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Variants of concern cause more than 40% of new COVID-19 cases in Ontario, experts say

Shiloh

Editor, Senior Moderator
Source: https://www.cbc.ca/news/canada/toronto/covid-19-ontario-march-11-2021-variants-of-concern-1.5945381

Variants of concern cause more than 40% of new COVID-19 cases in Ontario, experts say
Sudbury moving to grey-lockdown tier on Friday, health officials say
CBC News ? Posted: Mar 11, 2021 10:38 AM ET | Last Updated: 4 minutes ago

Ontario's Chief Medical Officer of Health Dr. David Williams is scheduled to hold a briefing on the COVID-19 situation in the province at 3 p.m. ET. He will be joined by Dr. Adalsteinn Brown, co-chair of Ontario's COVID-19 science advisory table, who will be presenting updated modelling.

You'll be able to watch it live in this story.

Variants of concern are currently responsible for about 42 per cent of new daily cases of COVID-19 in Ontario, the province's science advisory table said Thursday.

The group, made up of health experts and professionals, launched a new online dashboard focused on the variants of concern (VOCs) ahead of revised modelling that is set to be released at a briefing this afternoon.

It shows that the variants continue to spread. The data is more or less right on track with what was predicted in models released by the table in late February.

Critically, the reproduction value ? an estimate of how many people each positive case will go on to infect ? for VOCs is about 1.24, the table said. Any value above one suggests that the rate of new cases is growing.

Meanwhile, for the "old" variants ? those that were present before the current VOCs were circulating ? the reproduction value is 0.9.

So far in Ontario, labs have definitively linked 956 cases to the variant first found in the United Kingdom; 41 to the variant identified in South Africa and 28 to the variant found in Brazil.

But those figures are a drastic undercount of the real situation. Specific variants can only be confirmed once the samples have undergone whole genomic sequencing, an intensive process that can lead to reporting lags in the data of up to three weeks...
 
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