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UnitedStatesofAmerica CURRENT SITUATION · UnitedStatesofAmerica CURRENT SITUATION Figure4....
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IHME’s latest COVID-19 forecasts indicate that the US will reach nearly 300,000 deaths by December 1,
2020. If mask wearing in public increases to 95%, more than 66,000 lives could be saved.
Other major findings include:
1. Infections decreasing in some hot spots: Florida, Texas, California, and Arizona have brought
effective R below 1. Cases and hospitalizations have peaked but deaths are still rising. We expect
deaths to rise for another week and then level off. The peaking of transmission in these states
appears to be driven by the combination of local mandates for mask use and bar and restaurant
closures, along with more cautious behaviors from the public. Media reports of increasing case
numbers and deaths seems to be associated with more cautious behavior by the individuals in these
communities in response to these trends. This will be an important mechanism throughout the
coming year and will likely lead to oscillations in the epidemic in various states.
2. New hot spots: Based on cases, hospitalizations, and deaths, transmission of COVID-19 is increasing
in 11 states: Colorado, Idaho, Kansas, Kentucky, Mississippi, Missouri, Ohio, Oklahoma, Oregon,
Virginia, and Wisconsin. These states may experience increasing cases for several weeks. We hope
to see a behavioral response toward more cautious behavior in these states soon.
3. Mask use increasing thanks to mandates, penalties, and messaging: Since July 15, 12 states have
added mask mandates. Our statistical analysis of mask mandates suggests that a mandate with no
penalties is associated with an 8 percentage point increase of mask use, and a mandate with
penalties is associated with a 15 percentage point increase. These efforts and public information
have led to an increase in the US rate of mask wearing by about 5 percentage points since mid-July.
Mask wearing increases have been larger in states with larger epidemics.
4. Test, trace, and isolate likely no longer feasible in many states: The population protective effect of
testing, which is meant to capture the impact of a test, contact trace, and isolate strategy is
estimated in the model by examining the relationship between testing per capita and effective R.
The strength of this relationship is getting weaker over time. In settings with large-scale
transmission, test, trace, and isolate strategies are likely infeasible because of the huge volume of
contacts. These strategies are likely more important in settings where other measures such as mask
wearing or mandates have reduced transmission to quite low levels.
5. Transmission likely to increase in winter months: Our estimate of the effect of seasonality remains
large, implying that we should expect to see a substantial increase in transmission, all other things
being held equal, in the winter months. The large number of forecasted deaths that we estimate in
the month of November in the reference scenario, nearly 45,000 deaths in one month, is driven
substantially by this seasonal increase in transmission potential along with an assumption of further
relaxation of mandates.
6. 23 states likely need to re-impose mandates before December 1: In our model, we assume that
states will re-impose a package of mandates including non-essential business closures and stay-at-
home orders when the daily death rate reaches 8 per million. This threshold is based on the 90th
percentile of when states/locations imposed mandates in March and April. This threshold implies
that many states will have to reimpose mandates. If they do not, the number of infections and
United States of America CURRENT SITUATION
covid19.healthdata.org Institute for Health Metrics and Evaluation
deaths can be much higher, and this is captured by our mandates easing scenario. More specifically,
our model suggests that the following states will be at the point where they will need to reconsider
re-imposing mandates:
a. August: Arizona, Florida, Mississippi, South Carolina
b. September: Georgia, Texas
c. October: Colorado, Kansas, Louisiana, Missouri, Nevada, North Carolina, Oregon
d. November: Alabama, Arkansas, California, Iowa, New Mexico, Ohio, Oklahoma, Utah,
Washington, and Wisconsin.
If mask use is increased to 95%, the re-imposition of stricter mandates can be delayed 6-8 weeks on
average.
7. We may be over-estimating the impact of schools re-opening on transmission: We currently
assume that 50% of school districts in each state will opt for online instruction only. As data emerge
on actual decisions, we will incorporate this into future revisions of our model. We also assume the
impact of school re-openings on mobility will be of the same magnitude as the impact of school
closures in March, but in the opposite direction. Given mask use, likely restrictions on after-school
activities, and avoidance of social engagement related to schools by some parents, our estimated
impact of school openings may be overly pessimistic.
8. Lack of data sharing by the US government hampers our research: Our understanding of the drivers
of the pandemic beyond mask use, mobility, testing, and seasonality is hampered by the lack of
access to data. US CDC has many relevant datasets on the pandemic that they have refused to share
with the research community. The switch of data reporting from US CDC to the US HHS has had little
impact on our models since neither group is sharing much of their data with the research
community. Some data that are critical to monitoring the response to the pandemic, such as mask
use, are only collected through private-sector initiatives such as surveys conducted by Facebook,
Premise, and SurveyMonkey. Federal government efforts to fill these critical data gaps have been
limited to date.
Figures related to these findings may be found here. The new death projections and other information, such
as hospital resources usage, are available at https://covid19.healthdata.org.
