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Center for Infectious Disease Dynamics—YouTube. (n.d.). Retrieved 21 February 2021, from https://www.youtube.com/channel/UC1dZp4v6sF2jKjutJguk7ng/videos?view=0&sort=da&flow=grid&view_as=subscriber

Repostulation of Koch's rules in the era of the virueses.

The takeaway: Amino acids, represented by single letters such as N or Y make up proteins which are part of the coronavirus (as well as other biology such as animals, plants, microorganisms, etc.). Mutations are written with the original amino acid letter followed by the number of the amino acid and the new amino acid letter.

The claim: Proteins are made up of building blocks called amino acids. N501Y means that the 501st amino acid was originally an N, which stands for the amino acid asparagine, but has been changed to a Y, which stands for tyrosine.

The evidence:

Coronavirus is made up of greater than 20 proteins (1). The spike protein helps coronavirus attach and enter human cells which leads to infection and disease (1). The spike protein on SARS-CoV-2, the virus that causes COVID-19, is the target of many antibodies produced by the human body to fight the SARS-CoV-2 infection (2). Changes in the spike protein sequence may necessitate a change in the human immune system to produce antibodies which stop SARS-CoV-2 from infecting human cells. Changes in the amino acid sequence are written as was stated in the claim: original amino acid, number of the amino acid in the sequence, new amino acid.

Sources:

1) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7247499/

2) https://pubmed.ncbi.nlm.nih.gov/33448402/

Matrilocality, matrilinearity and egailitarianism.

Very interesting that a biology professor believes that 50% of what we learn can be wrong.

The takeaway: Even though mutations happen in all virus, vaccines still work. Current evidence about SARS-CoV-2 indicates that an effective COVID-19 vaccine can be obtained, and that it should be able to provide immunity against the virus.

The claim: A better analogy for COVID-19 is the mumps. For more than 45 years, we’ve had a very effective vaccine for measles, mumps, and rubella (which are also RNA viruses).

The evidence: We are all imperfect and we all make mistakes. For a virus, a mistake means the introduction of a mutation in its sequence, and RNA viruses (like the flu, mumps, measles virus, and SARS-CoV-2) have the highest error rates in nature. Mutations are indispensable for viral survival and evolution; this property is believed to benefit the viral population, allowing it to adapt and respond to different complex environments encountered during spread between hosts, within organs and tissues, and in response to the pressure of the host immune response [1]. How fast a virus is changing can be estimated by measuring its mutation rate, and then they can be classified as changing fast – high mutation rate – like HIV or Influenza, or as stable, like measles or mumps virus. SARS-CoV-2 has a mutation rate three times slower than the flu virus [2], but it's still changing faster than the mumps virus (the mutation rate of influenza is more than 10 times higher than mumps) [3]. Of course, how fast a virus can change has implications in the efficacy of treatments and vaccines, but it's not the only determinant. Even though mutations happen in all viruses, vaccines still work. A great example is the measles virus, as the antigenic composition of the vaccine (the molecules that “wake up” the immune system) used to prevent it has remained efficient since it was developed, in the 1960s, and confers protection against the 24 circulating genotypes [4]. The same is true for the mumps virus, with a vaccine that has been efficient for many decades [5]. Sequencing data suggest that coronaviruses change more slowly than most other RNA viruses, probably because of a viral ‘proofreading’ activity that corrects all the copying mistakes [6]. Taken together, all this evidence indicates that an effective COVID-19 vaccine can be obtained, and that it should be able to provide lasting immunity against the virus.

Sources:<br> 1

2 SARS-CoV-2 mutation rate: 1.26 x 10-3 substitutions/site/year

3 Influenza (flu-virus) mutation rate: 3.68 x 10-3 substitutions/site/year. Mumps mutation rate: 2.98 × 10−4 substitutions/site/year

4

5

6

scale free networks perhaps?

I had bookmarked this article in the form of tearing out and keeping a paper copy of it in my to read pile back in 2008. Finally getting around to reading it today. It's still an interesting introduction to the broader area which has moved forward, but not significantly enough to date the entire area.

