Analyzing Bird Flu Pandemic: Impact on Insurance Industry

1. Bird FluA threat to Insurance? Henk van Broekhoven

2. Preface • On request of EC Groupe Consultatif started a task force to analyse the possible impact on insurance because of the Bird Flu • Actuaries involved: • Anni Hellman (EC) • Henk van Broekhoven • Erik Alm • Tapani Tuominen • + experts (other disciplines) from EC

3. Pandemic • A Pandemic arises when a disease that affects at least 25% of the globe causes high morbidity, excess mortality and social and economic disruption • Pandemics cause a sudden explosion of illness putting heath services under strain • Pandemics spread very rapidly around the world

4. Pandemic • Three pandemics in the twentieth century: • 1918 Spanish Flu • By far the most deathly pandemic in the last 400 years (= observation period) • 99% of the deaths were younger than 65 (!) • Worldwide 40-50 million deaths

5. Pandemic • Three pandemics in the twentieth century: • 1957 Asian Flu • Global deaths 2 million (USA 70,000 excess) • 90% of the deaths were older than 65 • Looked more like a normal seasonal flu, but with more sick people (>25%) • Started in China Febr. 1957, reached Hong Kong in April and the rest of the world in 6 months

6. Pandemic • Three pandemics in the twentieth century: • 1968 Hong Kong Flu • Less deaths than the Asian Flu 1957 (USA 36,000) • Looked similar to the 1957 flu

7. Spanish Flu 1918 • Why was this pandemic so deathly? • 1918 end of first World War • Tuberculosis epidemic in same period • People died within 8 hours after detecting condition • In a normal flu and also in 1957 and 1968 extra deaths occur because of complications like pneumonia

8. A new Pandemic? • Experts: it WILL happen, only question when (it is assumed that chance for a new pandemic in the next ten years is above 50%) • Will H5N1 cause a new pandemic? • Chances are low (article nature) • Still new viruses can cause a pandemic

9. Would it look like the Spanish Flu? • Spanish Flu was very extreme • Unlikely that this happens again nowadays • Huge medical development since 1918 • Better prepared • People are in better condition • No TB epidemic and no WW 1 situations • Probability similar scenario << 1:400

10. How will pandemic look like? • Scientists simply don’t know • History shows that a pandemic comes in waves with a couple of months in between • Second wave worse than first one • Gives some time to develop a cure

11. Possible impact depends on .. • Can new virus easily infect humans • How easy is the transfer human – human • Power of making people sick • Incubation period • How fast can a cure be developed after virus is discovered

12. Possible deaths scenarios • WHO : between 2 million and 7.4 million globally • RIVM, extreme : 40,000 in the Netherlands on 16,000,000 people (= translated Spanish Flu) • RIVM, more real : 0 – 10,000 in NL

13. At what ages? • Will the extra mortality be age independent, or appear more likely at higher ages?

14. Spanish Flu in NL

15. Spread of pandemic deaths over the ages/gender • Suppose in extreme RIVM scenario deaths are spread age/gender independent • That will lead to the following overview:

16. RIVM extreme scenario

17. RIVM extreme scenario • Whole population in case of age independency shows an extra mortality of 0.25% (to be added up to the qx’s) • Supposing insured population in better health, so better protected: 60% of 0.25% gives an extra mortality of 0.15% • Calamity solvency capital can be calculated in this way!

18. RIVM other scenarios • Suppose 10,000 death in NL age independent: extra mortality for insured population: 0.0375% • Suppose 10,000 deaths 90% at higher ages (>65): x>65 extra 0.25% extra qx x<65 extra 0.005% extra qx

19. Other risks • A pandemic has also impact on other risk types: • Morbidity • P&C (Animal insurance) • Financial • Operational

20. Financial • Predicting the impact of Avian flu on global economy is impossible • A re-run of the Spanish flu could strip tens off GDP • In extreme cases goods more useful than cash • Also temporary impact possible in less severe pandemics, simply because of “fear” following the “hype”

21. Operational risk • More than 25% of employees are at home • Partly ill • Partly surging • Partly fear… • Precautions • Stocking medicines for employees? • Possibility working outside office (at home)

22. Morbidity risk • Products • Medical insurance • Hospitalisation • Sick leave insurance • Disability (?)

23. Medical insurance • Non severe scenario • High number of extra claims • Claims low (treatment costs are low) • Severe scenario • unclear

24. Hospitalisation • Non severe scenario • Some extra claims because of complications • Severe scenario • Unclear • Limited number of hospital beds • Temporary hospitals • Costs shared by governments and insurance companies (?)

25. Sick leave insurance • Non severe 15-25% extra claims (?) • Severe: >25% • what to do with people who are healthy but still stay at home (fear)?

26. Disability • Perhaps but unclear some impact in severe situation

27. Severe scenario • For health care we think that the first goal of people and governments will be that the virus is beaten ASAP • Independent on costs • Independent of insurance

28. Conclusion for insurance • It is impossible to set up a “best estimate” scenario, only “what if” scenarios • Impact unclear for some risk types • A solvency margin for calamity could be: 0.15% x NAR (better than something like doubling one-year claims) • Be careful with diversification within calamity -> correlation = 1

29. Conclusion Prof. Coutinho: • Be careful in communication • Try to prevent panic • In can last another 5-10 years before we have a pandemic • Publications on safety and heath are selling good: • A pandemic creates sensation in publications