COVID-19 Fact Base and Potential Implications for Brazil - Completo

COVID-19 Fact base
and potential implications
for Brazil
June 26th, 2020
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2Bain&Co - COVID19 Brazil POV - ...SAO
Context for these materials
• COVID-19 is a humanitarian crisis and a global challenge. In this interconnected world, we have seen the virus spread
rapidly, and we are still gathering information to understand both its origins and its impact
• We are grateful for the businesses, governments, non-profits, and individuals around the world that are working to
protect those that are sick or in danger of becoming so, and to “flatten the curve”
• There is a lot that is still unknown about COVID-19; these materials are an attempt to shed light on what we know so
far to help businesses make informed decisions
– The top priority for all businesses is to protect the safety and health of employees and customers, for which there are WHO, CDC, and
other national guidelines
– Bain is not an expert on epidemiology and containment policies, however, given our 45+ years of experience advising companies during both
economic booms and busts, we are committed to spreading accurate and timely information to reduce the unknowns for businesses
and business leaders
• Our focus is to enable companies to make rapid and practical decisions; with a global pandemic that is rapidly
spreading and changing, now is not the time for detailed decision making; the need for speed and the right directional
strategy outweighs the need to get intricate details right, and we are committed to helping business leaders navigate the
path forward

COVID-19 is more severe than recent epidemics due to high infectivity in an
interconnected world
Note: R0 refers to the average number of people infected by one sick person
Source: National Health Commission of the PRC; CDC – Emerging Infection Diseases; WHO; Lit research, Bain Macro Trends Group analysis
E P I D E M I O L O G Y
Cases
Fatality rate
Infectivity (R0)
Swine Flu, 2009-10
~750M-1.4B
COVID-19, 2019-20
~9.0M
Bird Flu, 2014-2017
~1,600
SARS, 2003
~8,000
~1%
Spanish Flu
~10%
SARS
~6.6%
Bird Flu
~40%
Bird Flu
0.03-0.4
Swine Flu
1.3-1.7
Spanish Flu
1.5-1.8
Swine Flu
~0.01-0.08%
~8.9
SARS
3.0
Case count is low, however, it
has only been ~5 months since
the outbreak
Implications
Fatality rate is TBD given
number of unreported cases;
more testing and information
needed but is likely to be on
lower end of spectrum
High spread rate when un-
encumbered by social
distancing, including
community transmissions,
drives global spread
Low HighSeverity
COVID-19
~0.5% COVID-19
~3.8
A S O F J U N E 2 2
Deaths
Bird Flu
~600
Spanish Flu
~50-100M
SARS
~776
COVID-19
~469K
Spanish Flu, 1918
~350M-750M
Swine Flu
~152-575K
Death count is relatively high
and still rising as containment
efforts continue

LatAm is the current COVID epicenter, with highest share of COVID-19 fatalities per
day
C U R R E N T S T A T U S
Note: Increase in Asia Pacific in mid-April is attributable to one-time adjustment in fatalities in Hubei, China on April 17; decreased fatalities in Europe in late May driven by adjustments in measurement protocols in multiple countries (e.g. Spain, France)
Source: Johns Hopkins University
A S O F J U N E 2 2
Global impact of COVID-19
~9.0M
Confirmed
cases
~469K
Confirmed
fatalities
March April MayFebruary June

The growth rate of infections and deaths has slowed in most countries
Country
Deaths /
100K pop.
Total deaths in
past 7 days One month prior One week prior Peak
7-day peak period
(deaths)
Cases
/ 100K pop.
United Kingdom 65 934 -61% -19% -86% Apr 8 - Apr 14 462
Spain 57 1,187 +2% N/A – 0 deaths last week -80% Mar 28 - Apr 3 493
Italy 56 289 -71% -35% -95% Mar 27 - Apr 2 382
Sweden 50 179 -36% -17% -76% Apr 18 - Apr 24 549
France 43 233 -69% -8% -97% Apr 3 - Apr 9 288
US 36 4,237 -50% -18% -73% Apr 12 - Apr 18 685
Brazil 24 7,259 +19% +6% 0% May 29 - Jun 4 513
Mexico 17 4,684 +111% +36% 0% Current week 140
Iran 11 786 +97% +41% -20% Mar 31 - Apr 6 241
Germany 11 94 -72% -19% -95% Apr 15 - Apr 21 238
India 1 4,179 +329% +81% 0% Current week 33
Japan 1 28 -66% +180% -83% Apr 29 - May 5 14
South Korea 1 3 -25% -25% -94% Mar 24 - Mar 30 24
Singapore 0.4 0 -100% -100% -100% Apr 27 - May 3 679
Malaysia 0.4 0 -100% -100% -100% Mar 29 - Apr 4 26
China 0.3 0 -100% -100% -100% Apr 11 - Apr 17 6
Taiwan 0.03 0 -100% -100% -100% Mar 24 - Mar 30 2
Source: Johns Hopkins University, CDC, WHO, Bain Macro Trends Group analysis
A S O F J U N E 2 2
Deaths over past 7 days vs.
E P I D E M I O L O G Y

A G E N D A
Epidemic evolution and challenges for South America
Perspectives for Brazil
International perspective on the reopening process
Countries Re-opening
Economic Recovery

Most global experiences of successful mobility restrictions presented bell-shaped curves
that peaked ~10-30 days post lockdown and consistently decreased following peak
Lockdown
is lifted
Most countries that went through lockdowns managed to reduce new infections
Note: COVID-19 new cases per day (7 day moving average); Date of lockdown lift is considered when there is a significant lift of schools, stores and/or services
Source: The Business Insider, Oxford Our World in Data Database (04/05)
Czechia
DenmarkNorwayNew Zealand
Lockdown
is lifted
Lockdown
is lifted
Lockdown
is lifted
Netherlands Finland
Lockdown
is lifted
Lockdown
to be lifted
(L+55)
G L O B A L L A N D S C A P EG L O B A L L A N D S C A P E

So, why don’t we see the same curve in South America? Even in countries with more
severe lockdowns, the recovery is taking much longer
New cases per day
(5 days moving average; From 100th case in a day)
Days from 100th new case per day
Note: On June 17th , the Ministry of Health of Chile informed additional 31k cases that hade delayed positive tests in previous weeks, and it is not considered in the graphic (1) Considering average mobility from June to June 22th
Source: JHU Data Stream; Google Mobility; Argentinian Department of Health
1
Even though some countries as Chile, Argentina and
Colombia had the spread initially under control, SA
countries are now experiencing a loss of control over case
growth
G L O B A L L A N D S C A P E A S O F J U N E 2 6

The shape of the curve is tied to R0 control; Countries need to bring R0 below 1 to control
the spread, then it is a matter of controlling R0 according to the health system capacity
R0 >>>1 R0 =~1 R0 < 1 R0 = ~1
# of active cases, # of hospitalizations and health system capacity
Health System Available Capacity
Active cases
Hospitalizations (20-30% of active cases)
Disease picks up
and the spread
is out of control
Countries deploy
measures (testing, tracing,
mobility reduction) to
control the spread
When measures are sufficiently successful
considering the conditions of the country, R0 is
reduced below 1, bringing down the number of
new and active cases.
South American countries have not yet
managed to enter this phase
After reducing the number of cases to a manageable level,
countries start planning on how to ease measures. This
requires active management, as new outbreaks may
appear and measures might need to be re-deployed.
Even after measures are lifted, R0 might stay low due to
technologies in place, new hygiene/protection habits, etc.

Measures taken can
mitigate the spread
Exposure immunity
helps reducing R0
Combination should
prevent HC collapse
The key is to get R0 below 1. It goes beyond reducing mobility; cities
demographics, testing, technology and exposure immunity also impact the R0
Specific demographics
lead to “baseline” R0
Different location / stage
leads to diff. strategy
R0 <=1
• Favorable demographics
lead to fewer needs of gov.
measures
1
• Government measures
(such as widespread testing
and screenings) reduce the
need for lockdowns
2
• Exposure immunity
develops as number of
cases increase, reducing
need of other measures
3
Note: Illustrative impact of different factors influencing R0
Source: Lit. research
1 2
3
COVID-19 R0 (as a function of contributing factors)
R0 can be kept at this
level after transmission
control is at low levels
All variables must be taken into consideration when reducing the contamination R0. Different countries are acting in very distinct
ways to approach the problem
At this stage, most
evidence suggests
contaminated patients
develop immunity, but
its length and strength
are still being debated
G L O B A L L A N D S C A P E