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Take Away: Most germicidal ultraviolet (UV) lamps emit a wavelength of around 254 nm. While these are very effective means of sterilization, they are also damaging to human skin and eyes and therefore are used in unoccupied spaces. However, a recent study has shown that a safer form of UV light at a wavelength of 222 nm is effective in killing SARS-CoV-2 virus in vitro.

The Claim: Researchers offer first proof that Ultraviolet C light with a 222 nm wavelength — which is safer to use around humans — effectively kills the SARS-CoV-2 virus.

The Evidence: The authors reference the safety of 222 nm UV light, and there are many studies to support this claim. 222 nm UV light has been shown to not cause DNA damage or skin lesions even at higher doses and for longer exposure times than used here (1, 2).

In the study referenced, researchers at Hiroshima University exposed SARS-CoV-2 virus to low dosage 222 nm UV light and subsequently measured the amount of viable virus (3). They found that exposure of 0.1 mW/cm^2 for 30 seconds reduced the amount of viable virus by 99.7%. However, as the authors note, this study was performed using virus plated on a dish in a hood, and translation of these results to a public setting is unclear. For instance, in a hospital, there are many different types of surfaces and direct/consistent exposure to the UV light might not be feasible. While this study is promising, additional studies need to be done before promoting this as a safe and effective means of killing SARS-CoV-2 in an occupied environment.

Sources: 1) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6059456/

2) https://onlinelibrary.wiley.com/doi/abs/10.1111/php.13269

3) https://www.sciencedirect.com/science/article/pii/S0196655320308099#:~:text=Results,after%20a%205%2Dmin%20irradiation.

Take Away: The exact frequency of false positive test results for COVID-19 is unknown. Real world data on COVID-19 testing suggests that rigorous testing regimes likely produce fewer than 1 in 10,000 (<0.01%) false positives, orders of magnitude below the frequency proposed here.

The Claim: The reported numbers for new COVID-19 cases are overblown due to a false positive rate of 0.8%

The Evidence: In this opinion article, the author correctly conveys the concern that for large testing strategies, case rates could become inflated if there is (a) a high false positive rate for the test and (b) there is a very low prevalence of the virus within the population. The false positive rate proposed by the author is 0.8%, based on the "lowest value" for similar tests given by a briefing to the UK's Scientific Advisory Group for Emergencies (1).

In fact, the briefing states that, based on another analysis, among false positive rates for 43 external quality assessments, the interquartile range for false positive rate was 0.8-4.0%. The actual lowest value for false positive rate from this study was 0% (2).

An upper limit for false positive rate can also be estimated from the number of tests conducted per confirmed COVID-19 case. In countries with low infection rates that have conducted widespread testing, such as Vietnam and New Zealand, at multiple periods throughout the pandemic they have achieved over 10,000 tests per positive case (3). Even if every single positive was false, the false positive rate would be below 0.01%.

The prevalence of the virus within a population being tested can affect the positive predictive value of a test, which is the likelihood that a positive result is due to a true infection. The author here assumes the current prevalence of COVID-19 in the UK is 1 in 1,000 and the expected rate of positive results is 0.1%. Data from the University of Oxford and the Global Change Data Lab show that the current (Sept. 22, 2020) share of daily COVID-19 tests that are positive in the UK is around 1.7% (4). Therefore, based on real world data, the probability that a patient is positive for the test and does have the disease is 99.4%.

Sources: (1) https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/895843/S0519_Impact_of_false_positives_and_negatives.pdf

(2) https://www.medrxiv.org/content/10.1101/2020.04.26.20080911v3.full.pdf+html

(3) https://ourworldindata.org/coronavirus-data-explorer?yScale=log&zoomToSelection=true&country=USA~DEU~IND~ITA~AUS~VNM~FIN~NZL~GBR&region=World&testsPerCaseMetric=true&interval=smoothed&aligned=true&smoothing=7&pickerMetric=location&pickerSort=asc

(4) https://ourworldindata.org/coronavirus-data-explorer?zoomToSelection=true&country=USA~DEU~IND~ITA~AUS~VNM~FIN~NZL~GBR&region=World&positiveTestRate=true&interval=smoothed&aligned=true&smoothing=7&pickerMetric=location&pickerSort=asc

Take Away: This is an incorrect usage of the term "false positive." A positive PCR test result from a recovered infection is a valid and true positive.

