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Table.  Unweighted Characteristics of Study Participants and Proportion With IgM or IgG for SARS-CoV-2
Unweighted Characteristics of Study Participants and Proportion With IgM or IgG for SARS-CoV-2
1.
Spychalski  P, Błażyńska-Spychalska  A, Kobiela  J.  Estimating case fatality rates of COVID-19.   Lancet Infect Dis. 2020;S1473-3099(20)30246-2. Accessed April 9, 2020. Published online March 31, 2020. doi:10.1016/S1473-3099(20)30246-2PubMedGoogle Scholar
2.
Bendavid  E, Mulaney  B, Sood  N,  et al. COVID-19 antibody seroprevalence in Santa Clara County, California. medRxiv. Preprint posted online April 30, 2020. doi:10.1101/2020.04.14.20062463
3.
Los Angeles County announces 18 new deaths related to 2019 novel coronavirus (COVID-19)—475 new cases of confirmed COVID-19 in Los Angeles County. News release. Los Angeles County Department of Public Health. April 10, 2020. Accessed April 26, 2020. http://publichealth.lacounty.gov/phcommon/public/media/mediapubdetail.cfm?unit=media&ou=ph&prog=media&prid=2309
11 Comments for this article
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Test Accuracy
Kamran Kadkhoda, Ph.D., D(ABMM), D(ABMLI) | Cleveland Clinic
According to the large epidemiologic joint report (China-WHO), only 1% of the public were asymptomatic based on typical symptoms; and of symptomatic cases 81% were mild and moderate and 19% were severe and critical. This was also reviewed and summarized later in JAMA (1). Although in almost all jurisdictions severe and critical cases get tested for RNA (plus less severe cases based on expanded other indications), it is relatively safe to multiply the announced number of confirmed cases by 5 to arrive at the estimated total number of infected patients. 

Since the total number of confirmed COVID-19 cases LA
County is 37,974, multiply by 5 to = 189,870. The population of LA County is 10.04 million, for an estimated sero-prevalence of 1.89% (2.5-times the calculated value). With “claimed” sensitivity of 82.7% and specificity of 99.5%, the calculated positive predictive value will be 76%, meaning 24% of results are false positive. Since this kit has not been reviewed by FDA and there is no independent validation done for it, it is hard to conclude if the performance characteristics are truly what they have been claimed. This is especially true for specificity of 99.5% despite what the manufacturer’s product insert states: "Positive results may be due to past or present infection with non-SARS-CoV-2 coronavirus strains, such as coronavirus HKU1, NL63, OC43, or 229E" (2).
 
REFERENCE

1. Wu Z, McGoogan JM. Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China - Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention. JAMA.;2020;323(13):1239-1242. doi:10.1001/jama.2020.2648. https://jamanetwork.com/journals/jama/fullarticle/2762130. 

2. 
https://premierbiotech.com/innovation/wp-content/uploads/2020/03/COVID-19-Letter-of-Intent-FDA.pdf



CONFLICT OF INTEREST: None Reported
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Implausible Estimate
Adam King, Ph.D. Biostatistics | California State Polytechnic University, Pomona
The authors estimate that around April 11 there were around 367,000 cumulative cases in L.A. county. At that time however, there were only around 600 total confirmed COVID-19 deaths in the entire state. Currently, L.A. county has around half the state's death total, so even if the 600 figure is an undercount of the California total by a factor of 2, we arrive at an infection fatality rate of 0.16%. On the other hand, New York City currently has a TOTAL fatality rate of 15789/8399000 = 0.188%. Given that seroprevalence studies in NYC are only estimating around 20% infected, that means the death rate in L.A. would have to be around five times lower than in NYC, which is completely implausible.
CONFLICT OF INTEREST: None Reported
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We Need Better Data Now
Ben Justice, Biological Sciences | Industry
The results from this study do not align with results from the much more extensive New York data available. Projecting New York data onto the Los Angeles population would have a 2 to 4% infected rate today, 05/19/20. This is far lower than the study estimated. Although there are many differences between the New York and the Los Angeles outbreaks, the author's projections could only be a result of radically different populations and are very unlikely.

https://www.worldometers.info/coronavirus/coronavirus-death-rate/

The fact that there has been no follow up data published or an attempt to repeat the results
using a more accurate serology test and better randomized sampling is very disappointing. I

Please LA County Health, start a project to understand the outbreak, perform daily random population surveillance sampling (using the virus and the antibody test), and begin testing all essential workers and everyone 15-30 once a week for the virus. This population is the highest risk spreaders. Eventually test everyone once per week.

