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Southern Hemisphere Influenza and Vaccine Effectiveness Research and Surveillance (SHIVERS). Comprehensive investigation of influenza epidemiology, aetiology, immunology and vaccine effectiveness US CDC 5 year funded project Started 2012. 9 objectives. - PowerPoint PPT Presentation
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Southern Hemisphere Influenza and Vaccine Effectiveness Research and
Surveillance (SHIVERS)
Comprehensive investigation of influenza epidemiology, aetiology, immunology and
vaccine effectiveness
US CDC 5 year funded projectStarted 2012
9 objectives
1. Understand severe respiratory diseases caused by influenza & other pathogens2. Assess influenza vaccine effectiveness3. Investigate interaction between influenza & other pathogens4. Understand causes of respiratory mortality5. Understand non-severe respiratory diseases caused by influenza & other
pathogens6. Estimate influenza infection by conducting serosurvey7. Identify & quantify risk factors (age, ethnicity, SES etc) for getting influenza 8. Assess immune response among individuals with varying disease spectrum9. Estimate healthcare, societal economic burden caused by influenza and
vaccine cost-effectiveness
Project Team – multi-centre and multi-disciplinary collaboration
• ESR—leading organization – Sue Huang—Principle Investigator (PI)– Graham Mackereth – Project Manager– Ruth Seeds – Project Officer
• Science teams:– Objective 1 Severe illnessSue Huang/Sally Roberts/Colin McArthur/Cameron Grant/Debbie Williamson/Adrian Trenholme/Conroy Wong/Susan Taylor/Graham Mackereth/Don Bandaranayake/Diane Gross/Marc-Alain Widdowson: – Objective 2 Vaccine EffectivenessNikki Turner/Heath Kelly/Nevil Pierse/Ange Bissielo/Michael Baker/Don Bandaranayake/Sue Huang – Objectives 3 & 7 Interactions between pathogens; risk factors for fluMichael Baker: – Objective 4 causes of respiratory mortalityColin McArthur/Sally Roberts: – Objective 5 Primary Care SurveillanceSue Huang/Nikki Turner– Objective 6 infection riskSue Huang/Don Bandaranayake: – Objective 8 immune responsesRichard Webby, Paul Thomas– Objective 9 economicsDes O’Dea:
Study site - Auckland
ADHB and CMDHB Population: 837,696
Two surveillance systems
• Hospital-based surveillance: enhanced, active, longitudinal (5 yrs), population based surveillance for hospital SARI cases, ICU admissions and deaths caused by influenza and other respiratory pathogens in Auckland
• Community-based surveillance: enhanced, active, longitudinal (4 yrs), population based surveillance for community ILI cases caused by influenza and other respiratory pathogens in Auckland
SHIVERS - Hospital SARI surveillance• all public hospitals in ADHB & CMDHB:- Auckland City hospital and Starship Childrens
hospital- Middlemore hospital and Kidz First Childrens
hospital
• SARI case definition: An acute respiratory illness with onset in the last 7 (10) days with a history of fever or measured fever of ≥ 38°C, and cough, requiring hospitalisation
• Data captured by case report form- Medical records/lab results- Interview patients
• Sample: NPS/NPA
Q Sue Huang et al Implementing hospital-based surveillance for severe acute respiratory infections caused by influenza and other respiratory pathogens in New Zealand WPSAR Vol 5, No.2 2014
Aims - Hospital-based surveillance (SARI)
1. 5-year surveillance for SARI cases 2. Non-SARI cases: contribution of influenza3. Incidence, prevalence, demographics, clinical outcomes:
SARI, influenza4. Vaccine effectiveness5. Etiology of SARI cases caused by influenza and other
pathogens6. Validity of hospital discharge data6. Risk factors (pregnancy, high BMI etc):
SARI Case ascertainment
SHIVERS SARI and influenza cases, 2013
0
20
40
60
80
100
120
140
18
20
22
24
26
28
30
32
34
36
38
40
42
44
46
48
50
52 2 4 6 8 10
12
14
16
May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr
SA
RI
ca
se
s
Week number 2013/2014
SARI cases - all others
SARI cases - influenza positive
2012/2013 SARI cases
SARI definition– Sensitivity of 84% – Specificity 31%– Positive predictive value of 17%– Negative predictive value of 92%.