2:1
(4.4%)
9:1
(7.6%)
17:1
(6.2%)
79:1
(4.7%)
98:1
(2.2%)
268:1
(0.6%)
22:1
(14.4%)
New York Brazil
Despite mobility reduction efforts, SA starts from a higher R0 and is not leveraging
any other tool to control the spread (testing, technology, etc.)
Switzerland
~43%
(From 870
cases)
~60-75%
(From ~6k
cases)
~46%
(From 2.5k
cases)
>5>5
Denmark
~39%
(From ~600
cases)
Source: JHU Coronavirus Data Stream 05/06; Tableau; Worldometers; Google Mobility Database, Bain Analysis.
Mitigation
(High use of
tecnology)
Suppression
(Mobility
reduction)
Time to
slowdown
• Technology usage
• # of tests applied vs
confirmed cases
(Mortality %)
• Mobility reduction
during lockdown (%)
• # of weeks from mobility
reduction to case under
control (<50 cases/1M)
LowLow Medium Medium
32
Unconstrained
R0
3-81-10 1-42.1
• Population density of
main cities (k hab / km2)
• # of people/household 3.32.5 2.5 2.2
S. Korea
Countries didn’t reach
such contamination levels
~25%
Very High
Hong Kong
~30%
Very High
4-17
2.5
7
2.8
Favorable DemographicsHigh use of technology S. AmericaStrong suppression
Italy
~70%
(From ~15k
cases)
>5
Low
2-2.6
2.6
Exposure
immunity
• Adjusted number of
cases / total pop. (%)
Governmentmeasures
Some east Asian
countries have
demographics that
were not favorable for
containing the virus
However, these countries not only
tested considerably but also utilized
screening technologies from the start
to isolate those contaminated with the
virus
The result is that even without high
levels of mobility reduction, these
countries managed to get the
disease under control very early and
never reached an outbreak level

2:1
(4.4%)
9:1
(7.6%)
17:1
(6.2%)
79:1
(4.7%)
98:1
(2.2%)
268:1
(0.6%)
22:1
(14.4%)
New York Brazil
Switzerland
~43%
(From 870
cases)
~60-75%
(From ~6k
cases)
~46%
(From 2.5k
cases)
>5>5
Denmark
~39%
(From ~600
cases)
Mitigation
(High use of
tecnology)
Suppression
(Mobility
reduction)
Time to
slowdown
confirmed cases
(Mortality %)
during lockdown (%)
32
Unconstrained
R0
3-81-10 1-42.1
S. Korea
~25%
Very High
Hong Kong
~30%
Very High
4-17
2.5
7
2.8
Italy
~70%
(From ~15k
cases)
>5
Low
2-2.6
2.6
Exposure
immunity
Governmentmeasures
Italy and NY are examples
of countries that also did
not have favorable
demographics to contain
the virus
Finally, to contain the spread, strong
mobility reduction measures had to be
taken, and the spread reduction was
slower than the one observed in the
Asian countries.
Due to higher contamination over time,
exposure immunity is starting to be
relevant and help the case spread control
Also, those
countries/states didn’t test
considerably and did not
use screening technologies
in order to control the virus

2:1
(4.4%)
9:1
(7.6%)
17:1
(6.2%)
79:1
(4.7%)
98:1
(2.2%)
268:1
(0.6%)
22:1
(14.4%)
New York Brazil
Switzerland
~43%
(From 870
cases)
~60-75%
(From ~6k
cases)
~46%
(From 2.5k
cases)
>5>5
Denmark
~39%
(From ~600
cases)
Mitigation
(High use of
tecnology)
Suppression
(Mobility
reduction)
Time to
slowdown
confirmed cases
(Mortality %)
during lockdown (%)
32
Unconstrained
R0
3-81-10 1-42.1
S. Korea
~25%
Very High
Hong Kong
~30%
Very High
4-17
2.5
7
2.8
Italy
~70%
(From ~15k
cases)
>5
Low
2-2.6
2.6
Exposure
immunity
Governmentmeasures
Those countries tested
considerably but did
not use advanced
screening technologies
As a result, those countries
could be less strict on
mobility reduction
measures, and controlled
the spread faster
On the other hand, some
countries have low densities and
number of people per
household; demographics that
are likely to reduce the spread

17:1
(6.2%)
79:1
(4.7%)
9:1
(7.6%)
98:1
(2.2%)
268:1
(0.6%)
22:1
(14.4%)
New York Brazil
Switzerland
~43%
(From 870
cases)
~60-75%
(From ~6k
cases)
~46%
(From 2.5k
cases)
>5>5
Denmark
~39%
(From ~600
cases)
Mitigation
(High use of
tecnology)
Suppression
(Mobility
reduction)
Time to
slowdown
confirmed cases
(Mortality %)
during lockdown (%)
32
Unconstrained
R0
3-81-10 1-42.1
S. Korea
~25%
Very High
Hong Kong
~30%
Very High
4-17
2.5
7
2.8
Italy
~70%
(From ~15k
cases)
>5
Low
2-2.6
2.6
Exposure
immunity
Governmentmeasures
Testing was poor in SA,
especially in Brazil, where
few technologies were
used and only people in
severe states were tested
Differently from NY/Italy, Brazil
opted on a moderate mobility
reduction mainly stimulated
through venue closure, with few
population support.
Cities are still far from developing
exposure immunity, which led to a
slow spread control, that will be
followed by a long recuperation
period with R0 of ~1
South American countries
depart from not favorable
demographics, with dense
cities and high number of
people per household
2:1
(4.4%)

New York Brazil
~43%
(From 870
cases)
~60-75%
(From ~6k
cases)
~46%
(From 2.5k
cases)
>5>5
Denmark
~39%
(From ~600
cases)
Mitigation
(High use of
tecnology)
Suppression
(Mobility
reduction)
Time to
slowdown
confirmed cases
(Mortality %)
during lockdown (%)
32
Unconstrained
R0
3-81-10 1-42.1
S. Korea
~25%
Very High
Hong Kong
~30%
Very High
4-17
2.5
7
2.8
Italy
~70%
(From ~15k
cases)
>5
Low
2-2.6
2.6
Exposure
immunity
Governmentmeasures
Switzerland
2:1
(4.4%)
9:1
(7.6%)
17:1
(6.2%)
79:1
(4.7%)
98:1
(2.2%)
268:1
(0.6%)
22:1
(14.4%)

Also, not all mobility reduction is the same, demographic and socioeconomic
reasons increase dependence and density of public transportation in South America
Sweden subway, 8h30am
Even with the reduced mobility, South America still
faces issues to keep social distancing
Motor vehicles per capita in SA vs
Europe2
Note: 1Considers number of metro stations per M passengers; 2Considers average of 5 largest economies in each continent; 2Copenhagenize Design Company's Index
Source: Lit. Research
Higher public transportation density
vs Europe1
+90%
-60%
0 / 10
1 / 20
Countries with Most Bicycles per
Capita in SA (8/10 in Europe)
Most Bike-Friendly Cities on the
Planet in SA (17/20 in Europe)3
• European countries usually have alternatives for public
transportation at their disposal. On the other hand, South
American are much more dependent on crowded buses and
subway systems

• Five companies using
AI to identify and
develop drugs for the
treatment of COVID-
19
• VR training for
healthcare workers on
the treatment of
patients with COVID-
19
Asia lead the use of technology to backup mitigation policies; South America is
lagging behind specially in tracing and target quarantine
Source: World Economic Forum “Here’s how Asia is using tech to tackle COVID-19”; New York Times “In Coronavirus Fight, China Gives Citizens a Color Code, With Red Flags”; CNBC “Singapore says it will make its contact tracing tech freely available to
developers”; CNN “Hong Kong managed to contain the virus, now it's worried international travelers will bring it back”; Forbes “Coronavirus Spy Apps: Israel Joins Iran And China Tracking Citizens' Smartphones To Fight COVID-19”; Spectrum “Five
Companies Using AI to Fight Coronavirus”
Healthcare system and capacity
Risks minimized in high vulnerability
settings
• Start-ups are developing
10-minute tests for
Coronavirus using
Internet of Things
• Temperature scanning
solutions to identify
potentially infected
people in crowds,
especially at airports
• Using geolocation data
stored in smartphones of
confirmed cases, to send
notifications for those who
were in close contact
• App to trace its users
movements and send
alerts in case they come in
contact with
someone
infected
• Wearables for workplace-
level contact tracing
• Wristbands and apps that
send notifications for
authorities in case the user
leaves the designated
quarantine area
• In China and Singapore,
drones and robots are
used to deliver food and
medicine to high-risk
areas as
well as to
conduct
disinfection
tasks
• Data to enable
detailed mapping of the
outbreak and hot spots
• Government response
tracker to evaluate
impact of public
measures
• Geolocation data for
governments to see
effects of confinement
measures
• Consolidate dashboards
with health data to give
decision-makers more
accurate visibility
• In China, new
software by
Alipay uses big
date to dictate
quarantines,
allowing user
to enter public
spaces, or not,
according to
their color
coding
Testing Tracing Target
quarantine
Transmission
control
Distancing Protective
gear
• Wristbands that vibrate to
notify the user who breaks
social distancing
Legend
Country with flagship usage of the technology
Measures alto taken by some SA countries

