COVID-19ResultsBrieﬁng · 12/23/2020 · Oct 20 Nov 20 Dec 20 Jan 21 Feb 21 Mar 21 Apr 21...

Utah COVID-19 RESULTS BRIEFING

COVID-19 Results Briefing

Utah

December 23, 2020

This document contains summary information on the latest projections from the IHME model on COVID-19in Utah. The model was run on December 22, 2020 with data through December 20, 2020.

Current situation

• Daily reported cases in the last week decreased to 2,600 per day on average compared to 2,700 the weekbefore (Figure 1).

• Daily deaths in the last week increased to 20 per day on average compared to 10 the week before (Figure2). This makes COVID-19 the number 1 cause of death in Utah this week (Table 1).

• Effective R, computed using cases, hospitalizations, and deaths, is greater than 1 in 31 states (Figure3). The Effective R in Utah on December 9 was 1.04.

• We estimated that 12% of people in Utah have been infected as of December 20 (Figure 4).• The daily death rate is greater than 4 per million in 46 states (Figure 6).

Trends in drivers of transmission

• In the last week, new mandates have been imposed in Indiana, Pennsylvania, Washington. Mandateshave been lifted in Alaska, Minnesota, Utah (Table 2).

• Mobility last week was 24% lower than the pre-COVID-19 baseline (Figure 8). Mobility was nearbaseline (within 10%) in Alabama, Mississippi, Nebraska, South Dakota, and Wyoming. Mobility waslower than 30% of baseline in in 12 states.

• As of December 20 we estimated that 75% of people always wore a mask when leaving their homecompared to 74% last week (Figure 9). Mask use was lower than 50% in no locations.

• There were 261 diagnostic tests per 100,000 people on December 20 (Figure 10).• In Utah 50.6% of people say they would accept a vaccine for COVID-19 and 24.6% say they are unsure

if they would accept one. The fraction of the population who are open to receiving a COVID-19 vaccineranges from 66% in Mississippi to 83% in Virginia (Figure 12).

• We expect that 1,593,500 will be vaccinated by April 1 (Figure 13). With faster scale-up, the numbervaccinated could reach 1,593,500.

Projections

• In our reference scenario, which represents what we think is most likely to happen, our model projects3,000 cumulative deaths on April 1, 2021. This represents 2,000 additional deaths from December 20 toApril 1 (Figure 14). Daily deaths will peak at 30 on January 21, 2021 (Figure 15).

• By April 1, 2021, we project that 100 lives will be saved by the projected vaccine rollout. If rapidrollout of vaccine is achieved, 200 lives will be saved compared to a no vaccine scenario. As compared toa no vaccine scenario, rapid rollout targeting high-risk individuals only could save 200 lives (Figure 14).

• If universal mask coverage (95%) were attained in the next week, our model projects 0 fewercumulative deaths compared to the reference scenario on April 1, 2021 (Figure 14).

• Under our mandates easing scenario, our model projects 4,000 cumulative deaths on April 1, 2021(Figure 14).

• We estimate that 53.3% of people will still be susceptible on April 1, 2021 (Figure 17).• The reference scenario assumes that 49 states will re-impose mandates by April 1, 2021 (Figure 18).

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

Utah COVID-19 RESULTS BRIEFING

• Figure 21 compares our reference scenario forecasts to other publicly archived models. Forecasts arewidely divergent.

• At some point from December through April 1, 47 states will have high or extreme stress on hospitalbeds (Figure 22). At some point from December through April 1, 48 states will have high or extremestress on ICU capacity (Figure 23).

Model updates

Methods have not been changed in this week’s update. However, vaccination scale-up has been modifiedto reflect the revised timing of expected approvals and new purchase agreements announced for the Pfizer,Moderna, and Astra-Zeneca vaccines in the EU, Mexico, China, and Malaysia.


Utah CURRENT SITUATION

Current situation

Figure 1. Reported daily COVID-19 cases

0

2,000

4,000

Mar 20 Apr 20 May 20 Jun 20 Jul 20 Aug 20 Sep 20 Oct 20 Nov 20 Dec 20 Jan 21Month

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 RankingCOVID-19 107 1Ischemic heart disease 57 2Stroke 25 3Chronic obstructive pulmonary disease 23 4Tracheal, bronchus, and lung cancer 15 5Chronic kidney disease 14 6Drug use disorders 13 7Diabetes mellitus 13 8Self-harm 12 9Lower respiratory infections 11 10

Figure 2a. Reported daily COVID-19 deaths

0

10

20

30

Mar 20 Apr 20 May 20 Jun 20 Jul 20 Aug 20 Sep 20 Oct 20 Nov 20 Dec 20 Jan 21

Dai

ly d

eath

s



Figure 2b. Estimated cumulative 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 99Age group

Sha

re o

f cum

ulat

ive

deat

hs, %

Figure 3. Mean effective R on December 09, 2020. The estimate of effective R is based on the combinedanalysis of deaths, case reporting, and hospitalizations where available. Current reported cases reflectinfections 11-13 days prior, so estimates of effective R can only be made for the recent past. Effective R lessthan 1 means that transmission should decline, all other things being held the same.

