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Update as of February 10, 2020
2019-nCoV Outbreak Update: Status, Risks, and Implications
1
2019-nCoVUpdate as of 10 Feb.
Cautious optimism based on most recent data: New cases of 2019-nCoV outside Hubei province have plateaued for a week, and very recently started to slow within Hubei
However, downside scenario still on the table—cannot rule out a pandemic until vaccine is in hand; Core risk dimensions:
Cycle risk: 2019-nCoV outbreak represents exogenous cycle risk, yet bar is high for viral pandemic to end the expansion
Financial risk: Confidence shocks can transmit to real economy, though would have to be both deep and sustained
Sector impact: relative clarity on current production and revenue risk, a serious acceleration of outbreak would blur impact
Knock-on effects: 2019-nCoV fits pattern of potential cascade of intersecting risk and uncertainty (human, economic, institutional…)
What firms can do: Invest in resilience, incl. precautionary containment measures, either as a tactical response to 2019-nCoV and/or pre-emptively for future threats
2
More than 40k 2019-nCoV cases, but highly concentrated
Hubei Province
Source: World Health Organization, National Health Commission China, Johns Hopkins CSSE, BCG Henderson Institute analysisNote: The data of n-COV cases was updated as of Feb. 10.
20,000
10,000
00
50 100 150 200
30,000
# of infected cases
Days since first infected case
SARS (8k Cases)
2019 n-COV (more than 40k Cases)
3
99% of cases in Chinese Mainland; 72% in Hubei provinceProvince1 Cases Casualties
Hubei 29631 871
Guangdong 1159 1
Zhejiang 1092
Henan 1073 6
Hunan 879 1
Anhui 830 3
Jiangxi 771 1
Jiangsu 492
Chongqing 473 2
Shandong 466 1
Sichuan 405 1
Beijing 337 2
Heilongjiang 331 7
Shanghai 299 1
Fujian 261
Hebei 218 2
Shaanxi 213
Province1 Cases Casualties
Guangxi 210 1
Yunnan 149
Hainan 138 3
Shanxi 119
Guizhou 109 1
Liaoning 108
Tianjin 95 1
Gansu 86 2
Jilin 80 1
Inner Mongolia 58
Ningxia 49
Xinjiang 49
Hong Kong 38 1
Taiwan 18
Qinghai 18
Macau 10
Tibet 1
Rest of the World 391 11. Provincial level administrative units in mainland China (includes provinces, municipalities, autonomous regions and special administrative regionsSource: National Health Commission China Data & other regional data as of 10th Feb, BCG Henderson Institute analysis
4
3%
Context: 2019-nCoV seems to have comparatively low fatality rate but high contagiousness
Outbreak Period Spread Deaths
2019 nCoV 2019-China and 24
others9082
Swine Flu 2009-10 World-wide 150-300 K
SARS 2003-04China and 26
others800
Hong Kong Flu 1968-70 SEA, USA, Europe 1-4 Mn.
Asian Flu 1957-58China, USA,
Europe1-2 Mn.
Spanish Flu 1918-19 World-wide 25 Mn.
Fatality rate Contagiousness1
1. R0: Avg. # of people infected by each sick person at peak of disease (changes over time based on public health response) 2. Data updated as of 10 Feb. Source: Bridgewater Associates, National Health Commission China, American Journal of Epidemiology, US National Library of Medicine, BCG Henderson Institute analysis
10%
0.03%
10% 3.0
1.5
2.0
1%-2% (est.) 1.5-3.5 (est.)
~0.2%
~0.2%
2.0
1.8
5
Current status (2/10/20): Cautiously optimistic on 2019-nCoV if you dare to extrapolate trends…
444
2,618
2,000
0
1,000
3,000
4,000
9-
Feb
Daily number of new cases detected
4-
Feb
30-
Jan
23-
Jan
24-
Jan
29-
Jan
25-
Jan
1-
Feb
26-
Jan
28-
Jan
31-
Jan
2-
Feb
3-
Feb
5-
Feb
6-
Feb
7-
Feb
8-
Feb
Hubei
province
Non-Hubei China
Non-China52
3,062
27-
Jan
60
40
20
-20
0
80
160
30-
Jan
4-
Feb
9-
Feb
Change in new cases detected (2-day avg. %)
26-
Jan
25-
Jan
6-
Feb
27-
Jan
7-
Feb
28-
Jan
29-
Jan
5-
Feb
31-
Jan
1-
Feb
2-
Feb
3-
Feb
8-
Feb
Hubei province
All Non-Hubei
Hubei cases
slowed in last
2 daysWuhan
lockdown
announced
Non-Hubei cases
plateaued at
start of Feb.