We can easily beat this disease with these types of data and contact tracing. We need to get this done and not rely on piecemeal studies. We need real and actionable data now.
CONFLICT OF INTEREST: None Reported
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Unapproved Test Kit
Ching Lin, PhD | UCSF
The antibody test kit used in this tudy was manufactured in China and later banned for export (1). This information should be disclosed by the authors.

REFERENCE

1. https://www.nbcnews.com/health/health-news/unapproved-chinese-coronavirus-antibody-tests-being-used-least-2-states-n1185131
CONFLICT OF INTEREST: None Reported
Results Interpretation
Chaim Jacob, MD PhD | University of Southern California School of Medicine
Based on 35 positives from 863 adults tested, Sood et al. estimate that 4.65% or 367,000 of the LA County’s adult population has antibody to the virus. Adjusting this estimate for statistical margin of error implies about 2.52% to 7.07% of the county’s adult population has antibody to the virus. This estimate is 23.5 to 66 times higher than the 8,430 confirmed SARS-CoV-2 cases reported to the county by the time of the study in early April. These results are similar to the results of the Santa Clara County COVID-19 seroprevalence study published (non-peer reviewed) online in MedRxiv on April 14 by a Stanford group lead by Jay Bhattacharya (1). The population prevalence of SARS-CoV-2 in Santa Clara ranged from 2.49% to 4.16%. These prevalence estimates represent a range between 48,000 and 81,000 people infected in Santa Clara County by early April, 50 to 85-fold more than the number of confirmed cases at the time.

The rapid antibody test used in both studies was the same (distributed by Premier Biotech but made by Hangzhou Biotest Biotech of China). Before being deployed to California, Premier’s test kit was run against a total of 401 samples known to be coronavirus negative. Premier’s test reported that 399 of the 401 were negative. The investigators interpreted this to mean that it most likely had a false-positive rate of 0.5%, but it could range somewhere between 0.1% and 1.7%, according to the researchers’ confidence interval. That matters because the Santa Clara study found antibodies in 50 of the 3,330 participants, or 1.5%. Since the test’s false-positive rate could be as high as 1.7%, it is possible that many of the so-called positives were not, in fact, positive. That possibility is even harder to rule out in situations when the number of actual infections is low. If only a minority of Santa Clara County or LA County residents are infected, the test would have a higher likelihood of turning up false positives.

Furthermore, in a Cell paper published online on May 14, a team from the La Jolla Institute for Immunology led by Alessandro Sette reports that SARS-CoV-2−specific CD4+ T cells were identified in 100% of COVID-19 convalescent patients tested (2). Most Ab responses are dependent on CD4+ T cell help and indeed, robust T-cell response correlated well with the magnitude of the anti-SARS-CoV-2 IgG titers in the patients. Importantly, the investigators detected SARS-CoV-2−reactive CD4+ T cells in 50% of stored blood samples collected between 2015 and 2018, well before the current pandemic began. The authors hypothesized that these cells were likely triggered by past infection with one of the four human coronaviruses that cause common cold. Indeed, all unexposed donors were found to be IgG seropositive to HCoV-OC43 and HCoV-NL63. Based on these observations, the antibody test’s accuracy rates may be shakier than presented by Sood et al. It is very possible that the serological test has significant cross-reactivity with other coronaviruses that cause widespread ‘common cold’.

