Triangulation number of the SARS CoV-19 virus

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Is the triangulation number of the SARS CoV-19 virus capsid, in the sense of the Caspar-Klug theory, known? In case the Caspar-Klug theory does not apply to it, is it known what is its tiling, in the sense of the viral tiling theory of Twarock (and coauthors)? I am a mathematician, trying to learn the geometric and group-theoretic aspects of virus structures.

Coronaviruses, like many viruses with a lipid membrane, are pleomorphic. The individual particles don't have a consistent shape. Here is a cryo-electron micrograph of SARS-CoV-1:

It might not be obvious, but each particle seen here is unique, they are not different rotations of identical copies. Since there is no consistent symmetry, there can be no triangulation number.

The image is from the following reference: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1563832/

SARS-CoV-19 variants

Posted on June 22nd, 2021 by Dr. Francis Collins

A key issue as we move closer to ending the pandemic is determining more precisely how long people exposed to SARS-CoV-2, the COVID-19 virus, will make neutralizing antibodies against this dangerous coronavirus. Finding the answer is also potentially complicated with new SARS-CoV-2 “variants of concern” appearing around the world that could find ways to evade acquired immunity, increasing the chances of new outbreaks.

Now, a new NIH-supported study shows that the answer to this question will vary based on how an individual’s antibodies against SARS-CoV-2 were generated: over the course of a naturally acquired infection or from a COVID-19 vaccine. The new evidence shows that protective antibodies generated in response to an mRNA vaccine will target a broader range of SARS-CoV-2 variants carrying “single letter” changes in a key portion of their spike protein compared to antibodies acquired from an infection.

These results add to evidence that people with acquired immunity may have differing levels of protection to emerging SARS-CoV-2 variants. More importantly, the data provide further documentation that those who’ve had and recovered from a COVID-19 infection still stand to benefit from getting vaccinated.

These latest findings come from Jesse Bloom, Allison Greaney, and their team at Fred Hutchinson Cancer Research Center, Seattle. In an earlier study, this same team focused on the receptor binding domain (RBD), a key region of the spike protein that studs SARS-CoV-2’s outer surface. This RBD is especially important because the virus uses this part of its spike protein to anchor to another protein called ACE2 on human cells before infecting them. That makes RBD a prime target for both naturally acquired antibodies and those generated by vaccines. Using a method called deep mutational scanning, the Seattle group’s previous study mapped out all possible mutations in the RBD that would change the ability of the virus to bind ACE2 and/or for RBD-directed antibodies to strike their targets.

In their new study, published in the journal Science Translational Medicine, Bloom, Greaney, and colleagues looked again to the thousands of possible RBD variants to understand how antibodies might be expected to hit their targets there [1]. This time, they wanted to explore any differences between RBD-directed antibodies based on how they were acquired.

Again, they turned to deep mutational scanning. First, they created libraries of all 3,800 possible RBD single amino acid mutants and exposed the libraries to samples taken from vaccinated individuals and unvaccinated individuals who’d been previously infected. All vaccinated individuals had received two doses of the Moderna mRNA vaccine. This vaccine works by prompting a person’s cells to produce the spike protein, thereby launching an immune response and the production of antibodies.

By closely examining the results, the researchers uncovered important differences between acquired immunity in people who’d been vaccinated and unvaccinated people who’d been previously infected with SARS-CoV-2. Specifically, antibodies elicited by the mRNA vaccine were more focused to the RBD compared to antibodies elicited by an infection, which more often targeted other portions of the spike protein. Importantly, the vaccine-elicited antibodies targeted a broader range of places on the RBD than those elicited by natural infection.

These findings suggest that natural immunity and vaccine-generated immunity to SARS-CoV-2 will differ in how they recognize new viral variants. What’s more, antibodies acquired with the help of a vaccine may be more likely to target new SARS-CoV-2 variants potently, even when the variants carry new mutations in the RBD.

It’s not entirely clear why these differences in vaccine- and infection-elicited antibody responses exist. In both cases, RBD-directed antibodies are acquired from the immune system’s recognition and response to viral spike proteins. The Seattle team suggests these differences may arise because the vaccine presents the viral protein in slightly different conformations.

Also, it’s possible that mRNA delivery may change the way antigens are presented to the immune system, leading to differences in the antibodies that get produced. A third difference is that natural infection only exposes the body to the virus in the respiratory tract (unless the illness is very severe), while the vaccine is delivered to muscle, where the immune system may have an even better chance of seeing it and responding vigorously.

Whatever the underlying reasons turn out to be, it’s important to consider that humans are routinely infected and re-infected with other common coronaviruses, which are responsible for the common cold. It’s not at all unusual to catch a cold from seasonal coronaviruses year after year. That’s at least in part because those viruses tend to evolve to escape acquired immunity, much as SARS-CoV-2 is now in the process of doing.

The good news so far is that, unlike the situation for the common cold, we have now developed multiple COVID-19 vaccines. The evidence continues to suggest that acquired immunity from vaccines still offers substantial protection against the new variants now circulating around the globe.

