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Lessons for Europe from the evidence to date Evolution of the H1N1 pandemic European Centre for Disease Prevention and Control Based on various talks given.

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Presentation on theme: "Lessons for Europe from the evidence to date Evolution of the H1N1 pandemic European Centre for Disease Prevention and Control Based on various talks given."— Presentation transcript:

1 Lessons for Europe from the evidence to date Evolution of the H1N1 pandemic European Centre for Disease Prevention and Control Based on various talks given by ECDC staff Version 31 July 2009

2 2 About this presentation This is an open-access ECDC Educational PowerPoint presentation, arranged in modules for use by professionals explaining about the pandemic (H1N1) 2009 to other professionals and policy makers. The slides should always be viewed with their accompanying notes, and ‘cutting and pasting’ is not recommended. A number of the slides will change with time. The slides are updated at intervals, and the user should periodically check for updates available on the ECDC website: http://ecdc.europa.eu/ Comments on the slides and the notes are very much welcomed to be sent to influenza@ecdc.europa.eu. Please state 'Pandemic PowerPoints' in the subject line.influenza@ecdc.europa.eu ECDC thanks the National Institute of Infectious Diseases, Japan, for the original work on Slide 3, and the Centers for Disease Control and Prevention, USA, for the original idea in Slides 4 and 36.

3 3 Pandemics of influenza H7 H5 H9 * 1980 1997 Recorded new avian influenzas 19962002 1999 2003 195519651975198519952005 H1N1 H2N2 1889 Russian influenza H2N2 1957 Asian influenza H2N2 H3N2 1968 Hong Kong influenza H3N2 H3N8 1900 Old Hong Kong influenza H3N8 1918 Spanish influenza H1N1 19151925195519651975198519952005 18951905 2010 2015 2009 Pandemic influenza H1N1 Recorded human pandemic influenza (early sub-types inferred) Reproduced and adapted (2009) with permission of Dr Masato Tashiro, Director, Center for Influenza Virus Research, National Institute of Infectious Diseases (NIID), Japan. Animated slide: Press space bar H1N1 Pandemic H1N1

4 4 Genetic origins of the pandemic (H1N1) 2009 virus: viral reassortment PB2 PB1 PA HA NP NA MP NS PB2 PB1 PA HA NP NA MP NS PB2 PB1 PA HA NP NA MP NS Classical swine, N. American lineage Avian, N. American lineage Human seasonal H3N2 Eurasian swine lineage Eurasian swine H1N1 N. American H1N1 (swine/avian/human) Pandemic (H1N1) 2009, combining swine, avian and human viral components

5 5 The situation could be a lot worse for Europe! (Situation circa summer 2009)  A pandemic strain emerging in the Americas.  Immediate virus sharing so rapid diagnostic and vaccines.  Pandemic (H1N1) currently not that pathogenic.  Some seeming residual immunity in a major large risk group (older people).  No known pathogenicity markers.  Initially susceptible to oseltamivir.  Good data and information coming out of North America.  Arriving in Europe in the summer.  Mild presentation in most. A pandemic emerging in SE Asia Delayed virus sharing Based on a more pathogenic strain, e.g. A(H5N1) No residual immunity Heightened pathogenicity Inbuilt antiviral resistance Minimal data until transmission reached Europe Arriving in the late autumn or winter Severe presentation immediately Contrast with what might have happened — and might still happen!

6 6 But no room for complacency (Situation and information: late May 2009)  Pandemics take some time to get going (1918 and 1968).  Some pandemic viruses have ‘turned nasty’ (1918 and 1968).  When the pandemic wave affects Europe the health services will be challenged  There will be severely ill people and deaths — in risk groups (young children, pregnant women and especially people with underlying illnesses).  As the virus spreads south, will it exchange genes with seasonal viruses that are resistant: A(H1N1)-H247Y, more pathogenic A(H3N2), or even highly pathogenic A(H5N1)?  An inappropriate and excessive response to the pandemic could be worse than the pandemic itself.

7 7 Candidate objectives of pandemic responses  Protect citizens and visitors against the health and wider consequences of the pandemic as far as this is possible.  Through surveillance and rapid studies undertake early assessment to determine the special features of this pandemic that will inform the needed countermeasures.  Identify and protect those most vulnerable to the pandemic.  Deploy the known effective countermeasures and adapt and employ other countermeasures so that they have a net positive effect.  Apply countermeasures as effectively and equitably as possible.  Organise and adapt health and social care systems to provide treatment and support for those likely to suffer from influenza and its complications whilst sustaining other essential care services.  Support the continuity of other essential services and protect critical infrastructure.  Support the continuation of everyday activities as far as practical.  Instill and maintain trust and confidence by ensuring that the professionals, the public and the media are engaged and well informed.  Promote a return to normality and the restoration of any disrupted services at the earliest opportunity.