SHIVERS Influenza cases by type, 2013
0
10
20
30
40
50
60
70
80
90
100
0
5
10
15
20
25
30
18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52
Pro
po
rtio
n p
osi
tive
Nu
mb
er o
f vi
ruse
s
Week
A (Not subtyped)A(H3)A(H1N1)pdm09B (Lineage not determined)B (Yamagata lineage)B (Victoria)Proportion positive for influenza
SARI related influenza hospitalisations by age groups
0 to 1 1 to 4 5 to 19 20 to 34 35 to 49 50 to 64 65 to 79 80 and over
influenza in-cidence
121.9884 48.80429 7.361602 9.72937 11.51175 31.17335 72.27981 69.26921
10
30
50
70
90
110
130SA
RI in
fluen
za in
cide
nce
(cas
es p
er 1
00 0
00)
SARI related Influenza incidence by ethnic groups
Maori Pacific Asian Others
Influenza incidence 26.78038 50.59705 10.54264 17.30869
5
15
25
35
45
55
SARI
influ
enza
inci
denc
e (c
ases
per
100
000
)
SARI related Influenza incidence by socioeconomic status
Known and unknown etiologies for SARI cases
Non-influenza Respiratory Viruses Number (%)
No. of specimens tested 870
No. of positive specimens 388
Rhinovirus 168 (44)
Respiratory Syncytial Virus 162 (42)
Parainfluenza 55 (14) - Parainfluenza 3 - 34 % of all PIV
- Parainfluenza 2 - 18 % of all PIV
- Parainfluenza 1 - 3 % of all PIV
Human metapneumovirus 46 (12)
Single virus detection (% of positive) 303 (78)
Multiple virus detection (% of positives) 85 (22)
SHIVERS SARI - other non-influenza respiratory viruses, 2013
0
10
20
30
40
50
60
70
80
90
100
0
5
10
15
20
25
30
35
40
45
18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52
Pro
port
ion
posi
tive
Num
ber
of v
irus
es
Week
RSV
parainfluenza 1
parainfluenza 2
parainfluenza 3
rhinovirus
adenovirus
hMPV
Proportion positive for non-influenza pathogen
SHIVERS - Community ILI surveillance• 18 practices: 103,752 enrolled patients
(~14% ADHB & CMDHB popn)- ADHB (60,068): ~17% ADHB popn- CMDHB (43,684): ~10% of CMDHB popn
• ILI case definition: An acute respiratory illness with onset in the last 10 (7) days with a history of fever or measured fever of ≥ 38°C, and cough, requiring GP consultation
• Data requirement:- Data from existing PMS- Data from an advanced form (includes
specimen request form)
• Sample: NPS/throat swab
Advanced form in MedTech
181,603 GP consultations– 2016 (1.1%) met ILI definition
• 1802 (89.4%) had lab test– 448 (24.9%) flu positive
ILI case definition– Sensitivity of 92%– Specificity 27%– Positive predictive value of 45%– Negative predictive value of 85%
SHIVERS ILI and influenza cases, 2013
SHIVERS ILI and influenza 29 April – 3 November 2013
Non-influenza viruses isolated from ILI samplesNon-influenza Respiratory Viruses Number (%)
No. of specimens tested 1686
No. of positive specimens 552
Rhinovirus 221 (40%)
Respiratory Syncytial Virus 154 (28%)
Parainfluenza 97 (17.5%)
- Parainfluenza 2 43 (8 %)
- Parainfluenza 3 43 (8%)
- Parainfluenza 1 11 (2%)
Human metapneumovirus 56 (10%)
Single virus detection (% of positive) 495 (89.7%)
Multiple virus detection (% of positives) 57 (10.3%)
Influenza disease burden by age, ILI vs SARI
Influenza incidence by ethnic groups, ILI vs SARI
Influenza incidence by SES groups, ILI vs SARI
Influenza disease burden, 2013
Vaccine Effectiveness
• Case test-negative design– SARI and ILI
• Cases = flu positive by PCR• Controls = flu negative by PCR
• Adjusted for timing of influenza season and propensity to be vaccinated = adjOR– Older, chronic diseases more likely to be vaccinated– No difference by ethnicity, gender, income, pregnancy,
obesity, self rated health, smoking, assisted living, or timing of admission
Flowchart of all selected, recruited and tested ILI and SARI cases for VE analysis
Recruited sample SARI = 1716 ILI: 1891
Incomplete records: No vaccination status
SARI = 71 ILI = 0
No date of birth SARI = 4
Lab sample not tested SARI = 111 ILI = 82
