Download - Bird Flu A threat to Insurance?
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