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Abdul-Jabbar, K. (2021, November 8). Aaron Rodgers Didn’t Just Lie [Substack newsletter]. Kareem Abdul-Jabbar. https://kareem.substack.com/p/aaron-rodgers-didnt-just-lie

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Shen, X.-R., Geng, R., Li, Q., Chen, Y., Li, S.-F., Wang, Q., Min, J., Yang, Y., Li, B., Jiang, R.-D., Wang, X., Zheng, X.-S., Zhu, Y., Jia, J.-K., Yang, X.-L., Liu, M.-Q., Gong, Q.-C., Zhang, Y.-L., Guan, Z.-Q., … Zhou, P. (2022). ACE2-independent infection of T lymphocytes by SARS-CoV-2. Signal Transduction and Targeted Therapy, 7(1), 1–11. https://doi.org/10.1038/s41392-022-00919-x

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AAI. (2022, January 29). More than seventy peer-reviewed #COVID-19, #SARS, and #MERS @J_Immunol articles are #FreeToRead http://ow.ly/lwTr50Hyu5F #immunology #ReadTheJI https://t.co/7Hi4g8ZySp [Tweet]. @ImmunologyAAI. https://twitter.com/ImmunologyAAI/status/1487425781647216646

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Murray, J. (2021, December 28). Omicron is ‘not the same disease’ as earlier Covid waves, says UK scientist. The Guardian. https://www.theguardian.com/world/2021/dec/28/omicron-is-not-the-same-disease-as-earlier-covid-waves-says-uk-scientist

Eric Topol. (2021, October 19). Just published @ScienceTM With blunting of the immune response, why it is so important for pregnant women to get a Covid vaccine https://science.org/doi/10.1126/scitranslmed.abm2070 w/ @ScienceVisuals https://t.co/aCY6LP4Taa [Tweet]. @EricTopol. https://twitter.com/EricTopol/status/1450475410328850435

Altmann, D. M., & Boyton, R. J. (2021). SARS-Cov-2 immune waning and reinfection in care-home settings. The Lancet. Healthy Longevity, 2(12), e776–e777. https://doi.org/10.1016/S2666-7568(21)00276-2

Where does all the mRNA end up, according to this 2015 study on mice](https://www.ncbi.nlm.nih.gov/labs/pmc/articles/PMC4624045/)?

Here we learn stuff not reorted in the paper.

Cause for optimism on Omicron: Our immune systems aren’t blank slates. (2021, December 1). STAT. https://www.statnews.com/2021/12/01/a-reason-for-optimism-on-omicron-our-immune-systems-are-not-blank-slates/

Interesting diffs between IgG1, Ig2, IgG3, IgG4.

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Mallapaty, S. (2021). The search for people who never get COVID. Nature. https://doi.org/10.1038/d41586-021-02978-6

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Willyard, C. (2021). How antiviral pill molnupiravir shot ahead in the COVID drug hunt. Nature. https://doi.org/10.1038/d41586-021-02783-1

COVID-19 immunity: Natural infection compared to vaccination | British Society for Immunology. (n.d.). Retrieved October 10, 2021, from https://www.immunology.org/coronavirus/connect-coronavirus-public-engagement-resources/covid-immunity-natural-infection-vaccine

Gee, S., Chandiramani, M., Seow, J., Pollock, E., Modestini, C., Das, A., Tree, T., Doores, K. J., Tribe, R. M., & Gibbons, D. L. (2021). The legacy of maternal SARS-CoV-2 infection on the immunology of the neonate. Nature Immunology. https://doi.org/10.1038/s41590-021-01049-2

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John Burn-Murdoch. (2021, August 23). NEW: in the last couple of weeks there have a lot of new studies out assessing vaccine efficacy, many of which have touched on the question of waning immunity. Unsurprisingly, these have prompted a lot of questions. Time for a thread to summarise what we do and don’t know: [Tweet]. @jburnmurdoch. https://twitter.com/jburnmurdoch/status/1429878189011111936

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What the World Health Organization really said about mixing COVID-19 vaccines | CBC News. (n.d.). Retrieved July 15, 2021, from https://www.cbc.ca/news/health/covid-19-vaccine-mixing-and-matching-who-1.6101047?__vfz=medium%3Dsharebar

