SHIVERSSouthern Hemisphere Influenza and Vaccine Effectiveness Research

and SurveillanceNikki TurnerMarch 2012

http://www.grabonestore.co.nz/man-flu-joke-set?utm_source=GrabOne+Store+New+Zealand&utm_campaign=ET_18393_nz-store_new-zealand_20120321&utm_medium=emailhttp://www.vaccineinfo.net/immunization/vaccine/influenza/index.shtmlhttp://fnp2011.wordpress.com/2011/03/04/having-influenza/http://www.briancombs.net/tag/swine-flu/

I have flu doctor…….• How do we recognise flu

o How much is really • in the community• In hospital presentations

o What are its characteristic presentationso Are we diagnosing it allo Is there subclinical/asymptomatic?

• How effective are current flu vaccineso In subpopulationso In different years with shifting strains

http://www.extension.org/pages/24425/avian-influenza-homepage

Influenza and other respiratory diseases in southern hemisphere

• CDC Announcement: 27 Dec 2010• Application Due date: 14 Mar 2011• Research for 9 objectives:

o Two primary objectiveso Seven additional objectives

• Study period: o 1st year: Two primary objectiveso 2nd – 5th years: Two primary objectives + additional objectives

• Notice of award: Oct 2011

CDCs 9 objectives1. 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 o Sue Huang—Principle investigator (PI)o Graham Mackereth – Project managero Ruth Seeds – Project Officer

• Science teams:o 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 1

o Nikki Turner/Heath Kelly/Nevil Pierse/Ange Bissielo/Michael Baker/Don Bandaranayake/Sue Huang: objective 2 Vaccine Effectiveness

o Michael Baker: objectives 3 & 7o Colin McArthur/Sally Roberts: objective 4o Sue Huang/Nikki Turner: objective 5 Primary Care Surveillanceo Sue Huang/Don Bandaranayake: objective 6o Richard Webby: objective 8o Des O’Dea: objective 9

Tools: Two surveillance systems

• Hospital-based surveillance: enhanced, active, year-round (5 yrs), population based surveillance for hospital SARI (sudden acute respiratory) caseso Auckland and Middlemore Hospitals

• Community-based surveillance: enhanced, active, (4 yrs), population based surveillance for community ILI (Influenza-like illness) cases caused by influenzao Recruitment of 50 – 100 ‘sentinel’ General Practices in

greater Auckland (200,000 – 400,000 patients)

Objective 1 – Hospital-based surveillance

• Identify the aetiology of hospitalised severe acute respiratory infections, including influenza

• Describe possible risk factors eg asthma high BMI, pregnancy etc

• Will need to access some practice data ?PMS extractiono Flu vccination hxo High risk medical conditionso Medication listso Pneumococcal vaccination hx

• Utilise this data for VE measures

Objective 5 – Community-based surveillance

Sue Huang and Nikki TurnerSHIVERS Researchers

• Identify the aetiologies of acute presentations to the general practice with respiratory symptoms, including influenza o Cougho Fever

• Describe possible risk factors eg asthma high BMI, chronic conditions,pregnancy, ethnicity, age, ses

• Utilise this data for VE measures

Needs…..• Sentinel GP surveillance starting in 2013

o 60 GPs: ~ 180,000 registered patients (14% Auckland population)

• ?All year round• All acute respiratory illnesses presenting if

possible:o Swabo Questionnaire (brief, advanced form)o PMS data extraction

Gains for General Practice• Improved understanding of causes of respiratory illnesses• Rapid feedback of swab results to the involved practices

o fluo Anther virus

• Information on spread of flu in the community in real time• Yearly Vaccine Effectiveness measures

o If numbers large enough, in subpopulations

• Better understanding of symptomatic presentation of flu/nonflu

• Hope to build into a Cornerstone indicator/ MOPS • Showcase NZ General practice to the world

o Enrolled populationso Excellent systemso Ability to utlilise PMS data/data extraction

Thank you

Data requirement (PMS)

• Influenza vaccination record: this year and previous years; type and date; batch number

• Pneumococcal vaccination record: type of vaccine, date • Read codes: high risk medical conditions.• Read codes: current, ex or non-smoker• Read codes: last recorded BMI or body weight• Medication list: identify medications associated with chronic disease (asthma,

heart disease, COPD, cancer, immunosuppression)• Outbox: count all hospital admissions, ED visits, A&M visits in the past 12

months• Count number of GP and practice nurse visits in the past 12 months• Any prescription issued for antivirals in the past 12 months (Tamiflu or Relenza)

Data requirement (Questionnaire)

• Clinical symptoms and history of current illness• Additional risk factor information• Treatment• Disease course • Employment condition• Living condition• BMI (if not available on PMS)• Pregnancy

Laboratory testing

Objective 6 – Serosurvey for seasonal influenza infection

Don Bandaranayake, Sue Huang

Specific aims• estimate the annual incidence of infection with

seasonal influenza in the Auckland region.• To collect information on host, environmental,

behavioral factors and health service utilization.• To estimate the disease burden of all seasonal

influenza infections [from asymptomatic, mild and severe infections to deaths].

Study area (Auckland) population in ADHB & CMDHB: 837,696

Hospital study population GP based study population

2 VE

7 Risk factor impact

9 Economics

Specimen flow

Data flow

All ILI patients

(respiratory specimen)Al

l SAR

I pati

ents

(res

pira

tory

spec

imen

)

Some SARI patients’ blood

Some ILI patients(Blood)

Strat. random sample

Cases + controls

Cases + controls Cases + controls

Cases + su

bcohort

Cases + controls

8 Immune response

6Infection risk

5 Mild disease 1

Severe disease

3 Interactions

4Mortality

Objectives1 Severe disease2 VE3 Interactions4 Mortality5 mild disease6 Infection risk7 Risk factor impact8 Immune response9 Economics