Bird FluA 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 H5N1 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 16,000,000 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 NLmortality development Netherlands 1910-1930

0

0.5

1

1.5

2

2.5

1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929

q(x,

1910

)=1

15-45 45-65 65-80 >80

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 scenarioSpread deaths independent of age

Age Group Pandemic death

Normal death

Extra mortality

0-25 12,201 2,362 517%25-45 12,781 4,631 276%45-65 9,609 20,506 47%65-85 4,848 71,736 7%>85 561 35,841 2%Total 40,000 135,075 30%25-65 22,390 25,137 89%

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