Current situation Trends in key drivers of transmission (mobility, … · 2020. 10. 15. ·...
Transcript of Current situation Trends in key drivers of transmission (mobility, … · 2020. 10. 15. ·...
United States Model updates for October 15, 2020
covid.healthdata.org Institute for Health Metrics and Evaluation
Daily cases have begun to increase and transmission has intensified in the northern half of the United States. We expect deaths to stop declining and begin increasing in the next 1–2 weeks. The winter surge appears to have begun somewhat later than the surge in Europe. Daily deaths will reach over 2,000 a day in January even with many states re-imposing mandates before the end of the year. Expanding mask use remains the best strategy to delay and reduce the magnitude of the surge.
Current situation
• Daily cases now appear to be rising, reaching 45,000 a day, up from 40,000 last week (Figure 1). • Despite the increase in cases, deaths have remained constant at 680 a day (Figure 2). • Effective R computed based on cases, hospitalizations, and deaths is above 1 across most of the northern half of
the continental states, representing a larger range of states than last week (Figure 3). • The daily death rate is over 4 per million in North Dakota, South Dakota, Arkansas, Tennessee, and Florida
(Figure 6). North Dakota presently has one of the highest COVID-19 death rates in the world.
Trends in key drivers of transmission (mobility, mask use, testing, and seasonality)
• Florida and Indiana removed any business closures; all other mandates remained the same (Figure 7). • Mobility in the last week has remained constant. The vast majority of states, including many with effective R
over 1, have mobility levels within 10% of the pre-COVID-19 baseline (Figure 8). • Mask use has remained constant over the last week. North Dakota and South Dakota, with the highest death
rates in the country, have the lowest mask use (Figure 9). • Diagnostic tests continue to increase slowly (Figure 10).
Projections
• Daily deaths in our reference scenario, the scenario that we think is most likely to occur, will peak in mid-January due to the winter surge at around 2,200 a day (Figure 13).
• Cumulative deaths by February 1 are expected to reach 389,000 (Figure 12). • Increasing mask use from 69%, the current US average, to 95%, the level seen in Singapore, could save 74,000
lives (Figure 12). • We expect in the reference scenario that many Midwestern states will have to re-impose mandates before the
end of this year (Figure 15). • Figure 18 compares our model forecasts to other publicly archived forecasts. While this week our forecasts have
not changed substantially, other models have revised their forecasts up substantially. The USC (SIKJalpha) model now shows a winter surge, but substantially smaller than in our model. The Imperial forecasts have not been revised upward but still show declines through into January in daily deaths. The MIT (Delphi) model has also been revised upward but still suggests a steady decline into mid-December. The Los Alamos National Labs model continues to show a brisk decline in daily deaths through to the end of November.
Model updates
There are no major updates to our model this week. We continue to search for evidence on whether the infection-fatality rate (IFR) has changed during the pandemic. There is a clear shift to younger ages in diagnosed cases. This shift alone would – because of the age dependence of the IFR – reduce the all-age IFR even if treatments have not improved. However, the shift in the age distribution of confirmed cases may be due to the scale-up in testing capacity. Analysis underway of data on individual clinical treatments and outcomes may provide a more direct measure of whether the IFR
United States Model updates for October 15, 2020
covid.healthdata.org Institute for Health Metrics and Evaluation
by age has changed. If the IFR has declined, this would alter our forecasted death rates; to date, however, we have not been able to find sufficient evidence to support this change to our model.
IHME wishes to warmly acknowledge the support of these and others who have made our COVID-19 estimation efforts possible. Thank you.
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.
United States of America MODEL UPDATES
COVID-19 Results Briefing: United States of America
Institute for Health Metrics and Evaluation (IHME)
October 15, 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 October 13, 2020.
Model updates
Updates to the model this week include additional data on deaths, cases, and updates on covariates.
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United States of America CURRENT SITUATION
Current situation
Figure 1. Reported daily COVID-19 cases
0
20,000
40,000
60,000
Feb Mar Apr May Jun Jul Aug Sep OctMonth
Cou
nt
Daily cases
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United States of America CURRENT SITUATION
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 4,771 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. Points shown are reporteddeaths, line and ribbon represent estimate with uncertainty.
0
1,000
2,000
Feb Mar Apr May Jun Jul Aug Sep Oct
Dai
ly d
eath
s
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United States of America CURRENT SITUATION
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 October 01, 2020. The estimate of effective R is based on the combinedanalysis of deaths, case reporting and hospitalizations where available. Current reported cases reflect infections11-13 days prior so estimates of effective R can only be made for the recent past. Effective R less than 1means that transmission should decline all other things being held the same.
<0.85
0.85−0.88
0.89−0.92
0.93−0.95
0.96−0.99
1−1.03
1.04−1.06
1.07−1.1
1.11−1.14
>=1.15
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United States of America CURRENT SITUATION
Figure 4. Estimated percent of the population infected with COVID-19 on October 12, 2020
<1
1−3.9
4−6.9
7−9.9
10−13.4
13.5−16.4
16.5−19.4
19.5−22.4
22.5−25.4
>=25.5
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 disease transmission model.