8 8 Idealised national curve for planning, Europe 2009: Reality is never so smooth and simple Single-wave profile showing proportion of new clinical cases, consultations, hospitalisations or deaths by week. Based on London, second wave 1918. Source: Department of Health, UK 0% 5% 10% 15% 20% 25% 123456789101112 Week Proportion of total cases, consultations, hospitalisations or de aths InitiationAccelerationPeakDeclining Animated slide: Please wait

9 9 One possible European scenario — summer 2009 In reality, the initiation phase can be prolonged, especially in the summer months. What cannot be determined is when acceleration takes place. 0% 5% 10% 15% 20% 25% AprMayJunJulAugSepOctNovDecJanFebMar Month Proportion of total cases, consultations, hospitalisations or deaths InitiationAccelerationPeakDeclining Animated slide: Press key Apr

10 10 How pandemics differ — and why they can be difficult

11 11 For any future pandemic virus – what can and cannot be assumed? What probably can be assumed: Known knowns  Modes of transmission (droplet, direct and indirect contact)  Broad incubation period and serial interval  At what stage a person is infectious  Broad clinical presentation and case definition (what influenza looks like)  The general effectiveness of personal hygiene measures (frequent hand washing, using tissues properly, staying at home when you get ill)  That in temperate zones transmission will be lower in the spring and summer than in the autumn and winter What cannot be assumed: Known unknowns  Antigenic type and phenotype  Susceptibility/resistance to antivirals  Age-groups and clinical groups most affected  Age-groups with most transmission  Clinical attack rates  Pathogenicity (case-fatality rates)  ‘Severity’ of the pandemic  Precise parameters needed for modelling and forecasting (serial interval, R o )  Precise clinical case definition  The duration, shape, number and tempo of the waves of infection  Will new virus dominate over seasonal type A influenza?  Complicating conditions (super-infections)  The effectiveness of interventions and counter-measures including pharmaceuticals  The safety of pharmaceutical interventions

12 12 Some of the 'known unknowns' in the 20th century pandemics  Three pandemics (1918, 1957, 1968).  Each quite different in shape and waves.  Some differences in effective reproductive number.  Different groups affected.  Different levels of severity including case fatality ratio.  Imply different approaches to mitigation.

13 13 0% 10% 20% 30% 40% 50% 60% 020406080 Age (midpoint of age class) % with clinical disease 1918 New York State 1918 Manchester 1918 Leicester 1918 Warrington & Wigan 1957 SE London 1957 S Wales 1957 Kansas City 1968 Kansas City With thanks to Peter Grove, Department of Health, London, UK Age-specific clinical attack rate in previous pandemics Animated slide: Press space bar

14 14 Different age-specific excess deaths in pandemics 0 2000 4000 6000 8000 10000 12000 14000 16000 0-45-910-1415-1920-2425-3435-4445-5455-6465-7475+ Age group Excess deaths 0 500 1000 1500 2000 2500 3000 3500 4000 <11-22-55-1010-1515-2020-2525-3535-4545-5555-6565-7575+ Age group Excess deaths Excess deaths, second wave, 1918 epidemic Excess deaths second wave 1969 pandemic, England and Wales Source: Department of Health, UK

15 15 1918/1919 pandemic: A(H1N1) influenza deaths, England and Wales 1918/19: ‘Influenza deaths’, England and Wales. The pandemic affected young adults, the very young and older age groups. R o = 2-3 (US) Mills, Robins, Lipsitch (Nature 2004) R o = 1.5-2 (UK) Gani et al (EID 2005) R o = 1.5-1.8 (UK) Hall et al (Epidemiol. Infect. 2006) R o = 1.5-3.7 (Geneva) Chowell et al (Vaccine 2006) Courtesy of the Health Protection Agency, UK Transmissibility: estimated Basic Reproductive Number (R o )

16 16 Estimated additional deaths in Europe if a 1918/19 pandemic occurred now – a published worst case scenario Austria13,000Latvia13,800Netherlands23,100 Belgium14,900Lithuania18,800Poland155,200 Bulgaria47,100Germany116,400Portugal25,100 Czech Rep34,100Greece27,400Romania149,900 Cyprus1,900Hungary37,700Slovenia5,000 Denmark7,300Ireland6,700Slovakia20,600 Estonia6,100Italy95,200Spain87,100 Finland8,100Luxembourg500Sweden13,300 France89,600Malta1,100UK93,000 Iceland420Norway5,800 EU total: 1.1 million Murray CJL, Lopez AD, Chin B, Feehan D, Hill KH. Estimation of potential global pandemic influenza mortality on the basis of vital registry data from the 1918–20 pandemic: a quantitative analysis. Lancet. 2006;368: 2211-2218.

