Update on COVID-19 Projections - Science Advisory and Modelling Consensus Tables September 28, 2021
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Update on COVID-19 Projections
Science Advisory and Modelling Consensus Tables
September 28, 2021
Key Findings
• New cases, hospitalisations and ICU occupancy are not increasing. There is
a wide range for case projections, reflecting the fragile situation and high
degree of instability as colder weather approaches with more time indoors.
• Continued control over case growth requires high vaccination rates in the
eligible population, continued public health measures, and a flattening of
growth in mobility.
• The risk of contracting COVID-19, being hospitalized for COVID-19, and
entering the ICU is several times higher for unvaccinated individuals.
• Vaccination coverage is increasing slowly.
• Post COVID-19 Condition – or Long COVID – will substantially impact the
health of thousands of Ontarians
2
Weekly new cases per 100,000 residents
100
110
10
20
30
40
50
60
70
80
90
0
Data source: CCM
Chatham-Kent
Wellington-Dufferin-Guelph
Eastern
Ottawa
Southwestern
Lambton
Waterloo
Halton
Peterborough
Haldimand-Norfolk
Huron Perth
Sudbury
14-day increases
Haliburton KPR
Leeds Grenville Lanark
KFLA
Algoma
September 7
Grey Bruce
Northwestern
Renfrew
Data note: Data for the most recent day have been censored to account for reporting delays
Windsor-Essex
Average weekly cases on:
Brant
Hamilton
September 20
Niagara
Peel
York
Cases are increasing in 19 of 34 public health units
Toronto
Middlesex-London
Durham
Simcoe Muskoka
Hastings & PEC
North Bay Parry Sound
14-day decreases
Porcupine
Thunder Bay
Timiskaming
Testing episodes per 1,000
(7-day avg.)
0
1
2
3
4
5
6
7
Aug 1
Aug 15
Aug 29
Sep 12
Sep 26
Oct 10
Oct 24
Nov 7
Data source:OLIS via SAS VA, data up to September 17
Nov 21
Dec 5
Dec 19
Jan 2
Jan 16
Jan 30
Feb 13
Feb 27
Mar 13
Specimen Date Mar 27
Apr 10
Apr 24
May 8
May 22
Jun 5
Jun 19
Jul 3
Jul 17
Jul 31
Aug 14
Aug 28
Sep 11
With the start of school, testing rates are up across Ontario
Ontario, 2
Timiskaming, 1
Chatham-Kent, 3
Test positivity appears to be declining
18
% positivity of daily testing episodes
16
14
12
(7-day avg.)
10
8
6
Chatham-Kent, 4.9%
4 Windsor, 4.2%
Brant, 4.0%
Ontario, 2.7%
2
0
Aug 15
Aug 29
Aug 14
Aug 28
Oct 10
Oct 24
Jun 19
Jun 5
Nov 21
Nov 7
Apr 10
Apr 24
Jan 16
Jan 30
Jul 17
Jul 31
Aug 1
Jul 3
Feb 13
Feb 27
Dec 19
Sep 12
Sep 26
Mar 13
Mar 27
Sep 11
May 22
Jan 2
May 8
Dec 5
Specimen Date
Data source:OLIS via SAS VA, data up to September 17
The most recent 3 days have been removed to account for incomplete data.Vaccination coverage is increasing slowly
Analysis: Secretariat of the Science Advisory Table (https://covid19-sciencetable.ca/ontario-dashboard/) 6
Data: https://data.ontario.ca/Vaccination continues to be highly effective
Unvaccinated people have a 7-fold higher risk of symptomatic COVID-19 disease, a 25-fold higher risk of
being in the hospital and 60-fold higher risk of being in the ICU compared to the fully vaccinated
Analysis: Secretariat of the Science Advisory Table (https://covid19-sciencetable.ca/ontario-dashboard/) 7
Data: https://data.ontario.ca/ and CCM plus; estimates of patients in hospital and ICU are age standardizedOur 4th wave has flattened due to continued public health
measures and vaccination but cases in children are increasing
MOBILITY - Analysis: Secretariat of the Science Advisory Table (https://covid19-sciencetable.ca/ontario-dashboard/) Data: 8
https://data.ontario.ca/ & https://ourworldindata.org/explorers/coronavirus-data-explorer CASES BY AGE - Analysis: PHO, Data: CCMThere is a wide range for case projections, reflecting the fragile
situation and high degree of instability as colder weather approaches.
Figure shows predictions
PREDICTED
6,000
based on a consensus across
5,000
models from 5 scientific teams.
