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7/25/2019 Health Pandemics
1/22
ICRM Symposium 2012 - Black Swan Events
Singapore, 21 22 February, 2012
Health Pandemics: From BlackSwans to . ?
Presented by Pane Stojanovski, Ph.D.with
Mary Chang, Peter Ulrich , Auguste Boissonnade
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Throughout history health pandemics
have been Black Swans not understood
and feared tremendously. With scientific,
medical, and health care advances in
the 20th century they have been tamed,understood, monitored, modeled, .
2
Could a pandemic return as a Black Swan today ?
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430 BC: Plague of Athens, killed 1/3 of Athenian population and was a
factor in the downfall of the Greek civilization, unknown cause buthypothesized to be everything from the plague to anthrax to viralhemorrhagic fever
251-266: Plague of Cyprian, measles? 5000 deaths/day in Rome
1347-1350 : Black Death Bubonic plague 25% Europe 25million deaths;16% world, 75 million deaths
1556 and 1560 European influenza epidemic with an estimatedmortality rate of 20%
1518 and 1568 The introduction of smallpox and measles into theAmericas by European explorers caused the population of Mexico tofall from 20 million to 3 million
1793 Yellow fever, U.S. Yellow fever 10% Philadelphia
18th Century Smallpox killed an estimated 60 million Europeans duringthe 18th century, 400,000 a year
19th century, tuberculosis killed an estimated one-quarter of the adultpopulation
A Few Notable Historical Pandemics Black Swans
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Comparative Numbers
Year Event Est. Number of Deaths
14th century Black Plague 75-200 million
1939-1945 WWII 50-70 million
1918 Spanish flu 40-50 million
20th century Smallpox 300-500 million
1980-today AIDS 25 million
1914-1918 WWI 20 million
1852-1860 3rd Cholera pandemic >1 million
1900-today Malaria >1 millionper year
1976 Tangshan EQ 242,000
2004 Aceh EQ, tsunami 230,000
2008 Cyclone Nargis 63,000-100,000
1952 Polio (U.S.) 3145
2005 Hurricane Katrina 1836
2002-2003 SARS 774
Infectious Diseases (ID) 4
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Immunizations
Sanitation Surgical milestones
Sterile techniques
Safer anesthesia
Less invasive methods
Transplantation of organs Diagnostic tools
Blood Tests
X-Rays
CT, MRI
ECG, EEG, EMG Pharmaceuticals
Antibiotics
Antivirals
Health Care Changes In The 20th Century - ReducedInfectious Diseases Risks
5
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Effect Of Health Care Improvements on Infectious Diseases
Achievements in Public Health, 1900-1999: Control of InfectiousDiseases. MMWR. July 30, 1999 / 48(29);621-6296
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Despite advances in hygiene and medical science, pathogens are
continually emerging and evolving
Scientific advances have reduced the severity of known diseases like
influenza and the risk will continue to diminish with antivirals and
vaccine development improvements. However,
The emergence of H5N1 and antiviral resistant strains demonstratethat extreme mortality and other correlated shocks are still possible
from influenza: 1918 is not a worst case!
We have no immediate medical answer for an emergent viral disease
with characteristics similar to historical causes of excess mortality like
smallpox, measles, and HIV
Global transmission will be faster than it has been historically and
urban populations are likely to be affected first
Challenges Today
7
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60
80
100
120
140
160
Doses(Millions)
2010 H1N1 Influenza Vaccine Doses Allocated, Ordered, and Shipped inthe U.S.
Allocated
Ordered
Shipped
Lowest virulence of any previously measured pandemicinfluenza virus
Some mortality reduction - pharmaceutical advances,public health measures, and pre-existing levels of immunity
The low number of fatalities can be predominantlyattributed to the genetic characteristics of the virus
Vaccine distribution primarily through public healthchannels with widespread shortages were reported
Government public health organizations slow to declare apandemic
Demonstrated inadequacies of categorization systems
2009 Pandemic A/H1N1
0
10
20
30
40
50
60
70
80
90
100
H1N1 Days until outbreak
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H5N1 Avian Flu
The virus high virulence resulted in a redefinition of whatwe knew about flu viruses
As of March 2010, 489 Cases in 15 countries resulting in289 deaths (60% death rate)
It is likely that migratory birds are spreading the H5N1 virus
and according the WHO, further spread to new areas isexpected.
