forecasts we extended our forecasts to january 1. we ... · 2020-09-03 · cumulative deaths...

UNITED STATES MODEL UPDATES FOR SEPTEMBER 03, 2020

covid19.healthdata.org Institute for Health Metrics and Evaluation

Current situation

• The number of reported cases peaked in the end of July at around 70,000 cases per day and has subsequently declined to around 45,000 cases per day. Given that the current lag between death rates and case rates appears to have lengthened to more than two weeks, deaths have only started to decline after the middle of August and are now averaging around 850 per day. COVID-19 remains the second-leading cause of death in the nation.

• Effective R is above 1 in 10 states: Idaho, Utah, Kansas, Oklahoma, Arkansas, Alabama, Virginia, West Virginia, Illinois, and Iowa. Increasing transmission in these states, however, is less than the decline in more populous states such as Texas, Florida, and California contributing to the national decline in cases.

• Only eight states have more than 10% of the population that has been infected with COVID-19: Arizona, Louisiana, Mississippi, Georgia, Delaware, New Jersey, New York, and Massachusetts.

• The death rate is over 4 per million per day in Nevada, Arizona, Texas, Louisiana, Arkansas, Mississippi, Georgia, Florida, and South Carolina.

Trends in key drivers

• The only change in mandates since August 27 has been the lifting of any business restrictions in South Carolina.

• National mobility levels continued to increase slowly in the last week, with increases in mobility seen in states such as California, New York, New Jersey, Nevada, and Arizona.

• Mask use continues to decline from a peak in early August. Declines are notable throughout the Midwest, including in some states such as Illinois and Iowa with increasing case numbers.

• Likely reflecting the declining number of individuals presenting with symptoms, national testing rates continued to decline slowly from a peak in early August.

Forecasts

• We extended our forecasts to January 1. We expect the daily death rate in the United States, because of seasonality and declining vigilance of the public, to reach nearly 3,000 a day in December. Cumulative deaths expected by January 1 are 410,000; this is 225,000 deaths from now until the end of the year.

• If a herd immunity strategy is pursued, namely no further government intervention is taken from now to January 1, then the death toll could increase to 620,000 by January 1. Compared to the reference scenario, this would be 210,000 more deaths from now to the end of the year.

• Increasing mask use remains an extraordinary opportunity for the US. Increasing mask use to the levels seen in Singapore would decrease the cumulative death toll to 288,000, or 122,000 lives saved compared to the reference scenario. This would be a 30% reduction in the deaths expected from now until the end of the year.

United States of America MODEL UPDATES

COVID-19 Results Briefing: United States of America

Institute for Health Metrics and Evaluation (IHME)

September 03, 2020

This briefing contains summary information on the latest projections from the IHME model on COVID-19 inUnited States of America. The model was run on September 02, 2020.

Model updates

Starting this week, we are reporting our projections up to January 01, 2021. Updates to the model this weekinclude additional data on deaths, cases, and updates on covariates. Since our model two weeks ago, we havebeen using an updated infection to fatality ratio (IFR) that substantially affects the number of estimatedinfections, particularly in younger age groups. The Preface Figure shows the age pattern as previously usedand the new age pattern. This curve is a global pattern and affects all locations.

Preface Figure.

0.01%

0.10%

1.00%

10.00%

0 5 10 20 30 40 50 60 70 80 95

Age

Infe

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Previous model Updated model

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Previous model Updated model

covid19.healthdata.org 1 Institute for Health Metrics and Evaluation

United States of America CURRENT SITUATION

Current situation

Figure 1. Reported daily COVID-19 cases

0

20,000

40,000

60,000

80,000

Apr May Jun Jul Aug SepMonth

Cou

nt

Daily cases



Table 1. 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 1COVID-19 6,014 2Tracheal, bronchus, and lung cancer 3,965 3Chronic obstructive pulmonary disease 3,766 4Stroke 3,643 5Alzheimer’s disease and other dementias 2,768 6Chronic kidney disease 2,057 7Colon and rectum cancer 1,616 8Lower respiratory infections 1,575 9Diabetes mellitus 1,495 10

