Influenza and influenza immunisation

Allen ChengProfessor of Infectious Diseases Epidemiology, Monash University

Director, Infection Prevention and Healthcare Epidemiology Unit, Alfred Health

Conflicts of interest

• Co-Chair, Australian Technical Advisory Group on Immunisation (ATAGI)

• Chair, Advisory Committee for Vaccines• Chair, ATAGI Influenza WG• Member, National Influenza Surveillance Committee

• Views expressed may not represent views of committees or government

Outline

• Global burden of influenza – how to measure?• Transmission, severity and impact – how to monitor?• Current global surveillance and emerging subtypes• Influenza vaccines• Vaccine coverage• Influenza vaccine effectiveness

Influenza surveillance

Influenza notifications, by month and year since 2008

0

20000

40000

60000

80000

100000

120000

Influenza notifications, by month and year

0

20000

40000

60000

80000

100000

1200002017

2009

2018

Burden of disease

ICU

Hospitalisations

Emergency department

Primary care

Mild respiratory tract symptoms

Asymptomatic illness

Deaths

Under-diagnosis• Not all influenza tested• Tests not completely sensitive• Delayed presentations• Secondary bacterial

pneumonia• Non-respiratory presentations

Over-diagnosis• ILI due to other viruses• SARI due to other pathogens• Hospitalisation/mortality not

always attributable to influenza

Approaches to measuring influenza burden

• Passive surveillance• Active surveillance• Modelling

• Time series studies/excess mortality• Attributable disease estimates

• Vaccine probe studies

Modelling approaches

• Global Burden of Disease• Proportion of LRTIs due to influenza• Number of hospitalisations and deaths due to LRTIs

• Stratified by age, sex, year, geographic region

GBD, Lancet RM 2019

Results

• Influenza• 5.6% of all LRTI deaths• 8.5% of all LRTI hospitalisations• 11.5% of all LRTI episodes

• Estimates in 2017• 145000 (98 000–200 000) deaths• 9459000 (3 709 000–22 935 000)

hospitalisations• 81536000 (24 330 000–259 851

000) hospital days• 54 481000 (38 465000–73 864

000)

GBD, Lancet RM 2019

GBD, Lancet RM 2019

GBD, Lancet RM 2019

Excess mortality approaches

• Influenza can indirectly cause cardiorespiratory disease• Secondary bacterial pneumonia• Exacerbation of asthma and COPD• AMI, cardiac arrhythmias

• Examine mortality/hospitalisations correlated with influenza activity• RSV potential confounder• Need to account for usual seasonal variation in mortality not related to

influenza

Poisson model

Serfling model

Newall EAI 2010

Newall EAI 2010

Dimensions of influenza

• WHO Pandemic Influenza Severity Assessment (PISA) - 2017• Transmission• Severity• Impact

• Thresholds set by Moving Epidemic Method

Not very transmissible

Very transmissible

Clinically severe

Mild illness

Broad impact

Little impact

Surveillance pyramid•Notified deaths•NSW influenza/pneumonia•FluCAN hospital mortality

•FluCAN•FluCAN-PAEDSICU

•FluCAN•FluCAN-PAEDS•EpiLog (Qld)

Hospitalisations

•NSW, WA ED ILI surveillanceEmergency department

•Sentinel GP surveillance systems (ASPREN)•Notification data (NNDSS)Primary care

•FluTracking•HealthDirect•Absenteeism

Mild respiratory tract symptoms

Asymptomatic illness

Deaths

Transmission

ICU

Hospitalisations

Emergency department

Primary care

Mild respiratory tract symptoms

Asymptomatic illness

Deaths ASPREN: rate of ILI per 1000 consultations x proportion positive of influenza swab testing

FluTracking: Rate of ILI per 1000 participants

HealthDirect: Rate of ILI per 1000 callers

Severity

ICU

Hospitalisations

Emergency department

Primary care

Mild respiratory tract symptoms

Asymptomatic illness

Deaths

FluCAN: Cumulative rate of ICU admissions per 100 confirmed influenza admissions

HealthDirect: (cumulative) Proportion of callers with ILI advised to seek urgent medical attention per 1000 callers with ILI (age stratified)

Impact

ICU

Hospitalisations

Emergency department

Primary care

Mild respiratory tract symptoms

Asymptomatic illness

Deaths

FluCAN: Rate of confirmed influenza admissions per 1000 available hospital beds

FluTracking: Rate of ILI + absent from normal duties per 1000 participants

Thresholds (admissions per 1000 hospital beds)

Methodological issues

• Need stable data over >5 years• MEM complex to implement• Inclusion of unusual years eg 2009, 2017• Metrics with low signal to noise ratio • Some metrics based on cumulative data

Influenza - OceaniaYear Rel IAV+IBV %IAV %H3/IAV

AU NZ AU NZ AU NZ2009 1.17 0.87 100% 100% 11% 3%2010 0.29 0.18 63% 100% 17% 1%2011 0.47 0.69 81% 53% 50% 83%2012 1.10 1.27 69% 90% 97% 86%2013 0.46 1.23 82% 59% 65% 69%2014 0.79 1.92 87% 90% 40% 19%2015 0.83 2.87 50% 48% 86% 98%2016 1.53 0.17 83% 92% 83% 72%2017 2.40 0.53 73% 57% 82% 89%2018 0.97 0.27 91% 91% 25% 15%

