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RNA from the SARS-CoV-2 virus taking over the cells it infects: Virulence – Pathogen’s ability to infect a Resistant Host: The Imbalance between Controlling Virus Replication versus Activation of the Adaptive Immune Response

Curator: Aviva Lev-Ari, PhD, RN – I added colors and bold face

 

See

The Genome Structure of CORONAVIRUS, SARS-CoV-2

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/05/04/the-genome-structure-of-coronavirus-sars-cov-2-i-awaited-for-this-article-for-60-days/

 

Imbalanced Host Response to SARS-CoV-2 Drives Development of COVID-19

Open Access Published:May 15, 2020DOI:https://doi.org/10.1016/j.cell.2020.04.026

Highlights

  • SARS-CoV-2 infection induces low IFN-I and -III levels with a moderate ISG response
  • Strong chemokine expression is consistent across in vitroex vivo, and in vivo models
  • Low innate antiviral defenses and high pro-inflammatory cues contribute to COVID-19

Summary

Viral pandemics, such as the one caused by SARS-CoV-2, pose an imminent threat to humanity. Because of its recent emergence, there is a paucity of information regarding viral behavior and host response following SARS-CoV-2 infection. Here we offer an in-depth analysis of the transcriptional response to SARS-CoV-2 compared with other respiratory viruses. Cell and animal models of SARS-CoV-2 infection, in addition to transcriptional and serum profiling of COVID-19 patients, consistently revealed a unique and inappropriate inflammatory response. This response is defined by low levels of type I and III interferons juxtaposed to elevated chemokines and high expression of IL-6. We propose that reduced innate antiviral defenses coupled with exuberant inflammatory cytokine production are the defining and driving features of COVID-19.

Graphical Abstract

Keywords

Results

Defining the Transcriptional Response to SARS-CoV-2 Relative to Other Respiratory Viruses

To compare the transcriptional response of SARS-CoV-2 with other respiratory viruses, including MERS-CoV, SARS-CoV-1, human parainfluenza virus 3 (HPIV3), respiratory syncytial virus (RSV), and IAV, we first chose to focus on infection in a variety of respiratory cell lines (Figure 1). To this end, we collected poly(A) RNA from infected cells and performed RNA sequencing (RNA-seq) to estimate viral load. These data show that virus infection levels ranged from 0.1% to more than 50% of total RNA reads (Figure 1A).

Discussion

In the present study, we focus on defining the host response to SARS-CoV-2 and other human respiratory viruses in cell lines, primary cell cultures, ferrets, and COVID-19 patients. In general, our data show that the overall transcriptional footprint of SARS-CoV-2 infection was distinct in comparison with other highly pathogenic coronaviruses and common respiratory viruses such as IAV, HPIV3, and RSV. It is noteworthy that, despite a reduced IFN-I and -III response to SARS-CoV-2, we observed a consistent chemokine signature. One exception to this observation is the response to high-MOI infection in A549-ACE2 and Calu-3 cells, where replication was robust and an IFN-I and -III signature could be observed. In both of these examples, cells were infected at a rate to theoretically deliver two functional virions per cell in addition to any defective interfering particles within the virus stock that were not accounted for by plaque assays. Under these conditions, the threshold for PAMP may be achieved prior to the ability of the virus to evade detection through production of a viral antagonist. Alternatively, addition of multiple genomes to a single cell may disrupt the stoichiometry of viral components, which, in turn, may itself generate PAMPs that would not form otherwise. These ideas are supported by the fact that, at a low-MOI infection in A549-ACE2 cells, high levels of replication could also be achieved, but in the absence of IFN-I and -III induction. Taken together, these data suggest that, at low MOIs, the virus is not a strong inducer of the IFN-I and -III system, as opposed to conditions where the MOI is high.
Taken together, the data presented here suggest that the response to SARS-CoV-2 is imbalanced with regard to controlling virus replication versus activation of the adaptive immune response. Given this dynamic, treatments for COVID-19 have less to do with the IFN response and more to do with controlling inflammation. Because our data suggest that numerous chemokines and ILs are elevated in COVID-19 patients, future efforts should focus on U.S. Food and Drug Administration (FDA)-approved drugs that can be rapidly deployed and have immunomodulating properties.