Claim: PCR tests for SARS-CoV-2 give false positive results when there is no active virus.

Evidence: The diagnostic PCR tests currently in widespread use are designed to detect the presence of the SARS-CoV-2 viral RNA in a clinical sample. The RNA is only a part of the complete virus and is not infectious on its own. Research has shown that viral RNA can be detected in some samples up to 12 weeks after onset of symptoms (1). In other words, this is like testing if an oven is warmer than the room temperature - it could be hot even after it has been turned off.

By definition, in the context of SARS-CoV-2 PCR tests, a "false positive" means that a test result is deemed positive when in reality there was no viral RNA in the sample. If a person is recovering from an infection, gets tested, and then is given a positive test result, that is a true positive regardless of whether they are infectious or not.

Sources: 1) https://www.cdc.gov/coronavirus/2019-ncov/hcp/duration-isolation.html

Take away: People are infectious for only part of the time they test positive. The tests for COVID-19 were granted emergency status by the FDA so some debate concerning the most ideal number of cycles is to be expected. It is worth noting that the FDA has the disclaimer "Negative results do not preclude 2019-nCoV infection and should not be used as the sole basis for treatment or other patient management decisions. Negative results must be combined with clinical observations, patient history, and epidemiological information (2)."

The claim: Up to 90 percent of people diagnosed with coronavirus may not be carrying enough of it to infect anyone else

The evidence: Per Walsh et al. (1), SARS-CoV-2 virus (COVID-19) is most likely infectious if the number of PCR cycles is <24 and the symptom onset to test is <8 days. RT-PCR detects the RNA, not the infectious virus. Therefore, setting the cycle threshold at 37-40 cycles will most likely result in detecting some samples with virus which is not infectious. As the PCR tests were granted emergency use by the FDA (samples include 2-9), it is not surprising that some debate exists currently about where the cycle threshold should be. Thresholds need to be set and validated for dozens of PCR tests currently in use. If identifying only infectious individuals is the goal, a lower cycle number may be justified. If detection of as many cases as possible to get closer to the most accurate death rate is the goal, setting the cycle threshold at 37-40 makes sense. A lower threshold will result in fewer COVID-19 positive samples being identified. It is worth noting that the emergency use approval granted by the FDA includes the disclaimer that a negative test does not guarantee that a person is not infected with COVID-19. RNA degrades easily. If samples are not kept cold or properly processed, the virus can degrade and result in a false negative result.

Source: 1 https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciaa638/5842165

2 https://www.fda.gov/media/134922/download

3 https://www.fda.gov/media/138150/download

4 https://www.fda.gov/media/137120/download

5 https://www.fda.gov/media/136231/download

6 https://www.fda.gov/media/136472/download

7 https://www.fda.gov/media/139279/download

8 https://www.fda.gov/media/136314/download

9 https://www.fda.gov/media/140776/download

Take Away: Diagnostic tests are most useful when they are both sensitive and rapid. The sensitivity of SARS-CoV-2 PCR tests is not the issue, but rather the time it takes to get a result. Additionally, the "90%" statistic is likely misleading due to the data source and not generalisable to all testing results.

The Claim: The usual PCR diagnostic tests may be too sensitive and too slow, with up to 90% of positive cases due to trace amounts of virus.

The Evidence: Polymerase Chain Reaction (PCR)-based tests, which are currently in the most widespread use for detection of SARS-CoV-2 RNA, involves a molecular process that amplifies target DNA sequences in repeated temperature-dependent cycles. The amount of target DNA is measured after each cycle and the number of the cycle when the target can be reliably detected is often referred to as the cycle threshold (Ct). The Ct value is proportional to the amount of starting DNA in the sample and can be used to estimate the viral load of a patient. In some ways this is like a teacher making photocopies of a chapter from a textbook until they have enough for all their students.

