It takes a week or two for an infected person to start producing the antibody IgG which is the type of antibody that typically gets tested for.

[[Z: Antibody tests are only useful to see if you had an infection in the past]]

Third of newborns with Covid infected before or during birth – study. (2020, October 15). The Guardian. http://www.theguardian.com/world/2020/oct/15/thirty-per-cent-of-newborn-babies-with-covid-contract-it-before-or-during-birth

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

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/

Lewandowsky, Stephan, Simon Dennis, Amy Perfors, Yoshihisa Kashima, Joshua White, Paul Michael Garrett, Daniel R. Little, and Muhsin Yesilada. ‘Public Acceptance of Privacy-Encroaching Policies to Address the COVID-19 Pandemic in the United Kingdom’. Preprint. PsyArXiv, 4 September 2020. https://doi.org/10.31234/osf.io/njwmp.

‘Schools “no Greater Risk” for Children and Staff’. BBC News, 5 September 2020, sec. Health. https://www.bbc.com/news/health-54025708.

Yong, Ed. ‘Immunology Is Where Intuition Goes to Die’. The Atlantic, 5 August 2020. https://www.theatlantic.com/health/archive/2020/08/covid-19-immunity-is-the-pandemics-central-mystery/614956/.

Aum, S., Lee, S. Y. (Tim), & Shin, Y. (2020). Inequality of Fear and Self-Quarantine: Is There a Trade-off between GDP and Public Health? (Working Paper No. 27100; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27100

Vaughan, A. (n.d.). Which covid-19 treatments work and how close are we to getting more? New Scientist. Retrieved 31 July 2020, from https://www.newscientist.com/article/2250176-which-covid-19-treatments-work-and-how-close-are-we-to-getting-more/

EDT, Bryan Kirk On 7/17/20 at 12:49 PM. ‘Parents Consider “COVID Mixers” to Infect Healthy Children and Build Herd Immunity’. Newsweek, 17 July 2020. https://www.newsweek.com/parents-mull-covid-mixers-infect-healthy-children-build-herd-1518661.

Expert comments about herd immunity | Science Media Centre. (n.d.). Retrieved April 14, 2020, from https://www.sciencemediacentre.org/expert-comments-about-herd-immunity/

r/medicine - Are “immunity certificates” actually feasible? Thoughts from an expert on viral antibodies. (n.d.). Reddit. Retrieved April 21, 2020, from https://www.reddit.com/r/medicine/comments/g1ty3g/are_immunity_certificates_actually_feasible/

Thread by @taaltree: Antibody tests are coming online. Never before have humans needed to understand Bayes rule more. Let’s talk about why it’s critical NOT to a…. (n.d.). Retrieved April 21, 2020, from https://threadreaderapp.com/thread/1248467731545911296.html

editor, S. B. H. (2020, April 20). WHO warns that few have developed antibodies to Covid-19. The Guardian. https://www.theguardian.com/society/2020/apr/20/studies-suggest-very-few-have-had-covid-19-without-symptoms

Bernheim, A., Mei, X., Huang, M., Yang, Y., Fayad, Z. A., Zhang, N., Diao, K., Lin, B., Zhu, X., Li, K., Li, S., Shan, H., Jacobi, A., & Chung, M. (2020). Chest CT Findings in Coronavirus Disease-19 (COVID-19): Relationship to Duration of Infection. Radiology, 200463. https://doi.org/10.1148/radiol.2020200463

Adams, E. R., Anand, R., Andersson, M. I., Auckland, K., Baillie, J. K., Barnes, E., Bell, J., Berry, T., Bibi, S., Carroll, M., Chinnakannan, S., Clutterbuck, E., Cornall, R. J., Crook, D. W., Silva, T. D., Dejnirattisai, W., Dingle, K. E., Dold, C., Eyre, D. W., … Sanchez, V. (2020). Evaluation of antibody testing for SARS-Cov-2 using ELISA and lateral flow immunoassays. MedRxiv, 2020.04.15.20066407. https://doi.org/10.1101/2020.04.15.20066407