A peer-reviewed research has claimed that global ivermectin use can end the COVID-19 pandemic, as the medicine significantly reduces the risk of contracting the deadly respiratory disease when used regularly.
IHME has produced a long sequence of bad forecasts, projections and studies.
The true death toll from COVID-19 across the nation is probably over 900,000, more than 50% higher than the most commonly used tallies, according to a new analysis by the Institute for Health Metrics and Evaluation (IHME) at the University of Washington School of Medicine.
While such work must be done, in these parts, everything coming from IHME is taken with a grain of salt, so to speak.
They estimate that 900,000 people died of Covid-19 over roughly the past 12 months.
In 2019, 2.85 million people died in the U.S. The number of deaths increases somewhat each year as the overall population increases. For 2020, a reasonable guess is to expect about 2.9 million deaths, absent Covid-19.
The U.S. announced it favors dropping intellectual property patent protections and forcing pharmaceutical companies to give away their vaccine designs to other nations.
Left out of this is that Moderna said over seven months ago that it would not enforce its patents related to their vaccines. Thus, the U.S. position appears to be moot and potentially a political or PR stunt. Another issue is that most organizations in a position to develop a vaccine, even with free access to the IP, are probably a year away from building up factories, obtaining raw materials, scaling up production, and delivering quality products.
More than a year after the emergence of COVID-19, significant regional differences in terms of morbidity persist, showing lower incidence rates in sub-Saharan Africa, Southeast Asia, and Oceania. Like SARS-CoV-1 and MERS viruses, SARS-CoV-2 is monophyletically positioned with parental species of chiropteran coronavirus. Furthermore, we observe that the spatial distribution of several targeted bat species (i.e., Coronavirus species hosts) overlaps the distribution of countries with low COVID-19 incidence. The work presented here aims to test the presence of natural immunity among population with a low COVD-19 prevalence, potentially due to a previous exposure to coronavirus antigens of a virus close related to SARS-CoV-2.
This map is making the social media rounds. It purports to show that parts of SE Asia and Africa may have had lower Covid-19 deaths perhaps because of some unrecognized pre-existing immunity or exposure to Covid-19. View this as speculative, someone making an hypothesis.
Model projections have been terrible, generally missing all of the important trends.
They missed the upswing in the fall. They missed the downturn in January.
They then forecast a huge rise in Mar-May – which didn’t happen either.
And to be fair – Nate Silver is a statistician forecaster of political events and he’s not been so great there either.
Predicting the future – accurately – is hard and fraught with error. That’s potentially okay as long as we do not take low quality forecasts seriously. The problem is the lack of context about model uncertainty. Most of these models are based on many assumptions for which the real world often disagrees.
The risk of being exposed to Covid-19 indoors is as great at 60 feet as it is at 6 feet — even when wearing a mask, according to a new study by Massachusetts Institute of Technology researchers who challenge social distancing guidelines adopted across the world.
Airborne spread in poorly ventilated areas is the problem.
They say there was no justification for the “six foot rule”. And in a poorly ventilated area, the risks may be similar at a variety of distances.
Wearing masks outdoors makes little sense.
Best thing to do is minimize being in poorly ventilated indoor areas, especially with many other people.
Corollary: During 2020, lock downs forced many people to remain inside – except when going out for groceries, health care or essential work. They then came back and shared poorly ventilated housing units with others. This did not make sense then and especially now after several studies on airborne spread inside. This may also explain why, last spring, about 2/3ds of cases were contact traced to close family and social contacts.
This study also explains that the value of cloth masks may be little when most spread is via aerosols. The CDC now says droplets and fomites don’t seem to be important vectors. Airborne spread explains how 90+ health care workers working in an ED, wearing PPE, all came down with Covid-19 at the same time – droplet and contact spread cannot explain that.
This Twitter thread argues that distance may still matter in some situations as aerosols dilute with distance. However, in enclosed spaces, where people stay for extended periods of time, and having poor ventilation that may not help a lot as the room’s atmosphere gradually collects aerosols.
Methods: The study included 44 U.S. states that instituted eviction moratoriums., followed from March 13th to September 3rd, 2020….
Findings: Twenty-seven states lifted eviction moratoriums during the study period. COVID-19 incidence in states that lifted their moratoriums was 1.6 (95% CI 1.0,2.3) times the incidence of states that maintained their moratoriums at 10 weeks post-lifting and grew to a ratio of 2.1 (CI 1.1,3.9) at ≥16 weeks. Mortality in states that lifted their moratoriums was 1.6 (CI 1.2,2.3) times the mortality of states that maintained their moratoriums at 7 weeks post-lifting and grew to a ratio of 5.4 (CI 3.1,9.3) at ≥16 weeks. These results translate to an estimated 433,700 excess cases (CI 365200,502200) and 10,700 excess deaths (CI 8900,12500) nationally.
Lifting eviction moratoriums was associated with increased COVID-19 incidence and mortality, supporting the public health rationale for use of eviction moratoriums to prevent the spread of COVID-19.
Cases exploded in all states from roughly Sep-Oct onward until collapsing in January. This study fails to take in to account the time dimension – which is that nearly everywhere, given time, has the same outcomes. Consequently, what they think they have discerned is likely a factor of the time dimension and nothing to do with eviction moratoriums.
This is the model from last December projecting daily new cases under various scenarios. The column chart at bottom are the actual real world numbers that occurred. Since they didn’t know which scenario would happen, their range went from nothing to infinity.
The next chart is projected deaths due to Covid-19, from mid-January (solid red line). The actual real world deaths are plotted in the individual red points, below, and even well below the 95% confidence band.
This table compares the March 2020 Imperial College London (ICL, Neil Ferguson) projected deaths with actual deaths. Note – the actual deaths in Japan were over 9,000 at end of March – the value of 10 is an error in this table.
Disease models appear to be unfit for any purpose. We have seen this before.
These results indicate that COVID-19 is hazardous not only for the elderly but also for middle-aged adults, for whom the infection fatality rate is two orders of magnitude greater than the annualized risk of a fatal automobile accident and far more dangerous than seasonal influenza. Moreover, the overall IFR for COVID-19 should not be viewed as a fixed parameter but as intrinsically linked to the age-specific pattern of infections. Consequently, public health measures to mitigate infections in older adults could substantially decrease total deaths.
All infectious disease data is biased by how or if data is collected. Presently, we encourage testing of everyone with or without symptoms, even without potential contacts.
Similarly, when someone dies today, they are frequently tested for Covid-19. (If you go into the hospital for anything you will likely be tested for Covid-19).
We’ve never tested for any prior disease with the intensity we are testing for Covid-19.
A study of elderly patients who died in Spain in 2016-2017 found that only 7% had been diagnosed with any infectious disease prior to death – but when they were tested post death, 18% tested positive for influenza virus and 47% to some respiratory virus. This suggests many deaths from influenza or other viruses are not recorded as deaths due to flu or the other virus detected.
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