0
20
40
Mar Apr May Jun Jul Aug Sep Oct
Per
cent
of i
nfec
tions
det
ecte
d
Republic of Korea Germany Italy United Kingdom United States of America
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United States of America CURRENT SITUATION
Figure 6. Daily COVID-19 death rate per 1 million on October 12, 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
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United States of America CRITICAL DRIVERS
Critical drivers
Table 2. Current mandate implementation
All
gath
erin
gs r
estr
icte
d
All
none
ssen
tial b
usin
esse
s cl
osed
Any
bus
ines
ses
rest
ricte
d
Mas
k us
e
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
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United States of America CRITICAL DRIVERS
Figure 7. Total number of social distancing mandates (including mask use)
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 Sep Oct
# of mandates
0
1
2
3
4
5
6
7
Mandate imposition timing
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United States of America CRITICAL DRIVERS
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 Oct
Per
cent
red
uctio
n fr
om a
vera
ge m
obili
ty
Republic of Korea Germany Italy United Kingdom United States of America
Figure 8b. Mobility level as measured through smartphone app use compared to January 2020 baseline(percent) on October 12, 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
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United States of America CRITICAL DRIVERS
Figure 9a. Trend in the proportion of the population reporting always wearing a mask when leaving home
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25
50
75
Jan Feb Mar Apr May Jun Jul Aug Sep Oct
Per
cent
of p
opul
atio
n
Republic of Korea Germany Italy United Kingdom United States of America
Figure 9b. Proportion of the population reporting always wearing a mask when leaving home on October12, 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
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United States of America CRITICAL DRIVERS
Figure 10a. Trend in COVID-19 diagnostic tests per 100,000 people
0
100
200
300
Jan Feb Mar Apr May Jun Jul Aug Sep Oct
Test
per
100
,000
pop
ulat
ion
Republic of Korea Germany Italy United Kingdom United States of America
Figure 10b. COVID-19 diagnostic tests per 100,000 people on October 07, 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
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United States of America CRITICAL DRIVERS
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%
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United States of America PROJECTIONS AND SCENARIOS
Projections and scenarios
We produce three scenarios when projecting COVID-19. The reference scenario is our forecast of what wethink is most likely to happen. We assume that if the daily mortality rate from COVID-19 reaches 8 permillion, social distancing (SD) mandates will be re-imposed. The mandate easing scenario is what wouldhappen if governments continue to ease social distancing mandates with no re-imposition. The universal maskmandate scenario is what would happen if mask use increased immediately to 95% and social distancingmandates were re-imposed at 8 deaths per million.
Figure 12. Cumulative COVID-19 deaths until February 01, 2021 for three scenarios.
0
100,000
200,000
300,000
400,000
500,000
0
50
100
150
Feb Apr Jun Aug Oct Dec Feb
Cum
ulat
ive
deat
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umulative deaths per 100,000
Continued SD mandate easing
Reference scenario
Universal mask use
Fig 13. Daily COVID-19 deaths until February 01, 2021 for three scenarios.
0
2,000
4,000
0.0
0.5
1.0
1.5
Feb Apr Jun Aug Oct Dec Feb
Dai
ly d
eath
sD
aily deaths per 100,000
Continued SD mandate easing
Reference scenario
Universal mask use
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United States of America PROJECTIONS AND SCENARIOS
Fig 14. Daily COVID-19 infections until February 01, 2021 for three scenarios.
0
200,000
400,000
600,000
800,000
0
50
100
150
200
Feb Apr Jun Aug Oct Dec Feb
Dai
ly in
fect
ions
Daily infections per 100,000
Continued SD mandate easing
Reference scenario
Universal mask use
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United States of America PROJECTIONS AND SCENARIOS
Fig 15. Month of assumed mandate re-implementation. (Month when daily death rate passes 8 per million,when reference scenario model assumes mandates will be re-imposed.)
October
November
December
JanuaryNo mandates before Feb 1
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United States of America PROJECTIONS AND SCENARIOS
Figure 16. Forecasted percent infected with COVID-19 on February 01, 2021
<1
1−3.9
4−6.9
7−9.9
10−13.4
13.5−16.4
16.5−19.4
19.5−22.4
22.5−25.4
>=25.5
Figure 17. Daily COVID-19 deaths per million forecasted on February 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
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United States of America PROJECTIONS AND SCENARIOS
Figure 18. 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 avail-able: 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/), the SI-KJalpha model from the University of Southern Cal-ifornia (SIKJalpha; https://github.com/scc-usc/ReCOVER-COVID-19), and Youyang Gu (YYG; https://covid19-projections.com/). Daily deaths from other modeling groups are smoothed to remove inconsistencieswith rounding. Regional values are aggregates from availble locations in that region.
500
1,000
1,500
2,000
2,500
Nov Dec Jan FebDate
Dai
ly d
eath
s
Models
IHME
Delphi
Imperial
LANL
SIKJalpha
YYG
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United States of America PROJECTIONS AND SCENARIOS
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-19 316,935 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) and the Facebook United States symptom survey(in collaboration with Carnegie Mellon University); Kaiser Family Foundation; YouGov COVID-19 BehaviourTracker 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.
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