current situation2020/10/29 · iran model updates for october 29, 2020 covid.healthdata.org...

Iran Model updates for October 29, 2020

covid.healthdata.org Institute for Health Metrics and Evaluation

IHME’s latest COVID-19 forecasts indicate that Iran will reach about 81,900 deaths by February 1, 2021. If mask wearing in public increases to 95%, there will be around 68,000 deaths, and about 13,900 lives could be saved.

Current situation

• COVID-19 transmission as captured by reported cases has been increasing and is now at its highest levels since the start of the pandemic (Figure 1). Deaths have increased since the beginning of September and are now higher than the peak level in the beginning of July; the number of daily deaths is over 300 a day now (Figure 2a).

• Examination of effective R (the number of new infections caused by each infection) on October 15, based on the combined analysis of data on cases, hospitalizations, and deaths, is over 1, which suggests that transmission is increasing in Iran (Figure 3).

• The percentage of the population infected with COVID-19 is still very low, at about 14% on October 26. This means that most Iranians are still susceptible to this virus (Figure 4).

• The fraction of infections being detected has declined in the past two months; the fraction of infections detected and reported as confirmed cases is about 4% (Figure 5).

• The daily death rate on October 26 is about 3.5 deaths per 100,000 people per day (Figure 6).

Trends in key drivers of transmission (mobility, mask use, testing, and seasonality)

• Social distancing mandates have stayed relatively constant over the last month (Table 2 and Figure 7). • Mobility measured by app use on smartphones, including Android and Apple iOS, has increased slightly in the

past week. Mobility is now about 8% less than the baseline in January (Figure 8b). • Despite mask mandates in Iran, mask use has remained the same in the past month at about 50% on October 26

(Figure 9a). • COVID-19 testing rates have declined in the past month and slightly increased the last week. The rate is now

about 35 per 100,000 (Figure 10a). • The risk of getting sick from pneumonia on August 1 compared with that on February 1 is about 70% higher

(Figure 11). Since pneumonia seasonality is strongly associated with COVID-19, we are expecting a surge of cases and deaths in the coming months.

Projections

• Our estimate of cumulative deaths for Iran has increased from about 80,000 deaths from our projections last week to about 81,900 deaths by February 1, 2021. As of today, about 34,000 COVID-19 deaths have occurred in Iran, and our estimates suggest about 47,900 deaths from now until February 1 (Figure 12).

• If a herd immunity strategy is pursued, we estimate 110,000 deaths in the country by February 1 (Figure 12). • We expect that the daily death rate will start increasing in the coming months and will peak in mid-December at

about 825 per day (Figure 13). • These forecasts assume that countries will on average re-impose a package of social distancing mandates when

the daily death rate reaches 8 per million. Our current projections show that Iran will re-impose mandates in December (Figure 15).

• If mask use were increased to 95%, the level observed in Singapore and several countries in Latin America, the projected number of deaths would be nearly 68,000 deaths, and about 13,900 lives could be saved. This is about a 29% reduction in the number of deaths expected between now and February 1 (Figures 12 and 13).

Iran Model updates for October 29, 2020

covid.healthdata.org Institute for Health Metrics and Evaluation

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.

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

http://www.healthdata.org/covid

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

Iran (Islamic Republic of) MODEL OVERVIEW

COVID-19 Results Briefing: Iran (Islamic Republic of)

Institute for Health Metrics and Evaluation (IHME)

October 29, 2020

This briefing contains summary information on the latest projections from the IHME model on COVID-19 inIran (Islamic Republic of). The model was run on October 28, 2020.

For more information on the model, including interactive visualizations, downloadable results, and modeldetails, please visit our site covid19.healthdata.org.

Model Overview

Updates to the model this week include additional data on deaths, cases, and updates on covariates.

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

https://covid19.healthdata.org/global

Iran (Islamic Republic of) CURRENT SITUATION

Current situation

Figure 1. Reported daily COVID-19 cases

0

1,000

2,000

3,000

4,000

5,000

Mar Apr May Jun Jul Aug Sep Oct NovMonth

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 2,156 1Ischemic heart disease 1,977 2Stroke 787 3Road injuries 406 4Hypertensive heart disease 355 5Diabetes mellitus 283 6Alzheimer’s disease and other dementias 268 7Chronic obstructive pulmonary disease 241 8Chronic kidney disease 241 9Stomach cancer 211 10

Figure 2a. Reported daily COVID-19 deaths.

0

100

200

300

Mar Apr May Jun Jul Aug Sep Oct Nov

Dai

ly d

eath

s



Figure 2b. Estimated cumulative deaths by age group

0.0

2.5

5.0

7.5

10.0

12.5

<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 15, 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.

