Acknowledgment: The authors thank all who have collected, prepared, and shared data throughout this outbreak. They are particularly grateful to Dr. Kaiyuan Sun, Ms. Jenny Chen, and Dr. Cecile Viboud from the Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health; Dr. Moritz Kraemer and the open COVID-19 data working group; and the Johns Hopkins Center for Systems Science and Engineering.
Grant Support: By the U.S. Centers for Disease Control and Prevention (NU2GGH002000), the National Institute of Allergy and Infectious Diseases (R01 AI135115), the National Institute of General Medical Sciences (R35 GM119582), and the Alexander von Humboldt Foundation.
Disclosures: Dr. Lauer reports grants from the National Institute of Allergy and Infectious Diseases and the U.S. Centers for Disease Control and Prevention during the conduct of the study. Ms. Grantz reports a grant from the U.S. Centers for Disease Control and Prevention during the conduct of the study. Dr. Reich reports grants from the National Institute of General Medical Sciences and the Alexander von Humboldt Foundation during the conduct of the study. Dr. Lessler reports a grant from the U.S. Centers for Disease Control and Prevention during the conduct of the study. Authors not named here have disclosed no conflicts of interest. Disclosures can also be viewed at
www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M20-0504.
Editors' Disclosures: Christine Laine, MD, MPH, Editor in Chief, reports that her spouse has stock options/holdings with Targeted Diagnostics and Therapeutics. Darren B. Taichman, MD, PhD, Executive Editor, reports that he has no financial relationships or interests to disclose. Cynthia D. Mulrow, MD, MSc, Senior Deputy Editor, reports that she has no relationships or interests to disclose. Eliseo Guallar, MD, MPH, DrPH, Deputy Editor, Statistics, reports that he has no financial relationships or interests to disclose. Jaya K. Rao, MD, MHS, Deputy Editor, reports that she has stock holdings/options in Eli Lilly and Pfizer. Christina C. Wee, MD, MPH, Deputy Editor, reports employment with Beth Israel Deaconess Medical Center. Sankey V. Williams, MD, Deputy Editor, reports that he has no financial relationships or interests to disclose. Yu-Xiao Yang, MD, MSCE, Deputy Editor, reports that he has no financial relationships or interest to disclose.
Corresponding Author: Justin Lessler, PhD, Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, 615 North Wolfe Street, Baltimore, MD 21205; e-mail,
[email protected].
Previous Posting: This manuscript was posted as a preprint on medRxiv on 4 February 2020. doi:10.1101/2020.02.02.20020016
Current Author Addresses: Drs. Lauer, Meredith, and Lessler; Ms. Grantz; Ms. Bi; Mr. Jones; and Ms. Zheng: Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, 615 North Wolfe Street, Baltimore, MD 21205.
Dr. Azman: Médecins Sans Frontières, Rue de Lausanne 72, 1202 Genève, Switzerland.
Dr. Reich: Department of Biostatistics and Epidemiology, Amherst School of Public Health and Health Sciences, University of Massachusetts, 715 North Pleasant Street, Amherst, MA 01003-9304.
Author Contributions: Conception and design: S.A. Lauer, K.H. Grantz, F.K. Jones, N.G. Reich, J. Lessler.
Analysis and interpretation of the data: S.A. Lauer, K.H. Grantz, Q. Bi, F.K. Jones, N.G. Reich, J. Lessler.
Drafting of the article: S.A. Lauer, K.H. Grantz, Q. Bi, F.K. Jones, A.S. Azman, N.G. Reich.
Critical revision of the article for important intellectual content: Q. Bi, F.K. Jones, A.S. Azman, N.G. Reich, J. Lessler.
Final approval of the article: S.A. Lauer, K.H. Grantz, Q. Bi, F.K. Jones, Q. Zheng, H.R. Meredith, A.S. Azman, N.G. Reich, J. Lessler.
Statistical expertise: Q. Bi, N.G. Reich, J. Lessler.
Collection and assembly of data: S.A. Lauer, K.H. Grantz, Q. Bi, F.K. Jones, Q. Zheng, H.R. Meredith.
This article was published at
Annals.org on 10 March 2020.
* Dr. Lauer and Ms. Grantz share first authorship.
The greatest thing we have to fear from CoVid-19.
If we knew nothing more, that should be enough to calm our fears and promote cooperation among all of us: that should be enough to halt the run on store products and stop the price gouging of tissue, hand cleaner and other items; and while calmly promoting restoration of the stock market, the world economy, and our countries.