Figure 2a. Reported daily COVID-19 deaths and smoothed trend estimate

0

1,000

2,000

Apr May Jun Jul Aug Sep

Dai

ly d

eath

s



Figure 2b. Estimated cumulative deaths by age group

0

5

10

15

<5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 99Age group

Sha

re o

f cum

ulat

ive

deat

hs, %

Figure 3. Mean effective R on August 20, 2020. The estimate of effective R is based on the combined analysisof deaths, case reporting and hospitalizations where available. Current reported cases reflect infections 11-13days prior so estimates of effective R can only be made for the recent past. Effective R less than 1 meansthat transmission should decline all other things being held the same.

<0.85

0.85−0.88

0.89−0.91

0.92−0.95

0.96−0.99

1−1.03

1.04−1.07

1.08−1.1

1.11−1.14

>=1.15



Figure 4. Estimated percent infected with COVID-19 on August 31, 2020

<0.5

0.5−3.9

4−6.9

7−9.9

10−12.9

13−15.9

16−18.9

19−21.9

22−24.9

>=25

Figure 5. 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

40

50

Feb Mar Apr May Jun Jul Aug Sep

Per

cent

of i

nfec

tions

det

ecte

d

Republic of Korea Italy United Kingdom United States of America



Figure 6. Daily COVID-19 death rate per 1 million on August 31, 2020

<1

1 to 1.9

2 to 2.9

3 to 3.9

4 to 4.9

5 to 5.9

6 to 6.9

7 to 7.9

>=8


United States of America CRITICAL DRIVERS

Critical drivers

Table 2. Current mandate implementation

All

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All

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Trav

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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



Figure 7. 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


# of mandates

0

1

2

3

4

5

6

Mandate imposition timing



Figure 8a. Trend in mobility as measured through smartphone app use compared to January 2020 baseline

−80

−60

−40

−20

0

Jan Feb Mar Apr May Jun Jul Aug Sep

Per

cent

red

uctio

n fr

om a

vera

ge m

obili

ty


Figure 8b. Mobility level as measured through smartphone app use compared to January 2020 baseline(percent)

=<−50

−49 to −45

−44 to −40

−39 to −35

−34 to −30

−29 to −25

−24 to −20

−19 to −15

−14 to −10

>−10



Figure 9a. Trend in the proportion of the population reporting always wearing a mask when leaving home

0

20

40

60

80

Jan Feb Mar Apr May Jun Jul Aug Sep

Per

cent

of p

opul

atio

n


Figure 9b. Proportion of the population reporting always wearing a mask when leaving home on August 31,2020

<30%

30 to 34%

35 to 39%

40 to 44%

45 to 49%

50 to 54%

55 to 59%

60 to 64%

65 to 69%

>=70



Figure 10a. Trend in COVID-19 diagnostic tests per 100,000 people

0

50

100

150

200

250


Test

per

100

,000

pop

ulat

ion


Figure 10b. COVID-19 diagnostic tests per 100,000 people on August 30, 2020

<5

5 to 9.9

10 to 24.9

25 to 49

50 to 149

150 to 249

250 to 349

350 to 449

450 to 499

>=500



Figure 11. Increase in the risk of death due to pneumonia on February 1 compared to August 1

<−80%

−80 to −61%

−60 to −41%

−40 to −21%

−20 to −1%

0 to 19%

20 to 39%

40 to 59%

60 to 79%

>=80%


United States of America PROJECTIONS AND SCENARIOS

Projections and scenarios

Figure 12. Cumulative COVID-19 deaths until January 01, 2021 for three scenarios. The reference scenariois our forecast of what we think is most likely to happen. The mandate easing scenario is what would happenif governments continue to ease social distancing mandates. The universal mask mandate scenario is whatwould happen if mask use increased immediately to 95%.