The hope is that acquired immunity from the vaccines will indeed produce long-lasting protection against SARS-CoV-2 and bring an end to the pandemic. These new findings point encouragingly in that direction. They also serve as an important reminder to roll up your sleeve for the vaccine if you haven’t already done so, whether or not you’ve had COVID-19. Our best hope of winning this contest with the virus is to get as many people immunized now as possible. That will save lives, and reduce the likelihood of even more variants appearing that might evade protection from the current vaccines.

Bloom Lab (Fred Hutchinson Cancer Research Center, Seattle)

NIH Support: National Institute of Allergy and Infectious Diseases

Introduction

Before 2003, only 2 human coronaviruses—Human Coronavirus (HCoV)-229E and HCoV-OC43, causing mild illness—were known [1,2,3]. However, the emergence of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV) changed the view worldwide because coronaviruses can cause life-threatening infections [4,5,6]. The ongoing pandemic of a novel strain of coronavirus, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), is posing an unforeseen public health and economic threats worldwide. As of June 27, 2020, SARS-CoV-2 has infected more than 9.65 million people, with 491,115 deaths reported from 215 countries and territories [7], of which there are 2,407,590 confirmed cases of COVID-19 and 124,161 deaths in the United States of America alone [8]. Recombination, mutator alleles, and mutational robustness are some of the evolutionary mechanisms [9] that make coronaviruses capable of expanding their host ranges, including humans. Therefore, understanding the virology of the coronaviruses at a structural level is of utmost importance because the health threats from these zoonotic viruses are constant and long-term.

Coronaviruses are large, enveloped, positive-stranded RNA viruses responsible for infecting a wide variety of mammalian and avian species [10]. These viruses contain spike-like projections of glycoproteins on their surface, which appear like a crown under the electron microscope hence, they are referred to as coronaviruses. The coronavirus genome encodes several structural and nonstructural proteins. The structural proteins are responsible for host infection [11], membrane fusion [12], viral assembly [13], morphogenesis, and release of virus particles [14], among other functions, and the nonstructural proteins (nsps) facilitate viral replication and transcription [15,16]. The membrane (M), the envelope (E), and the spike protein (S) make up the structural proteins and are associated with the envelope. Among these structural proteins, the trimeric S proteins protrude from the virus envelope and are the key machinery that facilitates virus entry into the host cell [10,17].

The S proteins are clove-shaped, type-I transmembrane proteins and have 3 segments: a large ectodomain, a single-pass transmembrane, and an intracellular tail. The ectodomain of S proteins consist of the S1 subunit, containing a receptor-binding domain (RBD), and the membrane-fusion subunit (S2). The host-cell receptor recognition by the RBDs on S proteins is the initial step of viral infection, and the binding interactions between the coronavirus spike and its receptor is one of the most critical factors for host range and cross-species transmission. Human coronaviruses recognize a variety of host receptors specifically, HCoV-229E recognizes human aminopeptidase N (hAPN) [18], MERS-CoV binds dipeptidyl peptidase-4 (DPP4) [19], HCoV-OC43 and HCoV-HKU1 bind certain types of O-acetylated sialic acid [20], and HCoV-NL63 and SARS-CoV recognize angiotensin-converting enzyme 2 (ACE2) [21,22]. Recent structures, along with functional studies, have suggested that the SARS-CoV-2 S proteins utilize ACE2 and Transmembrane Serine Protease 2 (TMPRSS2) for host-cell entry, which are very similar to the mechanisms exploited by SARS-CoV [23]. See the “Structure, function, antigenicity, and hACE2 receptor recognition by the SARS-CoV-2 S glycoprotein” section of this review for detailed information on the mechanism of coronavirus cell entry mediated by the viral S glycoproteins. The S proteins, common among all coronaviruses, are a major target for eliciting antibodies therefore, structural and molecular details of S protein and its interactions with cognate receptors would be vital in developing vaccines and antiviral drugs against SARS-CoV-2.

In this review, we discuss the coronavirus classification, details of SARS-CoV-2 emergence, morphology, and key virulence factors. We specifically explain the structure of RNA-dependent RNA polymerase of SARS-CoV-2 and its significance in drug discovery. Further, the structure, function, and antigenicity of S glycoproteins and their interactions with human ACE2 (hACE2) receptor are discussed.

COVID-19, MERS & SARS

In January 2020, a novel coronavirus, SARS-CoV-2, was identified as the cause of an outbreak of viral pneumonia in Wuhan, China. The disease, later named coronavirus disease 2019 (COVID-19), subsequently spread globally. In the first three months after COVID-19 emerged nearly 1 million people were infected and 50,000 died. By six months the number of cases exceeded 10 million and there were more than 500,000 deaths. One of the troubling observations about COVID-19 is that people who are infected with SARS-CoV-2 – some scientists estimate up to 40% -- can transmit the virus to others before they have symptoms or without ever having symptoms of disease.

The Centers for Disease Control and Prevention (CDC) developed a test to diagnose COVID-19 in respiratory and serum samples. NIAID also is accelerating efforts to develop additional diagnostic tests for COVID-19. These tests are helping facilitate preclinical studies and aid in the development of medical countermeasures.