17 17 1957/1958 pandemic: A(H2N2) — especially transmitted among children R o = 1.8 (UK) Vynnycky, Edmunds (Epidemiol. Infect.2007) R o = 1.65 (UK) Gani et al (EID 2005) R o = 1.5 (UK) Hall et al (Epidemiol. Infect. 2006) R o = 1.68 Longini et al (Am J Epidem 2004) 0 200 400 600 800 1,000 6 132027 3 10172431 7 142128 5 121926 29 162330 7 142128 4 111825 18 1522 JulyAugustSeptemberOctoberNovemberDecemberJanuaryFebruary Week number and month during the winter of 1957/58 Recorded deaths in England and Wales from influenza 1957/58: ‘Influenza deaths’, England and Wales Courtesy of the Health Protection Agency, UK Transmissibility: estimated Basic Reproductive Number (R o )

18 18 1968/1969 pandemic: A(H3N2) — transmitted and affected all age groups R o = 1.5-2.2 (World) Cooper et al (PLoS Med.2006) R o = 2.2 (UK) Gani et al (EID 2005) R o = 1.3-1.6 (UK) Hall et al (Epidemiol. Infect. 2006) 1968/69: GP consultations, England and Wales Courtesy of the Health Protection Agency, UK Initial appearance Seasonal influenza Transmissibility: estimated Basic Reproductive Number (R o )

19 19 Differing attack rates determined by serology: serological attack rate observed in the UK 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0-910-1920-2930-3940-4950-5960-6970-79 1969 (first wave)1970 (second wave)1957 Courtesy of the Health Protection Agency, UK

20 20 Idealised curves for local planning In reality, larger countries can experience a series of shorter but steeper local epidemics. 0% 5% 10% 15% 20% 25% 123456789101112131415 Week Proportion of total cases, consultations, hospitalisations or de aths Animated slide: Press space bar

21 21 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 1918 New York State 1918 Leicester 1918 Warrington and Wigan 1957 SE London 1968 Kansas City clinical attack rate (%) Numbers affected in seasonal influenza epidemics and pandemics Seasonal influenza (Overall clinical attack rate in the first wave of previous pandemics)

22 22 Seasonal influenza compared to pandemic — proportions of types of cases Asymptomatic Clinical symptoms Deaths Requiring hospitalisation Seasonal influenza Pandemic Asymptomatic Clinical symptoms Deaths Requiring hospitalisation

23 23 Initial experience in North America 2009

24 24 Emerging themes in North America, late July 2009 (1)  Early epidemic: –increased influenza-like illness reports due to increased consultations; –many cases attributable to seasonal influenza until mid-May.  Infection rate for probable and confirmed cases highest in 5−24 year age group.  Hospitalisation rate highest in 0−4 year age group, followed by 5−24 year age group. –Pregnant women, some of whom have delivered prematurely, have received particular attention seem to at somewhat greater risk from H1N1v than from seasonal influenza as already established.  Most deaths in 25−64 year age group in people with chronic underlying disease.  Adults, especially 60 years and old, may have some degree of preexisting cross-reactive antibody to the novel H1N1 flu virus.  Transmission persisting in several regions of the US, but not all areas are affected.

25 25 Emerging themes in North America, early June 2009 (2)  Containment with impossible with multiple introductions and R 0 1.4 to 1.6.  Initial focus on counting laboratory-confirmed cases has changed to seasonal surveillance methods with: –outpatient influenza-like illness, virological surveillance (including susceptibility), pneumonia and influenza mortality, pediatric mortality and geographic spread.  Stopped issuing reports of numbers of infected persons as these were meaningless.  Serological experiments and epidemiology suggest 2008–2009 seasonal A(H1N1) vaccine does not provide protection.  Preparing for the autumn and winter when virus is expected to return: –communications: a pandemic may be 'mild' yet cause deaths; –determining if and when to begin using vaccine; –abandoned previous plans to use proactive school closures as this was unworkable; –looking at the southern hemisphere temperate countries.

26 26 Initial experience in Europe: Planning assumptions

27 27 Revised European planning assumptions for the pandemic – first wave, pandemic (H1N1) 2009 12% of workforcePeak absence rate 0.1% to 0.2% (cannot exclude up to 0.35%) of clinical cases Case fatality rate 2% of clinical casesHospitalisation rate 15% of clinical casesComplication rate 6.5% (local planning assumptions 4.5% to 8%) per week Peak clinical attack rate 30%Clinical attack rate Courtesy of Department of Health, UK, http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/PublicationsPolicyAndGuidance/DH_102892 These assumptions represent a reasonable worst case applying to one European country (the United Kingdom) with data available as of July 2009. They should not be used for predictions.