In summary, South American countries are struggling to have R0 bellow 1 due to a
higher starting point and lack of mitigation policies
Eastern Asia: strong
mitigation/early action
Dense countries/cities:
strong suppression
Less dense Europeans:
favorable demographics
Contamination R0
Days from 100th case
Contamination R0
Contamination R0
Spain
USA (NY)
Italy
Brazil
Colombia
Chile
Argentina
Singapore
Taiwan
Hong Kong
Contamination R0
SA countries: none of the
previous situations
Portugal
Switzerland
Norway
Countries/regions that entered or are entering a recovery phase
Low
unconstrained R0
Mitigation (strong
technology)
Strong
suppression

Exposure immunity is also helping countries to slowdown the curve, Northern Italy and NYC
are good examples. Some Brazilian states are possibly starting to feel positive effects
Number of adjusted cases1 / Population
(# cases; %)
Note: (1) Adjusted cases per mortality, with death rates of 0,5% to 0,7%
Source: Oxford Our World in Data Database (May 15th); ING; Financial Times; Nordea; Governments; Euronews; World Economic Forum; Brazilian Ministry of Health.
Even Brazilian cities with the highest
levels of contamination are far from
cities such as NYC, which is starting
to show exposure immunity effects
G L O B A L L A N D S C A P E A S O F J U N E 2 6

Current landscape and implications for Brazil:
Yet a different progression story
• It is clear by now that South American countries will not follow the same trajectory (the bell-shaped curve) of most
Asian or European countries
– Even after more than 80 days of restriction measures, the peak does not seem to have been reached even under high mobility reduction (e.g.
Colombia, Peru and Argentina)
• Countries adopted different strategies to control the contagiousness level (R0); different combinations of favorable
demographics, the widespread use of technology/testing and harsh suppression measures were needed to take the
R0 below 1 and slowdown the curve
– Although there were some correct measures in places like early mobility restriction and even good testing levels in a few countries (e.g.
Colombia and Chile), this was not enough to compensate that higher starting R0
– Besides, not all mobility is the same, while in Europe people that needed to move was using their cars or even bikes, in South America the
mobility was in crowded buses and for longer distances
– Lastly, South American countries didn’t use technology in their favor – low/average testing levels, no use of tracing and no use of target
quarantine policies
• In summary, to compensate for the higher R0 starting point, South America should have used more weapons to
control the virus
– Brazil, in particular, has always had low testing levels, not enough mobility reduction in the high dense areas and no use of tracing
technologies
What can we expect going forward?

What we expected… and what we see now
What we expected... ...and what we see now
• A long plateau of the disease would be maintained over the
following 4-8 weeks at least, driven by states in multiple stages of
the spread
• The epidemiological perspective of a "long plateau scenario”
has materialized for Brazil as a whole during the past month and
continues to be our most likely scenario going forward
• The plateau has been driven by the different stages in which Brazilian
states find themselves, both in terms of the disease spread and in terms
of government actions
• The “shape of the curve” for each state would be driven
mostly by government actions, in order to balance the
healthcare system capacity vs the economy reopening
– As the disease progressed, we expected most states to trend towards
a “control zone”, with R0 ≈ 1 and ICU occupancy ≈ 60-70%
• Most states (14-18) have converged to the “control zone” in
the past 30 days, reaching R0 ≈ 1 and ICU occupancy ≈ 60-70%
– Most states that were in the medium/high risk areas improved and
progressed towards a “control zone” with suppression and immunity
– States that controlled contamination at a first stage started to release
measures and saw an increase in # of cases
– Only very few states that were in the low or medium risk zone "lost
control" for different reasons and advanced to the high risk zone
• We saw no evidence that more robust mitigation plans would
be put into place, making it very hard for states to control the
spread of the disease after lifting restrictions
– Reaching enough exposure immunity seemed to be the only feasible
way to get to a more controlled level of spread
• States that were heavily impacted in the beginning (AM, PA,
CE, MA) are the only ones to have managed to reduce
contamination considerably without major changes on
suppression and mitigation policies; their exposure immunity
level of ~20% is likely playing a major role in their situation
– There are still no clear signs that robust mitigation plans are “in-the
works” to help with reopening economies

Understanding the current situation in Brazil is hard. Brazil doesn’t test enough,
generating a critical delay in current situation understanding
Brazil is testing ~3:1 vs suggested
higher than 10:1
Death notification is experiencing
delays up to 15 days
Number of tests per confirmed cases
(# tests; confirmed cases)
Note: (1) Top 15 countries with more confirmed cases, excluding Brazil and China. Source: JHU Coronavirus Data Stream; Tableau; Worldometers; Fiocruz
Deaths per SARS related symptoms
(# of k deaths; epidemiological weeks 9 to 25)
Death notification
period is up to 15 days
after death occurrence;
Hospitalizations due to SARS pneumonia
(# of k cases; epidemiological weeks 9 to 25)
Brazil has ~50% of hospitalizations
still being investigated for COVID-19
B R A Z I L I A N P E R S P E C T I V E A S O F J U N E 2 6

Three main metrics that can be used to understand the Brazilian situation; despite
some lag, hospitalizations due to SARS is the most reliable figure we have
1. # of confirmed cases: delayed
and highly underestimated
2. # of deaths: more accurate than
cases, but significantly delayed
3. # of hospitalizations due to SARS:
broadest and most reliable metric
• Brazil has one of the worst testing levels
across the globe, testing only ~3 people for
each confirmed case (benchmark countries test
50-200/confirmed case)
• Due to lack of test availability, Brazil is
prioritizing people with severe symptoms
and so, the total number of confirmed cases
is highly underestimated. Besides, the time
between testing and notification is very long,
resulting in a significant delay
• Finally, as availability of tests increase, it is
likely that the number of cases grows because
of more testing, not necessarily because of
more cases
• Severe cases are prioritized for COVID-19
testing which leads to a more accurate number
of total deaths, but there are still important
issues with the indicator:
– Delay on death notification (~15 days)
– Sub notification of deaths causes (E.g. COVID death
being reported as pneumonia)
• Even with more testing, there is still a
significant # of deaths under investigation
for COVID
• Number of hospitalizations due to SARS does
not depend on the efficiency of the testing
system
• Using previous studies that indicate a
hospitalization level of 20-30% for COVID-19, it
is possible to estimate the number of cases
• In our point of view, the # of hospitalizations
due to SARS is the best proxy for the # of
COVID-19 hospitalizations; a comparison with
previous years allows for a reasonably good
estimate of the disease evolution
Source: Stanford; Healthline.

The SARS hospitalizations metric shows that Brazil remains on a plateau of the disease; after a
drop in weeks 21-22, week 23 (incomplete) already shows numbers trending up again
Source: Fiocruz, Ministry of Health
Epidemiological
Week
Hospitalizations due to SARS per epidemiological week
(k# cases; week of the beginning of symptoms)
A S O F J U N E 2 3B R A Z I L I A N P E R S P E C T I V E
Weeks that
are likely still
considerably
incomplete
on the
reports
Estimated curve
June-11
First wave of exponential growth -
Concentrated in the state capitals initially
more impacted (e.g. SP, RJ, CE, AM, MA, PA)
Increase of contamination due to virus
spread to other capitals, the
countryside and smaller cities
Long plateau - Growth in states that were
spared during initial wave (e.g. MG, RS, PR,
SC, MT, DF) combined with improving conditions
in more severely impacted regions

The number of new deaths per day has also been stable in recent weeks, reinforcing
that Brazil is in the long plateau stage
Source: Ministry of Health
COVID-19 confirmed deaths per day
(# deaths)
A S O F J U N E 2 9

The contamination curve for Brazil is, in fact, a combination of the different realities
we see across states
(# cases; week of the beginning of symptoms)
Some states that were heavily impacted by
COVID-19 in a first moment appear to have
reached the slowdown stage of SARS curve
Most of the states appear to be in a stable
level of contamination, having achieved a
plateau of the curve
E.g.: Amazonas curve E.g.: São Paulo curve
Some states that had previously had a very
low level of contamination are now facing
accelerated growth
E.g.: Minas Gerais curve
Source: Fiocruz
B R A Z I L I A N P E R S P E C T I V E A S O F J U N E 2 3
1 2 3

The contamination curve for Brazil is, in fact, a combination of the different realities
we see across states
Source: Fiocruz, Ministry of Health
Epidemiological
Week
(k# cases; week of the beginning of symptoms)
A S O F J U N E 2 3B R A Z I L I A N P E R S P E C T I V E
Weeks that
are still
considerably
incomplete
on the
reports
First wave of exponential growth -
Concentrated in the state capitals initially
more impacted (e.g. SP, RJ, CE, AM, MA, PA)
Increase of contamination due to virus
spread to other capitals, the
countryside and smaller cities
Long plateau - Growth in states that were
spared during initial wave (e.g. MG, RS, PR,
SC, MT, DF) combined with improving conditions
in more severely impacted regions
23,8%
54,8%
21,4%
21,5%
46,0%
32,5%
35,3%
47,3%
17,4%
XX,X% - Percentage of total new
hospitalizations for the period
1
2
3

