Results of the initial analysis on strain-based reporting

Eeva Broberg, Olav Hungnes, Adam Meijer, Katarina Prosenc, Brunhilde Schweiger

2

Background

• Discussions with the network since 2010 of enhancing the data collection towards molecular surveillance

• Strain-based reporting for antigenic and genetic characterisation was implemented in TESSy as a pilot in 2013-2014 season

• Variables for antigenic group and genetic clade added to existing antiviral susceptibility data collection

• Sequence accession numbers reported in existing variables

• Used existing reporting scheme for strain-based antiviral data

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Objective

To analyse the benefits of strain-based over the aggregated reporting through sub-objectives of:

1) To test the feasibility of strain-based reporting of antigenetic/genetic data to TESSy;

2) To study the representativeness of virus characterisation

3) To monitor the evolution of influenza viruses over time

4) To continue monitoring of antiviral susceptibility

5) To analyse distribution of virus (sub)types, genetic clades and antigenic groups by age and gender or any other variable with sufficient completeness.

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Methods

• Influenza virological data were retrieved from TESSy for the 2013-2014 season.

• Antigenic and genetic data were reported both in aggregate and strain-based manner by the pilot countries

• Descriptive analysis was performed

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Reporting countries

11 countries agreed to take part in the pilot and found this feasible.

N=1,633

BE DE EL ES FI IE IT NL NO PT SE0

100

200

300

400

500

600

Characterisation data by country

AGAG and GENGEN

Num

ber

of r

ecor

ds

6

Data completeness

subt

ype

repo

rting

cou

ntry

age

gend

er

antig

enic

grou

p

gene

tic cla

de

HA ISD n

r

hosp

italis

atio

n

outc

ome

vacc

inat

ion

stat

us

date

of o

nset

0102030405060708090

100

meaningful completeness (excl. unknowns)

Variable

%

7

Age and gender distribution – no difference by gender

<1

01-05

06-19

20-39

40-64

>=65

250 200 150 100 50 0 50 100 150 200 250

M F

Number of cases

Age-group (y)

Kruskal-Wallis equality of populations, gender vs age-group, p=0.1611; gender vs. subtype p=0.2849

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Detections and strain-based records

  Aggregated detections Strain-based recordsProportion of strain-

based out of detections (%)

  SentinelNon-sentinel

Total SentinelNon-sentinel

Unknown Total SentinelNon-sentinel

Total

A(H1N1)pdm09 2089 7690 9779 237 505 5 747 11.3 6.6 7.6

A(H3N2) 1714 3219 4933 311 464 4 779 18.1 14.4 15.8

B (lineage not determined)

60 663 723 0 0 0 0 0.0 0.0 0.0

B(Victoria) 7 9 16 9 11 0 20 128.6 122.2 125.0

B(Yamagata) 50 168 218 29 57 1 87 58.0 33.9 39.9

Total detections (aggregate) or reports (strain-based)

3920 11749 15669 586 1037 10 1633 14.9 8.8 10.4

Nr of specimens 11631 112571 124202 In strain-based the number of specimens is the total of reports. 

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Timing of strain-based records - A(H1N1)pdm09

detections

antigenic characterisations

genetic characterisations

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Timing of strain-based records - A(H3N2)

detections

antigenic characterisations

genetic characterisations

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Genetic evolution of viruses – example: B(Yam)

2015-2016 vacc.

2013-2014 vacc.

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Antiviral susceptibility

-2

-1

0

11.0

1.2

1.4

1.6

1.8

2.02

3

4

5

A(H1N1)pdm09

Antiviral drug

IC50 fold

change (

10lo

g)

I223R (n=1)

S247I (n=1)? (n=1)

HR

IR

IN

I

D199N

D199N

-2

-1

0

11.0

1.2

1.4

1.6

1.8

2.02

3

4

5

A(H3N2)

Antiviral drug

IC50 fold

change (

10lo

g) ?

HR

IR

IN

I?

?

-2

-1

0

0.8

1.0

1.2

1.4

1.6

2

3

4

5

B

Antiviral drug

IC50 fold

change (

10lo

g) ?

HR

IR

IN

I

A(H1N1)pdm09 A(H3N2) B

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Hospitalisations and genetic clade

N=325, comparison by age-group p=0.0190

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Genetic clade by age-group

N=1061, comparison by age-group, p=0.0014

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Age distribution H3 clades during 2014/2015 season

~80% 3C.3b

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Limitations

– Specimen selection for characterisation is based on individual laboratories’ decision, however, aiming for best possible representativeness by subtype, age, gender, severity and geographic location

– Not population-based or based on a specific study design

– This was a pilot, not an European-wide study– Provision of data by countries was not equal;

resource and approach differences– Data completeness for some variables such as

outcome and vaccination status was low

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Benefits of strain-based reporting

- Opportunity for deeper analysis- Validation possibility between genetic clade,

antigenic group and subtype reporting- Is of even more value in a season where a variant

strain emerges, e.g. in 2014/15 season where it was possible to analyse the deviation from the vaccine strain

- Gives a “fingerprint” or “pattern” of the season in terms of demographic or e.g. hospitalisation status

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What the strain-based reporting does not allow

- Draw strong conclusions about severity, mortality and vaccination status as the data is based on surveillance from both sentinel and non-sentinel sources without an agreed sampling scheme especially for the non-sentinel in different countries

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Conclusions

• Strain-based reporting should be recommended to all countries as it enhances understanding of circulation of influenza viruses in different populations

• Ca 10% of all detections were characterised• Good representation of different age-groups and

genders in data• Timing of characterisations matching well with the

epidemic • Genetic analysis shows e.g. that B/Yamagata Phuket-

strains were in circulation already in season 2013-2014

• Only a few viruses with reduced inhibition to oseltamivir or zanamivir reported from the pilot countries during the season

• Distribution of genetic clades by age-groups differs

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Acknowledgements

Strain-based reporting country contact points:Isabelle Thomas, Belgium

Niina Ikonen, Finland

Brunhilde Schweiger, Germany

Thanos Kossyvakis, Greece

Allison Waters, Ireland

Isabella Donatelli, Italy

Adam Meijer, Netherlands

Olav Hungnes, Norway

Raquel Guiomar, Portugal

Inmaculada Casas, Spain

Mia Brytting, Sweden

Rod Daniels, WHO CC

Adrian Prodan, ECDC

Working group members: Olav, Adam, Katarina, Bruni

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Questions to the WG

1. Do you agree with

• the added value of strain-based reporting?

• closing the aggregate reporting after season 2016/17?

2. What type of outputs do you expect with the new reporting and how often?

3. What needs to you have in your institute for support for implementation of strain-based reporting?

4. How can we improve the completeness of the data?

5. Are there possibilities to combine this data with the SARI/ICU reporting?

6. How can we improve the representativeness of the sampling? Should a separate study take place to assess the representativeness?