However, Ct values are relative measurements and need to be directly compared to controls for every sample - a Ct value taken alone can be meaningless. For instance, consider an infected patient who is tested twice: the first time they are gently swabbed and the sample is relatively dilute, the second time they are vigorously swabbed and the sample is relatively concentrated. The resulting Ct values could be drastically different. Therefore, Ct values need to be considered carefully in the proper context for making medical or policy decisions. The FDA also recommends that a PCR result alone should not be used to determine infection status.

Positive results are indicative of the presence of SARS-CoV-2 RNA; clinical correlation with patient history and other diagnostic information is necessary to determine patient infection status. (1)

Current PCR test results are generally given as a binary positive/negative based on a cutoff value for Ct. The cutoff needs to be determined based on the performance of each individually developed SARS-CoV-2 test, of which there are currently over 160 that have been granted emergency use authorization by the FDA (2). Based on unpublished data from the CDC, setting a stringent Ct cutoff of 30 could return negative results in patients who are both infected and potentially infectious (3 Fig 5). Furthermore, a 30 cycle cutoff would return invalid results for samples which are too diluted. Based on the same CDC data, up to 30% of potentially infectious patients would get invalid results and need to be re-swabbed, thereby extending the time between getting infected and getting a positive result.

The period of time when RNA from SARS-CoV-2 can be detected (and a positive PCR test result returned) may extend up to 12 weeks after recovery, with Ct values trending higher over time (3,4). According to The New York Times article, they looked at Ct values from people who tested positive in Massachusetts in July and found 85-90% of results had Ct values greater than 30. The epidemiology of COVID-19 is highly time and region dependent. Massachusetts had a peak in COVID-19 hospitalizations on April 21 (5), which is 9-12 weeks prior to the testing data analyzed by The NY Times. Therefore, the detection of a large proportion of people with lingering viral RNA is not surprising. These results are likely not universal and can not be applied to other regions, especially where community spread is still significant.

Sources:

(1) https://www.fda.gov/media/135900/download

(2) https://www.fda.gov/medical-devices/coronavirus-disease-2019-covid-19-emergency-use-authorizations-medical-devices/vitro-diagnostics-euas

(3) https://www.cdc.gov/coronavirus/2019-ncov/hcp/duration-isolation.html

(4) Li N, Wang X, Lv T. Prolonged SARS-CoV-2 RNA Shedding: Not a Rare Phenomenon. J Med Virol 2020 Apr 29. doi: 10.1002/jmv.25952.

(5) https://www.bostonherald.com/2020/05/22/massachusetts-finally-seeing-downward-coronavirus-trends/

Take away: Current polymerase chain reaction (PCR) testing technology is very sensitive and specific. Even for rapidly developed new tests for the novel coronavirus, SARS-CoV-2, available clinical data indicates they are highly accurate.

The claim: SARS-CoV-2 testing is unreliable and plagued by false positive results.

The evidence: Any diagnostic test has some degree of error that is typically very low for FDA approved products. For SARS-CoV-2 tests, which detect the presence of the virus that causes COVID-19, although rare, it is possible to get a positive result when you may not have been exposed or infected by the virus. In other words, a false positive. So how frequently do false positives occur?

There is no universal false positive rate for SARS-CoV-2 test results because there are dozens of different tests that have been developed and deployed, each with their own error rate. As of August 26, 2020, there are 146 commercial diagnostic tests that have received emergency use authorization from the FDA. Data from clinical performance testing submitted to the FDA indicates that PCR tests are highly accurate. For example, the specific PCR test mentioned by the author, Quest Diagnostics SARS-CoV-2 rRT-PCR, obtained 100% correct results in clinical evaluation studies (n = 60), and 100% true negative results in a random population of samples from before the pandemic (n = 72).