Epidemiological status by state on May 25th: As the disease progressed, we expected
most states would trend towards a “control zone”, with R0 ≈ 1 and ICU occupancy ≈ 60-70%
Contamination R0
ICU average occupancy ratio
B R A Z I L I A N P E R S P E C T I V E
GrowingSlowingDown
Low Risk Medium Risk High Risk
As states try to balance suppression/mitigation measures to
control the disease with a controlled reopening of economies,
we will likely see this “control zone” as a balancing point, with
stable growth of cases and ICU occupancy under control
Note: ICU occupancy in the state of Minas Gerais on May 25 updated from COVID-19 ICU occupancy to general ICU occupancy, a measure that the state started to adopt in the last few days; R0 calculated as the ratio of average new deaths in the last 7
days to the previous 7 days
Source: Ministry of Health and State Health Departments
State position on May 25th
A S O F M A Y 2 5
States with high ICU occupancy are at high risk of a health care system
collapse and need to keep the R0 (contagiousness level) consistently
below 1 so they can achieve a “sustainable” contamination stage

Evolution by state since May 25th: Many states that were in the medium and high
risk areas indeed improved and progressed towards the “control zone”
Contamination R0
GrowingSlowingDown
Among the states that were
considered critical, RJ, AM,
MA, PA and CE had the most
significant positive progress
N O T E X H A U S T I V E A S O F J U N E 2 6

Evolution by state since May 25th: In fact, many states that presented a lower risk
also progressed towards the “control zone”
Contamination R0
GrowingSlowingDown
With suppression measures being relaxed,
especially in the “better states”, it is natural to
see states in this area move to the right,
towards the same “control zone”
A S O F J U N E 2 6N O T E X H A U S T I V E

Evolution by state since May 25th : Unfortunately, a few states had their situation worsened,
demanding a higher level of attention and possible reinforcement of suppression measures
Contamination R0
Note: R0 calculated as the ratio of average new deaths in the last 7 days to the previous 7 days
GrowingSlowingDown
Last month MG had eased
suppression measures, but
with rapid worsening
returned to adopt more
restrictive measures
A S O F J U N E 2 6

Current situation in Brazil: most states are now classified as medium risk and we
expect states to continue orbiting around the “control zone” over the following weeks
0.806545 1.272405 99.6777 11.11
Contamination R0
Note: R0 calculated as the ratio of average new deaths in the last 7 days to the previous 7 days
GrowingSlowingDown
A S O F J U N E 2 6
As states try to balance suppression/mitigation measures to
control the disease with a controlled reopening of economies,
we will likely see this “control zone” as a balancing point, with
stable growth of cases and ICU occupancy under control

B R A Z I L I A N P E R S P E C T I V E M I T I G A T I O N
Very few states come close to having adequate testing levels (>10:1); this represents
a huge challenge for relaxing suppression measures without new outbreaks
Note: (1) Mortality calculated as % of confirmed cases
1
•
High Risk
• •
Medium Risk Low Risk
At current levels, Brazilian testing is not a lever to support the fight against COVID-19 spread in most States. The
vast majority of States only test severe cases, which does not work as a preventive measure.
Access to reliable data on testing is another major challenge because of: (i) Discrepancy among state departments
and the Ministry of Health; (ii) lack of reporting of private tests in most States and (iii) Long delay in reporting
A S O F J U N E 2 6

With economies starting to reopen across the country, mobility continues to trend up
in most states but remains well below pre-crisis levels
Mobility change from Jan-Feb baseline1
Source: Google Community Mobility Reports
Countries / cities with stricter isolation measures have reached levels of reduced mobility between 60-80% (eg.: Italy, Spain, NYC)
B R A Z I L I A N P E R S P E C T I V E S U P P R E S S I O N
High Risk Medium Risk Low Risk
A S O F J U N E 2 2

At least 8 capitals have reached or are close to exposure immunity levels of 15%,
which could already start to play a role in lowering/controlling the spread
Estimated exposed population (in %)
Note: Total number of cases estimated in function of the mortality rates; Considers only capitals with immunity >=1%
Source: Ministry of Health, Bain Analysis
B R A Z I L I A N P E R S P E C T I V E I M M U N I T Y
High Risk Medium RiskLegend Low Risk
A S O F J U N E 2 6

Going forward, we expect exposure immunity to play a major role in helping control
the disease in Brazil; there are three main ways the situation could play out
Exposure immunity
5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
R01
2.0 1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1 1.0
1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1 1.0 0.9
1.8 1.7 1.6 1.5 1.4 1.4 1.3 1.2 1.1 1.0 0.9
1.7 1.6 1.5 1.4 1.4 1.3 1.2 1.1 1.0 0.9 0.8
1.6 1.5 1.4 1.4 1.3 1.2 1.1 1.0 1.0 0.9 0.8
1.5 1.4 1.4 1.3 1.2 1.1 1.1 1.0 0.9 0.8 0.7
1.4 1.3 1.3 1.2 1.1 1.1 1.0 0.9 0.8 0.8 0.7
1.3 1.2 1.2 1.1 1.0 1.0 0.9 0.8 0.8 0.7 0.6
1.2 1.1 1.1 1.0 1.0 0.9 0.8 0.8 0.7 0.7 0.6
1.1 1.0 1.0 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.5
1.0 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.6 0.5 0.5
0.5 0.5 0.4 0.4 0.4 0.4 0.3 0.3 0.3 0.3 0.2
Note: 1R0 without exposure immunity
Source: University of Oxford, SEIR Model
Controlled R0 (<=1)High R0 (>=1.5)
B R A Z I L I A N P E R S P E C T I V E S C E N A R I O S
Brazil’s R0 has been oscillating
around 1,0-1,3. If R0 is above 1,
the disease continues to advance
I L L U S T R A T I V E

Exposure immunity
5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
R01
2.0 1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1 1.0
1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1 1.0 0.9
1.8 1.7 1.6 1.5 1.4 1.4 1.3 1.2 1.1 1.0 0.9
1.7 1.6 1.5 1.4 1.4 1.3 1.2 1.1 1.0 0.9 0.8
1.6 1.5 1.4 1.4 1.3 1.2 1.1 1.0 1.0 0.9 0.8
1.5 1.4 1.4 1.3 1.2 1.1 1.1 1.0 0.9 0.8 0.7
1.4 1.3 1.3 1.2 1.1 1.1 1.0 0.9 0.8 0.8 0.7
1.3 1.2 1.2 1.1 1.0 1.0 0.9 0.8 0.8 0.7 0.6
1.2 1.1 1.1 1.0 1.0 0.9 0.8 0.8 0.7 0.7 0.6
1.1 1.0 1.0 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.5
1.0 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.6 0.5 0.5
0.5 0.5 0.4 0.4 0.4 0.4 0.3 0.3 0.3 0.3 0.2
1.6
1.5
1.4
1.3
B R A Z I L I A N P E R S P E C T I V E S C E N A R I O 1 – R E L A X I N G S U P P R E S S I O N
With economies reopening, if no more suppression or
mitigation measures are put in place, the infection will only
start to decelerate as immunity grows significantly
However, this process takes a huge toll on the
healthcare system, most likely leading to its
collapse
As we have seen strong responses when the
healthcare system is struggling, we consider
this scenario very unlikely
1
2
3
No suppression
No mitigation
Nota: 1R0 without exposure immunity
Fonte: University of Oxford, SEIR Model
60~90 days

Exposure immunity
5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
R01
2.0 1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1 1.0
1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1 1.0 0.9
1.8 1.7 1.6 1.5 1.4 1.4 1.3 1.2 1.1 1.0 0.9
1.7 1.6 1.5 1.4 1.4 1.3 1.2 1.1 1.0 0.9 0.8
1.6 1.5 1.4 1.4 1.3 1.2 1.1 1.0 1.0 0.9 0.8
1.5 1.4 1.4 1.3 1.2 1.1 1.1 1.0 0.9 0.8 0.7
1.4 1.3 1.3 1.2 1.1 1.1 1.0 0.9 0.8 0.8 0.7
1.3 1.2 1.2 1.1 1.0 1.0 0.9 0.8 0.8 0.7 0.6
1.2 1.1 1.1 1.0 1.0 0.9 0.8 0.8 0.7 0.7 0.6
1.1 1.0 1.0 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.5
1.0 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.6 0.5 0.5
0.5 0.5 0.4 0.4 0.4 0.4 0.3 0.3 0.3 0.3 0.2
B R A Z I L I A N P E R S P E C T I V E S C E N A R I O 2 – O P E N I N G A N D C L O S I N G
Localized suppression measures
are deployed as a way to quickly
control the spread
1
With suppression
No mitigation
However, if no other measures are taken,
when suppression measures are lifted the R0
grows again, demanding new actions
2
With states trying to balance the epidemiological
and economic sides, it’s likely that we will see
this “up and down” pattern until immunity is
developed or a treatment is discovered
3