4,000 Range from
High uncertainty in estimates last briefing
Daily Cases
because: 3,000
• Uncertainty in vaccine
effectiveness against 2,000
infection
• Too early to see impact of 1,000
increased contacts with
return to school and -
2021-04-01 2021-05-01 2021-06-01 2021-07-01 2021-08-01 2021-09-01 2021-10-01 2021-11-01
workplaces
ON - Daily ON - 7-Day Average
• Seasonality and time spent High Trajectory (25%↑ in Transmission) Status Quo (no change in behaviour or policy)
indoors vs. outdoors Low Trajectory (25%↓ in Transmission)
Predictions informed by modeling from Fields
Institute, McMasterU, PHO, WesternU, YorkU 9
Data (Observed Cases): covid-19.ontario.caICU Occupancy estimates vary from under 200 beds to over
300 beds by the end of October
PREDICTED
1,000
900
800
700
ICU Occupancy
600
500 Range from
400
last briefing
300
200
100
-
21 1
21 8
21 5
21 2
21 9
21 6
21 3
21 0
21 7
21 3
21 0
21 7
21 4
21 1
21 8
21 5
21 2
21 9
21 5
21 2
21 9
21 6
21 2
21 9
21 6
21 3
21 0
21 7
21 4
21 1
28
0
0
1
2
2
0
1
2
2
0
1
1
2
0
0
1
2
2
0
1
1
2
0
0
1
2
3
0
1
2
4-
4-
4-
4-
4-
5-
5-
5-
5-
6-
6-
6-
6-
7-
7-
7-
7-
7-
8-
8-
8-
8-
9-
9-
9-
9-
9-
0-
0-
0-
0-
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
21
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
ON - Daily ON - 7-Day Average High Trajectory (25%↑ in Transmission)
Status Quo (no change in behaviour or policy) Low Trajectory (25%↓ in Transmission)
Predictions: COVID-19 ModCollab based on case predictions in previous slide.. 10
Data (Observed ICU Occupancy): CCSOThe 4th wave continues to put pressure on hospital capacity
in a number of jurisdictions
COVID-19 Patients in Hospital
Analysis: Secretariat of the Science Advisory Table 11
Data: https://data.ontario.ca/, https://resources-covid19canada.hub.arcgis.com and https://ourworldindata.org/explorers/coronavirus-data-explorerHowever, in Ontario hospital and ICU occupancy have been
stable for several weeks
2,500
Patients in ICU with COVID-related critical illness
2,000 Patients in inpatient beds (incl. ICU) with active COVID19
COVID inpatient and ICU total census
1,500
1,000
500
0
01-Sep-20 01-Oct-20 01-Nov-20 01-Dec-20 01-Jan-21 01-Feb-21 01-Mar-21 01-Apr-21 01-May-21 01-Jun-21 01-Jul-21 01-Aug-21 01-Sep-21 12Long-term predictions:
High risk of rapid increase in ICU occupancy can be reduced with a
cautious approach and early contact reductions.
40
Example: London-Middlesex, predicted ICU occupancy for a population of 500,000.
35
30
25
ICU Occupancy
20
15
10
5
0
2021-04-01 2021-05-01 2021-06-01 2021-07-01 2021-08-01 2021-09-01 2021-10-01 2021-11-01 2021-12-01 2022-01-01
Actual (Local demand only) 80% of pre-pandemic contacts 70% of pre-pandemic contacts Modelled to Sept 15
• Scenarios shown assume that as ICU occupancy and deaths increase, contacts will decrease due to behaviour change and implementation of public health measures
• Summer (Step 3) contacts approx. 82.5% compared to pre-pandemic contacts
• If scaling up to Ontario population, ICU occupancy predictions for Ontario would be expected to be higher and the peak to occur earlier, especially in large urban areas.
Predictions: WesternU
13Patients in ICU are expected to be younger compared to
earlier waves.
Example: London-Middlesex, predicted ICU occupancy for a population of 500,000.
40
Scenario: 80% of pre-pandemic contacts + behaviour change as ICU occupancy and deaths increase +
35 current estimates of vaccine effectiveness.
