Modeling to mitigate COVID-19
Transcript of Modeling to mitigate COVID-19
Modeling to mitigate COVID-19
Lauren Ancel MeyersUT COVID-19 Modeling Consortium
June 17, 2020
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
Background
Pandemic Exercise Tool (2013)
CDC FluCode - Pandemic Model (2020)
15% 35%
High risk
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
The key questions
Where and how is the virus spreading today?
Where will the virus be spreading in the future?
How to use limited resources to slow spread and save lives?
Situational awareness
Forecasting
Mitigation
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
Spread far and fast
-10 0 10 20Serial Interval (days)
0
3
6
9
12
15
Freq
uenc
y
-10 0 10 20Serial Interval (days)
0
3
6
9
12
15
Freq
uenc
y
-10 0 10 20Serial Interval (days)
0
3
6
9
12
15
Freq
uenc
y
Du et al. (2020) Serial Interval of COVID-19 among Publicly Reported Confirmed Cases. Emerging Infectious Diseases
Dec. 1
Dec. 8
Jan.
10
Jan.
22100
105
Cum
mul
ativ
e ca
ses
Cum
ulat
ive
case
s
Du et al. (2020) Risk for Transportation of 2019 Novel Coronavirus Disease from Wuhan to Other Cities in China. Emerging Infectious Diseases
425 cases
reported
12,400 cases
estimated
fast
silent
long
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
01-17
01-21
01-25
01-29
02-02
02-06
02-10
0
2
4
01-17
01-21
01-25
01-29
02-02
02-06
02-10
0
5
10
15
Rt
case
sEarly action matters
Du et al. (2020) Effects of Proactive Social Distancing on COVID-19 Outbreaks in 58 Cities, China. Emerging Infectious Diseases.
A 1-day delay in intervention prolongs the outbreak by ~2.4 days.
intervention
containment
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
The key questions
Where and how is it spreading today?
Where will it be spreading in the future?
How to use limited resources to slow spread and save lives?
Situational awareness
Forecasting
Mitigation
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
The IHME Model
Apr 6
900
600
300
0De
aths
Apr 13
Backcast for Spain
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
Our model
bars grocery
parksmedical
schoolsrestaurants
at home
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
Ensemble forecasting
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
The key questions
Where and how is it spreading today?
Where will it be spreading in the future?
How to use limited resources to slow spread and save lives?
Situational awareness
Forecasting
Mitigation
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep
5000
4000
3000
2000
1000
0
Hos
pita
lizat
ions
capacity
How will reopening play out?
Mar Apr May
1501251007550250
If transmission increases by 50% relative to the stay-home period …
over 3500
deaths
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep
3000
2500
2000
1500
1000
500
0
Hos
pita
lizat
ions
capacity
How will reopening play out?If transmission increases by 25% relative to the stay-home period …
~2100 deaths
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep
10,000
8,000
6,000
4,000
2,000
0
Hos
pita
lizat
ions
capacity
How will reopening play out?If transmission doubles relative to the stay-home period …
> 6000 deaths
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
Decision-support modeling
Goals: Avoid overwhelming surge and avoid stay-home orders
Approach: Multiple stages of risk to allow ‘tapping’ on brakes
What to track?
When to trigger?
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
Policy thresholds
Use this color-coded alert system to understand the stages of risk. This chart provides recommendations on what people should do to stay safe during the pandemic. Individual risk categories identified pertain to known risks of
complication and death from COVID-19. This chart is subject to change as the situation evolves.
COVID-19: Risk-Based Guidelines
AustinTexas.gov/COVID19 Published: May 13, 2020
Stage 5
Stage 4
Stage 3
Stage 2
Stage 1 • greater than 25
greater than 25
all businesses
essential and re-opened businesses
essential and re-opened businesses
expanded essential businesses
essential businesses only
gathering size TBD
greater than 10
except with precautions
except with precautions
except with precautions
except as essential
except as essential
except as essential
except as essential
except expanded essential
businesses
except as essential
social and
greater than 10
social and
greater than 10
social and
greater than 10
outside of household
outside of household
social and
greater than 2
• • •
• • • •
• • • • •
• • • • •
Practice Good
Hygiene
Stay Home If Sick
Maintain Social
Distancing
Wear Facial Coverings
Higher Risk IndividualsAge over 65, diabetes, high blood
pressure, heart, lung and kidney disease, immunocompromised, obesity
Lower Risk IndividualsNo substantial underlying health
conditions
Workplaces Open
Avoid Gatherings
Avoid GatheringsAvoid Sick
People
Avoid Non-
Essential Travel
Avoid Non-
Essential Travel
Avoid Dining/
Shopping
Avoid Dining/
Shopping
1
Triggers 7-day average
daily COVID-19 hospital admissions
5
20
70
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep
2000
1750
1500
1250
1000
750
500
250
0
Hos
pita
lizat
ions
capacity
stay
-hom
e
restricted relaxed
Projections with stages
~1800 deaths
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
Data-driven policy in action
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
Houston
4,500 beds
50179
380
7-day average COVID-19 admissions: 189
189
70450
780
9,000 beds
801140
1180
13,500 beds
189 189
UT COVID-19 Modeling Consortium https://covid-19.tacc.utexas.edu/ [email protected]
Funding and teamSimon Cauchemez, Institute Pasteur
Ben Cowling, U Hong KongMaytal Dahan, TACC
Oscar Dowson, Northwestern UniversityZhanwei Du, UT
Daniel Duque Villarreal, NorthwesternSpencer Fox, UT
Kelly Gaither, TACCAlison Galvani, Yale
Neo Huang, Precima, LoyaltyOneEmily Javan, UT
Clay Johnston, Dell MedMichael Lachmann, Santa Fe Institute
David Morton, NorthwesternCiara Nugent, UTRemy Pasco, UT
Michaela Petty, UTKelly Pierce, TACC
Michael Pignone, Dell MedJames Scott, UTMauricio Tec, UT
Suzanna Wang, UTSpencer Woody, UT
US Centers for Disease Control and PreventionNational Institutes of Health
National Science FoundationTexas Advanced Computing Center
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