Exposure immunity
5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
R01
2.0 1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1 1.0
1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1 1.0 0.9
1.8 1.7 1.6 1.5 1.4 1.4 1.3 1.2 1.1 1.0 0.9
1.7 1.6 1.5 1.4 1.4 1.3 1.2 1.1 1.0 0.9 0.8
1.6 1.5 1.4 1.4 1.3 1.2 1.1 1.0 1.0 0.9 0.8
1.5 1.4 1.4 1.3 1.2 1.1 1.1 1.0 0.9 0.8 0.7
1.4 1.3 1.3 1.2 1.1 1.1 1.0 0.9 0.8 0.8 0.7
1.3 1.2 1.2 1.1 1.0 1.0 0.9 0.8 0.8 0.7 0.6
1.2 1.1 1.1 1.0 1.0 0.9 0.8 0.8 0.7 0.7 0.6
1.1 1.0 1.0 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.5
1.0 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.6 0.5 0.5
0.5 0.5 0.4 0.4 0.4 0.4 0.3 0.3 0.3 0.3 0.2
B R A Z I L I A N P E R S P E C T I V E S C E N A R I O 3 – R O B U S T M I T I G A T I O N P L A N
With suppression
With mitigation
Suppression efforts are deployed where
necessary to control the current “wave”
of infection and stabilize R0
1
If a robust mitigation plan is put in place, it is able to
compensate for more lenient suppression measures,
allowing for a controlled reopening of the economy without
new spikes in the curve
2
Unfortunately, without robust testing/tracing
capabilities it is very difficult to have a
mitigation strategy, so this scenario is also
unlikely for Brazil
3

In fact, we already see signs that scenario 2 - “opening and closing” – is the most
likely for Brazil, with states struggling to reopen the economy
News reports in the past 15 days have filled-up with headlines about cases picking up and distancing measures being
reinforced after many states started to open up their economies
B R A Z I L I A N P E R S P E C T I V E U P C O M I N G S C E N A R I O

Going forward: The upcoming scenario will vary by state or even micro-regions, but
scenario 2 is the most likely to be the norm, until immunity is reached
Health System capacity
Scenario 1 – relaxing suppression
Estimated hospitalizations due to COVID-19
(# cases)
Epidemiological Week
• Strong peak of contamination
with little response, leading to
exponential case growth
• Probable Collapse of the
healthcare system
Current hospitalizations
Scenario 2 – opening and closing
(# cases)
• Continuous cycles of suppression to control R0
followed by easing of measures and R0 increase
• Staggered curves of BR states lead to plateau
• Healthcare is kept under stress during a
significant period, and contamination only starts to
slowdown due to exposure immunity
Scenario 3 – robust mitigation plan
(# cases)
• Suppression measures are
efficient and slowdown the curve in
the next few weeks
• Mitigation strategy is put in place
and mobility reduction measures are
lifted without new surges
Most likely to be the norm

Going forward: Combining effects from all States, the most likely scenario for Brazil
is a long plateau of the disease until exposure immunity starts to play a role
(# cases; epidemiological week of the beginning of symptoms) Projections
Note: (1) With SARS Pneumonia symptoms; Source: Brazilian Ministry of Health – Public Health Emergency Operations Center; Bain Estimate.
Healthcare
system capacity
Different stages of COVID-19
spread and government responses
across Brazilian state should
generate a long plateu in the curve
After a significant period, exposure
immunity should help states
reduce the spread more
consistently
With many states reopening their
economies, we will likely continue
to see cases go up and down for
the following weeks

Manufacture
Transport. &
Storage
Commerce
Economic impact: COVID-19 crisis will hit all sectors at different levels; while agriculture
still has a positive GPD forecast vs 2019, most industries & services will be severely hit
Legend
Note: 1Baseline projection on Feb/20; 2Projection on June/20; 32018 growth vs 2020 Post-COVID projection
Source: LCA GDP Growth projections; WTTC; FGV
2020 GDP growth projection before COVID-191
2020 GDP growth projection after COVID-192
ConstructionTourism3
Agriculture
Industries Services
Financial
Services
Real Estate Public. Adm
High Impact Medium Impact Low Impact
E C O N O M I C I M P A C T
Energy &
Water
Agriculture
Taxes
Other
Services
Information
Services
A S O F J U N E 2 6
Mineral
Extraction

Economic impact: Northeast & South economies expected to be more severely hit in 2020, mostly
due to tourism and industrial activities; North and Central-West to face slightly lower losses
• ~13% of the economy based on mineral extractives
and energy, with the modest drop and profitability
advantage
• ~10% of the economy based on agriculture will help
mitigate local services loss
High epidemiological impact
Low economic impact (5,0% vs 5,6% BR)
North
• ~10% of total GDP based on Tourism,
sector that will suffer a major blow
• ~42% of total state revenue based on
fiscal transfers that will be maintained by
the federal government using aid measures
• ~27% of GDP based on agribusiness; strong soy harvest and high USD
will keep 2020 performance similar to last years
• High public spending and FS shares will also mitigate the drop in the region
High economic impact (7,2% vs 5,6% BR)
Central-West
Northeast
Southeast
Low epidemiological impact
Low economic impact (5,1% vs 5,6% BR)
Average to high economic impact (5,2% vs 5,6% BR)
• ~13% share of manufacture in the economy
will lead GDP fall in the region
• ~16% participation of FS and professional
services in the economy will avoid an even
more delicate situation for SE
Epidemiological impact
High Medium Low
South
Medium epidemiological impact
High economic impact
(5,9% vs 5,6% BR)
• ~16% of the economy based on manufacture and higher concentration
of severely hit goods such as furniture, textiles, clothing and footwear
• While agriculture share is similar to other regions, weather will lead to
severe harvest losses in 2020 (47% loss of soybean harvest in RS)
E C O N O M I C I M P A C T
Epidemiological
risk in early May

Current landscape and implications for Brazil: States appear to be converging to
an equilibrium, but the situation is far from under control
• Be careful with the data: The most common data used (number of new cases) is unreliable for understanding the situation.
Hospitalizations due to SARS is still the most reliable info and suggests a much slower growth already
• The reality is still highly variable across states, but in the past weeks most states progressed in a healthy direction by
reducing contamination levels (the R0) and/or ICU occupancy, moving towards a “control zone”
– States that were classified as high risk and that adopted more restrictive measures managed to evolve to a better situation. Pará and Ceará
are good examples; both states were in a critical condition and reduced considerably the spread of the virus and the ICU occupancy in the
last 15 days
– States that were at low risk (e.g. Paraná and Distrito Federal) started to lift restrictions and re-open parts of their economies and, as a
consequence, increased the occupancy rate of the health system, but remain at a controlled level
• On the other hand, a few states evolved negatively in recent weeks demanding a higher level of attention
– Minas Gerais and Mato Grosso appear to have prematurely relaxed suppression measures and reached a high ICU occupancy, both states
are already returning to more restrictive measures. Acre and Rio Grande do Norte - two states where social vulnerability and a weak health
infrastructure makes disease control more challenging - also entered the high risk zone
• It is possible that current exposure levels in some cities are already having some positive effect. Belém and
Fortaleza, for example, achieved +20% of exposure immunity. Depending on how the disease progresses, other capitals in
the high and medium risk profiles should start to feel more positive effects from exposure immunity in 2-6 weeks
• The long plateau, driven by states balancing the disease spread and the economy, continues to be our most likely
scenario going forward and should remain a reality at least for another 4-8 weeks
– It is important to note that this plateau is the combined effect of all states which are going through different stages of the contamination

International perspective: countries re-opening and economic recovery
Economic recoveryCountries re-opening
• Are the reopenings around the world being successful?
• What main factors are determining whether the reopenings are
successful?
• Which of those conditions can we replicate in Brazil and other
countries?
• Now that countries are starting to reopen, what can we expect in
terms of economic recovery?
• What lessons can we draw from China, that is probably the
farthest ahead in the process?
• What does this mean for Brazil and other countries?