<0.9

0.9−0.92

0.93−0.94

0.95−0.97

0.98−0.99

1−1.01

1.02−1.04

1.05−1.06

1.07−1.09

>=1.1



Figure 4. Estimated percent of the population infected with COVID-19 on October 26, 2020

<0.5

0.5−2.9

3−4.9

5−7.4

7.5−9.4

9.5−11.9

12−13.9

14−16.4

16.5−18.9

>=19

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

2

4

6

Mar Apr May Jun Jul Aug Sep Oct Nov

Per

cent

of i

nfec

tions

det

ecte

d

Egypt Iran (Islamic Republic of) Iraq Pakistan Sudan



Figure 6. Daily COVID-19 death rate per 1 million on October 26, 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


Iran (Islamic Republic of) CRITICAL DRIVERS

Critical drivers

Table 2. Current mandate implementation

All

none

ssen

tial b

usin

esse

s cl

osed

Any

bus

ines

ses

rest

ricte

d

Any

gat

herin

gs r

estr

icte

d

Mas

k us

e

Sch

ool c

losu

re

Sta

y ho

me

orde

r

Trav

el li

mits

Yemen

United Arab Emirates

Tunisia

Syrian Arab Republic

Sudan

Somalia

Saudi Arabia

Qatar

Palestine

Pakistan

Oman

Morocco

Libya

Lebanon

Kuwait

Jordan

Iraq

Iran (Islamic Republic of)

Egypt

Djibouti

Bahrain

Afghanistan

Mandate in place No mandate



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

YemenUnited Arab Emirates

TunisiaSyrian Arab Republic

SudanSomalia

Saudi ArabiaQatar

PalestinePakistan

OmanMorocco

LibyaLebanon

KuwaitJordan

IraqIran (Islamic Republic of)

EgyptDjiboutiBahrain

Afghanistan

Feb Mar Apr May Jun Jul Aug Sep Oct Nov

# of mandates

0

1

2

3

4

5

6

7

Mandate imposition timing



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

−60

−40

−20

0

20

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov

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 October 26, 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 9a. Trend in the proportion of the population reporting always wearing a mask when leaving home

0

20

40


Per

cent

of p

opul

atio

n


Figure 9b. Proportion of the population reporting always wearing a mask when leaving home on October26, 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

20

40


Test

per

100

,000

pop

ulat

ion


Figure 10b. COVID-19 diagnostic tests per 100,000 people on October 23, 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%


Iran (Islamic Republic of) 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

30,000

60,000

90,000

0

50

100

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

300

600

900

0.0

0.5

1.0


Dai

ly d

eath

sD

aily deaths per 100,000


Reference scenario

Universal mask use



Fig 14. Daily COVID-19 infections until February 01, 2021 for three scenarios.

0

100,000

200,000

300,000

0

100

200

300

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 reference scenario model assumes mandates will be re-imposed.)

October

November

December

JanuaryNo mandates before Feb 1



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

<0.5

0.5−2.9

3−4.9

5−7.4

7.5−9.4

9.5−11.9

12−13.9

14−16.4

16.5−18.9

>=19

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



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.

0

500

1,000

1,500

2,000

Nov Dec Jan FebDate

Dai

ly d

eath

s

Models

IHME

Delphi

Imperial

LANL

SIKJalpha

YYG


https://www.covidanalytics.io/home

https://www.covidsim.org

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

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

https://covid19-projections.com/

https://covid19-projections.com/


Figure 19. 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.

Yemen


Tunisia

Syria

Sudan

Somalia

Saudi Arabia

Qatar

Palestine

Pakistan

Oman

Morocco

Libya

Lebanon

Kuwait

Jordan

Iraq

Iran

Egypt

Djibouti

Bahrain

Afghanistan

Apr Jun Aug Oct Dec Feb

Stress level

Low

Moderate

High

Extreme

All hospital beds



Figure 20. 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.

Yemen


Tunisia

Syria

Sudan

Somalia

Saudi Arabia

Qatar

Palestine

Pakistan

Oman

Morocco

Libya

Lebanon

Kuwait

Jordan

Iraq

Iran

Egypt

Djibouti

Bahrain

Afghanistan

Apr Jun Aug Oct Dec Feb

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 102,800 1COVID-19 71,806 2Stroke 40,900 3Road injuries 21,100 4Hypertensive heart disease 18,500 5Diabetes mellitus 14,700 6Alzheimer’s disease and other dementias 13,900 7Chronic obstructive pulmonary disease 12,600 8Chronic kidney disease 12,500 9Stomach cancer 11,000 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.


http://observcovid.miami.edu/

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