REFERENCES:
1. Bhattacharya, J et al, COVID-19 Antibody Seroprevalence in Santa Clara County, California. MedRxiv April 14, 2020.
2. Grifoni, A. et al., Targets of T cell responses to SARS-CoV-2 coronavirus in humans with COVID-19 disease and unexposed individuals. Cell, published online May 14, 2020.
CONFLICT OF INTEREST: None Reported
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Definition of Test Positivity Cut-Off
Kouji Harada, PhD, MPH | Kyoto University Graduate School of Medicine, Kyoto, Japan
Dr. Sood and colleagues evaluated the antibody (IgG/IgM) prevalence to SARS-CoV-2 in the general population in Los Angeles County [1] reporting a relatively high prevalence rate (4.65%). The authors evaluated the sensitivity and specificity of the kit used and determined that the specificity was particularly high (99.5%). However, the criteria for positive used in the performance samples have not been evaluated. [2]

The lateral flow immunoassay is a simple and convenient test method in clinical practice. However, the determination method is to visually read the barcode, and there is a problem with how much signal is determined to be
positive. In some cases, a weak signal intensity may be judged as positive. In that case, antibodies to coronaviruses other than SARS-CoV-2 are likely to react weakly with these assay kits, which may overestimate the prevalence. Variations in specificity among performance samples might be partly explained by different cut-offs. Hence, the criteria used in the performance samples should be validated. If the criteria determined by the authors in this study do not match to them, the sensitivity and specificity would be incorrect. This may not be ruled out even if the authors state "Each test was read by at least 2 study staff members." [1]

REFERENCE

1. Sood N, Simon P, Ebner P, et al. Seroprevalence of SARS-CoV-2–Specific Antibodies Among Adults in Los Angeles County, California, on April 10-11, 2020. JAMA. Published online May 18, 2020. doi:10.1001/jama.2020.8279
2. Bendavid E, Mulaney B, Sood N, et al. COVID-19 Antibody Seroprevalence in Santa Clara County, California. MedRxiv April 14, 2020. COVID-19 Antibody Seroprevalence in Santa Clara County, California. medRxiv 2020.04.14.20062463; doi: https://doi.org/10.1101/2020.04.14.20062463
CONFLICT OF INTEREST: None Reported
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Base Rate Fallacy and other errors
Thomas Digby, JD, MSc. | Attorney
A test with a 5% false positive rate (95% sensitivity) will generate an approximately equal number of true and false positives when the actual base rate of infection is around 5% . The 4.06% positive result would represent about 2.03% true positive and about 2.03% false positive. Am I correct that the authors have stumbled into the base rate fallacy?

What's more, with 43% having income greater than $100,000, the survey sample is heavily skewed towards people who can easily practice social distancing. We know the disease is spreading faster among lower income populations living in
crowded conditions. So this bias will underestimate prevalence.

Since the second error counterbalances the base rate fallacy, maybe the final result 4.65% is close to accurate?
CONFLICT OF INTEREST: None Reported
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SARS-CoV-2 Serology Concerns.
Gary Ordog, MD, DABMT, DABEM | County of Los Angeles, Department of Health Services (Physician Specialist retired)
Thank you for timely paper on this important subject. We definitely appreciate your urgent addition to the literature, but I do have concerns about the actual serology test that was used. There is suggestion of possible cross-reactivity between other coronaviruses that the subjects could have been exposed to previously. This alone adds question to the sensitivity and specificity of the test, and the probability of error in the results. With the low positivity rate to begin with, the increased error makes the probability of "zero" probable.

But my bigger concern is that at least 13% of subjects reported
medically treatable conditions (fever with cough and/or shortness of breath) within the past two months, but less than 10% of these tested positive for serology for SARS-CoV-2. Various conclusions could be hypothesized, including that the test has a lot more false negatives than reported, or that some other illness is causing 90% of the current fever/cough/shortness of breath symptoms. I would add "flu-like," but that would contribute a 'bias.' More research is required. 
CONFLICT OF INTEREST: Used to work for the County of Los Angeles, Department of Health Services. Used to work with the same department and knew Paul Simon, MD.
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But Is It Useful?
Gary Hurd, Ph.D. | Retired; UC Irvine, Medical College of Georgia (+ industrial, and private)
Both USC [1] and Stanford [2] have recently released studies of a commercially promoted method to test for the presence of SARS-CoV-2 IgM and IgG antibodies in blood. They applied their results to estimates of the larger population covid-19 prevalence.

