03 influenza Zhu 508

CDC ACIP — Vaccine Advisory Committee

Acip

Slides

15

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1Sophie Zhu, PhD, presenting on behalf of the study team
Epidemic Intelligence Service Officer 
California Department of Public Health
Influenza VEData: Interviews, 
electronic health records
New: California public 
health dataMultiple considerations for vaccine 
effectiveness (VE) calculation
Populations:
Pediatric, hospitalizedCare settings
2
New requirements for data reporting in 
California
•1/1/23: Influenza vaccination records  became 
reportable to the California Immunization 
Registry (CAIR) 
3•6/15/23: All negative influenza results (in 
addition to previously reportable positive 
influenza results) became reportable to the 
California Reportable Disease Information 
Exchange ( CalREDIE )
California VE Calculation
Attribute California
Data source Mandatory influenza results and influenza immunization records
Date available VE estimates and data available each December or earlier
Outcome(s) Laboratory -confirmed influenza using nucleic acid amplification 
tests (NAAT)
Population(s) Californians tested for influenza using NAAT from diverse care 
settings
4
Methods
5
•Inclusion criteria: California residents aged ≥6 months with molecular tests for 
influenza (A/B) captured by the state electronic laboratory reporting system
•Dates: October 1, 2023 —January 31, 2024
•Vaccination status: documented dose of seasonal influenza vaccine in CAIR ≥14 
days before testing
•Deduplicate results for persons with multiple records
•Remove results from laboratories weekly with ≥50% positive due to suspected 
underreporting of negative results (<5% of data)
•Analysis:  VE = (1 – adjusted OR) x 100%
•Mixed -effects logistic regression model adjusted for age, race, ethnicity, 
testing week (random effect), and county (random effect)
6Methods: unmatched case -control study
Number of influenza detections by type and subtype detected in RLN 
laboratories and percentage of specimens testing positive at clinical 
sentinel laboratories – 2023 -2024 season to date
7