It is clear that Brazil has a unique profile, but it is possible draw some important
lessons from Asian and European countries that are entering the recovery phase
• How fast are we growing? Are we trailing Europe?
• How long will it last until peak?
• Will we have a health crisis?
• Was contamination
detected soon enough
to be controlled?
• Do I have the
mitigation policies in
place?
• How other countries
are reopening?
• How is China
recovering?
• What is the economic
impact?
• How to ensure
contamination won’t
be back at
exponential growth?
• Curve slowdown after
suppression
measures
• Exponential or linear
growth of contamination
after loss of control
• Continued reduction
in the number of new
cases till zero
• Less than 100 cases
I II III IV V
Early phases Rapid growth Slowdown Recovery New normal
Key questions
• Set of measures in
place to keep
situation stable

Although government response stringency levels remain high, many regions have
started to ease restrictions
No lockdown Full lockdown
Note: Oxford’s Stringency Index is based on containment and closure policies (school and workplace closings, cancellation of public events, restrictions on gatherings, stay at home requirements and restrictions on internal and external movement) and the
availability of public health information campaigns
Source: Oxford Covid-19 Government Response Tracker (OxCGRT); Bain analysis
A S O F J U N E 2 5G L O B A L
April 15th
Most of the world with mid-high supression measures in-
place
June 15th
Visible reduction on the stringency of suppression
measures, especially in Europe and parts of Asia

Many Asian and European countries are successfully moving forward with relaxed
quarantine restrictions while closely monitoring case growth
Several APAC countries like South Korea and Japan are
managing resurgences after gradual reopening
A S O F J U N E 2 9
Containment strategies have shown differing levels of
success across European countries
Note: 7-day moving average reflects seven days prior to and including reporting date
Source: Johns Hopkins University, ABC News, CDC, WHO, Bloomberg, CNN, CBS News, Guardian, Inquirer, NHK World – Japan, Anadolu Agency, Focus Taiwan, The New York Times, VoA, Financial Times, Reuters, NPR, Taiwan News, Time Out,
Talking Points Memo, Bain Macro Trends Group analysis
R E C O V E R Y

Measures taken can
mitigate the spread
Exposure immunity
helps reducing R0
Combination should
prevent HC collapse
The key to the reopening is maintaining R0 below 1; Successful reopenings have
compensated more lenient suppression measures with robust mitigation strategies
Specific demographics
lead to “baseline” R0
Different location / stage
leads to diff. strategy
R0 <=1
• Favorable demographics
lead to fewer needs of gov.
measures
1
• Government measures
(such as widespread testing
and screenings) reduce the
need for lockdowns
2
• Exposure immunity
develops as number of
cases increase, reducing
need of other measures
3
Note: Illustrative impact of different factors influencing R0
Source: Lit. research
1 2
3
COVID-19 R0 (as a function of contributing factors)
R0 can be kept at this
level after transmission
control is at low levels
All variables must be taken into consideration when reducing the contamination R0. Different countries are acting in very distinct
ways to approach the problem
At this stage, most
evidence suggests
contaminated patients
develop immunity, but
its length and strength
are still being debated
Countries that are succeeding in
reopening have gradually relaxed
suppression measures and reinforced
mitigation actions
R E C O V E R Y

Activity Lockdown reopening strategy
Industrial &
workplaces
Medical Offices
Shops / Retail
Services
Restaurants
Public events
& entertainment
Major indoor
gatherings
Gyms / Fitness
centers
Schools
Most developed economies are using similar approaches to reopening their
countries, prioritizing sectors based on potential risk
Source: Media press search, lit research.
Phase One
N O N - E X H A U S T I V E
Reopening start
A S O F J U N E 1 1
Phase Two Phase Three
Initially returned with 1.5 meters
distance and no changing rooms
First openings where related to activities with
higher economic impact, and which did not
have high levels of contact between people Even at the third phase, mobility
in most countries have not
returned to its regular levels.
Germany and Italy are some
examples, with -17 and -31% vs
their baseline mobility
Most countries that reopened their
schools took strict measures, as
taking child temperatures in and
out, with required mask usage
R E C O V E R Y S U P P R E S S I O N

The reopening has been taking place progressively; large gatherings are restricted
for the foreseeable future and borders are still under control
Some countries are prohibiting
major events
• Other examples:
– Belgium: public sporting and culture events
banned until June 30th
– Netherlands: large events and contact sports
to be resumed in September
In general, mobility is still (well)
below previous levels
Oktoberfest – most traditional German event
cancelled
Borders are still not fully reopened
in Europe
• Many European countries have opened
their borders to EU citizens only
• Americans are still not allowed to travel
to most of the countries
Open border for
UE countries
Average mobility1 after reopening start date
(7 days average; days after reopening)
Part of the low
mobility is due to
fear of getting out
by the population,
behavior which is
helping the virus
containment
Note: (1) As a % of baseline mobility; 7 days average. Source: Media Press Search.

Source: Bloomberg; Media Press Search.
Italian Reopening prioritized easing the measures in regions that were less infected, travel between cities was also prohibited
Spain Reopening was divided between Phases Zero to Three;
Only travels 100km away from your initial location were permitted
France Reopening was based on red, yellow or green areas;
transit between regions was prohibited
Most countries adopted an approach based on a careful risk assessment; local
governments detailed/executed the plan whilst federal government coordinated the effort
Coordination between federal and regional government is key to successful reopening plans

Emergency plans have proven to be necessary in case of new outbreaks; some
countries have had to impose localized lockdowns to address case resurgences
China South Korea Germany
April 27th May 6th May 3rd
Reopening start date
Current Reopening
Phase
Current mobility
reduction1
New outbreaks and
reaction
Note: (1) Up to june 12th; vs mobility baseline with same weekdays considered; (2) Traffic used as a proxy. Sources: Media Press Search; Google Mobility.
• June 17th: New 1000+ cases
outbreak associated with a
slaughterhouse in Gütersloh led
to local lockdown comprising
two different districts
• May 9th: New outbreak of 100+
people in Seoul delayed
schools reopening and led
bars and nightclubs to close
once more
• May 14th: 6 new cases in Wuhan
led to 10 million tests
• May 19th: 34 new cases in
Shulan and Jilin led the cities to
lockdown as a response
• June 12th:150 new cases in
Beijing led to 350,000+ tests
and 10 neighborhoods isolated
Fully reopened
Partially delayed reopening
(Bars and nightclubs)
Advanced reopening (Large
events prohibited)
(2)

Mitigation: A robust mitigation strategy has these 3 pillars working in sync: Testing,
Tracing and Isolating
Mitigation
strategy
Isolating
Tracing
Testing
Logistics
Facilities
Collection
Who? & How? These are the key questions behind a mitigation strategy
IT for chain mgmt.
Equip. & material
R E C O V E R Y M I T I G A T I O N

Mitigation success stories: There are many success cases around the world that
show how powerful the testing, tracing, isolating pillars can be
South Korea and Vietnam controlled
the disease since its early signs
UK regained control by proactively
testing and tracing suspect cases
NZ and China are maintaining levels
of testing/tracing to control the virus
• South Korea had already realized 300.000+ tests In
March, when had ~10.000 cases. The strategy
allowed the contamination control in 30 days(1)
• Minimum suppression measures were needed, with
a maximum mobility reduction of 25%(2) (vs 63%
in Brazil, 47% in Japan and 93% in Italy)
• Besides not having mass testing available,
Vietnam was one of the first economies to reopen,
by applying intense tracing of cases
• Tests availability increased 40x between March 12th
and June 01st, reaching 60.000+ tests/day
• Number of new cases per day dropped 75%(3),
while mobility rose 80%(2)
• There’s no sign of appearance of second
outbreaks in the United Kingdom
• After eradicating COVID-19, New Zealand
reinforced its border control, requiring quarantine
from every international traveler
• With just 22 deaths, the country has a strong testing
program, with ~210 tests per confirmed case
• After controlling the cases in Wuhan, China has
executed constant mass testing
• After 150 cases in Beijing, more than 350.000 tests were
made and 10 neighborhoods were isolated
• 10 million inhabitants in Wuhan were tested with the
suspect of a new outbreak. No case was confirmed.
Note: (1) Period between first case and active cases peak, (2)Considers average mobility drrop in reatil, shops, transportation and workplace, (3) 7 days prior to peak average vs July 17th)
Source: Media Press, Worldometers, Google Mobility Reports.

Who? Besides to symptomatic, more comprehensive mitigation strategies test
vulnerable groups, essential workers and people exposed to the disease
Broad symptomatic Focus on vulnerableStrict symptomatic Widespread testing
• Visiting local
transmission zones,
traveled abroad, or had
contact with confirmed
cases on the last 14 days
• Present two or more
mild symptoms
Strict symptomatic
• People presenting acute
respiratory condition or
pneumonia who did not
visit a zone with local
transmission / had contact
with a confirmed case
• Less requirements for
vulnerable populations
(medical personnel, close
contacts, etc.), such as,
such as:
– Presenting only one
symptom
– No need of visiting a zone
with local transmission
• Cases presenting one of
COVID’s symptoms are
tested
• All close contacts to
confirmed cases are
tracked and tested
• Testing for all subjects
of risk populations
+ people tested
Who is eligible
for testing?
Introduced 5 changes to
the suspected case definition
Source: Argentina Ministry of Health; Chile Ministry of Health; Brazil Ministry of Health; Austria Ministry of Health; Business Insider; Asia Pacific Foundation of Canada; Europeum Think Tank
ChileBrazil Australia South
Korea
UKAustriaIsrael Swiss
Argentina
Even adopting relaxed testing
requirements high level
screening (by phone, on-line or
at testing premises) is necessary
SP

