Outline of this Presentation
1) Overview of Three CDC Investigations
a) Hoopa Valley Indian Reservation, CA, November 1999
b) Los Alamos National Laboratory, NM, May 2000
c) Bitterroot Valley, MT, November 2000
2) Conclusions and Future Directions
Assessment of Health Effects and Evaluation of
Interventions Associated with Forest Fires,
Hoopa, California, August-October 1999
Joshua Mott, PhD; Pamela Meyer, PhD; Eva Smith, MD;
David Mannino, MD; Emmett Chase MD; Stephen Redd, MD
EPI-AID 2000-09
Smoke from Wildand Fires in the area of the
Hoopa Valley Indian Reservation 9/30/1999
* Hoopa
The Big-Bar Fires, Shasta-Trinity Forest, 10/31/99
29 Miles
Hoopa Valley Indian Reservation
• Trinity River Valley, northern California
• 770 tribal households
• 57% poverty
• 32% unemployment
Temperature Inversions and Confining Topography
Ambient Particulate Matter < 10 Microns (PM10),
Hoopa Valley Indian Reservation,
September 28-October 28, 1999
700
600
µg/m3
500
PM10, 24-hour Average
Hazardous > 425 µg/m3 (24 hours)
400
300
200
Standard > 150 µg/m3 (24 hours)
100
0
Time period
Average Weekly PM10 Levels and Number of
Respiratory Visits to K’ima:w Medical Center,
By Week, August-November, 1998,1999
Pm10 (g/m3)
PM10 (g/m3)
400
Weekly # of respiratory visits
350
400
Weekly # of respiratory
visits
87
350
69
300
64 63
250
43 46 42 40
38
36
29
Aug.
Sep.
Oct.
1998
Nov.
200
39 37
150
100
300
250
55
54 53
200
31 32
29 27
24
65
150
22
26
100
50
50
0
0
Aug.
Sep.
Oct.
1999
Nov.
Number of Asthma Visits by Week of Visit and Average
Weekly PM10 Levels, Hoopa, CA,
1998, 1999*
400
400
40
350
40
350
300
300
30
30
250
250
200
20
200
20
150
100
10
150
100
10
50
0
0
1
2
3
4
5
6
7
8
9
1998
10
11
50
0
0
1
2
3
4
5
6
7
8
9
10
1999
* Average Number of People at Hotels funded by NCIDC in 1999 Wk 9: 66;
Wk 10: 444; Wk 11: 313
11
Number of COPD Visits by Week of Visit and Average
Weekly PM10 Levels, Hoopa, CA, 1998, 1999*
400
30
400
350
30
350
25
300
250
300
20
250
20
200
15
200
150
150
10
10
100
50
0
0
1
2
3
4
5
6
7
8
1998
9
10
11
100
5
50
0
0
1
2
3
4
5
6
7
8
9
10
1999
* Average Number of People at Hotels funded by NCIDC in 1999 Wk 9: 66;
Wk 10: 444; Wk 11: 313
11
Number of Visits for Headaches by Week of Visit and
Average Weekly PM10 Levels, Hoopa, CA, 1998, 1999*
400
15
400
350
350
300
300
10
250
250
200
200
150
150
5
100
100
50
50
0
1
2
3
4
5
6
7
8
9
1998
10
11
0
0
1
2
3
4
5
6
7
8
9
10
11
1999
* Average Number of People at Hotels funded by NCIDC in 1999 Wk 9: 66;
Wk 10: 444; Wk 11: 313
Number of Coronary Artery Disease Visits by Week of
Visit and Average Weekly PM10 Levels, Hoopa, CA, 1998,
1999*
400
40
16
400
14
350
12
300
10
250
200
8
200
150
6
150
100
4
100
50
2
50
0
0
350
300
30
250
20
10
0
1
2
3
4
5
6
1998
7
8
9
10
11
0
1
2
3
4
5
6
7
8
9
10
11
1999
* Average Number of People at Hotels funded by NCIDC in 1999 Wk 9: 66;
Wk 10: 444; Wk 11: 313
Selected Drugs Dispensed by KMC Pharmacy by
Year, Hoopa, CA, 1998-1999
350
319
Units Dispensed
300
250
200
178
150
106
100
50
Albuterol
Atrovent
Azmacort
Vancenase
24
56
50
22
15
0
1998
1999
Year
Interventions Implemented by Tribal Council
and Staff of K’ima:w Medical Center
September-October 1999
• Filtered and non-filtered masks
• Free hotel vouchers
• HEPA Cleaners
• Public service announcements (PSAs)
•
Preferential Distribution of Interventions
CDC arrived to assist in assessment of health effects and
evaluation of interventions – 11/08/99
