1. Ricardo Basurto-Dávila, PhD MS
Various Measures of 2009 H1N1 Influenza Vaccine Effectiveness Among Children Maine, 2009
Ricardo Basurto-Dávila, PhD MS
Influenza Division
Centers for Disease Control and Prevention
45th National Immunization Conference
March 31, 2011
National Center for Immunization & Respiratory Diseases
Influenza Division

2. 2009 H1N1 Influenza Vaccine Effectiveness Among Children
Background

3. 2009 Pandemic: Maine’s Early Vaccination Efforts Focused on Schools
State-wide school-based influenza vaccination campaign (SIV)
Most vaccinations among children in Maine were through SIV
Little pediatric immunization outside schools
High overall vaccination coverage
Coverage varied among schools
* Citations, references, and credits – Myriad Pro, 11pt

4. Opportunity To Evaluate Vaccine Effectiveness
First vaccination clinics in late October
Clinic dates varied across schools
Peak of H1N1 circulation in mid-November
H1N1 circulation until early January
We expect vaccination to reduce
Infection rates
Student absenteeism due to illness
* 95% of student absenteeism captured electronically

5. OBJECTIVES AND METHODS
2009 H1N1 Influenza Vaccine Effectiveness Among Children
OBJECTIVES AND METHODS

6. Study Objectives
To use various outcome measures to assess the effectiveness of single-dose 2009 H1N1 influenza vaccine among school-aged children.

7. Study 1 Data: School Absenteeism And Vaccination Among Students
Administrative records from elementary and middle schools in 4 counties in Maine:
We requested daily de-identified attendance records of all K-8 students: October thru December, 2009
Linked to individual immunization records with data on vaccination status and date of vaccination
Other student- and school-level characteristics
Virus circulation data from state laboratories:
Weekly percentage of specimens with positive RT- PCR tests for influenza and non-influenza viruses
NOTE: Data requested from all schools in Cumberland County and some schools (non-randomly selected) in the other three counties.
A subset of schools provided attendance and vaccination data up to March, 2010
For most schools we do not know cause of absence.
Student characteristics: gender, race-ethnicity, grade, language
School characteristics: rural or urban location, county, percentage of students on free or reduced-price lunch

8. Estimation of Vaccine Effectiveness (VE) Against Student Absenteeism
Survival models with repeated failures
Failure (outcome) definitions:
Single-day absences
Three-or-more consecutive day absences
Four-or-more consecutive day absences
VE defined as reduction in hazard of absenteeism for vaccinated students during flu-circulation period
VACCINATION: In all cases we are using only first-dose vaccination.

9. Study 2 Data: Influenza Illness And Vaccination Among Students
Household survey in one county: parents of
K-8 students with laboratory-confirmed H1N1 influenza
Classmates of these students with at least one absence during October-December, 2009
Random sample of classmates with no absences
Parent-reported influenza-like illness (ILI) symptoms, clinical diagnosis of influenza, and other health conditions
Vaccination and demographic information from school records
CASES: Disease onset on or after November 2, 2009 (7 days after first vaccination clinic)
ILI CASE DEFINITION: Flu or flu symptoms—fever or feverishness + cough or sore throat
Dates of recorded absences used to identify timing of ILI episodes

10. Estimation of VE Against Influenza
Case-control design, three case definitions:
Confirmed: RT-PCR positive pH1N1
Probable: Confirmed + Clinically diagnosed*
Possible: Probable + ILI symptoms*
Controls:
Students in same classroom as case with no ILI symptoms as of illness onset date of matched case
Logistic regression adjusting for confounders
VE defined as (1 – aOR) × 100%
aOR: adjusted odds ratio of being case for vaccinated vs. non-vaccinated
CONTROLS: Removed from sample if they reported ILI symptoms before case illness onset date. (ILI used because control may have had flu but was not tested.)
POTENTIAL CONFOUNDERS:
Sex, race, and previous asthma diagnosis
SURVEY LOGISTIC regression to account for sampling scheme.
* Physician diagnosis and ILI symptoms reported by parents.

11. 2009 H1N1 Influenza Vaccine Effectiveness Among Children
RESULTS

12. Student Absenteeism 93 of 104 schools (89%) agreed to participate
Vaccination and absenteeism data for more than 32,000 students (2.2 million obs.)
Average school-level vaccination coverage:
55% (range 18-83%)
More than 30% of students had been vaccinated by peak of influenza circulation
Vaccinated students:
Lower probability of being absent than non-vaccinated students
Regardless of vaccination status or flu activity
Out of 32,074 students, we received post-December 2009 data for 14,934 (47%)
Results from statewide representative surveys indicate Maine’s pH1N1 coverage was 60%; our sample has a slightly lower coverage. (Those estimates are for ages 5 months – 17 years and all counties in the state, not directly comparable to ours.)

13. Influenza Circulation and Vaccination
VACCINATED: Red line shows coverage by date of vaccination (no lag).
VIRUS CIRCULATION: Each bar represents one week.

14. Student Absenteeism, Influenza Circulation, and Vaccination
ABSENTEEISM: Green/Blue lines show absences for students who, by end of data period, had been vaccinated or not.
VACCINATION: Red line shows coverage by date of vaccination (no lag). Survival regressions used a 14-day lag to account for period needed for immunization.
VIRUS CIRCULATION: Each bar represents one week.