NIAID COVID-19 research efforts build on earlier research on severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), which also are caused by coronaviruses. MERS is a viral respiratory disease that was first reported in Saudi Arabia in September 2012 and has since spread to 27 countries, according to the World Health Organization. Some people infected with MERS coronavirus (MERS-CoV) develop severe acute respiratory illness, including fever, cough, and shortness of breath. From its emergence through January 2020, WHO confirmed 2,519 MERS cases and 866 deaths (about 1 in 3). Among all reported cases in people, about 80% have occurred in Saudi Arabia. Only two people in the United States have tested positive for MERS-CoV, both of whom recovered. They were healthcare providers who lived in Saudi Arabia, where they likely were infected before traveling to the U.S., according to the CDC.

Infection with SARS coronavirus (SARS-CoV) can cause a severe viral respiratory illness. SARS was first reported in Asia in February 2003, though cases subsequently were tracked to November 2002. SARS quickly spread to 26 countries before being contained after about four months. More than 8,000 people fell ill from SARS and 774 died. Since 2004, there have been no reported SARS cases.

Research evidence suggests that SARS-CoV and MERS-CoV originated in bats, and it is likely that SARS-CoV-2 did as well. SARS-CoV then spread from infected civets to people, while MERS-CoV spreads from infected dromedary camels to people. Scientists are trying to determine how SARS-CoV-2 spread from an animal reservoir to people.

Transmission lineage diversity and geographic range

We also characterized the spatial distribution of UK transmission lineages using available data on 107 virus genome sampling locations, which correspond broadly to UK counties or metropolitan regions (data S1). Although genomes were not collected randomly [some lineages and regions will be overrepresented because of targeted investigation of local outbreaks e.g., (22)], the number of UK lineages detected in each region correlates with the number of genomes sequenced (Fig. 4A Pearson’s r = 0.96 95% CI, 0.95 to 0.98) and the number of reported cases (fig. S10 Pearson’s r = 0.53 95% CI, 0.35 to 0.67 see also data S2) in each region. Further, larger lineages were observed in more locations every 100 additional genomes in a lineage increases its observed range by six or seven regions (Fig. 4B Pearson’s r = 0.8 95% CI, 0.78 to 0.82). Thus, bigger regional epidemics comprised a greater diversity of transmission lineages, and larger lineages were more geographically widespread. These observations indicate substantial dissemination of a subset of lineages across the UK and suggest that many regions experienced a series of introductions of new lineages from elsewhere, potentially hindering the impact of local interventions.

(A) Correlation between the number of transmission lineages detected in each region (points, median values bars, 95% HPD intervals) and the number of UK virus genomes from each region (Pearson’s r = 0.96 95% CI, 0.95 to 0.98). (B) Correlation between the spatial range of each transmission lineage and the number of virus genomes it contains (Pearson’s r = 0.8 95% CI, 0.78 to 0.82). (C) Map showing Shannon’s index (SI) for each region, calculated across the study period (2 February to 26 June). Yellow colors indicate higher SI values darker colors, lower values. (D) SI through time for the UK national capital cities. The dotted lines indicate the start of the UK national lockdown. (E) Illustration of the diverse spatial range distributions of UK transmission lineages. Colors represent the week of the first detected genome in the transmission lineage in each location. Circles show the number of sampled genomes per location. Histograms (bottom row) show the distribution of geographic distances for all sequence pairs within each lineage (see data S4 and fig. S12 for further details). Colored boxes next to lineage names are as depicted in Fig. 2D.

We quantified the substantial variation among regions in the diversity of transmission lineages present using Shannon’s index (SI this value increases as both the number of lineages and the evenness of their frequencies increase Fig. 4C and data S3). We observed the highest SIs in Hertfordshire (4.77), Greater London (4.62), and Essex (4.49) these locations are characterized by frequent commuter travel to or within London and proximity to major international airports (23). Locations with the three lowest nonzero SIs were in Scotland (Stirling = 0.96, Aberdeenshire = 1.04, Inverclyde = 1.32 Fig. 4C). We speculate that regional differences in transmission lineage diversity may be related to the level of connectedness to other regions.

To illustrate temporal trends in transmission lineage diversity, we plotted SI through time for each of the UK’s national capital cities (Fig. 4D). Lineage diversities in each peaked in late March and declined after the UK national lockdown, congruent with Fig. 3, C and D. Greater London’s epidemic was the most diverse and was characterized by an early, rapid rise in SI (Fig. 4D), consistent with epidemiological trends there (16, 24). Belfast’s lineage diversity was notably lower (data S4 shows other locations).

We observe variation in the spatial range of individual UK transmission lineages. Although some lineages are widespread, most are more localized and the range size distribution is right-skewed (fig. S11), congruent with an observed abundance of small lineages (Figs. 2C and 4B) and biogeographic theory [e.g., (25)]. For example, lineage DTA_13 is geographically dispersed (>50% of sequence pairs sampled >234 km apart), whereas DTA_290 is strongly local (95% of sequence pairs sampled <100 km apart) and DTA_62 has multiple foci of sampled genomes (Fig. 4E and fig. S12). The national distribution of cases therefore arose from the aggregation of multiple heterogeneous lineage-specific patterns.