Complete records SARI = 1530 ILI = 1809
Influenza negative SARI = 818 (79%) ILI = 1013 (68%) Vaccinated SARI = 372 (45%) ILI = 177 (17%)
Meets SARI definition = 2120 Meets ILI definition = 1891
Unique persons SARI = 1042 ILI = 1495
Influenza positive SARI = 224 (21%) ILI = 482 (32%)
Vaccinated SARI = 82 (36%) ILI = 44 (9%)
SARI no consent = 404
SARI cases = 1232 ILI cases = 1663
Exclusions : < 6months of age
SARI = 153 ILI = 5
< 9 yrs one dose SARI = 3 ILI = 34
<14 days since vaccination SARI = 33 ILI = 15 >7 days since onset symptoms SARI = 109
ILI = 92
Not in flu season SARI = 167 ILI = 110 Unused repeat admissions
SARI = 23 ILI = 58
Estimated vaccine effectiveness (VE), overall by age group and by influenza type and sub-type: crude and propensity adjusted models
Hospitalised with Severe Acute Respiratory Illness
General Practice visit for Influenza-like illness
Crude Model* Propensity Adjusted Model*
Crude Model* Propensity Adjusted Model*
VE % (95%CI) VE% (95% CI) VE % (95% CI) VE %(95% CI) Overall
32 (7 ,50) 52 (32, 66) 56 (37,70) 56 (34,70)
Influenza type or sub-type
A(H1N1)25 (-132,76) 48 (-74,85) 50 (-68,85) 49 (-90,86)
A(H3N2)11 (-33,40) 34 (-2,57) 56 (27,74) 61 (32,77)
All A15 (-21,40) 39 (10,58) 55 (29,71) 58 (32,74)
All B65 (36,81) 76 (54,87) 60 (32,77) 54 (19,75)
Age Group(years)
6m to 1772 (-22,93) 78 (2,95) 56 (6,79) 56 (6,79)
18 to 6466 (43,-79) 61 (34,77) 59 (32,75) 55 (24,73)
65 +35 (-25,66) 34 (-28,66) 74 (12,92) 76 (15,93)
*All models were adjusted for the number of weeks from the influenza peak
Turner, N. M., Pierse, N., Bissielo, A., Huang, Q. S., Radke, S., Kelly, H. (2014). Effectiveness of seasonal trivalent inactivated influenza vaccine in preventing influenza hospitalisations and primary care visits in Auckland, New Zealand, in 2013. Euro surveillance: bulletin Européen sur les maladies transmissibles= European communicable disease bulletin, 19(34).
NISG 2014, Refs Section 4.9
Elderly aged 65 years and over
(C oc hra ne rev iew 2010)
Elderly aged 65 years and
over (R earranged ana lys is of
C ochra ne stud ie s)
E f fectiveness in preventing
in fluenza, in fluenza- like-illne ss,
hosp ita lisations, complications
and m orta lity
Effec tive ness aga ins t non-fa ta l
and fa ta l complications
In fluenza-like illness
L aborato ry confirmed in flue nza
Inconc lus ive due to poor
qua lity of studies19
28% (26%-30%)20
39% (35%-43%)20
49% (33% - 62%)20
In fan ts under 6-months whose mothers rece ived in flue nz a vacc ine
during pregnancy
E f ficacy aga ins t laboratory confirmed in flue nza
41% - 48%15,16
H ea lthy c h ild ren under 2 years of age Ef ficacy aga ins t laboratory confirmed in flue nza
Insu ffic ien t da ta13,17
Effec tive ness aga ins t labora tory
confirmed in flue nza
66% (9% - 88%)18
H ea lthy c h ild ren aged 6-35 months Effec tive ness aga ins t labora tory confirmed in flue nza
66% (29% - 84%)18
H ea lthy c h ild ren under 16 years
of age TIV vacc ine e f ficacy in
prevention of laborato ry confirmed in flue nza in
R a ndom ised C on tro lle d Tr ia ls
59% (41% - 71%)17
H ea lthy adults (18-65 years) E ffec tive ness aga ins t in flue nza- like-illness
30% (17% - 41%)14
Ef ficacy aga inst
in fluenza symptoms
73% (54% - 84%)14
Population Type of outcome Level of protection (95% CIs)
Conclusions: 2013 • 2013 season low incidence and late peak
– Influenza activity peaked late in week 37 (mid Sept). – A (H3N2) and B most commonly detected– Very high hospitalisation rates in very young (122,100 000), then 80+ (69/100 000)– Pacific hospitalisation rates 4 times higher, Maori 1.5 times higher than other groups– Large differences by deprivation with lower quintile 4 times higher rates than upper quintile
• 2013 the first year of SHIVERS ILI surveillance – Approach was acceptable to working general practice– GP visits for influenza different pattern from hospitalisations