• Subtype distributions similar in Australia and NZ

• Discordant influenza activity

• Variation within Australia

Source: GISRS

Influenza - global

AU China UK US AU China UK US AU China UK US2008/2009 0.12 0.08 0.68 75% 90% 84% 68% 57% 13%2009/2010 1.17 1.99 0.29 1.14 100% 82% 99% 100% 11% 18% 1% 0%2010/2011 0.29 0.54 1.19 0.57 63% 81% 69% 74% 17% 52% 2% 62%2011/2012 0.47 0.66 0.31 0.25 81% 39% 89% 82% 50% 98% 99% 74%2012/2013 1.10 0.37 0.92 0.76 69% 95% 56% 70% 97% 55% 81% 96%2013/2014 0.46 1.07 0.45 0.55 82% 66% 95% 86% 65% 47% 21% 12%2014/2015 0.79 1.17 0.56 1.30 87% 73% 77% 83% 40% 99% 95% 100%2015/2016 0.83 1.36 1.45 1.01 50% 54% 68% 68% 86% 50% 4% 22%2016/2017 1.53 1.05 1.38 1.76 83% 90% 83% 71% 83% 80% 99% 97%2017/2018 2.40 1.99 4.37 2.98 73% 59% 54% 68% 82% 53% 92% 85%2018/2019 0.97 0.70 1.30 0.63 91% 99% 98% 95% 25% 14% 8% 19%

Rel IAV+IBV %IAV %H3/IAV

Source: GISRS

Influenza virology

• Haemagglutinin; neuraminidase classification• Current: A/H1N1/pdm; H3N2, • B (Victoria; Yamagata lineages)

• Avian strains• H5N6 – 20 cases since 2014• H7N9 - >1500 cases since 2013, but poultry vaccination in China since 2017• H9N2 – enzoonotic in Chinese poultry, occasional human cases• H5N1 – 800 cases with 50% mortality; but no cases in 2018 (suspected cases

in 2019?)

H7N9 influenza epidemiology

• All cases linked to China• Most cases associated with infected

chickens or contaminated environments eg live chicken markets

• Decreasing detections in chickens

• Small clusters reported but few cases in 2018

WHO Risk assessment

H7N9 clinical features

• 111 cases; wide age range (median 61 years)

• 31% female

• 77% admitted to ICU, most intubated

• 97% had radiological consolidation

• 27% mortalityDays 7, 9, 16, 42 Gao NEJM

2013

Swine influenza

• H1N2v strains• 25 human cases, • None required hospitalisation• most children at agricultural fairs

in US

FluCAN 2012-1821 hospitals (incl 6 paediatrichospitals)

17 hospitals used for surveillance

All states/territories

Metropolitan/regionalTemperate/tropical

>14% of national bed capacity

(TSANZ/ASID collaboration 2009)

Study design

Incidence density test-negative

Case = influenzaControl = non influenza ILI matched for date of presentationCase/control status assigned when test result knownAdjust for confounders

Vaccinated

Not vaccinated

Flu Non fluILI

“Exposure” “Outcome”

Admissions per week

• Elderly 30%• Children <16: 28%• Co-morbidities: 66%• ATSI: 6.4%• Pregnant: 2.2%

• FluA: 87%• 6% NSW – 28% SA

0

20

40

60

80

num

ber o

f adm

issi

ons

10 20 30 40 50epidemiological week

B A/unknown A/H3N2 A/H1N1

Peak admissions per week

• Max incidence 1.26 admissions/week (week 36)

• Mean LOS 4.6 days• Max prevalence <1%

0 2 4 6

WA RPWA PMHVIC RM

VIC MMCVIC GLVIC AHTas RHSA RAQld PAQld MAQld CBNT AS

NSW WENSW JHH

NSW CHWACT CA

ICU admissions

• Direct admission to ICU: 8.6%

• (Any admission to ICU 10%)

• ICU LOS 10 days (vs 3.8 days)

Influenza vaccines

• Funded on NIP• >65 years: aTIV (Fluad), hdTIV (Fluzone HD)• <65 years with risk factors: QIV

• Jurisdictional programs• <5 years: WA since 2008, others except NT 2018: QIV

Paediatric influenza

Risk factors by age group

NCIRS NSW report, 2016

0 16 65

No co-morbidities Chronic co-morbidities

Graphs by agegroup

Paediatric deaths from vaccine preventable diseases, NSW

FluCAN hospitalisations

Events in 2018 - Australia

• Vaccine shortages• Usual consumption predictable – 7-9

million doses/year• No major changes after 2009 pandemic• 2018 - >10 million doses (>30% increase

on 2017)• Sufficient to vaccinate >90% of elderly

• Shortages in May-June - patchy• Supply restored July

• Implications for purchase order next year?

• Implications for messaging about vaccine timing?