Matt Miller

Paul Rothlauf, a visiting scientist at Washington University School of Medicine in St. Louis, works with a lab-made virus that infects cells and interacts with antibodies just like the COVID-19 virus, but lacks the ability to cause severe disease. This safer virus makes it possible for scientists who do not have access to high-level biosafety facilities to join the effort to find drugs or vaccines for COVID-19.

Airborne and potentially deadly, the virus that causes COVID-19 can only be studied safely under high-level biosafety conditions. Scientists handling the infectious virus must wear full-body biohazard suits with pressurized respirators, and work inside laboratories with multiple containment levels and specialized ventilation systems. While necessary to protect laboratory workers, these safety precautions slow down efforts to find drugs and vaccines for COVID-19 since many scientists lack access to the required biosafety facilities.

To help remedy that, researchers at Washington University School of Medicine in St. Louis have developed a hybrid virus that will enable more scientists to enter the fight against the pandemic. The researchers genetically modified a mild virus by swapping one of its genes for one from SARS-CoV-2, the virus that causes COVID-19. The resulting hybrid virus infects cells and is recognized by antibodies just like SARS-CoV-2, but can be handled under ordinary laboratory safety conditions.

The study is available online in Cell Host & Microbe.

“I’ve never had this many requests for a scientific material in such a short period of time,” said co-senior author Sean Whelan, PhD, the Marvin A. Brennecke Distinguished Professor and head of the Department of Molecular Microbiology. “We’ve distributed the virus to researchers in Argentina, Brazil, Mexico, Canada and, of course, all over the U.S. We have requests pending from the U.K. and Germany. Even before we published, people heard that we were working on this and started requesting the material.”

To create a model of SARS-CoV-2 that would be safer to handle, Whelan and colleagues – including co-senior author Michael S. Diamond, MD, PhD, the Herbert S. Gasser Professor of Medicine, and co-first authors Brett Case, PhD, a postdoctoral researcher in Diamond’s laboratory, and Paul W. Rothlauf, a graduate student in Whelan’s laboratory – started with vesicular stomatitis virus (VSV). This virus is a workhorse of virology labs because it is fairly innocuous and easy to manipulate genetically. Primarily a virus of cattle, horses and pigs, VSV occasionally infects people, causing a mild flu-like illness that lasts three to five days.

Viruses have proteins on their surfaces that they use to latch onto and infect cells. The researchers removed VSV’s surface-protein gene and replaced it with the one from SARS-CoV-2, known as spike. The switch created a new virus that targets cells like SARS-CoV-2 but lacks the other genes needed to cause severe disease. They dubbed the hybrid virus VSV-SARS-CoV-2.

Using serum from COVID-19 survivors and purified antibodies, the researchers showed that the hybrid virus was recognized by antibodies very much like a real SARS-CoV-2 virus that came from a COVID-19 patient. Antibodies or sera that prevented the hybrid virus from infecting cells also blocked the real SARS-CoV-2 virus from doing so antibodies or sera that failed to stop the hybrid virus also failed to deter the real SARS-CoV-2. In addition, a decoy molecule was equally effective at misdirecting both viruses and preventing them from infecting cells.

“Humans certainly develop antibodies against other SARS-CoV-2 proteins, but it’s the antibodies against spike that seem to be most important for protection,” Whelan said. “So as long as a virus has the spike protein, it looks to the human immune system like SARS-CoV-2, for all intents and purposes.”

The hybrid virus could help scientists evaluate a range of antibody-based preventives and treatments for COVID-19. The virus could be used to assess whether an experimental vaccine elicits neutralizing antibodies, to measure whether a COVID-19 survivor carries enough neutralizing antibodies to donate plasma to COVID-19 patients, or to identify antibodies with the potential to be developed into antiviral drugs.

“One of the problems in evaluating neutralizing antibodies is that a lot of these tests require a BSL-3 facility, and most clinical labs and companies don’t have BSL-3 facilities,” said Diamond, who is also a professor of molecular microbiology, and of pathology and immunology. “With this surrogate virus, you can take serum, plasma or antibodies and do high-throughput analyses at BSL-2 levels, which every lab has, without a risk of getting infected. And we know that it correlates almost perfectly with the data we get from bona fide infectious SARS-CoV-2.”

Since the hybrid virus looks like SARS-CoV-2 to the immune system but does not cause severe disease, it is a potential vaccine candidate, Diamond added. He, Whelan and colleagues are conducting animal studies to evaluate the possibility.