These studies must address three questions; it is accurate, is it representative, and is it useful?

Is It Accurate?

The same rapid antibody test is used in both studies. It is a variant distributed by Premier Biotech, but made by Hangzhou Biotest Biotech of China. It was imported and widely distributed under multiple marketing names,
and companies. The US FDA has not approved this method, and the manufacturer has withdrawn it. [3]

Premier Biotech primarily markets drug testing kits used in sports, and some industrial/commercial drug testing situations. USC group received funding from The Foundation for Clean Competition, The Partnership for Clean Competition [4]. Both are closely associated with Premier Biotech [5].

A preprint provides an additional unrefereed critical review entitled “Test performance evaluation of SARS-CoV-2 serological assays [6]"

Is it Representative?

A major objection to the Stanford version of this study was that they had drawn a sample not representative of the population they claimed to model. The USC version tried to repair this by using a commercial marketing firm to generate their sample. However well intended, the sample design was not followed. The samples in both studies were grossly biased toward upper-middle class middle-aged white women. These studies failed to be representative and cannot be generalized.

It is Useful?

A biologically accurate immunological test for our body’s reaction to SARS-CoV-2 is needed. But reported data from the USC study questions if the tested method is any better than self reported symptoms. Specifically two reported facts by USC call this into question.

First, 28.6% of the total sample report prior symptoms. This returns to the “representative” question.
Second, of the volunteers 72% of total positives had also reported prior symptoms.

Urging people who experience symptoms to get a direct swab test will be far cheaper and more effective than the serological test procedures used here.

REFERENCES

[1] Sood N, Simon P, Ebner P, et al. Seroprevalence of SARS-CoV-2–Specific Antibodies Among Adults in Los Angeles County, California, on April 10-11, 2020. JAMA. Published online May 18, 2020. doi:10.1001/jama.2020.8279

[2] “COVID-19 Antibody Seroprevalence in Santa Clara County, California”
Eran Bendavid, Bianca Mulaney, Neeraj Sood, Soleil Shah, Emilia Ling, Rebecca Bromley-Dulfano, Cara Lai, Zoe Weissberg, Rodrigo Saavedra-Walker, James Tedrow, Dona Tversky, Andrew Bogan, Thomas Kupiec, Daniel Eichner, Ribhav Gupta, John Ioannidis, Jay Bhattacharya
medRxiv 2020.04.14.20062463; doi: https://doi.org/10.1101/2020.04.14.20062463

[3] USFDA https://www.fda.gov/medical-devices/emergency-situations-medical-devices/faqs-testing-sars-cov-2#5eca06b54859c

[4] The Partnership for Clean Competition, “… funds 80% of the worlds anti-doping research and development. Apply for a grant today!”

[5] "With Sports On Hold, A U.S. Anti-Doping Organization Switches Gears To COVID-19 Research" Karen Price | April 09, 2020 | Team USA. org
https://www.teamusa.org/News/2020/April/09/With-Sports-On-Hold-A-US-Anti-Doping-Organization-Switches-Gears-To-COVID-19-Research