30
25
ICU Occupancy
20
15
10
5
0
Sep-01 Oct-01 Nov-01 Dec-01 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-01
Under 12 years
12-17 years 50-59 years • Summer (Step 3) contact level approx. 82.5%
18-24 years 60-69 years • If scaling up to Ontario population, ICU occupancy predictions for Ontario would be
25-49 years Over 70 years expected to be higher and the peak to occur earlier, especially in large urban areas. Predictions: WesternU 14Post COVID-19 Condition – or Long COVID – will substantially
impact the health of thousands of Ontarians
• About 1 in 10 individuals with COVID-19 infection will continue to
have symptoms lasting more than 12 weeks (estimated 57,000 to
78,000 individuals in Ontario based on data up to August 2021)
• Most common symptoms: fatigue, shortness of breath, pain, anxiety and
depression, trouble thinking/concentrating (“brain fog”)
• Can impact individuals of any age or baseline health, and can occur even if
minimal to no symptoms during initial infection
• Vaccines are strongly protective:
• Reduce the chance of getting infected by about 85%
• Reduce the chance of developing Long COVID-19 in breakthrough infections
by about 50%Post COVID-19 Condition may substantially impact the health
system
Post COVID-19 Condition may result in significant burden on
individuals, healthcare system and society:
• Increased incidence of new chronic disease (e.g., diabetes or
cardiovascular disease)
• Higher healthcare utilization (physician visits, hospitalization)
• Severe impairment of home-life and day to day activities for some
individuals
• Longest follow-up study (12 months after infection):
• 12% of all infected individuals had not returned to work
• Among the 88% who returned, 24% had not returned to their pre-COVID-19
level of workKey Findings
• New cases, hospitalisations and ICU occupancy are not increasing. There is
a wide range for case projections, reflecting the fragile situation and high
degree of instability as colder weather approaches with more time indoors.
• Continued control over case growth requires high vaccination rates in the
eligible population, continued public health measures, and a flattening of
growth in mobility.
• The risk of contracting COVID-19, being hospitalized for COVID-19, and
entering the ICU is several times higher for unvaccinated individuals.
• Vaccination coverage is increasing slowly.
• Post COVID-19 Condition – or Long COVID – will substantially impact the
health of thousands of Ontarians
17Contributors
• COVID-19 Modeling Collaborative: Kali Barrett, Stephen Mac, David Naimark,
Aysegul Erman, Yasin Khan, Raphael Ximenes, Sharmistha Mishra, Beate Sander
• Fields Institute: Taha Jaffar, Kumar Murty
• McMasterU: Irena Papst, Michael Li, Ben Bolker, Jonathan Dushoff, David Earn
• Modeling Consensus Table: Isha Berry
• PHO: Kevin Brown, Sarah Buchan, Alyssa Parpia
• Science Advisory Table: Peter Juni, Kali Barrett, Karen Born, Nicolas Bodmer,
Shujun Yan
• Western University/London Health Sciences Centre : Lauren Cipriano, Wael
Haddara
• YorkU: Jianhong Wu, Yanyu Xiao, Zack McCarthy
18Content and review by Modelling Consensus and Scientific
Advisory Table members and secretariat
Beate Sander,* Peter Juni, Brian Schwartz,* Kumar Murty,* Upton Allen, Vanessa Allen, Kali Barrett,
Nicolas Bodmer, Isaac Bogoch, Karen Born, Kevin Brown, Sarah Buchan, Yoojin Choi, Troy Day, Laura
Desveaux, David Earn, Gerald Evans, Jennifer Gibson, Anna Greenberg, Anne Hayes,* Michael
Hillmer, Jessica Hopkins, Jeff Kwong, Fiona Kouyoumdjian, Audrey Laporte, John Lavis, Gerald
Lebovic, Brian Lewis, Linda Mah, Kamil Malikov, Doug Manuel, Roisin McElroy, Allison McGeer, David
McKeown, John McLaughlin, Sharmistha Mishra, Andrew Morris, Samira Mubareka, Laveena
Munshi, Christopher Mushquash, Ayodele Odutayo, Shahla Oskooei, Menaka Pai, Alyssa Parpia,
Samir Patel, Anna Perkhun, Bill Praamsma, Justin Presseau, Fahad Razak, Rob Reid,* Paula Rochon,
Laura Rosella, Michael Schull, Arjumand Siddiqi, Chris Simpson, Arthur Slutsky, Janet Smylie, Robert
Steiner, Ashleigh Tuite, Jennifer Walker, Tania Watts, Ashini Weerasinghe, Scott Weese, Xiaolin Wei,
Jianhong Wu, Diana Yan, Emre Yurga
* Chairs of Scientific Advisory, Evidence Synthesis, and Modelling Consensus Tables
For table membership and profiles, please visit the About and Partners pages on the Science
Advisory Table website.
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