- Oct 2020
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For every one confirmed case, Redfield said, the CDC estimates that 10 more people have been infected.
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
3) https://www.medrxiv.org/content/10.1101/2020.07.09.20148429v1
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