Why?
Because this is not some unknown enemy attacking us that we don’t know how to deal with.
This virus is transmitted by people sneezing or coughing on you. Masks are for those people who are coughing and sneezing—for them to wear to reduce their coughing or sneezing their virus upon you—not for you to wear when you’re not the one coughing or sneezing. This behavior of everyone wearing masks doesn’t stop the spread; in fact it may increase the potential for warm moist areas for the virus to survive and it promotes unnecessary fear.
(1) A major method of spreading the virus includes touching your face with your hands and then spreading the virus by touching others, as well as increasing the likelihood of further infecting yourself with more of the virus. As Ignaz Semmelweis demonstrated more than 150 years ago, hand washing (hand soap) dramatically reduces the transmission of pathogens from person to person.
(2) The virus attaches itself to the lungs and GI track, where IgA is primarily responsible for addressing immunologic responses. This means we know what to look for and what to treat, allowing those who are sickest to be best-taken care of. This is why we see the elderly immune-compromised and those with heart and lung problems most susceptible.
(3) Viruses don’t try to kill their host. If they were successful at that, it would prevent them from reproducing themselves and surviving.
CoVid-19 also presents us with the opportunity to learn and potentially develop new treatments for IgA disorders, CAD, and cancer.
This is not some unknown invader which we need to fear. This is a virus with all the limitations of a virus—not a zombie apocalypse.
Disclosures: No COI to declare.
COVID-19 symptoms and viral shedding: Implications for testing and self-Isolation
Lauer and colleagues contributed importantly to our nascent understanding of COVID-19 in their recent Annals publication regarding the incubation of symptomatic infections. The mean period is 5.1 days (95% CI, 4.5 to 5.8 days), an estimate based on analyses of 181 confirmed cases spanning 24 countries and regions outside mainland China, and 25 provinces within mainland China (1). Thus, under the best of circumstances, the average person will seek diagnosis in five days of exposure, with results available two days later.
Wölfel and colleagues have added an equally valuable piece to the COVID-19 puzzle in a non-peer-reviewed report (2). Nine patients in Germany, for whom the time of exposure to an index case of SARS-CoV-2 was known, provided biological samples for virology testing. Viral loads in the upper respiratory tract were detected among the first samples collected 48 hours from the onset of symptoms and peaked before day five. Viral concentrations were 1000 times higher than those observed in Hong Kong during the 2004 outbreak of SARS, a related coronavirus (3). Compared to SARS, the viral concentrations of COVID-19 have made contact tracing difficult, particularly in Western countries with highly itinerant populations. Regardless, diagnostic testing remains vital to estimating COVID-19 case-fatality rates, identifying and responding to emerging hotspots, and tailoring medical care at the individual level.
Within this context there is now a clear rationale for prioritizing self-isolation of the elderly and immunocompromised for an extended period of time, and promoting social distancing behavior for everyone else. Whether or not lower-risk population groups exposed to SARS-CoV-2 infection will end up developing related IgG, IgM, IgA antibodies and reduce the risk of exposure to groups most at risk of mortality, individuals who acquire immunological defenses will be better able to provide social support to the masses in self-isolation. These are among the most warranted measures now as we bide our time for a deployable COVID-19 vaccine 12 to 18 months from now.
References
1. Lauer SA, Grantz KH, Bi Q, Jones FK, Zheng Q, Meredith HR, et al. The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Annals of Internal Medicine. 2020.
2. Woelfel R, Corman VM, Guggemos W, Seilmaier M, Zange S, Mueller MA, et al. Clinical presentation and virological assessment of hospitalized cases of coronavirus disease 2019 in a travel-associated transmission cluster. medRxiv. 2020:2020.03.05.20030502.
3. Poon LL, Chan KH, Wong OK, Cheung TK, Ng I, Zheng B, et al. Detection of SARS coronavirus in patients with severe acute respiratory syndrome by conventional and real-time quantitative reverse transcription-PCR assays. Clinical chemistry. 2004;50(1):67-72.
