Post on 21-Feb-2021
transcript
United States Model updates for October 22, 2020
covid.healthdata.org Institute for Health Metrics and Evaluation
In the last week, the increase in daily cases has become much clearer, and for the first time since early August, daily deaths have begun to rise. We believe that the fall/winter surge has begun, albeit several weeks behind the massive surge in Europe. The fall/winter surge will intensify in November and December, reaching a peak in January. Many states will face enormous pressure on hospital capacity and will likely have to re-impose some social distancing mandates. The best strategy to delay re-imposition of mandates and the associated economic hardship is to expand mask use.
Current situation
• Daily cases have increased to nearly 50,000 a day in the last week up from 45,000 a day last week (Figure 1).• Daily deaths are up to 710 a day in the last week an increase from 680 a day last week. This is the first increase
in daily deaths since early August (Figure 2).• Effective R – computed on the basis of cases, hospitalizations, and deaths – is over 1 in many Northern states,
but also in Nevada, Colorado, New Mexico, Kansas, Oklahoma, Mississippi and Alabama (Figure 3).• The daily death rate is over 4 per million in eight states spanning from Montana to Florida (Figure 6).
Trends in key drivers of transmission (mobility, mask use, testing, and seasonality)
• Social distancing mandates remain largely unchanged over the last week with the exception of re-imposition ofsome gathering restrictions in Pennsylvania (Figure 7). Only one social distancing mandate remains in place inFlorida, Idaho, Missouri, Oklahoma, and South Dakota.
• Mobility remains constant at the national level. Only California and Hawaii have levels that are less than 35% ofthe pre-COVID-19 baseline (Figure 8).
• Approximately two-thirds of Americans are wearing a mask outside the home, and this level has remainedconstant over the last two weeks (Figure 9). The lowest mask use rates are in Wyoming, North Dakota, andSouth Dakota.
• Testing rates continue to rise since the first week of September, which is likely due to both increasing numbersof individuals with symptoms seeking testing and mandatory testing in some workplaces and educationalfacilities (Figure 10).
Projections
• In our reference scenario – the scenario that we think is most likely to happen – we expect daily deaths to reachnearly 2,200 a day in mid-January (Figure 13).
• Cumulative deaths by February 1 in the reference scenario reach 386,000 (Figure 12).• The reference scenario assumes re-imposition of social distancing mandates when the daily death rate reaches 8
per million in many states beginning with Montana and North Dakota in October, six states in November, 13states in December, and five states in January (Figure 15).
• Expanding mask use to 95%, the level seen in Singapore, can greatly delay the imposition of mandates and save63,000 lives (Figure 12).
• Figure 18 compares our forecasts with other publicly archived models. The USC (SIKJalpha) model shows anincrease in death reaching a peak in mid-November. The Imperial model has nearly flat daily deaths through tomid-January. MIT (Delphi) and Los Alamos National Labs continue to forecast steady declines in daily deaths tolower levels. Given US cases and deaths have started to increase, we expect many of these other models torevise their forecasts up in the next 1–3 weeks.
United States Model updates for October 22, 2020
covid.healthdata.org Institute for Health Metrics and Evaluation
Model updates
• There are no major updates the modeling strategy this week. We continue to examine a wide range of datasources including infection-fatality rates calculated from seroprevalence surveys, hospital-fatality rates, andselect individual hospital record databases to determine whether the age-specific infection-fatality rate hasdeclined.
• We are elaborating our model to allow for including the impact of vaccination scale-up in the first and secondquarters of 2021.
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 SUMMARY OF FINDINGS
COVID-19 Results Briefing: United States o f America
Institute for Health Metrics and Evaluation (IHME)
October 22, 2020
This briefing contains summary i nformation on t he l atest projections f rom t he IHME model on COVID-19 in United States of America. The model was run on October 20, 2020.
Model updates
Updates to the model this week include additional data on deaths, cases, and updates on covariates.
Summary of findings
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
Feb Mar Apr May Jun Jul Aug Sep OctMonth
Cou
nt
Daily cases
covid19.healthdata.org 2 Institute for Health Metrics and Evaluation
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 4,962 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.
0
1,000
2,000
Feb Mar Apr May Jun Jul Aug Sep Oct
Dai
ly d
eath
s
covid19.healthdata.org 3 Institute for Health Metrics and Evaluation
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 08, 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.
<0.91
0.91−0.93
0.94−0.95
0.96−0.97
0.98−0.99
1−1.01
1.02−1.03
1.04−1.05
1.06−1.08
>=1.09
covid19.healthdata.org 4 Institute for Health Metrics and Evaluation
United States of America CURRENT SITUATION
Figure 4. Estimated percent of the population infected with COVID-19 on October 19, 2020
<1
1−3.9
4−6.9
7−10.4
10.5−13.4
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
covid19.healthdata.org 5 Institute for Health Metrics and Evaluation
United States of America CURRENT SITUATION
Figure 6. Daily COVID-19 death rate per 1 million on October 19, 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
covid19.healthdata.org 6 Institute for Health Metrics and Evaluation
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
covid19.healthdata.org 7 Institute for Health Metrics and Evaluation
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 Nov
# of mandates
0
1
2
3
4
5
6
7
Mandate imposition timing
covid19.healthdata.org 8 Institute for Health Metrics and Evaluation
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 Nov
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 19, 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
covid19.healthdata.org 9 Institute for Health Metrics and Evaluation
United States of America CRITICAL DRIVERS
Figure 9a. Trend in the proportion of the population reporting always wearing a mask when leaving home
0
25
50
75
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov
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 October19, 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
covid19.healthdata.org 10 Institute for Health Metrics and Evaluation
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 Nov
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 14, 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
covid19.healthdata.org 11 Institute for Health Metrics and Evaluation
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%
covid19.healthdata.org 12 Institute for Health Metrics and Evaluation
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
hsC
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
covid19.healthdata.org 13 Institute for Health Metrics and Evaluation
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
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
covid19.healthdata.org 14 Institute for Health Metrics and Evaluation
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
covid19.healthdata.org 15 Institute for Health Metrics and Evaluation
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
7−10.4
10.5−13.4
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
covid19.healthdata.org 16 Institute for Health Metrics and Evaluation
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
Nov Dec Jan FebDate
Dai
ly d
eath
s
Models
IHME
Delphi
Imperial
LANL
SIKJalpha
YYG
covid19.healthdata.org 17 Institute for Health Metrics and Evaluation
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-19 318,735 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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