How to manage?
How? Countries testing a broader range of the population need to overcome operational
challenges; testing capacity and manual tracing seem to be key for success
LogisticsCollection
How to trace? How to isolate?
Lab & equipment Testing materials
How to test?
Network of test
collection locations
with great capillarity
and multiple
alternatives to reach
target population
Logistics with
response time under
24h from collection to
test results; usage of
larger facilities to
scale logistics
Development of “mega-
labs”, installation of new
equipment and broad
usage of PPPs
Redirect idle production
capacity and
development of multiple
suppliers
Manual tracing with
calls and follow-ups; it
might or not be
empowered with
technology
Constant follow-up of
isolated individuals by
tracers and availability
of adequate isolation
facilities (hotels and
clinics)
Development of new system layer connecting different links in the testing, tracing & isolation strategy;
system focused on usability and efficiency for the time being

How? Creative solutions and intensive usage of traditional methods are removing
bottlenecks and allowing for mass test collection around the globe
Spit tests for COVID-19 under
development
Unprecedented testing at large testing
centersDistribution of do-it-yourself tests
• UC San Diego spread boxes containing test kits
and instructions were distributed throughout
the campus
• The patient downloads the university testing
app, upload personal information and scans a
QR code to link ID and testing kit
• The patients collect the sample themselves
using the swab and deposits the kit in a box
• Samples are collected and tested within 24
hours; results are sent via app
• Fearing the surge of secondary waves, Wuhan
tested 10 million people in 10 days
– 190 collection centers were created
– Teams were sent to collect samples in the elderly
people's homes
• When identifying hotspots, Beijing invested in a
massive testing system
– 7,000 health workers and volunteers were
mobilized
– Collection capacity reached 500.00 kits / day, limited
to the analysis capacity of 230,000 / day
• Southampton in the UK to start a saliva testing
effectiveness study
– 14.000 people will be tested
• The main expected benefits are:
– Easier do-it-yourself at home
– Less discomfort
– Shorter analysis time
• This model might also allow continuous
testing of asymptomatic patients
M I T I G A T I O N S T R A T E G Y
Source: Lit Search.
A S O F J U N E 2 2

Cultural aspects are also key: social distancing etiquette generally stays in place and
masks are encouraged/required in many places; South America lags behind
Masks are a regular part of some
Japanese society
SA countries are still struggling to
introduce masks and distancing
“Face coverings on public transport will be
compulsory from 15 June in England to help
stop the transmission of coronavirus as more
people go back to work.”
The Guardian
“On May 10, France made the use of face
masks in public mandatory, as the country is
set to emerge from its coronavirus lockdown
the following day.”
Al Jazeera
Source: Media Press Search.
Line in Brazil marked for social distancing. People
left their bags on the marks, and agglomerated on
the other side of the street to escape from the sun.
Some European countries made
masks mandatory in public spaces
“It may seem a bit of a mystery to Westerners, but
masks as fashion have become a major part
of the Japanese world. A 2011 poll by Japanese
news site News Post Seven surveyed people in
Tokyo and learned that 30 percent of Japanese
wear masks for reasons not having to do with
sickness.”
GG Nihon
“The custom of facemask-wearing began in Japan
during the early years of the 20th century with
the Spanish Flu.”
Quartz
Interview in Peru: “We have to use three masks
throughout the month, so we re-use and re-use
it and what has happened? Where I work,
colleagues have caught the disease.”
Reuters

While successful reopening stories have managed to deploy robust mitigation tools,
other countries/states that lacked such tools have not been as successful
Mitigation
(High use of
technology)
Suppression
(Mobility
reduction)
• Utilization of effective
tracing system
• # of daily tests /
daily new cases1
• Big events authorization
Unconstrained
R0
• # of people/household
2-2.6
2.6
Exposure
immunity
• Case growth rate
after reopening (%)
Governmentmeasures
• Current mobility4 and
previous mobility5 (%)
Reopening
results
Italy
• Required mask usage
Banned Allowed
10195
Banned
Up to 15
people
234138
NYJapan IranGermany
-12%
(-27%)
-14%
(-34%)
-15%
(-37%)
-23%
(-68%)
4-124-103-55-9
2.42.12.4 3.5
2
(Manual
Tracing)
(Recent
app)
(App + Manual
Tracing)
(No structured
efforts mapped)
4-17
2.5
S. Korea
Banned
232
~0%
(-3%)
2
(Manual + Personal
Data Tracing)
N/A
Banned Banned
2-3
Brazil
-28%
(-40%)
3-8
3.3
(No structured
efforts mapped)
Stadiums/carnivals
at 50%capacity
15
Texas
-13%
(-21%)
1-1.5
2.8
(Some manual
tracing)
70
R E C O V E R Y
Note: (1) June 7th; (2) Only required in public transportation; (3) In closed public spaces + open lines (4) Versus baseline mobility; (5) Mobility on May 01st; Source: Google Mobility; Media Press Search; Bain Analysis; JHU Coronavirus Data Stream 10/06.
Inefficient suppression and mitigation measures led to case growth
(App + Manual
Tracing)
3
(Some cities)

Other places, as Iran and some American states, are struggling to slowdown the curve
after the reopening due to inefficient suppression and mitigation measures (1/2)
Iran eased its measures and saw a second outbreak,
with deaths starting to spike again
Texas has reopened and is facing one of the hardest
times during the pandemic
Source:Wordometers.
A S O F J U N E 2 9R E C O V E R Y

Other places, as Iran and some American states, are struggling to slowdown the curve
after the reopening due to inefficient suppression and mitigation measures (2/2)
California is facing its peak of new cases per day since
reopening started
Florida is reaching its historical highs in new cases per
day, with a recent increase after reopening Phase 2
Source:Wordometers.
A S O F J U N E 2 9R E C O V E R Y

Poland India Singapore
Localized new outbreaks across the world are also evidence that overcrowded places or
those with lack of basic services need to be monitored and managed closely
• On June 8th, Poland recorded a massive
outbreak in various coal mines (1000+
cases over the weekend)
– Mine-related cases now are 10%+ of total
– Poland shut 12 state-run mines for 3 weeks in
an attempt to control the local outbreaks
• Cases have surged in the midst of a rise
in movement from urban to rural areas
due to the return of migrant workers to
their home towns
– In the last 3 weeks, ~30-80% of cases
coming from rural areas (where access to
running water and other services is limited)
• Singapore experienced outbreak in April
with Immigrants living in poor
conditions accounting for ~75% of cases
– The rest of Singapore was controlled with few
cases, and the government gradually eased
the lockdown, allowing non-essential
services to reopen
Source: Financial Times (Poland to shut 12 coal mines in attempt to contain coronavirus); Times Of India (Convid’s new hunting ground: Rural India); Financial times (Singapore struggles to slash coronavirus infections))
R E C O V E R Y

Reopening lessons and implications for Brazil
• As government measures are successful and regions are able to control contamination levels, countries are starting to ease restrictions
and mobility starts to return to previous levels. Asian and European countries are moving forward with relaxed quarantine restrictions
while closely monitoring case growth
• Most developed economies are using similar approaches to reopen their countries; they are gradually relaxing suppression measures whilst
strongly reinforcing mitigation actions. There are a few important learnings for South American countries:
– The reopening has been taking place progressively; sectors with low exposure and high economic impact such as industrial and workplaces are prioritized
– On the other hand, there are specific mobility suppression measures being kept: major entertainment events, such as cultural activities and sports events, had
their reopening delayed and borders remain under tight control
– The reopening is usually regionalized and based on a careful risk assessment. The coordination between federal and local governments has been key to
the success of this process; federal governments are responsible to set the strategy and local authorities are responsible for detailing and executing; Transit
between regions of different risk profiles is usually restricted
– Emergency plans have proven to be essential in the case of insurgent new outbreaks; the ability to lock-down cities/neighborhoods goes a long way
– As countries started to reopen they gradually reinforced their mitigation efforts: ramping-up their testing, tracing and isolating capability to control
contamination
– A culture of social distancing and mandatory/wide mask usage is another key aspect of countries reopening process
• On the other hand, countries/regions such as Iran and a some USA states had issues to slowdown the curve after easing suppression
measures; those regions opened up before actually getting the situation under control and were not able to deploy mitigations tools efficiently
• Brazil is in a very similar position to Iran and USA states, easing suppression measures without fully controlling the disease and with no
real mitigation efforts in place. Building coordinated testing/tracing/isolating capabilities should be priority #1 for all States to allow for a
more smooth recovery process, with less need for another round of strong suppression measures
R E C O V E R Y

International perspective: countries re-opening and economic recovery
Economic recoveryCountries re-opening
• Are the reopenings around the world being successful?
• What main factors are determining whether the reopenings are
successful?
• Which of those conditions can we replicate in Brazil and other
countries?
• Now that countries are starting to reopen, what can we expect in
terms of economic recovery?
• What lessons can we draw from China, that is probably the
farthest ahead in the process?
• What does this mean for Brazil and other countries?