Case JB, Rothlauf PW, Chen RE, Liu Z, Zhao H, Kim AS, Bloyet L-M, Zeng Q, Tahan S, Droit L, Ilagan MXG, Tartell MA, Amarasinghe G, Henderson JP, Miersch S, Ustav M, Sidhu S, Virgin HW, Wang D, Ding S, Corti D, Theel ES, Fremont DH, Diamond MS, Whelan SPJ. Neutralizing antibody and soluble ACE2 inhibition of a replication-competent VSV-SARS-CoV-2 and a clinical isolate of SARS-CoV-2. Cell Host and Microbe. July 1, 2020. DOI: 10.1016/j.chom.2020.06.021

This study was supported by the National Institutes of Health (NIH), grant numbers R01AI127828, R37AI059371 and U01AI151810, and contract numbers 75N93019C00062 and HHSN272201700060C the Defense Advanced Research Projects Agency, contract number HR001117S0019 and Washington University in St. Louis.

Which Species Transmit COVID-19 to Humans? We&rsquore Still Not Sure.

Claire Jarvis
Mar 16, 2020

ABOVE: Civet cats are thought to have passed SARS-CoV, the virus that caused the 2003 SARS outbreak, from bats to humans.

W hen a new zoonotic outbreak occurs, scientists rush to trace the species the infection originated from. Often the infection jumps from its initial animal carrier to an intermediate host species, which then transmits the virus to humans. Identifying intermediate host species enable risk-mitigating public health policies to be implemented and gives researchers a better understanding of the disease evolution and pathogenesis.

SARS-CoV-2, the virus that causes COVID-19, belongs to the same family of viruses as SARS-CoV and MERS-CoV, which first circulated in bats before transmitting via intermediate hosts to humans. While SARS-CoV-2 is likely to have come to humans through a similar route, “we currently don’t have any evidence that there’s an intermediate host,” says William Karesh, the executive vice president for health and policy at EcoHealth Alliance, who notes that coronaviruses can directly transmit from bats to humans without an intermediate.

The 2003 SARS outbreak began with virus transmission between bats and civet cats, which then passed it on to humans. Similarly, the intermediate host during the 2012 MERS outbreak is believed to have been dromedary camels.

See “Where Coronaviruses Come From”

While the COVID-19 pandemic continues, scientists are using models to look for potential intermediate hosts. As of today (March 16), there have been more than 164,000 cases reported and 6,507 deaths. The first full COVID-19 genome sequences were released in January 2020, enabling researchers to compare the human version of the coronavirus to coronavirus strains already isolated in animals.

A recent paper from the labs of Ralph Baric and Fang Li, published in the Journal of Virology, used the 2003 SARS-CoV as a template to simulate the structure of key COVID-19 proteins and predict in which other species the virus strain could bind in a manner similar to how it does in humans.

The models support the well-accepted idea that the interaction between the receptor-binding domain (RBD) of the coronavirus spike protein and the host receptor angiotensin-converting enzyme 2 (ACE2) controls disease transmission in SARS and COVID-19. In other words, the spike protein grabs hold of ACE2 on host cells to gain entry into cells, where it replicates, bursts open the cell, and spreads to other cells. The researchers then modeled ACE2 receptor proteins belonging to different species to see which ones are vulnerable to SARS-CoV-2 infection. It turns out that pigs, ferrets, cats, orangutans, monkeys, at least some species of bats, and humans have similar levels of affinity for SARS-CoV-2 based on the structural similarity of their ACE2 receptors.

While the team did not rule out civets as intermediate hosts for the current outbreak, they noted several differences in the civet ACE2 receptor that made it less able to bind SARS-CoV-2. The going hypothesis is that the current outbreak started in bats, then moved to another species. While many of the earliest cases in Wuhan were linked to the Huanan Seafood market—which sold seafood and wildlife, including snakes and birds—not every case has a link to it. The wide variety of animal produce available at the market, and structural similarities of ACE2 receptors in many “suspect species” means scientists are still not confident about the transmission chain of SARS-CoV-2.

Although these models create a shortlist of potential reservoir species, “this study doesn’t identify intermediate hosts,” cautions Baric. He says he wants the findings to help researchers develop new coronavirus animal models to test vaccines and drugs and to study disease progression.

“There’s a lot of ongoing experimental work, which I think will be important for actually confirming some of the hypotheses advanced in this paper,” says Andrew Ward, a computational biologist at the Scripps Research Institute who was not involved in the study.

A similar modeling study by a different set of researchers was recently published in the Journal of Medical Virology. The authors propose—based on structural similarities between the viral RBD and host ACE2—that pangolins, snakes, and turtles could be possible intermediate hosts of SARS-CoV-2. The authors note that further research is needed to confirm these findings, while other experts have discredited the idea put forth by a different group of researchers in January that snakes are SARS-CoV-2 hosts.

Confirming the identity of any intermediate host through wet lab experimentation is a difficult process, and researchers may never nab the definitive culprit. “You can test thousands of bats, but to get the coronavirus you have to catch them on the day they’re shedding it,” says Karesh. He explains that it’s now several months since the initial animal-to-human SARS-CoV-2 transmission occurred, and the coronavirus circulation in animals may have dropped off, which would make the original strain even harder to find.

Y. Wan et al., “Receptor recognition by novel coronavirus from Wuhan: An analysis based on decade-long structural studies of SARS,” J Virology, doi:10.1128/JVI.00127-20, 2020.

