Risk factors and attack rates of seasonal influenza infection: Results of the SHIVERS sero-epidemiologic

cohort study

Dr. Sue Huang

Principal investigator of SHIVERSDirector, WHO National Influenza Centre

Institute of Environmental Science and ResearchSiena, 1 April, 2019

Influenza - The SHIVERS serosurvey

• Presented by • Edwin Reynolds

• GP (Northland)

• IMAC (University of Auckland)

• ARPHS (Auckland Regional Public Health Service)

Acknowledgement• ESR: Claire Newbern, Ruth Seeds, Don Bandaranayake, Graham Mackereth, Tim Wood, Ange Bissielo,

Thomas Metz, Anne McNicholas, Namrata Prasad, Ben Waite, Jenni Haubrock, Tiffany Walker, Nayyereh

Aminisani, Angela Todd, Lauren Jelly, Judy Bocacao, Jacqui Ralston, Wendy Gunn, IT staff

• ADHB: Sally Roberts, Colin McArthur, Debbie Williamson, Debbie Aley, Kathryn Haven, Bhamita Chand,

Fahimeh Rahnama, Research nurses, clinical team staff, laboratory staff, IT staff

• CMDHB: Adrian Trenholme, Conroy Wong, Susan Taylor, Shirley Lawrence, Research nurses, clinical team

staff, laboratory staff, IT staff

• University of Auckland: Nikki Turner, Cameron Grant, Sarah Redke, Barbara McArdle, Tracey Poole, Anne

McLean, Debbie Raroa, Carol Taylor

• University of Otago: Michael Baker, Nevil Pierse, William Leung, Trang Khieu

• Primarycare Advisory Group from PHOs (Procare, East Tamaki, Auckland) and ARPHS: John

Cameron, Bruce Adlam, Edwin Reynolds, Rosemary Gordon, Leane Els, Marion Howie, Gillian Davies

• ILI sentinel practices

• WHOCC-St Jude: Richard Webby, Paul Thomas, Sook-san Wong

• US-CDC: Mark Thompson, Marc-Alain Widdowson, Jazmin Duque, Diane Gross

• Funding from US-CDC: 1U01IP000480; Kind support from NZ Ministry of Health

Outline

• Background on SHIVERS & Sero-epidemiologic cohort

• Method

• Results

• Conclusions

SHIVERS (Southern Hemisphere Influenza and Vaccine Effectiveness Research and Surveillance)

• In 2010, US-CDC: Funding opportunity announcement “Influenza and other respiratory diseases in Southern Hemisphere”

• NZ: Southern hemisphere country with temperate climate

• NZ health infrastructure – public funded:

–National Health Index

–>98% of NZers registered with GPs

–NZ population - well-characterised: ethnicity, SES

–NZ labs using PCR as screening assay: great for burden study

• We won a competitive research award from US-CDC (NZ$9m) for 6 years (2012-2017) - SHIVERS

SHIVERS - overarching aims & 9 objectives

Hospital surveillance

disease burden

epidemiology etiologyrisk

factorsimmunology

vaccine effectiveness

prevention strategies

sentinel general practice surveillance

1. Understand severe respiratory diseases

2. Assess influenza vaccine effectiveness

3. Investigate interaction among respiratory pathogens

4. Understand causes of respiratory mortality

5. Understand non-severe respiratory diseases

6. Estimate influenza infection via serosurvey

7. Identify and quantify risk factors for getting influenza

8. Assess immune responses: severe/mild; ethnic groups

9. Estimate Economic burden and vaccine cost-effectiveness

Sero-epidemiologic cohort study, 2015

~90,000 enrolled patient list

(14 ILI GPs)

Enrolled Patient Sample

1,500

Random Patient

Sample:

- Stratified by age &

ethnicity

Pre-Season Blood Draw

& Questionnaire

ILI Season Weekly Check

&

ILI: Swab + PCR

Post-Season Blood Draw

& Questionnaire

- Collect a paired blood and test for HAI

and NAI antibody (seroconversion: 4

fold rise in HAI or NAI titres)

- Monitor ILI weekly and collect ILI

swabs for PCR testing

- Collect risk factor information

Flu infection (symptomatic/asymptomatic):

?

Flu consultation:

20 818

Flu Hospitalization:

1,600

Flu ICU:

89

Flu

Death:

20

New Zealand Population: 4,470,800

Aim: how many people were

actually infected with influenza?