Overall No. (%) Influenza positive No. (%) Influenza negative No. (%)
Total 678,422 (100) 77,501 (11.4) 600,921 (88.6)
Age ( yrs, median) 42 (17 –66) 31 (10 –52) 44 (19 –68)
Race
American Indian or Alaska Native
Asian
Black or African American
Native Hawaiian or Pacific Islander
White
Multiple Races
Other
Unknown2,919 (0.4)
53,419 (7.9)
40,069 (5.9)
2,878 (0.4)
301, 779 (44.5)
1,381 (0.2)
131,284 (19.4)
144,693 (21.3)326 (0.4)
6,252 (8.1)
4,033 (5.2)
300 (0.4)
29,908 (38.5)
130 (0.2)
16,098 (20.8)
20,454 (26.4)2,593(0.5)
47,167 (7.8)
36,036 (6.0)
2,578 (0.4)
271,871 (45.2)
1,251 (0.2)
115,186 (19.2)
124,239 (20.7)
Ethnicity
Hispanic or Latino
Not Hispanic or Latino
Unknown159,676 (23.6)
386,200 (56.9)
132,546 (19.5)21,309 (27.4)
38,653 (49.9)
17,539 (22.7)138,367 (23.1)
347,547 (57.8)
115,007 (19.1)
Vaccinated
Overall
Vaccinated during Oct. 1 –31
Vaccinated during Nov. 1 –30
Vaccinated during Dec. 1 –31
Vaccinated during Jan. 1 –31190,313 (28.1)
11,073 (13.1)
39,497 (25.3)
69,884 (30.1)
69,859 (33.9)13,905 (17.9)
93 (6.5)
1,357 (12.5)
7,104 (17.6)
5,351 (21.4)176,408 (29.3)
10,980 (13.2)
38,140 (26.3)
62,780 (32.7)
64,508 (35.6)Participant characteristics
8
Influenza vaccines protect against laboratory -
confirmed influenza
Influenza positive Influenza negative Adjusted VE*
Total Vaccinated no. 
(%)Total Vaccinated no. 
(%)% (95% CI)
Influenza A and B**
Overall 75,876 13,629 (18) 600,921 176,408 (29) 45 (44 –46)
<18 years 28,914 3,744 (13) 147,047 32,791 (22) 56 (54 –57)
18–49 years 26,435 3,334 (13) 189,129 36,171 (19) 48 (46 –50)
50–64 years 10,861 2,575 (24) 96,148 28,579 (30) 36 (33 –39)
≥65 years 9,666 3,976 (41) 168,597 78,867 (47) 30 (27 –33)
Study period: October 1, 2023 – January 31, 2024.
*VE was estimated using an unmatched case -control study as 100% x (1 -aOR) where aOR is the ratio of odds of vaccination among influenza 
positive cases versus influenza negative controls. ORs were estimated using mixed -effects logistic regression with adjustment fo r age, race, 
ethnicity as fixed effects and enrollment week and county of residence as random effects.
**VE for unknown influenza types was not calculated because of small sample size, and unknown influenza type results were exclu ded from 
overall influenza A and B VE estimation.
9
VE against influenza A was lower but still 
protective in all age groups
Influenza positive Influenza negative Adjusted VE*
Total Vaccinated no. 
(%)Total Vaccinated no. 
(%)% (95% CI)
Influenza A
Overall 68,716 13,118 (19) 600,921 176,408 (29) 42 (41 –43)
<18 years 25,393 3,517 (14) 147,047 32,791 (22) 52 (51 –53)
18–49 years 23,257 3,136 (14) 189,129 36,171 (19) 44 (42 –46)
50–64 years 10,546 2,532 (24) 96,148 28,579 (30) 35 (32 –38)
≥65 years 9,520 3,933 (41) 168,597 78,867 (47) 29 (26 –32)
Study period: October 1, 2023 – January 31, 2024.
*VE was estimated using an unmatched case -control study as 100% x (1 -aOR) where aOR is the ratio of odds of vaccination among influenza 
positive cases versus influenza negative controls. ORs were estimated using mixed -effects logistic regression with adjustment fo r age, race, 
ethnicity as fixed effects and enrollment week and county of residence as random effects.
10
VE against influenza B was highly protective 
across most age groups
Influenza positive Influenza negative Adjusted VE*
Total Vaccinated no. 
(%)Total Vaccinated no. 
(%)% (95% CI)
Influenza B
Overall 7,160 511 (7) 600,921 176,408 (29) 76 (73 –78)
<18 years 3,521 227 (6) 147,047 32,791 (22) 79 (76 –82)
18–49 years 3,178 198 (6) 189,129 36,171 (19) 75 (71 –78)
50–64 years 315 43 (14) 96,148 28,579 (30) 67 (55 –76)
≥65 years 146 43 (29) 168,597 78,867 (47) 54 (33–67)
Study period: October 1, 2023 – January 31, 2024.
*VE was estimated using an unmatched case -control study as 100% x (1 -aOR) where aOR is the ratio of odds of vaccination among influenza 
positive cases versus influenza negative controls. ORs were estimated using mixed -effects logistic regression with adjustment fo r age, race, 
ethnicity as fixed effects and enrollment week and county of residence as random effects.
11
Cumulative VE — Oct. 1, 2023 –Jan. 31, 2024
Influenza positive Influenza negative Adjusted VE*
Total Vaccinated no. 
(%)Total Vaccinated no. 
(%)% (95% CI)
Influenza A and B**
October 31st 1,455 93 (6) 83,403 11,021 (13) 46 (34, 57)
November 30th 11,703 1,376 (12) 223,921 47,682 (21) 51 (48, 54)
December 31st 53,181 8,695 (16) 416,136 110,816 (27) 47 (46, 48)
Overall (January 31st) 75,876 13,905 (18) 600,921 176,408 (29) 45 (44, 46)
*VE was estimated using an unmatched case -control study as 100% x (1 -aOR) where aOR is the ratio of odds of vaccination among influenza 
positive cases versus influenza negative controls. ORs were estimated using mixed -effects logistic regression with adjustment fo r age, race, 
ethnicity as fixed effects and enrollment week and county of residence as random effects.
**VE for unknown influenza types was not calculated because of small sample size, and unknown influenza type results were exclu ded from 
overall influenza A and B VE estimation.
12
Limitations
1.Likely incomplete documentation and reporting of mandatory vaccination and 
testing
2.Cannot assess partial/full vaccination status for children aged <9 years
3.Lack of symptom information, test setting, and outcome status (illness, 
hospitalization, or death)
4.Potential lack of generalizability across the US
5.Subtype information not available for positive influenza results
6.Lack of control for other confounders (health seeking behavior, pre -existing 
conditions)
13
Summary
•Current seasonal influenza vaccines provide protection against 
laboratory -confirmed influenza for persons aged ≥6 months
•Higher VE for influenza B & younger age groups (<18 years, 18 -49 
years)
•Mandatory public health data can be leveraged to calculate timely in -
season influenza effectiveness as an additional estimate supporting 
existing public health influenza efforts including vaccination messaging
•Useful to promote additional prevention measures prior to peak
•Prepare for increased hospital capacity
14
Acknowledgments
CDPH Division of Communicable Disease Control
Joshua Quint*
Tomás M. León*
Monica Sun*
Nancy J. Li*
Seema Jain*
Cora Hoover*
Robert Schechter*
Erin L. Murray* 
Timothy Lo
Celeste Romano
15CDC NCIRD
Mark Tenforde*
Jessie Chung
Sascha Ellington
*co-authorCalifornia’s local 
health 
departments