15. VE Against Student Absenteeism
Outcome
VE with Observed Flu Circulation
VE with 50% Positive Flu Tests*
1-Day+ Absences
19%
(95% CI: 16 – 22)
23%
(95% CI: 19 – 27)
3-Day+ Absences
33%
(95% CI: 26 – 40)
43%
(95% CI: 35 – 51)
4-Day+ Absences
(95% CI: 25 – 41)
45%
(95% CI: 36 – 55)
* First VE column was estimated using observed percentages of positive influenza tests. Second column was estimated assuming 50% positive tests over a four-week period.

16. Influenza Illness Case-Control Data
Confirmed
Probable
Possible
Cases
n=92
Controls
n=1,114
n=168
n=1,038
n=304
n=902
Response Rate*
88%
80% –
Asthma
30%
10%
28% 9%
20% 8%
Vaccinated
25%
60%
36%
61%
46%
Illness Length
< 3 days 0% 1%
3 – 7 days
70%
75%
7+ days
29% 5%
* Response rate cannot be calculated for two outcomes because their definition was derived from survey responses.

17. VE Against Influenza Outcomes
Case Definition
Unadjusted
Adjusted
Confirmed influenza
72%
(95% CI: 21 – 90)
69%
(95% CI: 12 – 89)
Probable influenza
26%
(95% CI: -16 – 53)
22%
(95% CI: -26 – 50)
Suspected influenza
(95% CI: -7 – 44)
19%
(95% CI: -12 – 42)
Estimated VE against confirmed influenza in children consistent with VEs estimated in recent international studies:
China: %
UK: %
UK: %
Canada: 100%

18. Limitations: VE Against Student Absenteeism
No outcome perfectly associated with influenza
Lack of true baseline absenteeism
We did not observe absenteeism rates before influenza circulation and vaccination
Potential for confounding
If other factors affect both vaccination and absenteeism patterns during high flu period
FIRST BULLET: If differences in absenteeism between vaccinated and non-vaccinated students change during influenza circulation, then estimates of VE against absenteeism can be biased. However, if this is a problem, it likely biases the estimates downwards: parents who make sure their children are vaccinated may also be more likely to keep them at home if they fear they can be infected at school, which would lower the estimates of vaccine effectiveness against absenteeism.
SECOND BULLET: We do not know which absences were due to flu and which ones weren’t, so there could be significant noise in our estimations (downward bias again).
THIRD BULLET: In addition to protection due to higher probability of being immunized, vaccinated students benefit from lower risk from infection if other kids around them are also vaccinated (i.e., if you are not immunized by the vaccine, at least others around you might be). We cannot separate both effects with this design.
FOURTH BULLET: We do not have data before October 5, when H1N1 was already circulating. It is unlikely, though, that absenteeism before flu circulation is different from absenteeism after flu circulation. Even if it were, this would only be a problem if such these differences were not the same for vaccinated and non-vaccinated students.

19. Limitations: VE Against Influenza Outcomes
Potential for case misclassification
If testing practices changed
Mild or asymptomatic cases
Potential biases
Differential access or propensity to seek care of cases and controls
Precision of parental recall (6-month gap)
FIRST BULLET: If testing for H1N1 was more common at some point, we could be missing more cases from a particular point in time. We also could have some controls who were infected with flu but did not report symptoms.

20. Conclusions 2009 pH1N1 influenza vaccine effective in preventing:
Student absences of 3 or more days
RT-PCR-confirmed cases of H1N1 influenza
Lower or zero effectiveness against other outcomes
Outcomes more specific to influenza are likely to provide more accurate VE estimates

21. Collaborators: Maine Center for Disease Control and Prevention
Maine Department of Education
University of Michigan, School of Public Health
U. S. Centers for Disease Control and Prevention
Dora Mills
Peter Smith
Meredith Tipton
Nancy Dube
Arnold Monto
Sandra S. Chaves
Jufu Chen
Jill Ferdinands
Lydia Foster
Paul Gargiullo
Sam Graitcer
Rebel Jackson
David Shay
Mark Thompson
Amra Uzicanin

22. Thank you! National Center for Immunization & Respiratory Diseases
Influenza Division

23. Gamma Survival Model: 1+ Days Absences (Accelerated Failure Time)
Variable
Coefficient
P-value
Immunization status (14-day lag)
-0.01
0.820
Percent laboratory tests positive for influenza
-2.03
<0.001
Immunization status * Percent flu-positive tests
0.49
Vaccinated (at end of data coverage period)
0.23
Percent lab tests positive for non-flu virus
-1.69
Rural school location
0.06
Percent students with free or reduced-price lunch
-0.32
Non-Hispanic Black student
0.10
Hispanic student
-0.18
Asian student
0.08
0.028
Indian/Pacific Islander student
-0.14
0.085
Non-Hispanic White student
Reference -
NOTE: In addition to listed variables, models also included county (Cumberland, Androscoggin, Penobscot, or York), whether day was a Monday or Friday, and whether day was on Thanksgiving week.