United States of America CURRENT SITUATION
covid19.healthdata.org Institute for Health Metrics and Evaluation
United States of America CURRENT SITUATION
COVID-19 Results Briefing: United States of America
Institute for Health Metrics & Evaluation (IHME)
07 August 2020
This short briefing contains summary information on the latest projections from the Institute for HealthMetrics and Evaluation (IHME) model on COVID-19 in United States of America.
Current Situation
Figure 1. Reported daily COVID-19 cases
0
30000
60000
90000
Apr May Jun Jul AugMonth
Cou
nt
Daily cases
covid19.healthdata.org 1 Institute for Health Metrics and Evaluation
United States of America CURRENT SITUATION
Figure 2. Reported daily COVID-19 deaths and smoothed trend estimate
0
1000
2000
Apr May Jun Jul Aug
Dai
ly d
eath
s
Figure 3. Estimated distribution of cumulative COVID-19 deaths by age group
0
5
10
<5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 99
Age group
Sha
re o
f cum
ulat
ive
deat
hs, %
covid19.healthdata.org 2 Institute for Health Metrics and Evaluation
United States of America CURRENT SITUATION
Figure 4. Mean effective R on 2020-07-23. The estimate of effective R is based on the combined analysis of deaths, case reporting, and hospitalizations where available. Current reported cases reflect infections 11-13 days prior so estimates of effective R can only be made for the recent past. Effective R less than 1 means that transmission should decline all other things being held the same.
<0.87
0.87−0.92
0.92−0.94
0.94−0.96
0.96−1
1−1.02
1.02−1.03
1.03−1.05
1.05−1.08
>1.08
No data
Figure 5. Estimated percent infected with COVID-19 on August 03, 2020
<4
4−6
6−8
8−10
10−12
12−14
14−16
16−18
18−20
>20
No data
covid19.healthdata.org 3 Institute for Health Metrics and Evaluation
United States of America CURRENT SITUATION
Figure 6. Percent of COVID-19 infections detected. This is estimated as the ratio of reported COVID-19cases to estimated COVID-19 infections based on the SEIR model.
0
10
20
30
Mar May Jul
Per
cent
of i
nfec
tions
det
ecte
d
Italy Republic of Korea United Kingdom United States of America
Figure 7. Daily COVID-19 death rate per 1 million on August 03, 2020
<1
1 to 2
2 to 3
3 to 4
4 to 5
5 to 6
6 to 7
7 to 8
>8
No data
covid19.healthdata.org 4 Institute for Health Metrics and Evaluation
United States of America CRITICAL DRIVERS
Critical Drivers
Table 1. Current mandate implementation
All
gath
erin
gs r
esric
ted
All
none
ssen
tial b
usin
esse
s cl
osed
Any
bus
ines
ses
rest
ricte
d
Sch
ool c
losu
re
Sta
y ho
me
orde
r
Trav
el li
mits
WyomingWisconsin
West VirginiaWashington
VirginiaVermont
UtahTexas
TennesseeSouth Dakota
South CarolinaRhode IslandPennsylvania
OregonOklahoma
OhioNorth Dakota
North CarolinaNew York
New MexicoNew Jersey
New HampshireNevada
NebraskaMontanaMissouri
MississippiMinnesota
MichiganMassachusetts
MarylandMaine
LouisianaKentucky
KansasIowa
IndianaIllinoisIdaho
HawaiiGeorgiaFlorida
District of ColumbiaDelaware
ConnecticutColoradoCaliforniaArkansas
ArizonaAlaska
Alabama
Mandate in place No mandate
covid19.healthdata.org 5 Institute for Health Metrics and Evaluation
United States of America CRITICAL DRIVERS
Figure 8. Total number of mandates
WyomingWisconsin
West VirginiaWashington
VirginiaVermont
UtahTexas
TennesseeSouth Dakota
South CarolinaRhode IslandPennsylvania
OregonOklahoma
OhioNorth Dakota
North CarolinaNew York
New MexicoNew Jersey
New HampshireNevada
NebraskaMontanaMissouri
MississippiMinnesota
MichiganMassachusetts
MarylandMaine
LouisianaKentucky
KansasIowa
IndianaIllinoisIdaho
HawaiiGeorgiaFlorida
District of ColumbiaDelaware
ConnecticutColoradoCaliforniaArkansas
ArizonaAlaska
Alabama
Feb Mar Apr May Jun Jul Aug
# of mandates
0
1
2
3
4
5
6
Mandate imposition timing
covid19.healthdata.org 6 Institute for Health Metrics and Evaluation
United States of America CRITICAL DRIVERS
Figure 9a. Trend in mobility as measured through smartphone app use compared to January 2020 baseline
−80
−60
−40
−20
0
Feb Apr Jun Aug
Per
cent
red
uctio
n fr
om a
vera
ge m
obili
ty
Italy Republic of Korea United Kingdom United States of America
Figure 9b. Mobility level as measured through smartphone app use compared to January 2020 baseline(percent)