Additional considerations: In addition to PCR technology-based tests, which detect the viral RNA genome and require lab processing, there are antigen tests, which use antibodies to detect viral proteins and can be rapidly performed in point-of-care settings. Antigen tests are much easier to perform than PCR tests, but they can be less sensitive. For example, the LumiraDx SARS-CoV-2 Ag Test, when compared to PCR, has an overall agreement of 96.9%.

The author provides two anecdotes of high-profile personnel who obtained false positive test results. For the Ohio Governor, his initial positive was from an antigen test, not a PCR test. The NFL quarterback is part of a unique population that is presumed to be largely SARS-CoV-2 negative but is being tested frequently and repeatedly. This scenario increases the probability that a positive test result may be false. However, the NFL in early August said it has conducted over 75,000 tests, so unless there are many additional cases of false positives, this suggests that their testing methodology is over 99.99% accurate.

Schizophrenia is unique to humans. There are also regions that human and other species have, but have undergone more rapid evolution in humans called Human Accelerated regions (HAR).

Maybe these HARs and Schizophrenia are linked.

Also HARs are regions whose purpose is to regulate the expression of other genes, not so much directly code for a protein.

Take away: The COVID-19 virus (SARS-CoV2) did not exist in 2012, however a related virus was isolated from bats in 2013.

The claim: The same virus that is causing the COVID-19 pandemic existed in miners in 2012.

The evidence:RaTG13, a virus that was isolated from bats by the Wuhan Institute of Virology in 2013 is the closest known relative to SARS-CoV2, the virus that causes COVID-19 (Ge 2016, Zhou 2020). This bat virus is not the same virus as SARS-CoV2, but is closely related (96% identical DNA). The virus was isolated from bats, not humans. However, it was isolated from a cave near where workers the previous year became sick and some died, and may be linked to the illnesses. The SARS-CoV2 virus shows a number of key adaptations that likely makes it much more infectious in humans than the related bat virus (Wrobel, 2020).

Source:

Ge XY, Wang N, Zhang W, Hu B, Li B, Zhang YZ, Zhou JH, Luo CM, Yang XL, Wu LJ, Wang B. Coexistence of multiple coronaviruses in several bat colonies in an abandoned mineshaft. Virologica Sinica. 2016 Feb 1;31(1):31-40.

Zhou P, Yang XL, Wang XG, Hu B, Zhang L, Zhang W, Si HR, Zhu Y, Li B, Huang CL, Chen HD. A pneumonia outbreak associated with a new coronavirus of probable bat origin. nature. 2020 Mar;579(7798):270-3.

Wrobel AG, Benton DJ, Xu P, Roustan C, Martin SR, Rosenthal PB, Skehel JJ, Gamblin SJ. SARS-CoV-2 and bat RaTG13 spike glycoprotein structures inform on virus evolution and furin-cleavage effects. Nature Structural & Molecular Biology. 2020 Aug;27(8):763-7.

LucyinLockdown: Viruses, Pandemics and Lessons Learnt with Dr Jane Greatorex—YouTube. (2020, June 18). https://youtu.be/5U1go5hyen8

Crespi, S., Wadman, M., (2020). Why men may have more severe COVID-19 symptoms, and using bacteria to track contaminated food. Science | AAAS. https://www.sciencemag.org/podcast/why-men-may-have-more-severe-covid-19-symptoms-and-using-bacteria-track-contaminated-food?utm_campaign=SciMag&utm_source=JHubbard&utm_medium=Twitter

This explanation is garbled and misstated. Genetic material is stored in DNA in the nucleus of the cell. Messenger RNA (mRNA) molecules carry the information stored within the DNA to the rest of the cell. Both DNA and RNA are a type of molecule called a "nucleic acid." Once outside the nucleus, the information in the messenger RNA can then be read, or "translated," to create proteins, such as the spike protein used by SARS-CoV-2. These proteins in turn carry out a wide variety of tasks that allow cells to function. This process is known as the "Central Dogma of Molecular Biology".

Bristol, U. of. (n.d.). Avon Longitudinal Study of Parents and Children | Avon Longitudinal Study of Parents and Children | University of Bristol. University of Bristol. Retrieved July 18, 2020, from http://www.bristol.ac.uk/alspac/

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