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Science could learn something from this. Science is too far focused on the idealized positive outcomes that it isn't paying attention to the negative outcomes and using that to better define its outline or overall shape. We need to define a scientific opportunity cost and apply it to the negative side of research to better understand and define what we're searching for.

Of course, how can we define a new scientific method (or amend/extend it) to better take into account negative results--particularly in an age when so many results aren't even reproducible?

Take Away: The new scientific paper confirms earlier modeling work and should not be interpreted as a detailed prediction for future deaths due to the ongoing pandemic.

The Claim: "A scientific review of the science behind lockdown concludes the policy was a MISTAKE & will have caused MORE deaths from Covid-19"

The Evidence: The scientific process involves replication and confirmation of experiments and studies. A new paper replicates and expands on an early modeling study of the COVID-19 pandemic in England (1). Their findings support the earlier results. However, there are limitations to the replication paper, which does not accurately reflect the current state of the pandemic response and does not make detailed predictions for a second wave of infections and deaths.

A recent expert response to the paper further explains (2):

"It needs to be stressed that all the simulations assume that interventions are only in place for 3 months (18th April – 18th July) and then completely relaxed. This gives rise to a strange set of scenarios where a second wave is allowed to progress in an uncontrolled manner."

“It is this that leads to the counter-intuitive headline finding “that school closures would result in more overall covid-19 deaths than no school closures” – actually what the authors find is that a short period of intense lock-down (including the closure of schools) leads to a large second wave if it is allowed to run with no controls. To be fair the authors do highlight this in the paper, but it is not in the reported press release." -Prof Matt Keeling, Professor of Populations and Disease, University of Warwick

Sources:

(1) https://www.bmj.com/content/371/bmj.m3588

(2) https://www.sciencemediacentre.org/expert-reaction-to-reanalysis-of-model-used-for-imperial-report-9-and-impact-of-school-closures/

Australian research gets billion-dollar boost in sweeping stimulus budget. (2020). Nature. Retrieved October 09, 2020, from https://www.nature.com/articles/d41586-020-02835-y?utm_source=twt_nnc&utm_medium=social&utm_campaign=naturenews

Take away: COVID-19 death rate is worse than seasonal influenza death rate.

The claim: Coronavirus mortality was over estimated as 10X worse than seasonal influenza to congress due to misclassifying influenza infection fatality rate as a case fatality rate.

The evidence: Comparing infection fatality ratio (IFR) and case fatality ratio (CFR) is an apples to oranges comparison (1). Case fatality ratios present higher death percentages than infection fatality ratios. At the same time, it is important to understand that COVID-19 and seasonal influenza CFR and IFR numbers are rough approximations of reality and the potential for errors exist in all calculations.

The seasonal IFR rate of influenza was overstated in this article. The claim that seasonal influenza IFR and COVID-19 IFR are the same is based on seasonal influenza IFR of 0.1%. Per the WHO report, seasonal influenza “is usually well below 0.1%” (2). This statement was translated into “0.1% or lower” and then “the WHO also reported that 0.1% is the IFR of seasonal influenza, not the CFR of seasonal influenza as reported in the NEJM editorial” (3).

The article is questioning whether COVID-19 is worse than seasonal influenza due to confusion with IFR and CFR. The article overstated influenza IFR to arrive at the conclusion that COVID-19 and seasonal influenza death rates are the same.

Comparison of influenza and COVID-19 deaths:

Influenza CFR = 0.1-0.2%

(Based on CDC data # deaths / # symptomatic cases, 4).

COVID-19 CFR = 2.8%

(In the USA as of 10/6/2020. Includes asymptomatic cases and may therefore be an underestimate of true CFR, 5-6)

It is also important to note that COVID-19 disease is ongoing with the potential for some of the 7,461,206 cases to die from COVID-19 later. Only 2,935,142 cases in the US are reported as recovered as of 10/6/2020.

Even with the inclusion of asymptomatic cases in the death rate calculation for COVID-19, deaths/cases is at least 10X higher than the deaths/cases calculation of symptomatic influenza based on CDC data.

Sources:

1 https://pubmed.ncbi.nlm.nih.gov/32234121/

2 https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200306-sitrep-46-covid-19.pdf?sfvrsn%3d96b04adf_4

3 https://www.cambridge.org/core/journals/disaster-medicine-and-public-health-preparedness/article/public-health-lessons-learned-from-biases-in-coronavirus-mortality-overestimation/7ACD87D8FD2237285EB667BB28DCC6E9/core-reader

4 https://www.cdc.gov/flu/about/burden/index.html#:~:text=While%20the%20impact%20of%20flu,61%2C000%20deaths%20annually%20since%202010

5 https://coronavirus.iowa.gov/pages/case-counts

6 https://coronavirus.jhu.edu/map.html

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Experiments have shown that simply visualizing an can have great impacts.

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Take away: In their 2019 report the WHO actually recommended for, not against, the use of masks in severe influenza epidemics or pandemics, contrasting the statement made in this tweet. Further, recent evidence overwhelmingly supports the benefit of masks for preventing the spread of SARS-CoV2, the virus that causes COVID-19.

The claim: Overall the claim here appears to be that masks are ineffective against the spread of SARS-CoV2, the virus that causes the clinical syndrome known as COVID-19. The evidence used in support of this claim is that “the WHO found ‘moderate’ evidence AGAINST using masks” in their 2019 report on the use of non-pharmaceutical interventions for mitigating influenza pandemics.

The evidence: This overall claim is poorly supported by data and the evidence used to support this claim is incorrectly characterized by the claimant. Narrowly, the claim that the WHO recommended against mask use is patently false. In their report, the WHO reviewed 10 separate studies and did conclude that there was scant evidence that masks significantly decreased spread of the flu. However, they found no evidence that masks increased spread, and based on mechanistic plausibility (i.e. masks are barriers that prevent droplets from passing between people) and the low risk/high reward, they made a conditional recommendation for mask use in severe influenza epidemics or pandemics.

While influenza does not behave exactly like the SARS-CoV2 virus, the similarities in mode of transmission make it reasonably likely that masks would also have protective effects against the spread of this virus is well. The best evidence is hard data, and that too increasingly points to the benefit of masks for slowing down or preventing the transmission of SARS-CoV2. A recent summary of that data is available here.

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