- May 2021
u/dawnlxh. (2021). Reviewing peer review: does the process need to change, and how?. r/BehSciAsk. Reddit
- peer review
- Nov 2020
Gov. Kristi Noem defended her hands-off approach to managing the deadly COVID-19 pandemic while addressing lawmakers earlier this week and called mandatory stay-at home orders "useless" in helping lower the spread.
Take away: Lower COVID-19 spread occurred after stay-at home orders were issued. Room for debate exists on how restrictive lockdowns should be.
The claim: Mandatory stay-at home orders are "useless" in helping lower the spread of SARS-CoV-2.
The evidence: Two publications showed that lower COVID-19 spread occurred after stay-at home orders were issued (1, 2). Hospitalizations were lower than predicted exponential growth rates after implementation of stay-at home orders (3). Some caveats to consider include that it is impossible to tease apart the effects of the stay-at home orders from other measure implemented simultaneously with stay-at home orders such as increased hygiene measures, social distancing guidelines, and school closures. It is also impossible to conclusively state that the effect is from the stay-at home order and not the natural progression of the disease.
The comparison between Illinois with stay-at home orders and Iowa without stay-at home orders resulted in an estimated 217 additional COVID-19 cases in Iowa over the course of a month (2). This small number raises the question, "are stay-at home orders worth it?" It is important to remember that comparison of Iowa and Illinois is the comparison of two social distancing strategies. Stay-at home orders close everything and then write the exceptions that can remain open. Iowa took the approach of leaving everything open except what the government choose to close (4). Some businesses in Iowa were still closed and many federal guidelines were still followed. A negative control showing disease progression without any mitigation measures does not exist in published literature.
We have designed a dimeric lipopeptide fusion inhibitor that blocks this critical first step of infection for emerging coronaviruses and document that it completely prevents SARS-CoV-2 infection in ferrets.
The takeaway: Dimeric lipopeptide fusion inhibitor prevented SARS-CoV-2 infection in all six ferrets tested. Much more work is needed before this could be used in humans.
The claim: Treatment of ferrets with a dimeric lipopeptide fusion inhibitor completely prevents SARS-CoV-2 infection in ferrets.
The evidence: Per Figure 3, SARS-CoV-2 was detected in all three animals inoculated with the virus, all six animals treated with a placebo, and none of the animals treated with the dimeric lipopeptide fusion inhibitor (1). Animals treated with dimeric lipopeptide fusion inhibitor did not mount an immune response to SARS-CoV-2 while an immune response was seen in inoculated animals and placebo treated animals (Figure 4).
More research is needed before this treatment can be used in humans. This preliminary study showed that in a small sample of animals which do not typically show COVID symptoms, SARS-CoV-2 infection was blocked by the dimeric lipopeptide fusion inhibitor. This paper describes the first step in a long journey. Before a new treatment is approved for use in humans, Phase I, II and III clinical trials must be completed (2) which includes showing that a treatment does no harm to healthy humans and proving that it works in humans. This work also needs peer-review in a published journal which may occur with time.
- Oct 2020
A scientific review of the science behind lockdown concludes the policy was a MISTAKE & will have caused MORE deaths from Covid-19
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
In testimony before US Congress on March 11, 2020, members of the House Oversight and Reform Committee were informed that estimated mortality for the novel coronavirus was 10-times higher than for seasonal influenza. Additional evidence, however, suggests the validity of this estimation could benefit from vetting for biases and miscalculations. The main objective of this article is to critically appraise the coronavirus mortality estimation presented to Congress. Informational texts from the World Health Organization and the Centers for Disease Control and Prevention are compared with coronavirus mortality calculations in Congressional testimony. Results of this critical appraisal reveal information bias and selection bias in coronavirus mortality overestimation, most likely caused by misclassifying an influenza infection fatality rate as a case fatality rate.
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.
- Aug 2020
twitter.com twitter.comAlex Berenson on Twitter: "1/ TL:DR - @who published a massive review/meta-analysis of interventions for flu epidemics in 2019, found "moderate" evidence AGAINST using masks. (They actually missed the 2015 Vietnam study, yet another brick in the wall.) 2019. So recent, yet so long ago. What's changed?" / Twitter1
@who published a massive review/meta-analysis of interventions for flu epidemics in 2019, found "moderate" evidence AGAINST using masks.
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.