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Lewis, D. (2021). Mix-and-match COVID vaccines: The case is growing, but questions remain. Nature. https://doi.org/10.1038/d41586-021-01805-2

Subbaraman, N. (2021). This COVID-vaccine designer is tackling vaccine hesitancy—In churches and on Twitter. Nature, 590(7846), 377–377. https://doi.org/10.1038/d41586-021-00338-y

Radbruch, A., & Chang, H.-D. (2021). A long-term perspective on immunity to COVID. Nature. https://doi.org/10.1038/d41586-021-01557-z

Ibarrondo, F. J., Hofmann, C., Fulcher, J. A., Goodman-Meza, D., Mu, W., Hausner, M. A., Ali, A., Balamurugan, A., Taus, E., Elliott, J., Krogstad, P., Tobin, N. H., Ferbas, K. G., Kitchen, S. G., Aldrovandi, G. M., Rimoin, A. W., & Yang, O. O. (2021). Primary, Recall, and Decay Kinetics of SARS-CoV-2 Vaccine Antibody Responses. ACS Nano. https://doi.org/10.1021/acsnano.1c03972

Vaccines should end the pandemic, despite the variants, say experts – Harvard Gazette. (n.d.). Retrieved June 19, 2021, from https://news.harvard.edu/gazette/story/2021/02/vaccines-should-end-the-pandemic-despite-the-variants-say-experts/

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ReconfigBehSci. (2020, November 21). RT @DrEricDing: Good question for immunologists like @michaelmina_lab @VirusesImmunity and @PeterHotez. Https://t.co/Rs1zaUPznm [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1334804615842439170

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Ledford, H. (2020). Oxford COVID-vaccine paper highlights lingering unknowns about results. Nature. https://doi.org/10.1038/d41586-020-03504-w

A Marm Kilpatrick. (2020, December 8). FDA Pfizer/BioNTech vaccine efficacy results are great, but aren’t nearly as great as presented for severe infections. Everyone has seen fig below on cases in vaccine (blue) & placebo (red) over time. Thread. Https://t.co/vlZyZgJ7hr https://t.co/9ZWeWCko1x [Tweet]. @DiseaseEcology. https://twitter.com/DiseaseEcology/status/1336446195284070400

The takeaway: Current data for three separate COVID-19 vaccines suggests that the vaccine prevents COVID-19 or lessens the disease severity. No data from top three COVID-19 vaccine candidates indicates that the vaccine makes the disease worse. Phase III clinical trials to conclusively prove the effect of the vaccine will be completed before administration of the vaccine to the general public.

The claim: The vaccine may make COVID-19 much, much worse in many people.

The evidence: A number of protein sequences encoded by SARS-CoV-2 genome are similar to human proteins (1). This similarity led to the hypothesis that a SARS-CoV-2 vaccine could result in more severe disease when exposure occurs after vaccination (1). For previous SARS and MERS, this severe reaction was observed during the animal studies and therefore the vaccines were not pursued. The hypothesis was proposed before SARS-CoV-2 animal study vaccines were published as stated in (1).

Three vaccines are currently in phase III clinical development in the USA, funded by Operation Warp Speed (2). Vaccine approval process involves four stages (3). Phase I is a small scale study in healthy people to make sure the vaccine does no harm. Phase II is a study with more people to test whether the vaccine does what it is supposed to do. Phase III study occurs in 300-3000 people to ensure that the vaccine works as intended in a larger group of people. Phase IV is post-approval monitoring of the vaccine for an adverse events that may happen after the drug is approved. Human study in Phase I clinical trials only occurs after the vaccine has been proven safe in animals first.

Moderna’s mRNA-1273 prevented COVID-19 disease in monkeys (4). Control monkeys' lungs showed signs of pneumonia from COVID-19. Lungs in vaccinated monkeys were normal after exposure to COVID. The virus was not detectable in the monkey's nose after two days for animals vaccinated with 100 ug dose. Phase I clinical trial data from humans is published and included older adults (5).