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Note on sensitivity and specificity data

Where available, we list the manufacturer-reported sensitivity and specificity data. A highly sensitive test should capture all true positive results. A highly specific test should rule out all true negative results. These measures are not independently validated by the Johns Hopkins Center for Health Security. If sensitivity or specificity is not listed, it was not available from the manufacturer at the time of posting. When available, the number of samples used for sensitivity/specificity definitions are listed in the product description.

The terms “sensitivity” and “specificity” may not appear in the manufacturers’ information sheets, but are often reported as “positive percent agreement” and “negative percent agreement.“ Sensitivity may also be measured by calculating the limit of detection, which is the lowest detectable number of virus copies in a sample at which the test will return a positive result at least 95% of the time. Essentially, a lower limit of detection indicates a more sensitive test, with fewer viral copies per sample necessary to elicit a positive test result. The US FDA recommends that manufacturers use these terms to indicate that a nonreference standard was used when evaluating the test.

Triangulation number of the SARS CoV-19 virus - Biology

We determined secondary attack rates (SAR) among close contacts of 59 asymptomatic and symptomatic coronavirus disease case-patients by presymptomatic and symptomatic exposure. We observed no transmission from asymptomatic case-patients and highest SAR through presymptomatic exposure. Rapid quarantine of close contacts with or without symptoms is needed to prevent presymptomatic transmission.

During the ongoing coronavirus disease (COVID-19) pandemic, worldwide, >85 million severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections had been reported as of January 7, 2021 (https://covid19.who.int). Although it was clear from the beginning of the pandemic that symptomatic transmission of SARS-CoV-2 occurs, presymptomatic transmission has also been described (16). Furthermore, transmission from asymptomatic cases was deemed possible on the basis of findings that viral load of asymptomatic cases was similar to that of symptomatic cases (7). Understanding how transmission occurs from asymptomatic cases and from symptomatic cases in their presymptomatic and symptomatic phase, as well as the frequency of transmission, is essential for public health management. We assessed asymptomatic, presymptomatic, and symptomatic transmission during an outbreak investigation of 59 COVID-19 cases by determining secondary attack rates (SAR) according to the respective exposure periods. In addition, we estimated key parameters such as serial interval and incubation period.

The Study

On February 29, 2020, a COVID-19 case was notified to the local public health authority (LPHA) of a rural district in southern Germany without previously observed community transmission. During their infectious period, the case-patient had attended several carnival events in the district. The LPHA immediately initiated contact tracing, identifying all close contacts they were quarantined and tested irrespective of symptoms. By the end of March 2020, a cluster of 59 cases had been identified through successive contact tracing activities.

We interviewed the case-patients of the cluster by phone regarding symptoms developed during SARS-CoV-2 infection potential source cases or events and household contacts (HCs) and close nonhousehold or other contacts (OCs) in their infectious period (Appendix). We obtained an empirical distribution of the serial interval from the average over all possible transmission trees of the cluster. We obtained generation time and incubation period by averaging over the estimates as described by Reich et al. (8) (Appendix).

To estimate SAR and relative risks (RRs) we conducted a retrospective cohort study, including all HCs and OCs as recalled by the case-patients that met inclusion criteria (Appendix). We calculated pooled SAR of HCs and OCs for 2 outcomes, laboratory confirmation (SARlab) and development of respiratory symptoms (SARres) in the following groups: HCs and OCs of asymptomatic case-patients who never experienced symptoms HCs and OCs of symptomatic case-patients in which the phase with contact could not be specified by the case-patient or with contact in both phases OCs of symptomatic case-patients with contact only in the presymptomatic phase and OCs of symptomatic case-patients with contact only in the symptomatic phase.

Figure. Transmission tree of the investigated cluster of coronavirus disease that evolved in a district in southern Germany. Cases 39, 40, and 60 participated in the survey but were not included.

We were able to contact 53/59 (90%) case-patients. Three case-patients were children <15 years of age (Table 1). Forty-six (87%) were symptomatic, and 7 (13%) were asymptomatic (Appendix Figure 1). The cluster resulted in 144 possible transmission trees, which span over 5 generations (Figure). No secondary transmission resulted from asymptomatic cases. We determined a median serial interval of 3.0 (IQR 1.0–6.0) days and a median incubation period of 4.3 (IQR 2.5–6.5) days (Appendix Table 1).

In total, 42 HCs and 212 OCs were included in the cohort study (Table 1). The overall SARlab was 13% (4/32) for HCs and 14% (20/148) for OCs. The overall SARres was 29% (12/42) for HCs and 17% (29/170) for OCs (Table 2). We did not identify any HC who tested positive or experienced respiratory symptoms after contact with asymptomatic case-patients. Neither SARlab nor SARres of HCs of symptomatic case-patients were significantly higher compared with HCs of asymptomatic cases (SARlab p = 1.0 SARres p = 0.23). We observed no laboratory-confirmed SARS-CoV-2 transmission from asymptomatic case-patients to any of the 22 OCs (Table 2 Appendix Figure 2). SARlab was highest for OCs with contact during the case-patients’ presymptomatic phases (21% 15/72) yielding a RR of 6.5 (95% CI 1.1–∞) when compared with contacts of asymptomatic case-patients. Adjusting for case-patients’ age, sex, and number of contact persons showed no substantial changes in the magnitude of estimates (data not shown). Presymptomatic transmission accounted for > 75% of all transmissions to OCs in the cohort (Appendix).

