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
1.
2.
3.
4.
5.
6.
7.
8.
9.
Understand severe respiratory diseases caused by influenza & other pathogens
Assess influenza vaccine effectiveness
Investigate interaction between influenza & other pathogens
Understand causes of respiratory mortality
Understand non-severe respiratory diseases caused by influenza & other
pathogens
Estimate influenza infection by conducting serosurvey
Identify & quantify risk factors (age, ethnicity, SES etc) for getting influenza
Assess immune response among individuals with varying disease spectrum
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 illness
Sue 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 Effectiveness
Nikki Turner/Heath Kelly/Nevil Pierse/Ange Bissielo/Michael Baker/Don Bandaranayake/Sue Huang
–
Objectives 3 & 7 Interactions between pathogens; risk factors for flu
Michael Baker:
–
Objective 4 causes of respiratory mortality
Colin McArthur/Sally Roberts:
–
Objective 5 Primary Care Surveillance
Sue Huang/Nikki Turner
–
Objective 6 infection risk
Sue Huang/Don Bandaranayake:
–
Objective 8 immune responses
Richard Webby, Paul Thomas
–
Objective 9 economics
Des 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 influenza
3. Incidence, prevalence, demographics, clinical outcomes:
SARI, influenza
4. Vaccine effectiveness
5. Etiology of SARI cases caused by influenza and other
pathogens
6. Validity of hospital discharge data
6. Risk factors (pregnancy, high BMI etc):
SARI Case ascertainment
SHIVERS SARI and influenza cases, 2013
SARI cases - all others
140
SARI cases - influenza positive
120
2012/2013 SARI cases
80
60
40
20
0
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
SARI cases
100
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Jan
Week number 2013/2014
Feb
Mar
Apr
SARI definition
– Sensitivity of 84%
– Specificity 31%
– Positive predictive value of 17%
– Negative predictive value of 92%.
SHIVERS Influenza cases by type, 2013
Number of viruses
25
A (Not subtyped)
A(H3)
A(H1N1)pdm09
B (Lineage not determined)
B (Yamagata lineage)
B (Victoria)
Proportion positive for influenza
20
100
90
80
70
60
15
50
40
10
30
20
5
10
0
0
18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52
Week
Proportion positive
30
SARI related influenza hospitalisations by age groups
SARI influenza incidence (cases per 100 000)
250
200
150
100
50
0
influenza incidence
0 to 1
1 to 4
5 to 19
20 to 34
35 to 49
50 to 64
65 to 79
80 and
over
122.0
48.8
7.4
9.7
11.5
31.2
72.3
69.3
SARI related Influenza incidence by ethnic groups
SARI influenza incidence (cases per 100 000)
70
60
50
40
30
20
10
0
Influenza incidence
Maori
Pacific
Asian
Others
26.8
50.6
10.5
17.3
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
45
RSV
100
parainfluenza 1
Number of viruses
35
30
parainfluenza 2
parainfluenza 3
80
rhinovirus
adenovirus
hMPV
25
90
70
60
Proportion positive for non-influenza pathogen
50
20
40
15
30
10
20
5
10
0
0
18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52
Week
Proportion positive
40
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 samples
Non-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
Meets SARI definition = 2120
SARI no consent = 404
Meets ILI definition = 1891
Recruited sample
SARI = 1716
ILI: 1891
Complete records
SARI = 1530
ILI = 1809
SARI cases = 1232
ILI cases = 1663
Unique persons
SARI = 1042
ILI = 1495
Incomplete records:
No vaccination status
SARI = 71
ILI = 0
No date of birth
SARI = 4
Lab sample not tested
SARI = 111
ILI = 82
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
Influenza positive
SARI = 224 (21%)
ILI = 482 (32%)
Influenza negative
SARI = 818 (79%)
ILI = 1013 (68%)
Vaccinated
SARI = 82 (36%)
ILI = 44 (9%)
Vaccinated
SARI = 372 (45%)
ILI = 177 (17%)
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
Overall
Influenza
type or subtype
A(H1N1)
A(H3N2)
All A
All B
Age
Group
(years)
6m to 17
18 to 64
65 +
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)
32 (7 ,50)
52 (32, 66)
56 (37,70)
56 (34,70)
25 (-132,76)
48 (-74,85)
50 (-68,85)
49 (-90,86)
11 (-33,40)
34 (-2,57)
56 (27,74)
61 (32,77)
15 (-21,40)
39 (10,58)
55 (29,71)
58 (32,74)
65 (36,81)
76 (54,87)
60 (32,77)
54 (19,75)
72 (-22,93)
78 (2,95)
56 (6,79)
56 (6,79)
66 (43,-79)
61 (34,77)
59 (32,75)
55 (24,73)
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).
Population
Type of outcome
Level of protection (95% CIs)
Infants under 6-months whose
mothers received influenza vaccine
during pregnancy
Efficacy against laboratory
confirmed influenza
41% - 48%15,16
Healthy children under 2 years of age
Efficacy against laboratory
confirmed influenza
Insufficient data13,17
Effectiveness against laboratory
confirmed influenza
66% (9% - 88%)18
Healthy children aged 6-35 months
Effectiveness against laboratory
confirmed influenza
66% (29% - 84%)18
Healthy children under 16 years
of age
TIV vaccine efficacy in
prevention of laboratory
confirmed influenza in
Randomised Controlled Trials
59% (41% - 71%)17
Healthy adults (18-65 years)
Effectiveness against influenzalike-illness
30% (17% - 41%)14
Efficacy against
influenza symptoms
73% (54% - 84%)14
Elderly aged 65 years and over
(Cochrane review 2010)
Effectiveness in preventing
influenza, influenza-like-illness,
hospitalisations, complications
and mortality
Inconclusive due to poor
quality of studies19
Elderly aged 65 years and
over (Rearranged analysis of
Cochrane studies)
Effectiveness against non-fatal
and fatal complications
28% (26%-30%)20
Influenza-like illness
39% (35%-43%)20
Laboratory confirmed influenza
49% (33% - 62%)20
NISG 2014, Refs Section 4.9
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 type/
age group
Influenza-negative
Vaccine Effectiveness
Unadjusted
Adjusted1
VE %
95% CI
VE %
95% CI
Number
Vaccinated
Total
%
Number
Vaccinated
Total
%
35
148
24
118
371
32
34
N/A
SARI
Overall
(years)
-42 - 80
-18 - 87
54
N/A
46
74
58
51
19 - 71
65
33 - 81
22
61
43 - 74
48 - 79
N/A
67
N/A
66
57
N/A
73
N/A
50 - 85
-3 - 57
6mo -17
4
42
10
15
193
8
N/A2
18-49
9
58
16
13
52
25
45
-42 - 79
50-64
10
29
34
29
51
57
60
-3 - 84
65+
12
19
63
61
75
81
61
22
119
18
118
371
32
37
384
10
116
535
19 - 74
N/A
23 - 91
-36 - 87
A(H1N1)pdm09
ILI
Overall
6mo-17
2
143
1
26
226
12
N/A2
18-49
12
168
7
32
195
16
61
21 - 81
50-64
12
60
20
26
75
35
53
-4 - 79
65+
11
13
85
32
39
82
N/A2
N/A
14
220
6
116
535
22
75
56 - 86
82
N/A2
N/A
N/A
30 - 84
-1 - 82
N/A
A(H1N1)pdm09
65+
1
2
50
32
39
Manuscript in preparation Turner et al 2014
N/A
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