Disclosures: None
Optimizing Policy in Response to COVID-19
We estimated country-specific logistic growth curves as functions of time from Day Zero (when the cumulative number of reported cases surpasses 100)2 using linear models and ridge regression with leave-one-out cross-validation, estimating Hubei Province separately from the rest of China. Cumulative case curves are similarly shaped among all countries with growth rates lying between those for Hubei and South Korea. While case and fatality reporting in different countries may be subject to differential reporting biases, they are unlikely time-varying. All countries reporting cases 25+ days after Day Zero have demonstrated rapid declines in new cases by Day 25, with growth rates in all countries declining by Day 15. (https://rpubs.com/nzawadzki/covid19-by-country, https://drive.google.com/file/d/1LX2IamvOebtg7Xan9nIvKJ-zVAqbVQlr/view?usp=sharing).
Each 1% increase in unemployment corresponds to ~4000 additional deaths per year. Based on these curves, global cumulative cases are unlikely to exceed 500,000 or deaths 50,000, regardless of measures taken. Financial markets have lost >$15 trillion, resulting in more lives lost from panic and economic disruption than gained from social distancing and economy shutdown, at a cost of ~$300 million per life.
References
Lauer SA, Grantz KH, Bi Q, Jones FK, Zheng Q, Meredith HR, et al. The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Ann Intern Med. 2020.
Kuhn A. South Korea's Drive-Through Testing For Coronavirus Is Fast — And Free. Online: NPR; 2020. Available: https://www.npr.org/sections/goatsandsoda/2020/03/13/815441078/south-koreas-drive-through-testing-for-coronavirus-is-fast-and-free
Maharaj S, Kleczkowski A. Controlling epidemic spread by social distancing: do it well or not at all. BMC Public Health. 2012;12:679.
Hastie T. cv.glmnet - Cross-Validation for Glmnet. RDocumentation. Online: R. Available: https://www.rdocumentation.org/packages/glmnet/versions/3.0-2/topics/cv.glmnet
Roelfs DJ, Shor E, Davidson KW, Schwartz JE. Losing life and livelihood: a systematic review and meta-analysis of unemployment and all-cause mortality. Soc Sci Med. 2011;72(6):840-54.
14-Day Quarantine, Incubation Period, and Asymptomatic Transmission of COVID-19
Little is known about asymptomatic cases, or the corresponding dynamics of transmission, but some studies provide at least minimal guidance. The proportion of asymptomatic infections is estimated at 15-20% based on observations from passengers on the Diamond Princess cruise ship (3). The period of communicability in asymptomatic cases is challenging to predict. In one cohort (of symptomatic patient) the median length of illness from onset of symptoms until a negative viral test was 10.5 days, with 2.5 days occurring after resolution of symptoms (4). Thus, assuming a period of communicability of 3-10 days, the proportion of potentially transmissible asymptomatic individuals at the end of 14 days in quarantine is 0.4% on the lower end, and up to 15% on the higher end, by considering a 75% chance of developing COVID-19 on or after day 4 of quarantine, with 20% of those potentially unknowingly communicable ten days later. Moreover, the risk of transmission from asymptomatic cases would be additive to those who have not yet shown symptoms as described by Lauer, Grantz et al.
The authors’ study design did not intend to capture the risk of asymptomatic transmission, and less was known about this risk at the time the study was conducted. Indeed, at the time this study was published online, the World Health Organization had not yet declared COVID-19 a pandemic. But given the emergence of new data, the study’s conclusion is misleading. Perhaps a more accurate take-away is that, after 14 days, the number of individuals who are neither showing symptoms, nor asymptomatically infected, is low. This nuanced distinction may hold significant implications in determining length of quarantine and/or the utility of testing those at high-risk of contracting the virus even in the absence of symptoms.
1. Lauer SA, Grantz KH, Bi Q, Jones FK, Zheng Q, Meredith HR, et al. The incubation period of coronavirus disease 2019 (COVID-19) from publicly reported confirmed cases: estimation and application. Annals of internal medicine. 2020.
2. Bai Y, Yao L, Wei T, Tian F, Jin D-Y, Chen L, et al. Presumed asymptomatic carrier transmission of COVID-19. Jama. 2020.
3. Mizumoto K, Kagaya K, Zarebski A, Chowell G. Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020. Eurosurveillance. 2020;25(10).
4. Chang D, Mo G, Yuan X, Tao Y, Peng X, Wang F, et al. Time Kinetics of Viral Clearance and Resolution of Symptoms in Novel Coronavirus Infection. American Journal of Respiratory and Critical Care Medicine. 2020(ja).