SOURCE

https://www.cell.com/cell/fulltext/S0092-8674(20)30489-X

SARS-CoV-2 ORF3b is a potent interferon antagonist whose activity is further increased by a naturally occurring elongation variant

Yoriyuki KonnoIzumi KimuraKeiya UriuMasaya FukushiTakashi IrieYoshio KoyanagiSo NakagawaKei Sato

Abstract

One of the features distinguishing SARS-CoV-2 from its more pathogenic counterpart SARS-CoV is the presence of premature stop codons in its ORF3b gene. Here, we show that SARS-CoV-2 ORF3b is a potent interferon antagonist, suppressing the induction of type I interferon more efficiently than its SARS-CoV ortholog. Phylogenetic analyses and functional assays revealed that SARS-CoV-2-related viruses from bats and pangolins also encode truncated ORF3b gene products with strong anti-interferon activity. Furthermore, analyses of more than 15,000 SARS-CoV-2 sequences identified a natural variant, in which a longer ORF3b reading frame was reconstituted. This variant was isolated from two patients with severe disease and further increased the ability of ORF3b to suppress interferon induction. Thus, our findings not only help to explain the poor interferon response in COVID-19 patients, but also describe a possibility of the emergence of natural SARS-CoV-2 quasi-species with extended ORF3b that may exacerbate COVID-19 symptoms.

Highlights

  • ORF3b of SARS-CoV-2 and related bat and pangolin viruses is a potent IFN antagonist

  • SARS-CoV-2 ORF3b suppresses IFN induction more efficiently than SARS-CoV ortholog

  • The anti-IFN activity of ORF3b depends on the length of its C-terminus

  • An ORF3b with increased IFN antagonism was isolated from two severe COVID-19 cases

Competing Interest Statement

The authors have declared no competing interest.

Paper in collection COVID-19 SARS-CoV-2 preprints from medRxiv and bioRxiv

 

SOURCE

https://www.biorxiv.org/content/10.1101/2020.05.11.088179v1

 

 

A deep dive into how the new coronavirus infects cells has found that it orchestrates a hostile takeover of their genes unlike any other known viruses do, producing what one leading scientist calls “unique” and “aberrant” changes.Recent studies show that in seizing control of genes in the human cells it invades, the virus changes how segments of DNA are read, doing so in a way that might explain why the elderly are more likely to die of Covid-19 and why antiviral drugs might not only save sick patients’ lives but also prevent severe disease if taken before infection.“It’s something I have never seen in my 20 years of” studying viruses, said virologist Benjamin tenOever of the Icahn School of Medicine at Mount Sinai, referring to how SARS-CoV-2, the virus that causes Covid-19, hijacks cells’ genomes.

The “something” he and his colleagues saw is how SARS-CoV-2 blocks one virus-fighting set of genes but allows another set to launch, a pattern never seen with other viruses. Influenza and the original SARS virus (in the early 2000s), for instance, interfere with both arms of the body’s immune response — what tenOever dubs “call to arms” genes and “call for reinforcement” genes.

The first group of genes produces interferons. These proteins, which infected cells release, are biological semaphores, signaling to neighboring cells to activate some 500 of their own genes that will slow down the virus’ ability to make millions of copies of itself if it invades them. This lasts seven to 10 days, tenOever said, controlling virus replication and thereby buying time for the second group of genes to act.

This second set of genes produce their own secreted proteins, called chemokines, that emit a biochemical “come here!” alarm. When far-flung antibody-making B cells and virus-killing T cells sense the alarm, they race to its source. If all goes well, the first set of genes holds the virus at bay long enough for the lethal professional killers to arrive and start eradicating viruses.

