Update on COVID-19 Projections

Science Advisory and Modelling Consensus Tables April 16, 2021 Key Findings

• COVID-19 cases, hospitalizations and ICU occupancy are at their highest levels since March 2020 and variant cases continue to rise sharply. • ICU occupancy is compromising care for all patients. • Ontarians can help themselves and others by limiting mobility to truly necessary trips and always wearing a mask and keeping 6 feet distant when in contact with anyone outside their household. • Although improving, vaccination is not reaching people at high-risk fast enough to overcome the level of serious illness in our communities and our hospitals. • Without stronger system-level measures and immediate support for essential workers and high-risk communities, high case rates will persist through the summer.

2 Cases are rapidly increasing in most Public Health Units

March 29 April 11 300

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100

0 Peel York Kent KFLA Weekly new cases residents per 100,000 Weekly - Brant Essex - Halton Guelph Ottawa Eastern Norfolk London Niagara Algoma Toronto Durham Sudbury - Renfrew Lambton Hamilton Waterloo Porcupine Grey Bruce Grey Huron Perth Huron Timiskaming Thunder Bay Thunder Peterborough Northwestern Southwestern Chatham Windsor Hastings & PEC Haliburton KPR - Dufferin Simcoe Muskoka - Middlesex Haldimand - Leeds Grenville Leeds Grenville Lanark North Bay Parry Sound Parry North Bay

Data source: CCM Wellington Data note: Data for the most recent day have been censored to account for reporting delays 3 Test positivity rates are increasing across Ontario

Dec 26 Jan 18 Apr 3 16 Province-wide lockdown First dose Province-wide 14-days for N. Ontario vaccination emergency brake 28-days for S. Ontario complete in Peel, 15.0% prioritized PHUs 14

12 Toronto, 11.3% 10 York , 10.4% Durham, 9.0% 8

day avg.) Ontario, 7.9% - (7 6

% positivity of daily testing episodes 2

0 Jan 2 Dec 5 Aug 1 Nov 7 Jan 16 Jan 30 Oct 24 Oct 10 Apr 10 Feb 13 Feb 27 Feb Sep 12 Sep 26 Dec 19 Aug 15 Aug 29 Nov 21 Mar 13 Mar 27 Mar

Specimen Date 4 Data source: Ontario Laboratory Information System (OLIS), data up to April 9 Ontario testing rates are flat – the increase in cases is because there are more cases, not more tests being done 700

600

500 Hastings & PEC, 473

400 day avg.) - (7 300 Ontario, 320

Testing episodes per 100,000 per episodes Testing 200

Windsor-Essex, 145 100 Jan 2 Dec 5 Aug 1 Nov 7 Jan 16 Jan 30 Oct 10 Oct 24 Apr 10 Feb 13 Feb 27 Feb Sep 12 Sep 26 Dec 19 Aug 15 Aug 29 Nov 21 Mar 13 Mar 27 Mar 5 Data source: Ontario Laboratory Information System (OLIS), data up to April 9 Specimen Date The number of variant cases continues to rise and variants now dominate, but even the original strain is rising.

6 A record number of Ontarians are in hospital due to COVID-19

2000

1800 Patients in Inpatient Beds with COVID19 1600 Patients in ICU with COVID-Related Critical Illness Last 2 weeks: 1400 67% growth in hospitalizations 51% growth in ICU 1200 occupancy

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0 01-Sep 08-Sep 15-Sep 22-Sep 29-Sep 06-Oct 13-Oct 20-Oct 27-Oct 03-Nov 10-Nov 17-Nov 24-Nov 01-Dec 08-Dec 15-Dec 22-Dec 29-Dec 05-Jan 12-Jan 19-Jan 26-Jan 02-Feb 09-Feb 16-Feb 23-Feb 02-Mar 09-Mar 16-Mar 23-Mar 30-Mar 06-Apr 7 Data Sources: MOH COVID Inpatient Census and Critical Care Information System A 6 week stay-at-home order with a vaccination rate of at least 100K doses per day is the only way to flatten the curve.