[6] Jeffrey D. Whitman, et al, “Test performance evaluation of SARS-CoV-2 serological assays” May 17, 2020. medRxiv https://www.medrxiv.org/content/10.1101/2020.04.25.20074856v2
CONFLICT OF INTEREST: None Reported
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Specificity and Result Interpretation of Premier Ab Test
William Katz, PhD, MD | HHMI Janelia Research Campus
The specificity of the Premier Biotech test is described as 99.5% with 95% CI of 99.2%-99.7%, and this estimate was from the preprint of the Stanford Santa Clara study. Just before this letter was accepted for publication, the COVID Testing Project released their analysis of Ab tests and found the Premier test to have 97.2% specificity with a 95% CI of 92.1%-99.4% [1]. Furthermore, there was a widely publicized whistleblower complaint that the Stanford paper was rushed into preprint before ELISA validation. According to a news article about the complaint, "Using ELISA tests to reassess the samples of community members who had come up positive for antibodies on the Premier test, he [Stanford pathologist Scott Boyd] had ended up getting positive results for a little over half of them." If the article is true, it would further cloud the cited specificity of the test.

Finally, there is no elaboration of the precise method for assessing what can be ambiguous visual results of the Premier test. Did they require a very opaque line or a barely visible one to classify the result as a positive? This test interpretation ambiguity and need for result scoring was recently mentioned by one of the leads of the COVID Testing Project in a UCSF Medicine Grand Rounds [2].

REFERENCES

[1] Whitman, et al. Test performance evaluation of SARS-CoV-2 serological assays. medRxiv, April 29, 2020. https://www.medrxiv.org/content/10.1101/2020.04.25.20074856v1

[2] UCSF Medical Grand Rounds, May 14, 2020. https://youtu.be/n3mtPC6V408?t=4843
CONFLICT OF INTEREST: None Reported
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Follow-On Study: Round Two LA Antibody Testing (May 8-12) Initial Results
Daniel Brolin, MSci |
I note that Los Angeles County Health Department Officers, along with Dr. Sood, reported preliminary results from their second round of SARS-Cov-2 antibody testing on May 20, 2020. Unlike the first round in which results were prominently released, no official press release of detailed preliminary second round results has been made available thus far.

The press conference at which they reported their limited results of testing indicated that 1014 adults over the age of 18 were tested and the unweighted proportion of positive Ig tests was 2.1% (vs the 4.06% reported within this research letter) (1). Apparently efforts were
made to increase the representative sample of Latino and Asian ethnic individuals although no specific numbers have yet been released with regard to ethnic or geographic weighted prevalence.

I look forward to a detailed report on this and future rounds of testing but believe that the wide disparity between this second round of tests should be considered with special emphasis to previously expressed concerns regarding antibody test specificity and sampling variance.

REFERENCE

1. Serology study results discussed at 12:36 mark:
https://covid19.lacounty.gov/covid19-news/covid-19-briefing-with-la-county-officials-may-20-2020/
CONFLICT OF INTEREST: None Reported
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Research Letter
May 18, 2020

Seroprevalence of SARS-CoV-2–Specific Antibodies Among Adults in Los Angeles County, California, on April 10-11, 2020

Author Affiliations
  • 1Schaeffer Center for Health Policy and Economics, Sol Price School of Public Policy, University of Southern California, Los Angeles
  • 2Los Angeles County Department of Public Health, Los Angeles, California
  • 3Keck School of Medicine, University of Southern California, Los Angeles
  • 4Sports Medicine Research and Testing Laboratory, Salt Lake City, Utah
  • 5LRW Group, Los Angeles, California
  • 6Stanford University School of Medicine, Palo Alto, California
JAMA. 2020;323(23):2425-2427. doi:10.1001/jama.2020.8279

Inadequate knowledge about the extent of the coronavirus disease 2019 (COVID-19) epidemic challenges public health response and planning. Most reports of confirmed cases rely on polymerase chain reaction–based testing of symptomatic patients.1 These estimates of confirmed cases miss individuals who have recovered from infection, with mild or no symptoms, and individuals with symptoms who have not been tested due to limited availability of tests.

We conducted serologic tests in a community sample to estimate cumulative incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, as serologic tests identify both active and past infections.

Methods

This study was approved by the Los Angeles County Department of Public Health Institutional Review Board, and written informed consent was obtained.