“Most other viruses interfere with some aspect of both the call to arms and the call for reinforcements,” tenOever said. “If they didn’t, no one would ever get a viral illness”: The one-two punch would pummel any incipient infection into submission.

SARS-CoV-2, however, uniquely blocks one cellular defense but activates the other, he and his colleagues reported in a study published last week in Cell. They studied healthy human lung cells growing in lab dishes, ferrets (which the virus infects easily), and lung cells from Covid-19 patients. In all three, they found that within three days of infection, the virus induces cells’ call-for-reinforcement genes to produce cytokines. But it blocks their call-to-arms genes — the interferons that dampen the virus’ replication.

The result is essentially no brakes on the virus’s replication, but a storm of inflammatory molecules in the lungs, which is what tenOever calls an “unique” and “aberrant” consequence of how SARS-CoV-2 manipulates the genome of its target.

In another new study, scientists in Japan last week identified how SARS-CoV-2 accomplishes that genetic manipulation. Its ORF3b gene produces a protein called a transcription factor that has “strong anti-interferon activity,” Kei Sato of the University of Tokyo and colleagues found — stronger than the original SARS virus or influenza viruses. The protein basically blocks the cell from recognizing that a virus is present, in a way that prevents interferon genes from being expressed.

In fact, the Icahn School team found no interferons in the lung cells of Covid-19 patients. Without interferons, tenOever said, “there is nothing to stop the virus from replicating and festering in the lungs forever.”

That causes lung cells to emit even more “call-for-reinforcement” genes, summoning more and more immune cells. Now the lungs have macrophages and neutrophils and other immune cells “everywhere,” tenOever said, causing such runaway inflammation “that you start having inflammation that induces more inflammation.”

At the same time, unchecked viral replication kills lung cells involved in oxygen exchange. “And suddenly you’re in the hospital in severe respiratory distress,” he said.

In elderly people, as well as those with diabetes, heart disease, and other underlying conditions, the call-to-arms part of the immune system is weaker than in younger, healthier people, even before the coronavirus arrives. That reduces even further the cells’ ability to knock down virus replication with interferons, and imbalances the immune system toward the dangerous inflammatory response.

The discovery that SARS-CoV-2 strongly suppresses infected cells’ production of interferons has raised an intriguing possibility: that taking interferons might prevent severe Covid-19 or even prevent it in the first place, said Vineet Menachery of the University of Texas Medical Branch.

In a study of human cells growing in lab dishes, described in a preprint (not peer-reviewed or published in a journal yet), he and his colleagues also found that SARS-CoV-2 “prevents the vast amount” of interferon genes from turning on. But when cells growing in lab dishes received the interferon IFN-1 before exposure to the coronavirus, “the virus has a difficult time replicating.”

After a few days, the amount of virus in infected but interferon-treated cells was 1,000- to 10,000-fold lower than in infected cells not pre-treated with interferon. (The original SARS virus, in contrast, is insensitive to interferon.)

Ending the pandemic and preventing its return is assumed to require an effective vaccine to prevent infectionand antiviral drugs such as remdesivir to treat the very sick, but the genetic studies suggest a third strategy: preventive drugs.

It’s possible that treatment with so-called type-1 interferon “could stop the virus before it could get established,” Menachery said.

Giving drugs to healthy people is always a dicey proposition, since all drugs have side effects — something considered less acceptable than when a drug is used to treat an illness. “Interferon treatment is rife with complications,” Menachery warned. The various interferons, which are prescribed for hepatitis, cancers, and many other diseases, can cause flu-like symptoms.

But the risk-benefit equation might shift, both for individuals and for society, if interferons or antivirals or other medications are shown to reduce the risk of developing serious Covid-19 or even make any infection nearly asymptomatic.

Interferon “would be warning the cells the virus is coming,” Menachery said, so such pretreatment might “allow treated cells to fend off the virus better and limit its spread.” Determining that will of course require clinical trials, which are underway.