• Mild influenza not requiring GP

visit

• Asymptomatic infections

Predominant strains in 2015

0

100

200

300

400

500

600

700

800

900

0

5

10

15

20

25

30

18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39

May Jun Jul Aug Sep

Nu

mb

er o

f n

o-I

LI r

esp

on

ses

Nu

mb

er o

f IL

I an

d in

flu

enza

-co

nfir

med

ILI

B/Victoria lineage B/Yamagata lineage A (not subtyped)

A(H3N2) ILI-non influenza no-ILI

0

50

100

150

200

250

300

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51

Co

nsu

ltati

on

rate

(p

er

100

,000

)

Week

2009201020112012201320142015

May Sep

baseline level

above seasonal level

high seasonal level

moderate seasonal level

low seasonal level

Proportions of HAI and NAI seroconversion

influenza PCR

N = 58

No flu PCR

N = 33

Influenza negative N = 28

Influenza positive N = 30

Unvaccinated cohort N=911

No. person with ILI N =91

No. person with ILI N =13

HAI aloneSeroconverters

N =46

NAI aloneSeroconverters

N =100

No. person with ILI N =52

influenza PCR

N = 9

Influenza negative

N = 8

Influenza positive

N = 1

No flu PCR

N = 4

influenza PCR

N = 42

Influenza negative N = 23

Influenza positive N = 19

No flu PCR

N = 10

HAI & NAI Seroconverters

N =175

No. person with ILI N =131

influenza PCR

N = 100

Influenza negative N = 100

Influenza positive

N = 0

No flu PCR

N = 31

Non-Seroconverters

N =590

• More NAI than HAI seroconversion:

- NAI: 30%, 275/911

- HAI: 24%, 221/911

• Of infected: 31% (100/321) had NAI alone seroconversion

• Of non-seroconverters, no PCR positives: 100% agreement

Huang et al. Journal of Infectious Diseases 2019;219:347-57

Serologically defined infection by age and ethnicity

• The highest attack rates of influenza infection:

- children aged <5 years

- Pacific peoples

NAI alone seroconversion rates - age-specific and strain-specific

Difference (%NAI-%HAI):

• Children < 5yo (14%) vs other ages (4%), p<0.001

• Infected individuals: B (7%) vs A(H3N2) (0.3%), p<0.001

0-4 yo 5-19 yo 20-64 yo ≥65 yo

%HAI 11 11 6 7

%NAI 27 18 11 12

%NAI-%HAI 16 7 4 5

0

2

4

6

8

10

12

14

16

0

5

10

15

20

25

30

35

40

45

50

Dif

fere

nce

in s

ero

con

vers

ion

%

% S

ero

con

vers

ion

Influenza B

0-4 yo 5-19 yo 20-64 yo ≥65 yo

%HAI 19 25 11 9

%NAI 22 24 12 7

%NAI-%HAI 3 -1 1 -2

-4

-2

0

2

4

6

8

10

12

14

16

0

5

10

15

20

25

30

35

40

45

50

Dif

fere

nce

of

sero

con

vers

ion

ra

tes

% S

ero

con

vers

ion

ra

tes

A(H3N2)

A full influenza burden pyramid

Age and ethnicity adjusted estimates

1,000,000 people over one season

• 32% of population - flu infected

• Of infected:

- 24% developed influenza-like illness

- 76% did not develop ILI

• Of infected with PCR confirmed ILI:

- 26% visited a GP

- 74% did not seek care

Flu infection 319,000 (32% of total population)

Flu GP visits

5,919 (1:62 infected)

Flu Hospitalization

639 (1 in 510 infected)

Flu ICU

26 (1 in 13,000)

Flu

Death

8 (1 in 40,000)

Conclusion

• A third of unvaccinated individuals had either HAI or NAI seroconversion.

• NAI alone seroconversion – 1/3 of all seroconverted individuals: higher in children<5 years and influenza B virus infected individuals

• Importance of NA: measuring NAI and HAI seroconversion - accurate infection rate in sero-epidemiologic cohort studies

• Importance of NA: understand immune correlates of protection, improve vaccine design and vaccine content standardization

Influenza- SHIVERS

• The Southern Hemisphere Influenza and Vaccine Effectiveness, Research and Surveillance (SHIVERS)

• Serosurvey, in 2015

• The results showed that 32% of people were infected with influenza (A or B)

• About 4 out of 5 of these people (76%) were asymptomatic carriers.

• These carriers could have spread the virus among their family, co-workers, classmates and patients without ever realising it.

• Pregnancy and young children at high risk of disease and there are ethnic differences

• Implication for health workers

14

Influenza this winter

• Flu vaccine prevents CV events

• Promotes healthy aging

• As strong a intervention measure as a statin or antihypertensive

• Anti-frailty intervention

16

Efficacy of intervention

Coronary Intervention Prevention Efficacy against AMI

Smoking cessation Secondary 32-43%

Statins Secondary 19-30%

Antihypertensive drugs Secondary 17-25%

Influenza Vaccine Secondary 15-45%