28 28 Risk groups

29 29 Risk groups for the A(H1N1) pandemic 2009 The following groups are considered more at risk of experiencing severe disease than the general population should they become infected with the pandemic A(H1N1) virus 2009:  People with chronic conditions in the following categories: –chronic respiratory diseases; –chronic cardiovascular diseases (though not isolated mild hypertension); –chronic metabolic disorders (notably diabetes); –chronic renal and hepatic diseases; –persons with deficient immunity (congenital or acquired); –chronic neurological or neuromuscular conditions; and –any other condition that impairs a person’s immunity or prejudices their respiratory (breathing) function, including severe or morbid obesity. Note: These categories will be subject to amendment and development as more data become available. These are very similar underlying conditions that serve as risk factors for seasonal influenza. What is especially different from seasonal influenza is that the older age groups (over the age of 60 years) without underlying conditions are relatively unaffected by the pandemic strain.  Pregnant women.  Young children (especially those under two years). Sources: ECDC Pandemic 2009 Risk Assessment. Available from: http://www.ecdc.europa.eu/en/Health_topics/novel_influenza_virus/2009_Outbreakhttp://www.ecdc.europa.eu/en/Health_topics/novel_influenza_virus/2009_Outbreak Finelli L. CDC Influenza Surveillance. Available from: http://www.cdc.gov/vaccines/recs/ACIP/downloads/mtg-slides-jun09/15-2-inf.pdfhttp://www.cdc.gov/vaccines/recs/ACIP/downloads/mtg-slides-jun09/15-2-inf.pdf Nicoll A et al. Eurosurveillance, Volume 13, Issue 43, 23 October 2008. Available from: http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=19018http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=19018 Jamieson D et al. Lancet 2009; July 29, 2009 DOI:10.1016/S0140-6736(09)61304-0 CDC 2009 ACIP Meeting, 31 July 2009. Novel influenza A(H1N1) epidemiology update. Available from: http://www.cdc.gov/vaccines/recs/ACIP/downloads/mtg-slides-jul09-flu/02- Flu-Fiore.pdfhttp://www.cdc.gov/vaccines/recs/ACIP/downloads/mtg-slides-jul09-flu/02- Flu-Fiore.pdf CDC 2009 ACIP Meeting, 31 July 2009. Vaccine workgroup considerations. Available from: http://www.cdc.gov/vaccines/recs/ACIP/downloads/mtg-slides-jul09-flu/11-Flu- Fiore.pdfhttp://www.cdc.gov/vaccines/recs/ACIP/downloads/mtg-slides-jul09-flu/11-Flu- Fiore.pdf

30 30 Measuring the severity of a pandemic

31 31 There is an expectation that pandemics should be graded by severity But there are difficulties:  severity varies from country to country;  it can change over time;  some relevant information is not available initially;  key health information includes medical and scientific information: –epidemiological, clinical and virological characteristics.  There are also social and societal aspects: –vulnerability of populations; –capacity for response; –available health care; –communication; and –the level of advance planning.

32 32 What is meant by 'mild' and 'severe'? Not a simple scale  Death ratio. Expectation of an infected person dying (the Case Fatality Ratio).  Number of people falling ill with respiratory illnesses at one time — 'winter pressures'. Pressure on the health services' ability to deal with these — very related to preparedness and robustness.  Critical service functioning. Peak prevalence of people off ill or caring for others.  Certain groups dying unexpectedly, e.g. children, pregnant women, young healthy adults.  Public and media perception.  Conclusions. Not easy to come up with a single measure.  May be better to state what interventions/countermeasures are useful and justifiable (and what are not). http://www.who.int/csr/disease/swineflu/assess/disease_swineflu_assess_20090511/en/index.html and http://www.who.int/wer/2009/wer8422.pdf

33 33 Arguments for and against just undertaking mitigation and not attempting delaying or containment

34 34 Arguments for just mitigating and not attempting delaying or containment:  Containment specifically not recommended by WHO in Phases 5 and 6.  Was not attempted by the United States for this virus.  Delaying or containment cannot be demonstrated to have worked — would have seemed to have worked in 1918 and 1968 without doing anything.  Very labour-intensive — major opportunity costs.  Will miss detecting sporadic transmissions.  Overwhelming numbers as other countries ‘light up’.  When you change tactic, major communication challenge with stopping prophylaxis. Policy dilemma – mitigating vs. attempting delaying (containing) pandemics?

35 35 Policy dilemma – mitigating vs. attempting delaying (containing) pandemics? Arguments for case-finding, contact tracing and prophylaxis:  Countries are then seen to be doing something.  Recommended in one specific circumstance by WHO (the rapid containment strategy).  There are some places it would work in Europe (isolated communities).  It is what public health people do for other infections.  Public may expect it.

36 36 With interventions Aims of community reduction of influenza transmission — mitigation  Delay and flatten epidemic peak.  Reduce peak burden on healthcare system and threat.  Somewhat reduce total number of cases.  Buy a little time. Daily cases Days since first case No intervention Animated slide: Press key Based on an original graph developed by the US CDC, Atlanta


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