<0.92

0.92−0.93

0.94−0.95

0.96−0.97

0.98−0.99

1−1.01

1.02−1.03

1.04−1.05

1.06−1.07

>=1.08



Figure 4. Estimated percent of the population infected with COVID-19 on December 20, 2020

<5

5−9.9

10−14.9

15−19.9

20−24.9

25−29.9

30−34.9

>=35

Figure 5. Percent of COVID-19 infections detected. This is estimated as the ratio of reported dailyCOVID-19 cases to estimated daily COVID-19 infections based on the SEIR disease transmission model.

0

20

40

60

Mar 20 Apr 20 May 20 Jun 20 Jul 20 Aug 20 Sep 20 Oct 20 Nov 20 Dec 20 Jan 21

Per

cent

of i

nfec

tions

det

ecte

d

California Florida New York Texas Utah



Figure 6. Daily COVID-19 death rate per 1 million on December 20, 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


Utah CRITICAL DRIVERS

Critical drivers

Table 2. Current mandate implementation

Prim

ary

scho

ol c

losu

re

Sec

onda

ry s

choo

l clo

sure

Hig

her

scho

ol c

losu

re

Bor

ders

clo

sed

to a

ny n

on−

resi

dent

Bor

ders

clo

sed

to a

ll no

n−re

side

nts

Indi

vidu

al m

ovem

ents

res

tric

ted

Cur

few

for

busi

ness

es

Indi

vidu

al c

urfe

w

Gat

herin

g lim

it: 6

indo

or, 1

0 ou

tdoo

r

Gat

herin

g lim

it: 1

0 in

door

, 25

outd

oor

Gat

herin

g lim

it: 2

5 in

door

, 50

outd

oor

Gat

herin

g lim

it: 5

0 in

door

, 100

out

door

Gat

herin

g lim

it: 1

00 in

door

, 250

out

door

Res

taur

ants

clo

sed

Bar

s cl

osed

Res

taur

ants

/ ba

rs c

lose

d

Res

taur

ants

/ ba

rs c

urbs

ide

only

Gym

s, p

ools

, oth

er le

isur

e cl

osed

Non

−es

sent

ial r

etai

l clo

sed

Non

−es

sent

ial r

etai

l cur

bsid

e on

ly

Non

−es

sent

ial w

orkp

lace

s cl

osed

Sta

y ho

me

orde

r

Sta

y ho

me

fine

Mas

k m

anda

te

Mas

k m

anda

te fi

ne

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

Mandate in place (imposed this week)

No mandate

No mandate (lifted this week)

*Not all locations are measured at the subnational level.



Figure 7. Total number of social distancing mandates (including mask use)

WyomingWisconsin

West VirginiaWashington

VirginiaVermont

UtahTexas

TennesseeSouth Dakota

South CarolinaRhode IslandPennsylvania

OregonOklahoma

OhioNorth Dakota



New HampshireNevada




MarylandMaine

LouisianaKentucky

KansasIowa



District of ColumbiaDelaware

ConnecticutColoradoCaliforniaArkansas

ArizonaAlaska

Alabama

Mar

20

Apr 2

0

May

20

Jun

20

Jul 2

0

Aug 2

0

Sep 2

0

Oct 20

Nov 2

0

Dec 2

0

Jan

21

# of mandates

0

1−5

6−10

11−15

16−20

20−25

Mandate imposition timing



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

−50

−25

0

Jan 20 Feb 20 Mar 20 Apr 20 May 20 Jun 20 Jul 20 Aug 20 Sep 20 Oct 20 Nov 20 Dec 20 Jan 21

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) on December 20, 2020

=<−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 8c. Trend in visits to restaurants as measured through cell phone data compared to 2019 average

WYWI

WVWAVAVTUTTXTNSDSCRIPA

OROKOHNDNCNYNMNJNHNVNEMTMOMSMNMI

MAMDMELAKYKSIAINILIDHI

GAFLDCDECTCOCAARAZAKAL

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

% of 2019 mean

1.2+

(1,1.2]

(0.8,1]

(0.6,0.8]

(0.4,0.6]

(0.2,0.4]

(0,0.2]

Figure 8d. Trend in visits to bars as measured through cell phone data compared to 2019 average

WYWI






% of 2019 mean

1.2+

(1,1.2]

