other hurricanes • Issues are timeliness and lack of accurate capture of disaster-related deaths in some areas (e.g., COD “fall” but does not mention Hurricane as cause)

32. CoAuthors • Renata Howland, MPH (CSTE epi fellow) • WenhuiLi, PhD (in attendance at NAPHSIS) • Ann Madsen, PhD, MPH • Howard Wong, MSc • Tara Das, PhD (in attendance at NAPHSIS) • Thomas Matte, MD, MPH • Catherine Stayton, DrPH, MPH

35. All Cause Death Counts, Nov 1–10, 2010–2012

36. Death Registration

37. Mortality Surveillance Findings • Pre-registration certificates provided timely and relatively high quality data • Address most likely to be missing (80%), delaying geographical analyses • Retrospective comparison between queried records and registered records showed high agreement (94%) where fields were present