Vaccine coverage

• Moderate coverage in elderly

• Poor coverage in younger target groups

• Increase in coverage with paediatric programs0

.2

.4

.6

.8

Est

imat

ed v

acci

ne c

over

age

No comorbidities Comorbidities

<18 y

ears

18-64

years

65+ y

ears

<18 y

ears

18-64

years

65+ y

ears

Vaccine effectiveness (FluCAN 2017)

All patients

Flu A

A/H1N1*

A/H3N2*

Flu B

Target population

Risk factors

Elderly

Non elderly adults

Children

-20 0 20 40 60 80VE

Historical context

All2011

2012201320142015

2016Subtotal (I-squared = 66.2%, p = 0.011)

Elderly2011

20122013201420152016

Subtotal (I-squared = 67.5%, p = 0.009)

year

0.40 (0.02, 0.64)

0.38 (0.23, 0.51)0.50 (0.33, 0.63)0.50 (0.40, 0.59)0.49 (0.38, 0.58)

0.19 (0.02, 0.32)0.44 (0.39, 0.49)

0.41 (-0.62, 0.79)

0.36 (0.11, 0.54)0.53 (0.22, 0.71)0.49 (0.31, 0.62)0.42 (0.23, 0.56)-0.21 (-0.59, 0.08)

0.40 (0.31, 0.49)

VE (95% CI)

2.78

14.1311.6130.9329.03

11.51100.00

1.53

17.0612.4632.7929.256.90

100.00

Weight%

0.40 (0.02, 0.64)

0.38 (0.23, 0.51)0.50 (0.33, 0.63)0.50 (0.40, 0.59)0.49 (0.38, 0.58)

0.19 (0.02, 0.32)0.44 (0.39, 0.49)

0.41 (-0.62, 0.79)

0.36 (0.11, 0.54)0.53 (0.22, 0.71)0.49 (0.31, 0.62)0.42 (0.23, 0.56)-0.21 (-0.59, 0.08)

0.40 (0.31, 0.49)

VE (95% CI)

2.78

14.1311.6130.9329.03

11.51100.00

1.53

17.0612.4632.7929.256.90

100.00

Weight%

0-.5 0 .5 1

All types • Influenza vaccine effectiveness moderate until 2016

• Particularly low in elderly in 2016

VE issues in 2016-17

• A/H3 subtype predominating• Tends to affect elderly• Genetically diverse subtype compared to A/H1 and B

• Egg adaptation of H3 vaccine strain• Fewer vaccine candidates• Difficult to match against diverse H3 strains

• Poorly protective vaccine-induced antibodies• Vaccine poorly immunogenic in high risk groups• A/H3 vaccine issues

H3N2 diversity

• Significant genetic diversity within H3N2 circulating strains• Various clades – recent strains in 3C.2a1• Recent diversification in 2a1 clade

Hong Kong vaccine strain (2016-17)

Singapore vaccine strain (2018)

3C.2a1 clade

Nextstrain.org

Vaccine effectiveness (FluCAN 2018)

• H1 dominant season• Overall VE 55.5%• Higher in children: VE 78%

• Similar in elderly to non-elderly adults (50% vs 43%)

All patients

Flu A

A/H1N1*

A/H3N2*

Flu B

Target population

Risk factors

Elderly

Non elderly adults

Children

0 20 40 60 80VE

VE: enhanced vaccines (elderly)

hdTIV

aTIV

QIV

-1 -.5 0 .5 1VE

• hdTIV: VE 56% (14%, 78%)• aTIV: VE 44% (-6%, 70%)• QIV: VE 44%, (-66%, 81%)

• hdTIV-aTIV, p=0.44

• Many limitations- small numbers, incomplete ascertainment

Conclusions

• Complex epidemiology; surveillance requirements• Disease, vaccine coverage, vaccine effectiveness, vaccine safety• Multiple streams of data

• Gap in surveillance of vaccine coverage• Vaccine effectiveness – could be more precise

Acknowledgements

• FluCAN investigators, including Paul Kelly, Tom Kotsimbos• PAEDS investigators, including Kristine Macartney, Chris Blyth

• AuxVaxSafety – Catherine Glover

• Alfred Health Infection Prevention & Healthcare Epidemiology Unit

Vaccine safety

• Febrile convulsions related to Fluvax Jr - 2010

• WA paediatric program – febrile convulsions in 1%

• Higher rates of fever (57% Fluvax vs 17% Influvac)

• Several cases of severe neurological outcomes Saba Button (Photo: PerthNow)

Safety

• Partially unsplit products• Insufficient content of TDOC for

two new viruses• (Marakvosky, Rockman Vaccine

2012)

• Program suspended• Stokes report (WA); Horvath

report (TGA)• ACSOV established• WA: fall in vaccine coverage

from >50% (2008-09) to <20% (2010-12)

Safety

• Combination of active and passive surveillance• AusVaxSafety and associated systems• Jurisdictional surveillance – SAEFVIC, WAVSS• TGA DAEN

• International data• Specific safety studies eg Guillain Barre syndrome in 2009/10• Sponsor data - PSUR

AusVaxSafety 2018 data - influenza