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Is Remdesivir the miracle cure or a short term cure for COVID-19?

Reporter: Irina Robu, PhD

 

Updated on 5/23/2020

 

New England Journal of Medicine

SOURCE

https://www.nejm.org/doi/full/10.1056/NEJMoa2007764

Disclosures

The trial was sponsored and primarily funded by the National Institute of Allergy and Infectious Diseases, the NIH, and funded in part by the NIAID and the National Cancer Institute, NIH. The trial has also been funded in part by the governments of Japan, Mexico, Denmark, and Singapore. The trial site in South Korea received funding from the Seoul National University Hospital. Support for the London International Coordinating Centre was also provided by the United Kingdom Medical Research Council.

Beigel disclosed no conflicts of interest.

Other co-authors disclosed support from NIH/NIAID/DMID, University of Minnesota, Medical Research Council U.K., Novo Nordisk Foundation, Simonsen Foundation, GSK, Pfizer, Boehringer Ingelheim, Gliead, MSD, Lundbeck Foundation, Merck, Sanofi-Pasteur,Cepheid, Ellume, Genentech, Janssen, ViiV Healthcare, Integrum Scientific LLC, UCL, Bristol University, Gilead Sciences Europe, ECDC, EU Social funds and National resources.

One co-author is an employee of the U.S. government.

Abstract

BACKGROUND

Although several therapeutic agents have been evaluated for the treatment of coronavirus disease 2019 (Covid-19), none have yet been shown to be efficacious.

METHODS

We conducted a double-blind, randomized, placebo-controlled trial of intravenous remdesivir in adults hospitalized with Covid-19 with evidence of lower respiratory tract involvement. Patients were randomly assigned to receive either remdesivir (200 mg loading dose on day 1, followed by 100 mg daily for up to 9 additional days) or placebo for up to 10 days. The primary outcome was the time to recovery, defined by either discharge from the hospital or hospitalization for infection-control purposes only.

RESULTS

A total of 1063 patients underwent randomization. The data and safety monitoring board recommended early unblinding of the results on the basis of findings from an analysis that showed shortened time to recovery in the remdesivir group. Preliminary results from the 1059 patients (538 assigned to remdesivir and 521 to placebo) with data available after randomization indicated that those who received remdesivir had a median recovery time of 11 days (95% confidence interval [CI], 9 to 12), as compared with 15 days (95% CI, 13 to 19) in those who received placebo (rate ratio for recovery, 1.32; 95% CI, 1.12 to 1.55; P<0.001). The Kaplan-Meier estimates of mortality by 14 days were 7.1% with remdesivir and 11.9% with placebo (hazard ratio for death, 0.70; 95% CI, 0.47 to 1.04). Serious adverse events were reported for 114 of the 541 patients in the remdesivir group who underwent randomization (21.1%) and 141 of the 522 patients in the placebo group who underwent randomization (27.0%).

CONCLUSIONS

Remdesivir was superior to placebo in shortening the time to recovery in adults hospitalized with Covid-19 and evidence of lower respiratory tract infection. (Funded by the National Institute of Allergy and Infectious Diseases and others; ACCT-1 ClinicalTrials.gov number, NCT04280705. opens in new tab.)

References (14)

  1. Helmy YAFawzy MElaswad ASobieh AKenney SPShehata AA. The COVID-19 pandemic: a comprehensive review of taxonomy, genetics, epidemiology, diagnosis, treatment, and control. J Clin Med 2020;9(4):E1225E1225.

    Google Scholar. opens in new tab

  2. Cao BWang YWen D, et al. A trial of lopinavir–ritonavir in adults hospitalized with severe Covid-19. N Engl J Med 2020;382:17871799.

    Google Scholar. opens in new tab

  3. Borba MGSVal FFASampaio VS, et al. Effect of high vs low doses of chloroquine diphosphate as adjunctive therapy for patients hospitalized with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection: a randomized clinical trial. JAMA Netw Open 2020;3(4):e208857e208857.

