Bird Flu A threat to Insurance Henk van

Bird Flu A threat to Insurance? Henk van Broekhoven

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

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

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

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

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

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

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 H 5 N 1 cause a new pandemic? – Chances are low (article nature) • Still new viruses can cause a pandemic

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

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

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

Possible deaths scenarios • WHO : between 2 million and 7. 4 million globally • RIVM, extreme : 40, 000 in the Netherlands on 16, 000 people (= translated Spanish Flu) • RIVM, more real : 0 – 10, 000 in NL

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

Spanish Flu in NL

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:

RIVM extreme scenario Spread deaths independent of age Age Group Pandemic death 12, 201 Normal death 2, 362 Extra mortality 517% 25 -45 12, 781 4, 631 276% 45 -65 9, 609 20, 506 47% 65 -85 4, 848 71, 736 7% 561 35, 841 2% Total 40, 000 135, 075 30% 25 -65 22, 390 25, 137 89% 0 -25 >85

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!

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

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

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”

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)

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

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

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 (? )

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)?

Disability • Perhaps but unclear some impact in severe situation

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

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

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