Since 1997 the virus has adapted to infect moremammalian species and has become more virulent
A reassortment or adaptive mutation of the virus to amore transmissible form could result in a highlyvirulent virus that would be nearly impossible to control
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Moderate
Severe
VerySevere
Mild
Pandemic Viruses - Infectiousness & Virulence
InitialDeathsperCase
30%
10%
5%
2.5%
1%
0.5%
0.1%
7
6
5
4
3
2
1
1.25 1.75 2.25 2.75 3.25 3.75
R0 Basic Reproductive Number
Seasonal Flu
1957
1968
1918
1.0 1.5 2.0 2.5 3.0 3.5 4.0
PandemicSeverity
0%
0.2%
0.75%
2.0%
3.5%
7.5%
20%
50%
Infectiousness
Virulence
ModeledScenario
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Direct Pandemics Risk Quantification
Epidemiological Model
0.0
0.5
1.0
0 10 20 30
$Bn
Probability
of
Exceedance
Exceedance Probability Output
Pathogen Characteristics
Probabilistic model of virus characteristics: Frequency of antigenic shift mutations Virulence: Death per Case (DpC)
Infectiousness: Initial Reproductive Number (R0) Other qualitative factors including
pathology mechanism (e.g. cytokine storm)
Incubation time and symptomatic period
Population Spread Model International Spread
Age response
Background immunity
Behaviour assumptions
Antibody
VirusHA Antigen
Susceptible, Infected, Recovered (SIR) Modelling
National Government Response Model Public health capability and strategy
Anti-Viral Administration
Vaccine Development
Non-Pharmaceutical Interventions
Portfolio-Specific Impact Modeling
0.000
0.050
0 20 60 80 Age
AgeMortalityCurves
General Population Age Distribution
Total Risk Capital by Age
40
Portfolio
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0
5,000,000
10,000,000
15,000,000
20,000,000
25,000,000
30,000,000
35,000,000
40,000,000
45,000,000
1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728293031323334353637383940414243444546474849505152
All New Cases by Week in Working Population
Brazil Indonesia
China Rest of Asia
Rest of Middle East, including North Africa Rest of South America, Central America & Caribbean
Rest of Sub-Saharan Africa. United States of America
Direct Impact Modeling Caseload Timelines in Populations
Modeled Scenario:R0 = 3.25;DpC = 0.5%;Outbreak location = Vietnam
12
l d d li l b l l
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Correlated Impact Modeling Global GDP, Employment,Exports
-7.0
-6.0
-5.0
-4.0
-3.0
-2.0
-1.0
0.0
1.0
2.0
3.0
2009Q4 2010Q2 2010Q4 2011Q2 2011Q4 2012Q2 2012Q4 2013Q2 2013Q4 2014Q2 2014Q4 2015Q2 2015Q4
Global GDP
Global employment
Global exports
G Verikios. M. Sullivan, P. Stojanovski, J. Giesecke and G. Woo, The Global Economic Effects of Pandemic Influenza.)14th Annual Conference on Global Economic Analysis, Venice, June 16-18, 2011.
Modeled Scenario:R0 = 3.25;DpC = 0.5%;Outbreak location = Vietnam
~$2.8 trillion lost inglobal GDP
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Correlated Impact Modeling Tourism
-6.0
-5.0
-4.0
-3.0
-2.0
-1.0
0.0
1.0
2.0
3.0
2009Q4 2010Q2 2010Q4 2011Q2 2011Q4 2012Q2 2012Q4 2013Q2 2013Q4 2014Q2 2014Q4 2015Q2 2015Q4
tourism shocks health services shocks
labour producitivity shocks population and labour supply shocks
G Verikios. M. Sullivan, P. Stojanovski, J. Giesecke and G. Woo, The Global Economic Effects of Pandemic Influenza.)14th Annual Conference on Global Economic Analysis, Venice, June 16-18, 2011.
Modeled Scenario:
R0 = 3.25;DpC = 0.5%;Outbreak location = Vietnam
~ 330 billion lost
in tourism andtravel sectors
14
Travel and tourism industry about 9% of total GDP
235 million jobs
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-12.0
-10.0
-8.0
-6.0
-4.0
-2.0
0.0
2.0
4.0
2009Q4 2010Q2 2010Q4 2011Q2 2011Q4 2012Q2 2012Q4 2013Q2 2013Q4 2014Q2 2014Q4 2015Q2 2015Q4
China
Singapore
USA
Germany
Rest of Asia
Japan
Correlated Impact Modeling GDP for Selected Regions
G Verikios. M. Sullivan, P. Stojanovski, J. Giesecke and G. Woo, The Global Economic Effects of Pandemic Influenza.)14th Annual Conference on Global Economic Analysis, Venice, June 16-18, 2011.
15
~ $33 billion lostin Singapore GDP
Modeled Scenario:
R0 = 3.25;DpC = 0.5%;Outbreak location = Vietnam
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Thinking of Expanded Correlations - Pandemics, EconomicShocks and Financial Capital Shocks
Unpublished research communications
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With advances in public health, global preparation,medicine, sanitation, .., vector control, . could a
pandemic Black Swan return?
Long historical record and experienceAdvances in science , sanitation, .. ., prevention
Global watch (WHO)
Ability to model pandemics and correlated impacts for risk
quantification and management
Pandemics do not appear to be in the unknown unknowns
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Could a Pandemic Black Swan Return?
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Nature, Volume:481,pp: 417418, January 26 , 2012
Caution Urged For Mutant Flu Work (H5N1)
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Ongoing creation of mutated strains of the H5N1 virus for surveillance of flu
viruses could allow health organizations to monitor birds and other animals forthe mutations early warning of a pandemic
Surveillance of H5N1 in poultry worldwide is patchy, particularly in poorer
countries, where the virus is prevalent, and the mutated strain may not be
caught early enough
Just five mutations allowed avian H5N1 virus to spread easily among ferrets
(good proxy for flu behavior in mammals, including humans). Mutations
spotted individually (not together in wild viruses); .
Risk of accidental or intentional release of similar mutant viruses
New research shows that H5N1 seems capable of evolving the ability tospread rapidly among humans
Existing vaccine technologies incapable of supplying vaccine earlier than six
months after a pandemic starts.
Why Caution ?
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New strain
High InfectiousnessHigh virulence
Compromise / failures of response / defenses
Pandemics - Black Swans ?
-40.0%
-35.0%
-30.0%
-25.0%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
10.0%
0 5 10 15 20 25
"Experienced"
Black Swan 2
Black Swan 3
Black Swan 1
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Black Swan WILL HAPPEN, it is
only matter of time
Health Pandemics: From Black Swans to . ?
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GLOBAL impact
Human Fatalities and HUGEeconomic and financial impact
Further research in related scientific fields to be betterprepared (medically and economically)
Correlated catastrophe shocks (stress tests) for betterstrategic foresight, planning and response
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