University of Oxford and AstraZeneca’s AZD1222 (ChAdOx1 nCoV-19) prevented pneumonia in monkeys and did not cause disease enhancement (6). AZD1222 reduced the number of SARS-CoV-2 (virus) in the lung of the monkeys but did not stop the virus from leaving the nose of the monkeys. Early results from the phase I/II clinical trials demonstrate the safety of the vaccine (7). Further research is ongoing to establish safety and efficacy. This includes phase III clinical trials with more participants and one year monitoring of Phase II participants.

Pfizer and BioNTech's BNT162 is several different vaccine candidates which were tested simultaneously to determine the vaccine with the best protection and least number of reactions such as pain at the injection site, fever, etc (8). In phase I/II clinical trails, the reactions to BNT162b1 were mild to moderate and did not last long (9). Animal studies are presented as a pre-print (10). From the pre-print, it is unclear whether the vaccine prevented lung damage because both vaccine and control group had no lung damage. In other rhesus macaque COVID infections with no vaccine, lung damage was observed (4, 6). BNT162b2 COVID vaccine resulted in no detectable COVID virus after the first day of challenge in monkeys (10).

Sources:

1) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7142689/

2) https://www.raps.org/news-and-articles/news-articles/2020/3/covid-19-vaccine-tracker

3) https://www.fda.gov/patients/drug-development-process/step-3-clinical-research

4) https://pubmed.ncbi.nlm.nih.gov/32722908/

5) https://www.nejm.org/doi/full/10.1056/NEJMoa2028436?query=featured_home

6) https://pubmed.ncbi.nlm.nih.gov/32731258/

7) https://pubmed.ncbi.nlm.nih.gov/32702298/

8) https://www.nejm.org/doi/full/10.1056/NEJMoa2027906?query=featured_home#

9) https://pubmed.ncbi.nlm.nih.gov/32785213/

10) https://www.biorxiv.org/content/10.1101/2020.09.08.280818v1.full.pdf

Take away: While this estimate may be the most accurate at the time there are several reasons (addressed below) why any estimate provided at this time may be imprecise. As more data is accrued, including information on the immunological dynamics of the SARS-CoV2 antibodies, we should expect to see a more accurate estimate.

The claim: For every one confirmed case the CDC estimates that another 10 more people have been infected.

The evidence: This estimate was revealed in a press briefing with CDC Director Robert Redfield on June, 25, 2020. It is important to emphasize that this is an estimate extrapolated from the collective data of numerous seroprevalence surveys (antibody tests) performed in different locations across the U.S. While it is most definitely true that the reported case numbers are lower than the actual, given the prevalence of asymptomatic individuals that do not visit medical centers to be tested, the actual figure may be lower or higher than the estimate presented here due to a variety of factors including:

1) Areas surveyed: Indeed, it is known that the number of cases vary disproportionately across different areas of the U.S. According to the CDC, three types of seroprevalence surveys are commonly performed: large-scale geographic, community-level, and special populations. It is important to note that each survey may or may not be completely representative of the specific area yet alone the U.S. as a whole.

2)Type of antibody testing: The FDA reported on the performance of numerous EUA authorized serology tests. The conclusion is that each test has varying levels of accuracy and confidence intervals. As the estimate provided by Redfield was most likely obtained from data derived from the specific test used at each individual surveillance site, the figure may be further skewed by the accuracy of each test.

3)Origin of blood samples: The type of individuals from which the blood samples tested originated may have a significant effect on the Redfield’s estimate. For example, if certain surveillance sites are exclusively testing samples from sick patients, the estimate may be an overestimate as a population presenting COVID symptoms is more likely to test positive than a healthy-looking population. Therefore, a detailed characterization of the individuals from which the blood was obtained would be needed in order to uphold accuracy.

4)Time of tests: As the advent of antibodies can occur a week or longer post-infection, individuals who have recently been infected may not have detectable levels of antibodies and may come up as false negatives. It is also possible for an individual to simply not produce enough antibodies to be detectable by a given serology test. Furthermore, a recent paper published in medrxiv suggests that certain antibodies have reduced titers within 50 days of symptom onset.

Take away: While this estimate may be the most accurate at the time there are several reasons (addressed below) why any estimate provided at this time may be imprecise. As more data is accrued, including information on the immunological dynamics of the SARS-CoV2 antibodies, we should expect to see a more accurate estimate.