    Google Scholar. opens in new tab

  4. Sheahan TPSims ACLeist SR, et al. Comparative therapeutic efficacy of remdesivir and combination lopinavir, ritonavir, and interferon beta against MERS-CoV. Nat Commun 2020;11:222222.

    Google Scholar. opens in new tab

  5. Agostini MLAndres ELSims AC, et al. Coronavirus susceptibility to the antiviral remdesivir (GS-5734) is mediated by the viral polymerase and the proofreading exoribonuclease. mBio 2018;9(2):e00221-18e00221-18.

    Google Scholar. opens in new tab

  6. Brown AJWon JJGraham RL, et al. Broad spectrum antiviral remdesivir inhibits human endemic and zoonotic deltacoronaviruses with a highly divergent RNA dependent RNA polymerase. Antiviral Res 2019;169:104541104541.

    Google Scholar. opens in new tab

  7. Sheahan TPSims ACGraham RL, et al. Broad-spectrum antiviral GS-5734 inhibits both epidemic and zoonotic coronaviruses. Sci Transl Med 2017;9:eaal3653eaal3653.

    Google Scholar. opens in new tab

  8. Wang MCao RZhang L, et al. Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro. Cell Res 2020;30:269271.

    Google Scholar. opens in new tab

  9. de Wit ERasmussen ALFalzarano D, et al. Middle East respiratory syndrome coronavirus (MERS-CoV) causes transient lower respiratory tract infection in rhesus macaques. Proc Natl Acad Sci U S A 2013;110:1659816603.

    Google Scholar. opens in new tab

  10. de Wit EFeldmann FCronin J, et al. Prophylactic and therapeutic remdesivir (GS-5734) treatment in the rhesus macaque model of MERS-CoV infection. Proc Natl Acad Sci U S A 2020;117:67716776.

    Google Scholar. opens in new tab

  11. Royal College of Physicians. National Early Warning Score (NEWS) 2. 2017(https://www.rcplondon.ac.uk/projects/outputs/national-early-warning-score-news-2. opens in new tab).

    Google Scholar. opens in new tab

  12. King JCBeigel JHIson MG, et al. Clinical development of therapeutic agents for hospitalized patients with influenza: challenges and innovations. Open Forum Infect Dis 2019;6:ofz137ofz137.

    Google Scholar. opens in new tab

  13. Wang YZhang DDu G, et al. Remdesivir in adults with severe COVID-19: a randomised, double-blind, placebo-controlled, multicentre trial. Lancet 2020;395:15691578.

    Google Scholar. opens in new tab

  14. The CONSORT Group. 3b. Changes to trial design (http://www.consort-statement.org/consort-2010. opens in new tab).

    Google Scholar

Remdesivir Data from NIAID Trial Published

— “Not a panacea” or a “cure-all,” expert cautions

Peer-reviewed findings were published late Friday from one of the key trials of remdesivir, perhaps the most promising antiviral agent for COVID-19, confirming and extending topline results announced a month ago via press release.

Hospitalized patients with COVID-19 who received remdesivir had a median recovery time of 11 days versus 15 days with placebo (rate ratio for recovery 1.32, 95% CI 1.12-1.55, P<0.001), reported John Beigel, MD, of the National Institute of Allergy and Infectious Diseases (NIAID), and colleagues.

Mortality estimates by 14 days were lower for the remdesivir group compared to placebo, but non-significant (HR for death 0.70, 95% CI 0.47-1.04), the authors wrote in the New England Journal of Medicine.

Interestingly, when researchers examined outcomes on an 8-point ordinal scale, they found patients with a baseline ordinal score of 5 had a rate ratio for recovery of 1.47 (95% CI 1.17-1.84), while patients with a baseline score of 7 had a rate ratio for recovery of 0.95 (95% CI 0.64-1.42).

