Health
Professor Philip Nolan defends NPHET after claiming wrong R number
Professor Philip Nolan defended NPHET after claiming that he was wrong about the R number in October.
The number of cases is declining faster than the NPHET prediction tweeted by Claire TD Michael McNamara. “On October 22, NPHET said:” The current estimate of R is 1.3-1.4. “That was clearly wrong. “
However, Professor Philip Nolan says he is confident that their R rate estimate is good.
“No, I’m sure it was a good estimate of the number of recalls,” said the professor. The estimates were made on October 20, 2020, until midnight, October 18, 2020, based on the confirmed cases. It may help explain the basic principles behind the various methods. Estimate R.
“R is an estimate of the virus infection rate. If a person is infected with a virus, how many people will continue to be infected on average?
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“We don’t know the R of today or yesterday. If people are infected with the virus today, it will take time for the resulting infected person to show symptoms, be tracked, be tested, and be identified as a case. It takes. You can only reliably estimate today’s R. In 7-14 days.
“These infections are not known until symptoms appear or are tracked, tested and confirmed. This can take a variety of times. Usually 5-7 days before symptoms appear, until symptoms appear. It will take 7-12 days. Confirmed case.
“Therefore, infection cannot be measured. Infection can only be inferred from the pattern of cases over time. Cases do not appear in infection and lockstep, are highly variable, and some infections are detected at all. It will not be.
“Various methods of estimating R use statistics and modeling to infer the underlying pattern of infection from known case patterns, but the most important limitation is infection that is estimated 1-2 weeks ago. (And social contact).
“There are several ways to’nowcast’R, but these have serious limitations. This is why we use a variety of indicators and analyzes rather than relying solely on R estimates to understand possible epidemic trajectories. “
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