Objectives of the CDC Investigation
• To assess the health impact of the smoke
 By pre-existing cardiopulmonary condition
• To evaluate the impact of interventions
Methods
•Cross-sectional survey
 No pre-existing conditions, N=197
 Pre-existing conditions, N=92
 Pre-existing conditions defined as…
“one or more visits in the last year for CAD,
asthma, COPD, or other lung disease”
•N=289, 78.5% response rate
Survey questions
• Measures of Exposure
• Symptom frequency (on a scale of 1-5)
– BEFORE
the heavy smoke began (baseline)
– DURING the heavy smoke (Aug. 23-Oct. 26)
– AFTER the heavy smoke ended (Oct. 27-Nov.15)
Outcome Definition
• Lower respiratory symptoms
 Breathing difficulty
 Chest pain
 Coughing
• Dichotomous outcome variables
 Worse from before to during the smoke
 Worse from before to after the smoke
(post-fire symptoms)
Self-Reported Impact of the Heavy Smoke
on Lower Respiratory Symptoms
Pre-existing
conditions
No pre-existing
conditions
% worse during the smoke
64.1%
61.9%
% still worse after the smoke
23.9%
21.3%
Mean Number of Reported Lower Respiratory
Symptoms: Before, During, and After the Smoke
Pre-existing
condition
Before the smoke
During the smoke
After the smoke
1.08
1.46
0.92
No pre-existing
condition
0.38
1.07
0.52
Sample Participation Rates For Interventions
Implemented by K’ima:w Medical Center
Number
Participating
Wore a Mask
Evacuated Reservation
Ran HEPA Cleaner at Home
Recalled and Recited a PSA
100/286
140/287
98/287
223/289
Percent
Participating
35%
48%
34%
77%
Intervention Evaluation:
Analysis Strategy for Confounding by Severity
• Outcome of interest is post-fire symptoms
• Assessed increased participation among only those
who received interventions
• Multiple logistic regression, all results are adjusted
for:




Frequency of symptoms at baseline
Income
Age
Hours per day normally spent outside
Associations Between Exposure Indices and the
Odds of Reporting Worsening Lower Respiratory
Symptoms, Hoopa, California, 1999
Odds of worsening lower
respiratory symptoms
aOR
95% CI
p-value
Household income
1.19
0.98-1.44
.080
Female Sex
1.75
0.88-3.49
.111
Poorer home condition
Home < 650 feet in altitude
Hours per day outside
1.40
6.02
1.12
0.97-2.04
0.75-48.56
1.03-1.22
.075
.092
.007
Effect of Duration of Mask Use Among Those Who
Received Filtered Masks, Hoopa, California, 1999
Odds of worsening lower
respiratory symptoms
aOR
95% CI
Bottom 25% (wore mask 0-2 hours/week)
Reference Group
26-50% (wore a mask 3-7 hours/week)
1.78
1.59
1.45
51-75% (wore a mask 8-24 hours/week)
Top 25% (wore a mask > 25 hours/week)
N = 100 (those who received filtered masks)
0.47-6.69
0.39-6.45
0.33-6.34
Effect of Duration and Timing of Evacuation
Among Those Who Left the Reservation,
Hoopa, California, 1999
Odds of worsening lower
respiratory symptoms
aOR
95% CI
Total Days Away from Reservation
0.98
0.91-1.06
Evacuated for top 3 days of PM10
1.20
0.39-3.64
N = 140 (who evacuated the reservation)
Effect of Duration of HEPA Cleaner Use Among
Those Who Received HEPA Cleaners,
Hoopa, California, 1999
Odds of worsening lower
respiratory symptoms
Total time HEPA Cleaner was run
Bottom 25% (0-72 hours of use)
26-50% (73-162 hours of use)
51-75% (163-336 hours of use)
Top 25% (> 337 hours of use)
N = 98 (those who received HEPA filters)
aOR
95% CI
0.95
0.89-1.00
Reference Group
0.59 0.13-2.73
0.39 0.11-1.45
0.18 0.04-0.87
HEPA Cleaners vs. Evacuation?