0

200,000

400,000

600,000

0

100

200

300

400

500

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Cum

ulat

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hsC

umulative deaths per 100,000

Continued SD mandate easing

Reference scenario

Universal mask use

Fig 13. Daily COVID-19 deaths until January 01, 2021 for three scenarios. The reference scenario is ourforecast of what we think is most likely to happen. The mandate easing scenario is what would happen ifgovernments continue to ease social distancing mandates. The universal mask mandate scenario is whatwould happen if mask use increased immediately to 95%.

0

3,000

6,000

9,000

12,000

0

1

2

3


Dai

ly d

eath

sD

aily deaths per 100,000


Reference scenario

Universal mask use



Fig 14. Daily COVID-19 infections until January 01, 2021 for three scenarios. The reference scenario isour forecast of what we think is most likely to happen. The mandate easing scenario is what would happenif governments continue to ease social distancing mandates. The universal mask mandate scenario is whatwould happen if mask use increased immediately to 95%.

0

500,000

1,000,000

1,500,000

0

200

400


Dai

ly in

fect

ions

Daily infections per 100,000


Reference scenario

Universal mask use

Fig 15. Month of assumed mandate re-implementation. (Month when daily death rate passes 8 per million,when model assumes mandates will be re-imposed.)

September

October

November

DecemberNo mandates before Jan 1



Figure 16. Forecasted percent infected with COVID-19 on January 01, 2021

<0.5

0.5−3.9

4−6.9

7−9.9

10−12.9

13−15.9

16−18.9

19−21.9

22−24.9

>=25

Figure 17. Daily COVID-19 deaths per million forecasted on January 01, 2021 in the reference scenario

<1

1 to 1.9

2 to 2.9

3 to 3.9

4 to 4.9

5 to 5.9

6 to 6.9

7 to 7.9

>=8



Table 3. Ranking of COVID-19 among the leading causes of mortality in the full year 2020. Deaths fromCOVID-19 are projections of cumulative deaths on Jan 1, 2021 from the reference scenario. Deaths fromother causes are from the Global Burden of Disease study 2019 (rounded to the nearest 100).

Cause name Annual deaths RankingIschemic heart disease 557,600 1COVID-19 410,451 2Tracheal, bronchus, and lung cancer 206,200 3Chronic obstructive pulmonary disease 195,800 4Stroke 189,500 5Alzheimer’s disease and other dementias 143,900 6Chronic kidney disease 107,000 7Colon and rectum cancer 84,000 8Lower respiratory infections 81,900 9Diabetes mellitus 77,700 10

Mask data source: Premise; Facebook Global symptom survey (This research is based on survey resultsfrom University of Maryland Social Data Science Center); Kaiser Family Foundation; YouGov COVID-19Behaviour Tracker survey

A note of thanks:

We would like to extend a special thanks to the Pan American Health Organization (PAHO) for keydata sources; our partners and collaborators in Argentina, Brazil, Bolivia, Chile, Colombia, Cuba, theDominican Republic, Ecuador, Egypt, Honduras, Israel, Japan, Malaysia, Mexico, Moldova, Panama, Peru,the Philippines, Russia, Serbia, South Korea, Turkey, and Ukraine for their support and expert advice; andto the tireless data collection and collation efforts of individuals and institutions throughout the world.

In addition, we wish to express our gratitude for efforts to collect social distancing policy information inLatin America to University of Miami Institute for Advanced Study of the Americas (Felicia Knaul, MichaelTouchton), with data published here: http://observcovid.miami.edu/; Fundación Mexicana para la Salud(Héctor Arreola-Ornelas) with support from the GDS Services International: Tómatelo a Pecho A.C.; andCentro de Investigaciones en Ciencias de la Salud, Universidad Anáhuac (Héctor Arreola-Ornelas); Lab onResearch, Ethics, Aging and Community-Health at Tufts University (REACH Lab) and the University ofMiami Institute for Advanced Study of the Americas (Thalia Porteny).

Further, IHME is grateful to the Microsoft AI for Health program for their support in hosting our COVID-19data visualizations on the Azure Cloud. We would like to also extend a warm thank you to the many otherswho have made our COVID-19 estimation efforts possible.


http://observcovid.miami.edu/

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