(0.8,1]

(0.6,0.8]

(0.4,0.6]

(0.2,0.4]

(0,0.2]



Figure 8e. Trend in visits to elementary & secondary schools as measured through cell phone data comparedto 2019 average

WYWI






% of 2019 mean

1.2+

(1,1.2]

(0.8,1]

(0.6,0.8]

(0.4,0.6]

(0.2,0.4]

(0,0.2]

Figure 8f. Trend in visits to department stores as measured through cell phone data compared to 2019average

WYWI






% of 2019 mean

1.2+

(1,1.2]

(0.8,1]

(0.6,0.8]

(0.4,0.6]

(0.2,0.4]

(0,0.2]



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

0

20

40

60

80


Per

cent

of p

opul

atio

n


Figure 9b. Proportion of the population reporting always wearing a mask when leaving home on December20, 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

250

500

750

1000


Test

per

100

,000

pop

ulat

ion


Figure 10b. COVID-19 diagnostic tests per 100,000 people on December 16, 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 2020 compared to August 1 2020

<−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%



Figure 12. This figure shows the estimated proportion of the adult (18+) population that is open toreceiving a COVID-19 vaccine based on Facebook survey responses

<50%

50−59%

60−69%

70−74%

75−79%

80−84%

>85%

Figure 13. The number of people who receive any vaccine and those that are immune accounting for efficacy,loss to follow up for 2 dose vaccines, and a 28 day delay between first dose and immunity for 2 dose vaccines.

0

500,000

1,000,000

1,500,000

0

20

40

60

Dec 2

0

Jan

21

Feb

21

Mar

21

Apr 2

1

Peo

ple

Percent of adult population

Reference rollout Rapid rollout

Solid lines represent the total vaccine doses, dashed lines represent effective vaccination


Utah PROJECTIONS AND SCENARIOS

Projections and scenarios

We produce six scenarios when projecting COVID-19. The reference scenario is our forecast of what we thinkis most likely to happen. We assume that if the daily mortality rate from COVID-19 reaches 8 per million,social distancing (SD) mandates will be re-imposed. The mandate easing scenario is what would happen ifgovernments continue to ease social distancing mandates with no re-imposition. The universal mask mandatescenario is what would happen if mask use increased immediately to 95% and social distancing mandateswere re-imposed at 8 deaths per million. These three scenarios assume our reference vaccine delivery scale upwhere vaccine delivery will scale to full capacity over 90 days.

The rapid vaccine rollout scenario assumes that vaccine distribution will scale up to full delivery capacity inhalf the time as the reference delivery scenario and that the maximum doses that can be delivered per day istwice as much as the reference delivery scenario. The rapid vaccine rollout to high-risk populations scenariois the same but high-risk populations are vaccinated before essential workers or other adults. The no vaccinescenario is the same as our reference scenario but with no vaccine use.



Figure 14. Cumulative COVID-19 deaths until April 01, 2021 for six scenarios

0

1,000

2,000

3,000

4,000

0

25

50

75

100

125

Oct 20 Nov 20 Dec 20 Jan 21 Feb 21 Mar 21 Apr 21

Cum

ulat

ive

deat

hsC

umulative deaths per 100,000

Reference scenario

Universal mask use

Continued SD mandate easing

Rapid rollout

Rapid rollout to high−risk

No vaccine

Figure 15. Daily COVID-19 deaths until April 01, 2021 for six scenarios

0

10

20

30

0.0

0.3

0.6

0.9

Feb 20 Apr 20 Jun 20 Aug 20 Oct 20 Dec 20 Feb 21 Apr 21

Dai

ly d

eath

sD

aily deaths per 100,000

Reference scenario

Universal mask use


Rapid rollout


No vaccine



Figure 16. Daily COVID-19 infections until April 01, 2021 for six scenarios

0

2,500

5,000

7,500

10,000

0

100

200

300

Feb 20 Apr 20 Jun 20 Aug 20 Oct 20 Dec 20 Feb 21 Apr 21

Dai

ly in

fect

ions

Daily infections per 100,000

Reference scenario

Universal mask use


Rapid rollout


No vaccine

Figure 17. Susceptible population, accounting for infections and people immune through vaccination

0

1,000,000

2,000,000

3,000,000

0

25

50

75

100

Oct 20 Nov 20 Dec 20 Jan 21 Feb 21 Mar 21 Apr 21

Peo

ple

susc

eptib

leP

ercent susceptible

Reference scenario

Universal mask use


Rapid rollout


No vaccine



Figure 18. Month of assumed mandate re-implementation. (Month when daily death rate passes 8 permillion, when reference scenario model assumes mandates will be re-imposed.)