We tested for SARS-CoV-2–specific antibodies using a lateral flow immunoassay test (Premier Biotech). Residents of Los Angeles County, California, within a 15-mile (24 km) radius of the testing site were eligible for participation. Participants were offered testing at 6 study sites on April 10 and April 11, 2020; those unable to come to the testing sites were offered in-home testing on April 13 and April 14, 2020.

We used a proprietary database representative of the county maintained by LRW Group, a market research firm, to select participants. A random sample of these residents was invited, with quotas for enrollment for subgroups based on age, sex, race, and ethnicity distribution of Los Angeles County residents. Participation was restricted to 1 adult per household. Each test was read by at least 2 study staff members.

We used these data to estimate the population prevalence of SARS-CoV-2 antibodies. The unweighted and weighted proportions of positive tests (either IgM or IgG) in the analysis sample were calculated. Because the sample differed on demographics and income distribution from Los Angeles County, weights were calculated to match the 2018 census on sex, race/ethnicity, and income. We then adjusted the weighted and unweighted proportion of positive results for accuracy of the test. Estimates of the sensitivity (82.7%; 95% CI, 76.0%-88.4%) and specificity (99.5%; 95% CI, 99.2%-99.7%) of the test kits were obtained from 16 different samples.2 95% Confidence intervals for unweighted data were estimated using exact binomial models and for weighted and adjusted estimates using bootstrap methods. We used Stata version 16 for the analysis.

Results

Of 1952 individuals invited to participate in antibody testing, 1702 (87.2%) provided consent and 865 (50.9%) were tested. Those not tested could not schedule testing or did not appear. Two test results were inconclusive due to faulty test kits and were removed from the analysis sample. Of 863 adults included, 60% were women, 55% were aged 35 to 54 years old, 58% were white, and 43% had yearly household incomes greater than $100 000. Thirteen percent reported fever with cough, 9% fever with shortness of breath, and 6% loss of smell or taste (Table).

Thirty-five individuals (4.06% [exact binomial CI, 2.84%-5.60%]) tested positive. The fraction that tested positive varied by race/ethnicity, sex, and income (Table). The weighted proportion of participants who tested positive was 4.31% (bootstrap CI, 2.59%-6.24%). After adjusting for test sensitivity and specificity, the unweighted and weighted prevalence of SARS-CoV-2 antibodies was 4.34% (bootstrap CI, 2.76%-6.07%) and 4.65% (bootstrap CI, 2.52%-7.07%), respectively.

Discussion

In this community seroprevalence study in Los Angeles County, the prevalence of antibodies to SARS-CoV-2 was 4.65%. The estimate implies that approximately 367 000 adults had SARS-CoV-2 antibodies, which is substantially greater than the 8430 cumulative number of confirmed infections in the county on April 10.3 Therefore, fatality rates based on confirmed cases may be higher than rates based on number of infections. In addition, contact tracing methods to limit the spread of infection will face considerable challenges.

This study has limitations. Selection bias is likely. The estimated prevalence may be biased due to nonresponse or that symptomatic persons may have been more likely to participate. Prevalence estimates could change with new information on the accuracy of test kits used. Also, the study was limited to 1 county. Serologic testing in other locations is warranted to track the progress of the epidemic.

Section Editor: Jody W. Zylke, MD, Deputy Editor.
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Article Information

Corresponding Author: Neeraj Sood, PhD, University of Southern California, University Park Campus, Verna & Peter Dauterive Hall, 635 Downey Way, Los Angeles, CA 90089 (nsood@healthpolicy.usc.edu).

Accepted for Publication: May 1, 2020.

Published Online: May 18, 2020. doi:10.1001/jama.2020.8279

Author Contributions: Dr Sood had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: Sood, Simon, Ebner, Reynolds, Bendavid, Bhattacharya.

Drafting of the manuscript: Sood, Bendavid, Bhattacharya.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Sood, Simon, Reynolds, Bendavid, Bhattacharya.

Obtained funding: Sood, Eichner, Reynolds, Bendavid.

Administrative, technical, or material support: Sood, Simon, Ebner, Eichner, Reynolds, Bhattacharya.