TotalWHO declares health
emergency
Source: National Health Commission China, BCG Henderson Institute analysis
2/10 00:00 2/10 00:00
6
Cautious optimism, not complacency
Despite cautious optimism, firms need to remain vigilant
and prepare for downside scenarios:
Elevated level of risk remains until vaccine is in hand
Current situation fragile, virus could spread to regions
with less capacity to respond forcefully
Re-acceleration possible, as happened in 1957-58 Asian
flu, with second wave more deadly than first
2019-nCoV a pattern of broader, multi-dimensional
risk landscape
7
Start
(US)
Start
(HK)
Peak
(US)
Economy: High bar for virus to end an expansion, even when cycle vulnerable and epidemic is severe
Hong Kong flu (1968-69)
Epidemic U.S. cyclical tightness1 (unemployment rate, %)
1. We use US data for this analysis because the most granular historical economic data is available there 2. De-mobilization lead to rise in unemployment/recession in 1918 not shown hereSource: NBER, Bureau of Economic Analysis, WHO, BCG Henderson Institute analysis
1968
8
1962 1964 1966
4
1970
6
Spanish flu(1918-20)
U.S. cyclical narrative
Very long, tight expansion Vulnerable to exogenous
shocks, similar to today Hong Kong flu hits in 1968,
but didn't cause economic recession immediately
19201914 19191915 1916 1917 1918 19210
5
10 Spanish flu intersects with end
of WWI (1918) De-mobilization of war effort
primes economy for recession2
Yet, recession does not hit until 1920
Recessions
US WW I effort
Peak
(US)
RecessionsRecessions
8
Financial risk: Confidence shocks can transmit to real economy, but requires deep and sustained drawdown
5
450 650500 7006005500
10
15
HH savings rate (%)
HH Net Worth / Disposable income
2009-19 expansion:
Savings rate elevated
Source: NBER, BEA, Federal Reserve Board, BCG Henderson Institute analysis Financial shocks shrink household wealth…
…pushing up
the savings
rate/reducing
consumption
Transmission mechanism: Market
sell-off (confidence shock) can
transmit to real economy, as wealth
shrinks, savings rise, and consumption
drops
Higher bar: in the U.S. a sell-off
would need to be both deep and
sustained to feed through to real
economy
High savings rate: Current expansion
has seen high savings rate, suggesting
some household resilience to wealth
shocks
Savings rate currently high, suggesting some
household resilience to financial shocks
1
2
9
Sector impact: Relative clarity on current impact dimensions, downside scenario requires re-think
Revenue
risk
(demand)
Production risk (supply chain)
Pharma
Healthcare
providers
Electronics
manufacturer
Oil
producers
Airline
Automotive
Illustrative exposure in baseline scenario: Plateau/decline continues
Note: Illustrative examples of potential exposure; will vary by company
Illustrative Exposure in downside scenario: Outbreak intensifies
Upside
Downside
Gaming
industry
Revenue
risk
(demand)
Production risk (supply chain)
Pharma
Healthcare
providers
Electronics
manufacturer
Oil
producers
Airline
Automotive
Upside
Downside
Gaming
industry
?
?
?
10
Coronavirus fits pattern of rising, intersecting risks
Institutional
Medical/human
…
EconomicUnknown
dimensions…Domestic
political economy repercussions
Multilateral
institutional cooperation
Growth
Markets
Uncertainty
Coronavirus
outbreak
Spectrum of elevated, intersecting risks:
Potentially
proliferating, multi-
dimensional risk
landscape
Need to build
resilience into
supply chains,
strategies
Tactically
(2019-nCoV) or
pre-emptively
(future threats)
11
Hope for the best, prepare for the worst
What companies can do:
• Monitor leading indicators: trend of new cases,
change in contagion rate, spread to new locations
• Assess exposure by developing multiple scenarios
and identifying potential impact on your business
and operating models (as well as your suppliers' or
customers')
• Take or prepare specific resilience initiatives, e.g.
increasing supply chain adaptiveness, keeping
financial buffers, shrinking decision cycles
• Develop containment plans and clear
travel/mobility guidelines
• Leverage an opportunity to reevaluate broader
resilience and risk management strategies
12
BCG are ready to support clients in these areas during this extraordinary period
Global health
Contingency planning &
crisis response
Strategy
Macroeconomics
Sector-specific responses
bcg.com