The claim: For every one confirmed case the CDC estimates that another 10 more people have been infected.

The evidence: This estimate was revealed in a press briefing with CDC Director Robert Redfield on June, 25, 2020. It is important to emphasize that this is an estimate extrapolated from the collective data of numerous seroprevalence surveys (antibody tests) performed in different locations across the U.S. While it is most definitely true that the reported case numbers are lower than the actual, given the prevalence of asymptomatic individuals that do not visit medical centers to be tested, the actual figure may be lower or higher than the estimate presented here due to a variety of factors including:

1) Areas surveyed: Indeed, it is known that the number of cases vary disproportionately across different areas of the U.S. According to the CDC, three types of seroprevalence surveys are commonly performed: large-scale geographic, community-level, and special populations (1). It is important to note that each survey may or may not be completely representative of the specific area yet alone the U.S. as a whole.

2)Type of antibody testing: The FDA reported on the performance of numerous EUA authorized serology tests (2). The conclusion is that each test has varying levels of accuracy and confidence intervals. As the estimate provided by Redfield was most likely obtained from data derived from the specific test used at each individual surveillance site, the figure may be further skewed by the accuracy of each test.

3)Origin of blood samples: The type of individuals from which the blood samples tested originated may have a significant effect on the Redfield’s estimate. For example, if certain surveillance sites are exclusively testing samples from sick patients, the estimate may be an overestimate as a population presenting COVID symptoms is more likely to test positive than a healthy-looking population. Therefore, a detailed characterization of the individuals from which the blood was obtained would be needed in order to uphold accuracy.

4)Time of tests: As the advent of antibodies can occur a week or longer post-infection, individuals who have recently been infected may not have detectable levels of antibodies and may come up as false negatives. It is also possible for an individual to simply not produce enough antibodies to be detectable by a given serology test. Furthermore, a recent paper published in medrxiv suggests that certain antibodies have reduced titers within 50 days of symptom onset (3).

To conclude, while this estimate may be the most accurate at the time given the available data, many factors can affect the figure and, in some instances, more information is needed as it is unclear exactly how this number was obtained from the information provided in the press briefing.

Sources: 1) https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/about-serology-surveillance.html

2) https://www.fda.gov/medical-devices/coronavirus-disease-2019-covid-19-emergency-use-authorizations-medical-devices/eua-authorized-serology-test-performance

3) https://www.medrxiv.org/content/10.1101/2020.07.09.20148429v1

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Scientists study whether immune response wards off or worsens Covid. (2020, October 4). The Guardian. http://www.theguardian.com/science/2020/oct/04/scientists-study-whether-immune-response-wards-off-or-worsens-covid

Take away: More research is needed before the conclusion can be reached that T-cells from common cold coronaviruses are protective against SARS-CoV-2.

The claim: A significant part of the population may be immune to SARS-CoV-2 due to cross-reactivity to T-cells from HCo infections (“common cold viruses”).

The evidence: T- cell cross reactivity between common cold coronaviruses and SARS-CoV-2 occurred in 20-50% of people not exposed to SARS-CoV-2 (1-4). This cross-reactivity from T-cells led to the speculative hypothesis that cross-reactivity explains why children and young adults are not affected as badly as older adults (1). Additional research is needed to conclude that the presence of cross-reactive T-cells leads to less severe COVID-19 disease and does not result in the cytokine storm which is harmful instead of helpful in recovery from COVID-19 (2, 4). Significant cross-reactivity between SARS-CoV-2 and HCo antibodies was not observed with 1064 serum samples when tested with ELISA (5). A small study found some cross-reactivity between SARS-CoV-2 and HCo using rapid immunochromatographic antibody test which tests the ability of antibodies to react with SARS-CoV-2 (6).

The immune system uses multiple components to rid the body of an infection. Innate immunity includes inflammation, fever, and cells which non-specifically destroy infectious/toxic particles (7). The adaptive immune system includes cells which adapt to the specific pathogen it is attacking (8). The adaptive immune system includes B cells and T cells. B cells produce antibodies. Antibodies bind and neutralize toxins/infectious particles. T cells kill infected human cells which present antigens, infectious particle identifiers, which specific T cells recognize. A summary of the immune system's interaction with SARS-CoV-2 is written (9). Additional discussion can be found (10, 11).