Conclusions

In this cluster of COVID-19 cases, little to no transmission occurred from asymptomatic case-patients. Presymptomatic transmission was more frequent than symptomatic transmission. The serial interval was short very short intervals occurred.

The fact that we did not detect any laboratory-confirmed SARS-CoV-2 transmission from asymptomatic case-patients is in line with multiple studies (911). However, Oran et al. have speculated that asymptomatic cases contribute to the rapid progression of the pandemic (12). Some studies may be prone to misclassify presymptomatic cases as asymptomatic, leading to heterogeneous reporting of SAR of asymptomatic cases, because of different case definitions or differential duration of follow-up. In our study we used a very sensitive case definition for symptomatic cases that did not require specific symptoms (e.g. fever) to be present. Also, timing of our study would have enabled detection of late onset of symptoms, which gives us confidence in our classification of exposure groups.

The 75% of SARS-CoV-2 transmissions in our cohort from case-patients in their presymptomatic phase exceeds reported transmission rates from other investigations (1,13,14). Possible reasons are the prior evidence that infectiousness peaks around the date of symptom onset, declining thereafter (15), and that case-patients probably reduced social contacts themselves once they experienced symptoms or when ordered to self-isolate. A large proportion of cases with presymptomatic transmission in our cluster is further supported by the median serial interval of 3 days.

Of note are the consequences for public health management: first, the need for early detection of COVID-19 cases and for initiation of contact tracing as soon as possible to quarantine close contacts, particularly because short serial intervals may lead to further transmission chains. Second, suspect case-patients or persons with any respiratory illness should immediately self-isolate and inform their contacts met in the presymptomatic and symptomatic phases.

A limitation of our study is that evidence was obtained from a single outbreak and might not be applicable to other settings. We used only information as recalled by the case-patients, which is imperfect and may introduce errors or bias. Because we used development of respiratory symptoms as a proxy for possible SARS-CoV-2 infections among contacts, and because incidence of respiratory illnesses was still high in this winter timeframe, SARres may be overestimated. However, this possible source of misclassification should be nondifferential between groups. We excluded many HCs because of uncertainties about the potential simultaneous introduction of SARS-CoV-2 in the household, which may have led to an underestimation of SAR among HCs. In the transmission tree, we had to omit various source case–infectee pairs because case-patients’ recalled symptom onset differed substantially from surveillance data and was not plausible (Appendix). Finally, although community transmission of SARS-CoV-2 was deemed unlikely in the affected district at the time, we cannot rule out that some cases acquired infections from other sources.

In conclusion, our study suggests that asymptomatic cases are unlikely to contribute substantially to the spread of SARS-CoV-2. COVID-19 cases should be detected and managed early to quarantine close contacts immediately and prevent presymptomatic transmissions.

Dr. Bender is a fellow of the European Public Health Microbiology Training Programme of the European Centre for Disease Prevention and Control. She is a microbiologist affiliated with the Nosocomial Pathogens and Antibiotic Resistances Unit, Department of Infectious Diseases of the Robert Koch Institute. Her research interest focuses on the emergence of multidrug-resistant nosocomial pathogens.

Acknowledgment

As J.K.B. is a fellow of the European Public Health Microbiology Training at the European Centre for Disease Prevention and Control (ECDC) Fellowship Programme (and supported financially by this program) and M.B. is a fellow of the European Programme for Intervention Epidemiology Training at the ECDC and the Postgraduate Training for Applied Epidemiology at the Robert Koch Institute, we first acknowledge these programs. We also thank the local public health authority of the district for their continuous efforts fighting the COVID-19 pandemic as well as for providing us with information about the cluster and corresponding data for subsequent analysis. We thank the team of researchers assisting with the case interviews: Johannes Zeiher, Nora-Katharina Küpke, Sandra Niendorf, Sangeeta Banerji, and Susann Dupke. Furthermore, we especially thank all COVID-19 case-patients of this cluster for their participation in the study.

References

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Suggested citation for this article: Bender JK, Brandl M, Höhle M, Buchholz U, Zeitlmann N. Analysis of asymptomatic and presymptomatic transmission in SARS-CoV-2 outbreak, Germany, 2020. Emerg Infect Dis. 2021 Apr [date cited]. https://doi.org/10.3201/eid2704.204576

Original Publication Date: February 18, 2021

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Jennifer K. Bender, Department of Infectious Diseases, Robert Koch Institute, Burgstrasse 37, 38855 Wernigerode, Germany

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SARS-CoV-2 circulated undetected months before first COVID-19 cases in Wuhan, China: study

The SARS-CoV-2 virus under a microscope. Credit: National Institute of Allergy and Infectious Diseases

Using molecular dating tools and epidemiological simulations, researchers at University of California San Diego School of Medicine, with colleagues at the University of Arizona and Illumina, Inc., estimate that the SARS-CoV-2 virus was likely circulating undetected for at most two months before the first human cases of COVID-19 were described in Wuhan, China in late-December 2019.