Of those who participated in each intervention…
Evacuation
% participated during
three days of highest
PM10
Mean duration of
participation
17%
7.6 days
HEPA Cleaners
49%
14.9 days
Financial and Occupational Barriers
to Evacuation.
• 44% of the responses of those who didn’t go to a
hotel indicated occupational barriers.
• 12% indicated economic constraints.
• Those with pre-existing conditions were not less
likely than those without pre-existing conditions
to work in the fire camps.
Public Service Announcements
Remain indoors - 78.6%
Wear face covering - 44.1%
Leave area temporarily - 34.5%
Close windows - 23.9%
Restrict strenuous outdoor activity - 19.4%
Use air conditioning - 9.7%
Source
Radio - 51.5%
Doctor - 37.2%
Friend/family - 21.3%
Employer - 17.2%
Television - 13.9%
Newspaper - 6.7%
Effect of Receiving Public Service Announcements
(PSAs), Hoopa, California, 1999
Odds of worsening lower
respiratory symptoms
aOR
Did not recall any PSAs
Recited one PSA
Recited two PSAs
Recited three or more PSAs
N = 289
95% CI
Reference Group
0.47
0.38
0.03
0.21-1.05
0.17-0.89
0.01-0.22
Limitations
1. Observational Study
• looked for dose-response effects within groups
• post-fire outcomes
2. No Measure of Personal Exposure
• Urinary methoxyphenols not validated
• DNA, Hb and Albumin Adducts not yet validated
• Could not use personal exposure monitors
3. Self-report data
• Uncertain correlation with more severe outcomes
• Recall bias
• Common reporter bias
Conclusions: Health Effects
• Prioritize interventions to those with
pre-existing cardiopulmonary conditions
• Continue to implement programs to reduce
exposure in the entire population
Conclusions: Interventions
• Mask Use: Ineffective
• PSA’s: Effective, but mechanism unclear
• HEPA Cleaners: Effective, need validation
• Evacuation: Ineffective, not feasible
Future Directions
• Validate a biomarker for wood smoke exposure.
• Continue to evaluate interventions using objective
indicators of exposure and health effects.
Investigation of Exposures from the
Cerro Grande Fire, Los Alamos, New
Mexico, May 2000
Epi-Aid 2000-40
Mitchell Wolfe, Joshua Mott, Ron Voorhees, C. Mack Sewell,
C.M. Wood, Dan Paschal, Stephen Redd
Background
Cerro Grande Fire
• May 4: Controlled burn by Nat’l Park Service begins in
Bandelier National Monument adjacent to Los Alamos National
Lab (LANL), approx 25 mi. NW of Santa Fe.
• May 5: Declared wildland fire. Continued spread.
• May 10&11: 239 houses burned; 25,000 evacuated.
– Mandatory: Los Alamos, White Rock
– Voluntary: Española
• May 18: 100% contained, 47,650 acres, 5% LANL property
• May 18: NMDOH invited CDC to assist:
– Mitchell Wolfe, Josh Mott, and C.M. Wood departed May 18th
Española
Los Alamos
May 11, 2000
CDC Objectives
1) Assess environmental monitoring data
2) Assess need for human screening for
specific exposures
3) Perform necessary screening
Environmental monitoring in response to the
Cerro Grande Fire
• Chemicals and metals (EPA)
– 6 sites around LANL, May 12-17.
– VOCs, PAHs, pesticides, and metals
– Results: very low VOC, PAH, and metals
• Particulate Matter (NMED, EPA)
– Additional sites and intervals
– Española began May 13
– Results: low except elevated PM10 on LANL May 12-13.
• Asbestos (NMED)
– air/wipe samples in Los Alamos town
– Results: Low
• Radionuclides (Many agencies)
– Results: Some samples contained small amounts of radioactive
material, mostly from natural sources, but the concentrations in the
samples were several orders of magnitude below any regulatory limit
Potential human exposure
• 1,600 firefighters
– 1,400 (88%) during May 11-15, when most of LANL burned
• Several hundred National Guard, City and State Police
– Evacuations
– Roadblocks
– Traffic control, etc
• Residents of Española (pop. 9,000) and environs
• Metal levels
Discussion
– Some elevated values, but only Ni and U above expected number
of elevated values
• Neither Ni or U associated with smoke exposure.