Great caution needed to use the Lauer study in the guidance of health policies
In a paper published by the Annals of Internal Medicine, Lauer et al. [3] (“Lauer study” below) estimated the incubation period of the coronavirus disease (COVID-19) using confirmed cases outside Wuhan, China. Their results are being used by the Centers for Disease Control and Prevention (CDC) in guidelines for management of confirmed COVID-19 patients [2].
When analyzing emerging epidemic outbreaks using limited observation data, there are many forms of biases in the estimation of basic epidemiological parameters [1]. Although the Lauer study acknowledged some potential limitations
in their discussion, they failed to give adequate warnings about the potential magnitude of selection bias in their analysis.
We believe there are at least three major sources of biases in this study:
1. Ignoring the epidemic growth. Among the 181 cases used by the Lauer study, the majority (161) were residents of the Hubei province or had known travel to Wuhan. A crucial assumption, as acknowledged by the authors, is a “constant risk for SARS-CoV-2 infection in Wuhan from 1 December 2019 to 30 January 2020”. However, the epidemic was almost certainly growing rapidly in Wuhan before its lock-down.
2. Right-truncation. Although in the abstract the authors stated that the COVID-19 cases they used were confirmed between 4 January 2020 and 24 February 2020, a closer examination of their dataset reveals that only 4 cases were confirmed in February. Therefore, most of the cases who left Wuhan days before its lock-down on 23 January and had longer incubation periods were not confirmed by the end of January and were not included in the dataset.
3. Non-random sample selection. The Lauer study did not give a clear description of how they decided which cases were included in their dataset and which were excluded. In their discussion they mentioned that cases in their dataset may under-represent mild symptoms, but they did not comment on whether their dataset may even adequately represent the more severe cases (or any other well-defined population).
Any of the above issues could incur severe bias. By analyzing a carefully constructed dataset with a generative statistical model, we found that these issues indeed lead to substantial biases, and 5% of the symptomatic cases may develop symptoms after 14 days since infection. Our study is available as a preprint on arXiv [4], has its own limitations, and has yet to undergo rigorous peer review. Nevertheless, the unaccounted and under-acknowledged biases in the Lauer study suggest that their results should be used with great caution in the guidance of health policies.
[1] T. Britton and G. Scalia Tomba. Estimation in emerging epidemics: Biases and remedies. Journal of the Royal Society Interface, 16(150):20180670, 2019.
[2] Centers for Disease Control and Prevention. Interim clinical guidance for management of patients with confirmed coronavirus dis-
ease (COVID-19). https://www.cdc.gov/coronavirus/2019-ncov/hcp/clinical-guidance-management-patients.html. Retrieved: April 15, 2020.
[3] S. A. Lauer, K. H. Grantz, Q. Bi, F. K. Jones, Q. Zheng, H. R. Meredith, A. S. Azman, N. G. Reich, and J. Lessler. The incubation period of coronavirus disease 2019 (COVID-19) from publicly reported confirmed cases: estimation and application. Annals of Internal Medicine, 2020.
[4] Q. Zhao, N. Ju, and S. Bacallado. BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic, 2020. arXiv: 2004.07743
QUARANTINE AND VIRUS CLEARANCE IN COVID-19
I am writing in response to an article which appeared on the May 5, 2020 issue of Annals of Internal Medicine, reporting that 101 out of every 10,000 cases of Covid-19 will develop symptoms after 14 days of quarantine (1). These data suggest that a 14-day quarantine is 99% effective, but 1% of cases would be missed and could still spread the infection after completing the quarantine. Complicating things is the fact that 15% to 20% of infections are asymptomatic (2). I believe the way to solve this dilemma is to test the patient for coronavirus before the quarantine is lifted. After successful recovery from the illness it is vital to confirm clearance of the virus.
Patients should be tested with two separate nasal swabs performed at least 24 hours apart. A positive test should trigger repeat testing at 7 days interval, until the test becomes negative. This procedure should be also followed for patient that are completing the quarantine. The 1% of patients that remains positive for coronavirus would continue quarantine for 7 days, at which point they will be tested again until they clear the virus and the quarantine will be stopped only if they clear the virus.
1. Lauer S, Grantz K, Bi Q, Jones F, et al. The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Ann. Intern. Med. 2020;172(9):577-582. doi: 10.7326/M20-0504.
2. Mizumoto K, Kagaya K, Zarebski A, Chowell G. Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020. Eurosurveillance. 2020;25(10).