December 2020

January 2021

February 2021

March 2021No mandates before April 1 2021



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

<5

5−9.9

10−14.9

15−19.9

20−24.9

25−29.9

30−34.9

35−39.9

>=40

Figure 20. Daily COVID-19 deaths per million forecasted on April 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



Figure 21. Comparison of reference model projections with other COVID modeling groups. For thiscomparison, we are including projections of daily COVID-19 deaths from other modeling groups when available:Delphi from the Massachussets Institute of Technology (Delphi; https://www.covidanalytics.io/home),Imperial College London (Imperial; https://www.covidsim.org), The Los Alamos National Laboratory (LANL;https://covid-19.bsvgateway.org/), and the SI-KJalpha model from the University of Southern California(SIKJalpha; https://github.com/scc-usc/ReCOVER-COVID-19). Daily deaths from other modeling groupsare smoothed to remove inconsistencies with rounding. Regional values are aggregates from availble locationsin that region.

0

10

20

Jan 21 Feb 21 Mar 21 Apr 21Date

Dai

ly d

eath

s

Models

IHME

Delphi

LANL

SIKJalpha


https://www.covidanalytics.io/home

https://www.covidsim.org

https://covid-19.bsvgateway.org/

https://github.com/scc-usc/ReCOVER-COVID-19


Figure 22. The estimated inpatient hospital usage is shown over time. The percent of hospital beds occupiedby COVID-19 patients is color coded based on observed quantiles of the maximum proportion of beds occupiedby COVID-19 patients. Less than 5% is considered low stress, 5-9% is considered moderate stress, 10-19% isconsidered high stress, and greater than 20% is considered extreme stress.

WyomingWisconsin

West VirginiaWashington, DC

WashingtonVirginia

VermontUtah

TexasTennessee

South DakotaSouth Carolina

Rhode IslandPennsylvania

OregonOklahoma

OhioNorth Dakota



New HampshireNevada




MarylandMaine

LouisianaKentucky

KansasIowa



DelawareConnecticut

ColoradoCaliforniaArkansas

ArizonaAlaska

Alabama

Apr 20 Jun 20 Aug 20 Oct 20 Dec 20 Feb 21 Apr 21

Stress level

Low

Moderate

High

Extreme

All hospital beds



Figure 23. The estimated intensive care unit (ICU) usage is shown over time. The percent of ICU bedsoccupied by COVID-19 patients is color coded based on observed quantiles of the maximum proportion ofICU beds occupied by COVID-19 patients. Less than 10% is considered low stress, 10-29% is consideredmoderate stress, 30-59% is considered high stress, and greater than 60% is considered extreme stress.

WyomingWisconsin

West VirginiaWashington, DC

WashingtonVirginia

VermontUtah

TexasTennessee

South DakotaSouth Carolina

Rhode IslandPennsylvania

OregonOklahoma

OhioNorth Dakota



New HampshireNevada




MarylandMaine

LouisianaKentucky

KansasIowa



DelawareConnecticut

ColoradoCaliforniaArkansas

ArizonaAlaska

Alabama

Apr 20 Jun 20 Aug 20 Oct 20 Dec 20 Feb 21 Apr 21

Stress level

Low

Moderate

High

Extreme

Intensive care unit beds



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 3,000 1COVID-19 1,364 2Stroke 1,300 3Chronic obstructive pulmonary disease 1,200 4Tracheal, bronchus, and lung cancer 800 5Chronic kidney disease 700 6Drug use disorders 700 7Diabetes mellitus 700 8Self-harm 600 9Lower respiratory infections 600 10


Utah MORE INFORMATION

More information

Data sources:

Mask use data sources include PREMISE; Facebook Global symptom survey (This research is based onsurvey results from University of Maryland Social Data Science Center) and the Facebook United Statessymptom survey (in collaboration with Carnegie Mellon University); Kaiser Family Foundation; YouGovCOVID-19 Behaviour Tracker survey.

Vaccine hesitancy data are from the COVID-19 Beliefs, Behaviors, and Norms Study, a survey conducted onFacebook by the Massachusetts Institute of Technology (https://covidsurvey.mit.edu/).

Data on vaccine candidates, stages of development, manufacturing capacity, and pre-purchasing agreementsare primarily from Linksbridge and supplemented by Duke University.

A note of thanks:

We wish to warmly acknowledge the support of these and others who have made our covid-19 estimationefforts possible.

More information:

For all COVID-19 resources at IHME, visit http://www.healthdata.org/covid.

Questions? Requests? Feedback? Please contact us at https://www.healthdata.org/covid/contact-us.


https://covidsurvey.mit.edu/

https://www.healthdata.org/covid/acknowledgements

http://www.healthdata.org/covid

https://www.healthdata.org/covid/contact-us

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