Writing in the March 18, 2021 online issue of Science, they also note that their simulations suggest that the mutating virus dies out naturally more than three-quarters of the time without causing an epidemic.

"Our study was designed to answer the question of how long could SARS-CoV-2 have circulated in China before it was discovered," said senior author Joel O. Wertheim, Ph.D., associate professor in the Division of Infectious Diseases and Global Public Health at UC San Diego School of Medicine.

"To answer this question, we combined three important pieces of information: a detailed understanding of how SARS-CoV-2 spread in Wuhan before the lockdown, the genetic diversity of the virus in China and reports of the earliest cases of COVID-19 in China. By combining these disparate lines of evidence, we were able to put an upper limit of mid-October 2019 for when SARS-CoV-2 started circulating in Hubei province."

Cases of COVID-19 were first reported in late-December 2019 in Wuhan, located in the Hubei province of central China. The virus quickly spread beyond Hubei. Chinese authorities cordoned off the region and implemented mitigation measures nationwide. By April 2020, local transmission of the virus was under control but, by then, COVID-19 was pandemic with more than 100 countries reporting cases.

SARS-CoV-2 is a zoonotic coronavirus, believed to have jumped from an unknown animal host to humans. Numerous efforts have been made to identify when the virus first began spreading among humans, based on investigations of early-diagnosed cases of COVID-19. The first cluster of cases—and the earliest sequenced SARS-CoV-2 genomes—were associated with the Huanan Seafood Wholesale Market, but study authors say the market cluster is unlikely to have marked the beginning of the pandemic because the earliest documented COVID-19 cases had no connection to the market.

Regional newspaper reports suggest COVID-19 diagnoses in Hubei date back to at least November 17, 2019, suggesting the virus was already actively circulating when Chinese authorities enacted public health measures.

In the new study, researchers used molecular clock evolutionary analyses to try to home in on when the first, or index, case of SARS-CoV-2 occurred. "Molecular clock" is a term for a technique that uses the mutation rate of genes to deduce when two or more life forms diverged—in this case, when the common ancestor of all variants of SARS-CoV-2 existed, estimated in this study to as early as mid-November 2019.

Molecular dating of the most recent common ancestor is often taken to be synonymous with the index case of an emerging disease. However, said co-author Michael Worobey, Ph.D., professor of ecology and evolutionary biology at University of Arizona: "The index case can conceivably predate the common ancestor—the actual first case of this outbreak may have occurred days, weeks or even many months before the estimated common ancestor. Determining the length of that 'phylogenetic fuse' was at the heart of our investigation."

Based on this work, the researchers estimate that the median number of persons infected with SARS-CoV-2 in China was less than one until November 4, 2019. Thirteen days later, it was four individuals, and just nine on December 1, 2019. The first hospitalizations in Wuhan with a condition later identified as COVID-19 occurred in mid-December.

Study authors used a variety of analytical tools to model how the SARS-CoV-2 virus may have behaved during the initial outbreak and early days of the pandemic when it was largely an unknown entity and the scope of the public health threat not yet fully realized.

These tools included epidemic simulations based on the virus's known biology, such as its transmissibility and other factors. In just 29.7 percent of these simulations was the virus able to create self-sustaining epidemics. In the other 70.3 percent, the virus infected relatively few persons before dying out. The average failed epidemic ended just eight days after the index case.

"Typically, scientists use the viral genetic diversity to get the timing of when a virus started to spread," said Wertheim. "Our study added a crucial layer on top of this approach by modeling how long the virus could have circulated before giving rise to the observed genetic diversity.

"Our approach yielded some surprising results. We saw that over two-thirds of the epidemics we attempted to simulate went extinct. That means that if we could go back in time and repeat 2019 one hundred times, two out of three times, COVID-19 would have fizzled out on its own without igniting a pandemic. This finding supports the notion that humans are constantly being bombarded with zoonotic pathogens."

Wertheim noted that even as SARS-CoV-2 was circulating in China in the fall of 2019, the researchers' model suggests it was doing so at low levels until at least December of that year.

"Given that, it's hard to reconcile these low levels of virus in China with claims of infections in Europe and the U.S. at the same time," Wertheim said. "I am quite skeptical of claims of COVID-19 outside China at that time."

The original strain of SARS-CoV-2 became epidemic, the authors write, because it was widely dispersed, which favors persistence, and because it thrived in urban areas where transmission was easier. In simulated epidemics involving less dense rural communities, epidemics went extinct 94.5 to 99.6 percent of the time.

The virus has since mutated multiple times, with a number of variants becoming more transmissible.

"Pandemic surveillance wasn't prepared for a virus like SARS-CoV-2," Wertheim said. "We were looking for the next SARS or MERS, something that killed people at a high rate, but in hindsight, we see how a highly transmissible virus with a modest mortality rate can also lay the world low."