• Uranium naturally-occurring
• History of high natural U in previous water studies in area.
• No positive association of metals with smoke exposure
– Only exception is cadmium in National Guard, and small mean
difference in exposed vs unexposed
– Some negative associations (lower mean values in exposed)
Difficult Issues
• Health effects of “elevated” values
• Clinical/public health interface (acute/long-term follow-up)
Limitations and Future Needs
• Time interval
– Because of time interval (approx 2 ½ weeks) from fire to testing, may be
an assessment of background levels in populations
– Many factors influence half-life, so difficult to reconstruct dose.
• Urine testing
– Spot urine performed, but not as accurate as 24-hour urine
– Because of issues regarding distribution in the body, measuring urine
may not be as accurate a measure as serum or other fluids/tissues
• Classification of exposure
– No biomarker for smoke exists. Definition of exposure based on
presence in a city, or fighting fires, on certain days. May not be
specific—need a validated biomarker of exposure.
Respiratory and Circulatory Hospital
Admissions Associated with Forest Fires Montana, July-September, 1999 & 2000
Charon Gwynn, Joshua A. Mott, Todd Damrow
David Mannino, Stephen Redd
EPI-AID 2001-07
Background
• Forest fires in Bitterroot
Valley burned approximately
950,000 acres
• 24-hour PM10 concentrations
reached 300g/m3
• Concerns prompted a
request for assistance
Objectives
• Quantify county-level admission rates for
cardio-vascular and respiratory illness
• Compare admission rates based on year
and level of exposure
Case Definition
• Patients admitted July 1 - September 15,
1999 and 2000 for:
– cardiovascular illness (ICD9: 390-459)
– respiratory illness (ICD9: 460-519)
• Residents of 4 Counties with varying
exposure levels
Missoula
Lewis
&
Clark
Ravalli
Yellowstone
Increase in Average PM Concentration
Between the 1999 & 2000 Study Periods
70
1999
2000
60
50
PM10 40
(g/m3) 30
20
10
0
-2.5
1.5
5.5
9.5
13.5
Ravalli
Missoula
Lewis
&
Clark
Yellowstone
17.5
Methods
• Information abstracted from 2,250 medical
records
• Variables collected included:
– Primary & secondary discharge diagnosis
– Admission/discharge date
– Demographic information
– History of illness
• 1999 & 2000 hospitalization rates calculated
using the 1999 Census population estimates
Odds Ratios for Admission in 2000 Compared
to 1999 for Each Exposure Level
5
No Exposure
Moderate Exposure
High Exposure
4
3
OR
2
1
0
-3
2
TOTAL
7
RESP
12
COPD
17
PNEU
22
CIRC
27
IHD
32
HF
37
DYS
42
CVD
Conclusions
• Risk of admission for circulatory and respiratory
illness was greater:
– in highly exposed area during the 2000 fire than the
unexposed area
– in 2000 than 1999 in smoke exposed areas
• From 1999 to 2000, risk of admission generally
increased with exposure
• Evidence of the influence of biomass smoke
exposure on more severe health endpoints.
Future Directions
• Investigate temporal PM-hospital admission
relationship
• Evaluate history of illness
• Investigate potential biomarkers of smoke
exposure
Conclusions From Three
Investigations
Health Effects
Smoke exposure associated with:
• increased self reported symptoms (Hoopa)
• increased ED visits for resp. diseases (ICD-9 460-519)
• increased hospitalizations for respiratory diseases,
COPD, IHD.
– mortality?
– short term health effects?
– disease susceptibility, longer term health effects?
– studies of biologic plausibility?
Conclusions (Cont.)
Indicators of Exposure
Health effects associated with:
• geographic proximity to fires/PM
• self reported hours of outdoor activity
– other indicators? (phenols, PAHs, nickel, CO)
Effectiveness of Interventions
• HEPA Cleaner use (Hoopa and Malaysia)
• Recollection of PSAs
– randomized trials?