• higher rates in mid-ages • less lower socioeconomic presentations
• Vaccine is ‘moderately’ effective against hospitalisation and general practice influenza
…..2014
• Average flu season• Dominated by A(H1N1), occasional A(H3N2)• 12% B
….2014• Dominated by A(H1N1)• Few A(H3N2)• 12% B
Ref: ESR 2014
Study participants with influenza-like illness (ILI) and severe acute respiratory infections (SARI) who were influenza positive or negative, by week, New
Zealand, 28 April to 31 August 2014
Estimated influenza vaccine effectiveness, by participant age group and by influenza virus type and subtype: crude plus age and time adjusted models,
New Zealand, 28 April to 31 August 2014
Influenza-positive Influenza-negative Vaccine Effectiveness Unadjusted Adjusted1
Influenza type/ age group
Number Vaccinated
Total % Number Vaccinated
Total % VE % 95% CI VE % 95% CI
SARI Overall(years)
35 148 24 118 371 32 34 -3 - 57 54 19 - 746mo -17 4 42 10 15 193 8 N/A2 N/A N/A N/A
18-49 9 58 16 13 52 25 45 -42 - 79 46 -42 - 8050-64 10 29 34 29 51 57 60 -3 - 84 74 23 - 9165+ 12 19 63 61 75 81 61 -18 - 87 58 -36 - 87
A(H1N1)pdm09
22 119 18 118 371 32 51 19 - 71 65 33 - 81
ILIOverall 37 384 10 116 535 22 61 43 - 74 67 48 - 796mo-17 2 143 1 26 226 12 N/A2 N/A N/A N/A18-49 12 168 7 32 195 16 61 21 - 81 66 30 - 8450-64 12 60 20 26 75 35 53 -4 - 79 57 -1 - 8265+ 11 13 85 32 39 82 N/A2 N/A N/A N/A
A(H1N1)pdm09
14 220 6 116 535 22 75 56 - 86 73 50 - 8565+ 1 2 50 32 39 82 N/A2 N/A N/A N/A
Manuscript in preparation Turner et al 2014
Gains
• SHIVERS data contributed to influenza vaccination policy changes 2013– <5 yrs with significant respiratory illness
• SHIVERS data contributed to finalising WHO SARI case definitions for ‘global influenza surveillance standards’
Vaccine Effectiveness: Outstanding challenges
• Further delineation of higher risk groups– VE by different age groups, other risk groups,
history of vaccination• Do we have the right schedule?• Do we have the right vaccines?
– Mediocre VE• Likely to be lower in some groups
– Directed at personal protection• May be less effective in higher risk individuals
Future VE
• Better capture of vaccination record– NIR
• Consider possible other confounders– ?previous presentations with respiratory illness
• Analysis also include by history of previous vaccination
• Analysis by numbers of hospitalisations and GP visits prevented
Future for flu vaccines?
• Schedule decisions– Personal protection versus community immunity– Ring protection around very vulnerable– Targeted high risk groups
• Newer vaccines ?– Quadrivalent (x2A, x2 B)– Live attenuated for children (LAIV)– Adjuvanted for elderly, higher risk
Thank you
The second SHIVERS science meeting, 7-8 November, 2012
Acknowledgement• ESR: Don Bandaranayake, Ruth Seeds, Tim Wood, Ange Bissielo, Sarah Radke,
Graham Mackereth, Thomas Metz, Anne McNicholas, Angela Todd, Laboratory staff, IT staff
• ADHB: Sally Roberts, Colin McArthur, Debbie Williamson, Research nurses, clinical team staff, laboratory staff, IT staff
• CMDHB: Adrian Trenholme, Conroy Wong, Susan Taylor, Lyndsay Le Comte, Research nurses, clinical team staff, laboratory staff, IT staff
• University of Auckland: Nikki Turner, Cameron Grant, Gary Reynolds, Barbara McArdle, Tracey Poole, Anne McLean, Debbie Raroa, Carol Taylor
• University of Otago: Michael Baker, Nevil Pierse, David Murdoch• Primarycare Advisory Group from PHOs (Procare, East Tamaki, Auckland) and
ARPHS: John Cameron, Bruce Adlam, Gary Reynolds, Rosemary Gordon, Sam Wong, Leane Els, Marion Howie, Gillian Davies
• ILI sentinel practices• WHOCC-St Jude: Richard Webby, Paul Thomas• US-CDC: Marc-Alain Widdowson, Mark Thompson, Jazmin Duque, Diane Gross• Funding from US-CDC: 1U01IP000480-01