Supervision: Sood, Simon, Ebner, Reynolds, Bhattacharya.

Conflict of Interest Disclosures: Dr Sood reported receiving funding from Jedel Foundation, USC Schwarzenegger Institute, USC Lusk Center, USC President's Office, Catherine Ahmed, Brent Bayless, Carole King, Daniel Eichner, Regina Nordhal, Tore Nordhal, and Gauri Jauhar during the conduct of the study; and reported serving as a scientific advisor to Payssurance and Virta Health; serving as an expert witness for the American Medical Association and Goldman, Ismail, Tomaselli, Brennan, and Baum; serving as an international expert for the China Development Research Foundation and the Pharmaceutical Research and Manufacturers of America; and receiving grants from the Agency for Healthcare Research and Quality, the National Institutes of Health, the National Institute for Health Care Management Foundation, Health Care Services Corporation, and the Patient-Centered Outcomes Research Institute outside the submitted work. Drs Bhattacharya and Bendavid reported receiving support from Jedel Foundation and the Stanford COVID-19 Seroprevalence Studies Fund during the conduct of the study. No other disclosures were reported.

Funding/Support: We received partial financial support for this project through the Stanford COVID-19 Seroprevalence Studies fund. We acknowledge funding from USC Schwarzenegger Institute, USC Lusk Center, USC President’s Office, Jedel Foundation, LRW Group, Soap Box Sample, Foundation for Clean Competition, Partnership for Clean Competition, and several individual donors.

Role of the Funder/Sponsor: Funding organizations and donors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We thank Jim Tedrow, BS, MT, The Compliance Resource Group; Thomas Kupiec, PhD, ARL Bio Pharma Inc; Manish J. Butte, MD, PhD, University of California, Los Angeles; Jason Brooks, LRW Group; and Thomas MaCurdy, Frank Wolak, and John P. A. Ioannidis, MD, DSc, Stanford University, for contributing to study design. We thank Ricardo Basurto-Davila, PhD, and Irene Vidyanti, PhD, Los Angeles County Chief Information Office, for contributing to study design and data collection. We thank Kevin de Leon, BA, and Conyers Davis, MA, Schwarzenegger Institute for State and Global Policy at the University of Southern California; and Carole King, MEd, Sol Price School of Public Policy, University of Southern California, Los Angeles, for logistical support during data collection and securing funding. We thank John Walton Senterfitt and Alysia Kwon, ScM, Los Angeles County Department of Public Health, for IRB support. We thank Elinor Gaida, MBA, MPH, and Jacqueline Rosales, BS, LRW Group, for contributing to recruiting and data collection. We thank Janelle Cyprich, BS, Acacia Hori, BA, Alexandra Obremskey, BS, Katharine B. Stiers, BA, Silena Te, BA, Omar Toubat, BA, and other medical student volunteers from USC Keck School of Medicine for contributions to data collection. None of the individuals acknowledged received compensation from the study team.

References
1.
Spychalski  P, Błażyńska-Spychalska  A, Kobiela  J.  Estimating case fatality rates of COVID-19.   Lancet Infect Dis. 2020;S1473-3099(20)30246-2. Accessed April 9, 2020. Published online March 31, 2020. doi:10.1016/S1473-3099(20)30246-2PubMedGoogle Scholar
2.
Bendavid  E, Mulaney  B, Sood  N,  et al. COVID-19 antibody seroprevalence in Santa Clara County, California. medRxiv. Preprint posted online April 30, 2020. doi:10.1101/2020.04.14.20062463
3.
Los Angeles County announces 18 new deaths related to 2019 novel coronavirus (COVID-19)—475 new cases of confirmed COVID-19 in Los Angeles County. News release. Los Angeles County Department of Public Health. April 10, 2020. Accessed April 26, 2020. http://publichealth.lacounty.gov/phcommon/public/media/mediapubdetail.cfm?unit=media&ou=ph&prog=media&prid=2309
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