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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