In conclusion, T-cell cross reactivity was shown to occur (1-4). More research is needed to conclusively determine whether the presence of HCo cross-reactive T-cells leads to prevention or less severe infection by SARS-CoV-2.

Sources:

1 https://www.nature.com/articles/s41577-020-0389-z

2 https://www.cell.com/cell/fulltext/S0092-8674(20)30610-3?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0092867420306103%3Fshowall%3Dtrue

3 https://pubmed.ncbi.nlm.nih.gov/32766111/

4 https://www.nature.com/articles/s41586-020-2550-z

5 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7417941/

6 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7381928/

7 https://www.ncbi.nlm.nih.gov/books/NBK26846/

8 https://www.ncbi.nlm.nih.gov/books/NBK21070/

9 https://www.cell.com/trends/pharmacological-sciences/pdf/S0165-6147(20)30130-9.pdf?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0165614720301309%3Fshowall%3Dtrue

10 https://blogs.sciencemag.org/pipeline/archives/2020/07/07/more-on-t-cells-antibody-levels-and-our-ignorance

11 https://twitter.com/EricTopol/status/1278400526716211200?s=20

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Broader impact on economy - college campuses, tourism.

Why wasn't more testing done?

CNN, A. K. (n.d.). Fewer than 10% in the US have antibodies to the novel coronavirus. CNN. Retrieved September 29, 2020, from https://www.cnn.com/2020/09/25/health/coronavirus-antibodies-dialysis-patients/index.html

Over 250,000 volunteers now registered for new COVID-19 vaccine trials as recruitment begins for Novavax study. (n.d.). Retrieved September 28, 2020, from https://www.nihr.ac.uk/news/over-250000-volunteers-now-registered-for-new-covid-19-vaccine-trials-as-recruitment-begins-for-novavax-study/25731

Doshi, P. (2020). Covid-19: Do many people have pre-existing immunity? BMJ, 370. https://doi.org/10.1136/bmj.m3563

Take away: Waning antibodies don’t necessarily mean that immunity will also decrease, because other components of the immune system retain “memory” for an infection and can combat invaders even after antibody counts have gone down.

The claim: “If you were infected with the novel coronavirus, a new study suggests that your immunity to the virus could decline within months.”

The evidence: This study [1], along with others [2], does indeed show evidence for declining neutralizing antibodies within a few months after infection; however, antibody counts alone are not enough to predict whether a patient will have durable immunity to a virus. Neutralizing antibodies are generated by B cells, a type of immune cell that patrols the body looking for their molecular targets. Some B cells carry “memory,” a quality that allows them to respond quickly when they see a virus or pathogen that they have encountered before, which allows them to pump out large quantities of antibody rapidly to fight the infection [3]. It’s actually normal in many viral infections for antibody levels within the blood to wane over time; the real concern is whether there are enough memory B cells to generate new antibodies at a moment’s notice.

In addition to B cells, a second type of immune cell known as a “T cell” is critical for predicting durable immunity. Like B cells, some T cells carry “memory” and can patrol the body for years looking for their targets. Some T cells play a role in helping B cells produce antibodies quickly, and other T cells can actually target the infection directly [4]. Studies have now shown that T cell responses can persist after SARS-CoV-2 infection, and some patients even have T cells that can react to SARS-CoV-2 due to “cross-reactivity,” likely from preexisting immunity from common cold viruses that share some characteristics of SARS-CoV-2. While this cross-reactivity does not guarantee immunity, the presence of robust B and T cell responses is important, and could be more predictive than presence of antibodies alone.

This article, written by a two well-known immunologists and COVID-19 experts at Yale University, provides a nice summary of the data that puts these claims in context [6].

Ponchner, D. (n.d.). Costa Rica Readies Horse Antibodies for Trials as an Inexpensive COVID-19 Therapy. Scientific American. Retrieved September 8, 2020, from https://www.scientificamerican.com/article/costa-rica-readies-horse-antibodies-for-trials-as-an-inexpensive-covid-19-therapy/