The Covid crisis is expected to impose harsh economic losses across the globe,
even more severe than what was seen in 2009
Source: IMF World Economic Outlook
A S O F J U N E 2 2E C O N O M I C R E C O V E R Y G D P I M P A C T

Governments are heavily investing in fiscal measures to provide liquidity to the
economy and contain the damage from COVID-19
Fiscal measures taken by country to fight COVID-19
(as % of GDP)
Additional package, possibly reaching
3 trillion USD under consideration by the gov.
Note: Currency conversion on march 31st; 2019 GDP in USD, 1Not at scale
Source: Trading Economics; Morningstar
Mortality
(deaths per million people)
3881
5741
4441
E C O N O M I C R E C O V E R Y F I S C A L M E A S U R E S
1031
A €750B aid package for the EU under
study, but countries are not agreeing
on weather it will be in grants or loans
A S O F J U N E 2 6

Countries across the globe are trying to reignite their economies; workplace foot
traffic is ~20-30% below pre-crisis levels, after being down by 40-70% in most places
Americas
Europe
March
APAC
A S O F J U N E 2 2
Source: Google COVID-19 Mobility Data
April May June
March April May June
March April May June
E C O N O M I C R E C O V E R Y S T A T U S

China: China is further ahead the recovery process; estimates suggest that the
country has reached ~85% of pre-pandemic economic activity levels
Financial Times estimates that China’s current activity level is ~70% of Jan 1 levels, and is down ~15% YoY
A S O F J U N E 5 2 0 2 0
Note: FT index is a mix of domestic economic indicators, trade activity, and social and environmental activity; Coal consumption includes top 6 largest state power plants
Source: Financial Times, Bain Macro Trends Group analysis
Jan
Economic
activity fell
nearly 50% during
lockdown period
As of June 4, activity
remains ~15% below
June 2019
China’s deeper and longer economic
contraction is likely driven by
reduced demand from overseas
customers in the US and EU
Wuhan lockdown
begins Jan 23
MayFeb Mar Apr
E C O N O M I C R E C O V E R Y C H I N A

China - Industry: With most of the economy open at this point, key metrics show
that the industrial sector has returned or is very close to pre-pandemic levels
Industrials Impact
Note: *January data not available – values reflect accumulated growth rate (%) investment of real estate
Source: Trading Economics, Reuters, CNBC, IPSOS, CEIC, Bloomberg, Financial Times, NBS of China, Bain Macro Trends Group analysis
• New orders dropped through the month of
February, as companies adjusted forecasts and
weighed the impacts of COVID-19 on their
businesses
• However, manufacturing PMI rose from a low
of 40.3 to 50.7 in May, indicating
manufacturing firms are reopening
Exports
2019 2020
A S O F J U N E 5
Coal consumption
2019 2020
• Coal represents 60-70% of Chinese electric
energy consumption, being a great driver for
the industry activity level
• Coal monthly consumption has decreased 10-
12 points during the pandemic, but has
already shown improvement during the month
of May, achieving higher levels than 2019
• Foreign demand for imports hit its lowest
level in February since summer ‘09, and
remains below pre-COVID levels
• Even though other countries haven’t fully
recovered, Chinese exports are already
increasing and have already gotten bigger
than April’s 2019 YoY
2019 2020
Coal Montlhy consumption in largest state power plant
(Montlhy ; Indexed: Jan 2019 = 100)
Caixin General Manufacturing PMI Change in Chinese export volume, YoY

China - Consumption: On the other hand, economic sectors more dependent on
consumption seem to be taking longer to recover to pre-pandemic levels
Retail & Wholesale Impact Real Estate Impact
Note: *January data not available – values reflect accumulated growth rate (%) investment of real estate
Source: Trading Economics, Reuters, CNBC, IPSOS, CEIC, Bloomberg, Financial Times, NBS of China, Bain Macro Trends Group analysis
• A combination of mandatory quarantine efforts and consumer fear led to
the steep drop in YoY sales, which have yet to fully cover
• In March and April, retail sales started to converge with 2019 sales,
hovering ~5-15% below 2019
• Real estate saw higher than expected returns in March
– MSCI China Real Estate Index improved slightly toward the end of March, logging
~10% drop vs. the ~20% dip for all of Q1
– Index gathers data of money invested in large and mid-cap real state related securities
• New home prices rose ~0.5% in April vs. March, the fastest pace since
October 2019
2019 2020 2019 2020
A S O F J U N E 5E C O N O M I C R E C O V E R Y C H I N A

China - Consumption: consumers are still planning on saving more in the second
quarter, but the future perspective is positive
Consumers are positive about the future economy
What is your opinion about the economy of your city and
your future spending power after COVID-19？
Q
Source: South China Morning Post; China’s Southwestern University of Finance and Economics Survey; Wind; amap.com; National Bureau of Statistics; Morgan Stanley; Everbright Securities; Bain analysis
Savings have increased significantly during the pandemic
Second quarter expected expenditure (N =~28k)
How much do you plan on spending on the second
quarter vs the first one?
Q
Consumer sentiment towards economy after COVID-19 (N =~28k)

China - Consumption: Under uncertain conditions, consumers focused on essentials during
the peak of the crisis (Feb); most other categories have started to recover, but still lag behind
Essentials Non-essentials
Note: (*) Includes oral care and body care
Source: Taoshuju; Bain analysis
FMCG Consumer durables
Selected sub-categories
O N L I N E - P L A T F O R M S A L E SE C O N O M I C R E C O V E R Y C H I N A

Twin-engine
recovery
Online leading
recovery
Waiting for
recovery
Total retail sales, Q1
2020, B RMB
100
Change in ONLINE retail sales by sector
(April1 2020, YoY LFL%)
Change in online AND offline retail sales by sector
(April 2020, YoY LFL%)
China - Consumption: Leveraging digital channels has been an essential part of
the recovery for most consumption-related segments
Note: (1) For non-available segments; march as used as reference value. Source: China National Bureau of Statistics; Tmall & Taobao data; Bain analysis

China - Consumption: Traditional brands that embraced digital channels seem to
be leapfrogging competitors during the recovery
Source: Lit search; Bain analysis
Louis Vuitton Forest Cabin (Chinese cosmetics brand)
Before
COVID
• Sales and customer interaction heavily reliant on
traditional/ offline channels, similar to other luxury
brands
• Sales primarily done through 300+ self-operated retail
stores throughout China, with in-store beauty advisors
to help guide customers
During/
after
COVID
• Digital Valentine’s Day: new WeChat mini-program pop-
up store developed, enabling customers to interact with
store associates online for pre-sale consultations/ post-
sales customer service and place orders
– YoY online Valentine’s sales increased 2x vs. 2019
• New product releases streamed online for the first time
through official LV Xiaohongshu account
• Company redeployed its beauty advisors from physical
stores to become online influencers, using platforms
such as WeChat and Taobao to engage with customers,
stream content, and drive online sales
– YoY online sales increased >100% vs. 2019, with >200%
growth in Wuhan after retail store sales dropped ~90% in
January 2020
New WeChat mini program
developed with new functions,
e.g. pre-sale consultations
New product intros
done through streaming
In-store beauty
advisors turned
into online
influencers
Online product
demonstrations
and customer
engagement
E X A M P L E SE C O N O M I C R E C O V E R Y C H I N A

Other countries: There are early signs that other countries are in the same recovery path
as China; PMI is starting to recover in many European countries, even the most affected
PMI seems to be slowly recovering all around the world, indicating the return of supply activities
Purchasing Managing Index (PMI) per country
(%)
Note: Recovery delta between two subsequent months.
Source: Trading Economics
Future misbalance between supply
and non–essentials demand may
slow down the return process
E C O N O M I C R E C O V E R Y O T H E R C O U N T R I E S

Other countries: Energy consumption went trough a stronger reduction in countries
that experienced more severe lockdowns, but already recovered to at least ~90%
Daily average electric energy consumption vs 2019
(100 basis from 1st day; 7 days average)
Note: (1) From day 1 consumption; Source: Bruegel; ONS.
11%12% 9%3% 7%
Days after quarantine measures where put in place
24%18% 17%10% 11%
Average
reduction1
30 days after
measures
Last 15 days
Average ~90% consumption

Essentials
Source: Opportunity Insights; Bain analysis
USA - Consumption: Consumption is starting to come back; recovery pace is faster
for essential categories, but even those are still behind January levels
USA monthly consumption per segment
(% of January; Indexed)
Segments directly affected by the pandemicNon-essentials

USA – Consumption: Most of the consumption gap, however, comes from high
income households which are still spending ~13% below January levels
USA spending per income segment
(% of January; Indexed)
USA Personal saving as a percentage of disposable personal income
(%; Monthly Average)
The low income segment, more focused on essentials
in its purchases, is recovering faster
Savings have increased significantly, starting on march;
variation explains part of the consumption reduction
Higher Lower
Essentials as % of spending
Source: Opportunity Insights; USA Department of Commerce; Bain analysis
Low and middle income
segments are the ones receiving
government support

COVID-19 Fact Base and Potential Implications for Brazil - Completo

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