Figure summarizes predictions across 4 models with many scenarios. Stay-at-home order assumptions: • 4 or 6 weeks starting Apr 8 • Weak to strong effect on transmission Vaccine assumptions: • 60% effective in preventing infection • 100,000 doses/day • Administered at random

Predictions informed by modeling from COVID-19 ModCollab, Fields Institute, McMasterU, PHO, YorkU 8 Data (Observed Cases): covid-19.ontario.ca Under every scenario, more vaccines mean a faster resolution in the long-run

Daily Cases 35,000

30,000

25,000

20,000

15,000

10,000

5,000

- 01-01 01-08 01-15 01-22 01-29 02-05 02-12 02-19 02-26 03-05 03-12 03-19 03-26 04-02 04-09 04-16 04-23 04-30 05-07 05-14 05-21 05-28 06-04 06-11 06-18 06-25 ON - Daily ON - 7-Day Average Weak PH Measures 4 wks + 100k doses/day Moderate PH Measures 6 wks + 100k doses/day Strong PH Measures 6 wks + 100k doses/day Weak PH Measures 4 wks + 300k doses/day Moderate PH Measures 6 wks + 300k doses/day Strong PH Measures 6 wks + 300k doses/day

9 As predicted, ICU occupancy is rising dramatically. System-level public health measures will help blunt some of the impact.

Predictions: COVID-19 ModCollab. 10 Data (Observed ICU Occupancy): CCSO Mobility has declined slightly but not enough to bring current growth under control.

Predictions: COVID-19 SAT. 11 Data Google and Apple Mobility data Mobility has declined slightly across settings. Further reducing mobility and always wearing a mask and distancing is how Ontarians help reduce cases.

Predictions: COVID-19 SAT. 12 Data Google and Apple Mobility data The access to care deficit is building which will be felt by 250,000 Ontarians well past the pandemic Cumulative backlog: 248,109 cases

200,000

150,000

100,000

50,000

13 Data Source: Wait Times Information System. Backlog estimated based on comparison of 2020/21 with 2019/20 surgical volumes First dose vaccine coverage expanding but remains incomplete More than 3m doses administered

Data Sources MOF Population Projections COVAX analytical file, extracted, 8:00 pm Apr 12 2021, CPAD, MOH COVAX Skedulo, extracted 6:00pm Apr 12 2021 14 Vaccination by risk is improving but remains a key to controlling spread Figure excludes long-term care vaccination – at least 1 dose as of April 12, 2021

Source: ICES 15 What happens if we vaccinate 3 million adults over the next 30 days? 100,000 vaccinations per day, top 20% highest incidence neighbourhoods

Potential impact at 60 days: % of cumulative cases averted, compared to no vaccination moving forward 70 60 50 Number 40 vaccines 30 per case 59 34 20 averted 10 0

% cumulative cases averted Age 16-59 (60 days) Age 60+ (60 days) Total population (60 days) Population

Age-based, per-capita Enhanced to high-incidence FSAs

Analysis: COVID Heterogeneity Research Group, COVID-19 ModCollab, PHO. 16 Data: CCM Key Findings

17 Contributors

• COVID Heterogeneity Research Group: Rafal Kustra, Huiting Ma, Siyi Wang, Gary Moloney, Kristy Yiu, Beate Sander, Jeff Kwong, Stefan Baral, Sharmistha Mishra • 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 • ICES: Jeff Kwong, Hannah Chung, Kinwah Fung, Michael Paterson, Susan Bronskill, Laura Rosella, Astrid Guttmann, Charles Victor, and Michael Schull, Marian Vermeulen • McMasterU: Michael Li, Irena Papst, Ben Bolker, Jonathan Dushoff, David Earn • YorkU: Jianhong Wu, Francesca Scarabel, Bushra Majeed • MOHLTC: Michael Hillmer, Kamil Malikov, Qing Huang, Jagadish Rangrej, Nam Bains, Jennifer Bridge • OH: Erik Hellsten, Stephen Petersen, Anna Lambrinos, Chris Lau, Access to Care Team • PHO: Kevin Brown • Science Advisory Table: Peter Juni

18 Content provided by Modelling Consensus and Scientific Advisory Table members and secretariat

Beate Sander,* Peter Juni, Brian Schwartz,* Kumar Murty,* Upton Allen, Vanessa Allen, Nicholas Bodmer, Isaac Bogoch, Kevin Brown, Sarah Buchan, Yoojin Choi, Troy Day, Laura Desveaux, David Earn, Gerald Evans, David Fisman, 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, Antonina Maltsev, Doug Manuel, Roisin McElroy, Allison McGeer, David McKeown, John McLaughlin, Sharmistha Mishra, Justin Morgenstern, Andrew Morris, Samira Mubareka, Laveena Munshi, Christopher Mushquash, Ayodele Odutayo, Shahla Oskooei, Menaka Pai, 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, Nathan Stall, 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.