<−46
−46 to −40
−40 to −34
−34 to −28
−28 to −21
−21 to −15
−15 to −9
−9 to −3
−3 to 3
>3
No data
covid19.healthdata.org 7 Institute for Health Metrics and Evaluation
United States of America CRITICAL DRIVERS
Figure 10a. Trend in the proportion of the population reporting always wearing a mask when leaving home
0
20
40
60
80
Feb Apr Jun Aug
Per
cent
of p
opul
atio
n
Italy Republic of Korea United Kingdom United States of America
Figure 10b. Proportion of the population reporting always wearing a mask when leaving home on August 03, 2020
<34%
34 to 37%
37 to 41%
41 to 45%
45 to 49%
49 to 52%
52 to 56%
56 to 60%
60 to 64%
>64
No data
covid19.healthdata.org 8 Institute for Health Metrics and Evaluation
United States of America CRITICAL DRIVERS
Figure 11a. Trend in COVID-19 diagnostic tests per capita
0
50
100
150
200
250
Mar May Jul
Test
per
100
,000
pop
ulat
ion
Italy Republic of Korea United Kingdom United States of America
Figure 11b. COVID-19 diagnostic tests per 100,000 people on July 29, 2020
<150
150 to 210
210 to 270
270 to 330
330 to 390
390 to 440
440 to 500
500 to 560
560 to 620
>620
No data
covid19.healthdata.org 9 Institute for Health Metrics and Evaluation
United States of America CRITICAL DRIVERS
Figure 12. Increase in the risk of death due to pneumonia on February 1 compared to August 1
<−80%
−80 to −60%
−60 to −40%
−40 to −20%
−20 to 0%
0 to 20%
20 to 40%
40 to 60%
60 to 80%
>80%
No data
covid19.healthdata.org 10 Institute for Health Metrics and Evaluation
United States of America PROJECTIONS AND SCENARIOS
Projections and Scenarios
Figure 13. Cumulative COVID-19 deaths until December 01, 2020, for three scenarios. The reference scenario is our forecast of what we think is most likely to happen. The mandate easing scenario is what would happen if governments continue to ease social distancing mandates. The universal mask mandate scenario is what would happen if mask use increased immediately to 95%.
0
100,000
200,000
300,000
400,000
0
500
1000
1500
Feb Apr Jun Aug Oct Dec
Cum
ulat
ive
Dea
ths
Cum
ulative deaths per 100,000
Continued SD mandate easing
Reference scenario
Universal mask use
Figure 14. Daily COVID-19 deaths until December 01, 2020, for three scenarios. The reference scenario is our forecast of what we think is most likely to happen. The mandate easing scenario is what would happen if governments continue to ease social distancing mandates. The universal mask mandate scenario is what would happen if mask use increased immediately to 95%.
0
1,000
2,000
3,000
4,000
5,000
0
5
10
15
20
Feb Apr Jun Aug Oct Dec
Dai
ly D
eath
sD
aily deaths per 100,000
Continued SD mandate easing
Reference scenario
Universal mask use
covid19.healthdata.org 11 Institute for Health Metrics and Evaluation
United States of America PROJECTIONS AND SCENARIOS
Figure 15. Daily COVID-19 infections until December 01, 2020, for three scenarios. The reference scenario is our forecast of what we think is most likely to happen. The mandate easing scenario is what would happen if governments continue to ease social distancing mandates. The universal mask mandate scenario is what would happen if mask use increased immediately to 95%.
0
250,000
500,000
750,000
0
1000
2000
3000
Feb Apr Jun Aug Oct Dec
Dai
ly In
fect
ions
Daily infections per 100,000
Continued SD mandate easing
Reference scenario
Universal mask use
Figure 16. Forecasted percent infected with COVID-19 on December 01, 2020
<4
4−6
6−8
8−10
10−12
12−14
14−16
16−18
18−20
>20
No data
covid19.healthdata.org 12 Institute for Health Metrics and Evaluation
United States of America PROJECTIONS AND SCENARIOS
Figure 17. Daily COVID-19 deaths per million forecasted on December 01, 2020, in the reference scenario
<1
1 to 2
2 to 3
3 to 4
4 to 5
5 to 6
6 to 7
7 to 8
>8
No data
Table 2. Ranking of COVID-19 among the leading causes of mortality this week, assuming uniform deathsof non-COVID causes throughout the year
Cause name Weekly deaths RankingIschemic heart disease 10,724.0 1COVID-19 7,238.4 2Tracheal, bronchus, and lung cancer 3,965.3 3Chronic obstructive pulmonary disease 3,765.9 4Stroke 3,643.4 5
covid19.healthdata.org 13 Institute for Health Metrics and Evaluation