Transcript Bird Flu A threat to Insurance?

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:
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–
–
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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 ..
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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 NL
mortality development Netherlands 1910-1930
2.5
2
q(x,1910)=1
1.5
1
0.5
0
1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929
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 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