Some of these data were released by the NIAID on April 29, but without further details such as 95% confidence intervals. On May 1, the FDA agreed to let remdesivir be used clinically under an emergency use authorization. Since then, however, clinicians and other researchers have clamored for a fuller report, to help guide their clinical practice. For example, questions were raised as to whether particular subgroups got more benefit from the drug than others.

David Aronoff, MD, of Vanderbilt University Medical Center in Nashville, who was not involved in the research, noted the drug seemed more effective when given to patients who weren’t as severely ill, earlier in the course of disease. He added this wasn’t surprising, given remdesivir’s mechanism of action as an antiviral, which works by blocking the virus from replicating.

“The drug doesn’t affect the host, it only affects the virus. What seems to cause major problems late in the course of disease is the inflammatory response to the initial damage the virus causes,” he told MedPage Today.

Aronoff likened the virus to an arsonist setting fires, and antivirals like remdesivir as the police trying to catch the arsonist before they set more fires.

“But once the building is on fire, it doesn’t matter where the arsonist is,” he noted.

This is why combining a drug to address the viral response with a drug to address the host response may be critical to treating the virus. Aronoff cited the NIAID’s ACTT-2 trial in progress, which will examine combination therapy with remdesivir and anti-inflammatory drug, baricitinib, versus remdesivir alone.

SOURCE

https://www.medpagetoday.com/infectiousdisease/covid19/86670?xid=NL_breakingnewsalert_2020-05-23&eun=g99985d0r&utm_source=Sailthru&utm_medium=email&utm_campaign=RemdesivirAlert_052320&utm_term=NL_Daily_Breaking_News_Active

 

Is Remdesivir the miracle cure or a short term cure for COVID-19?

Reporter: Irina Robu, PhD

 

In 1947, amid the “Golden Age” of antibiotic research that yielded many of the medicines used against bacteria such as chloramphenicol, a molecule that could combat a wide array of bacteria from different families. It was among the first FDA-approved broad-spectrum antibiotics used against typhus/meningitis. Now, chloramphenicol’s side effects make it a last-resort drug but it remains invaluable against a host of bacterial infections.
Viruses are more slippery targets than bacteria and they are a hundred times smaller and consist only of bare-bones cellular machinery. There are simply fewer targets at which to aim antivirals, especially for drugs that would shoot for the rare viral components that remain common across diverse types of viruses. Scientists call this virus-pinpointing model the “one drug, one bug” approach. An antiviral’s mechanism can’t be too generic, either.

Even with that, there is no common mechanism to target all viruses but instead researchers hope to expand the existing list of broad-spectrum antivirals and find more medicines that work on all viruses of a certain family. This reality makes the search for treatments for SARS-CoV-2 all the more challenging. Presently, no broad-spectrum antiviral is accepted for the treatment of all coronaviruses of which a new strain has driven the current pandemic.

With no specific antiviral drug for treatment of patients with severe COVID-19, scientists are rushing to find a solution. Yet, remdesivir’s journey from hypothesis to treatment is unparalleled. The drug was originally investigated by Gilead as a treatment for another lethal viral disease, Ebola. Remdesivir, a nucleoside analogue prodrug has inhibitory effects on pathogenic animal and human coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in vitro, and inhibits Middle East respiratory syndrome coronavirus, SARS-CoV-1, and SARS-CoV-2 replication in animal models.

However, Gilead was unwilling to give up on its investment in the drug and remained hopeful that the drug might be useful in treating COVID-19. In collaboration with Chinese researchers, the National Institute of Allergy and Infectious Diseases (NIAID) and the pharmaceutical company behind the drug, Gilead, all launched studies of remdesivir’s efficacy in treating COVID-19. Based on those encouraging results in May 1, the FDA issued an emergency-use authorization that permits doctors to treat severely ill COVID-19 patients with remdesivir. Japanese health officials issued a similar clearance days later.

On top of the biological challenge of finding new broad-spectrum antiviral drugs lies an economic one, partly because there is little financial incentive to develop broad-spectrum drugs against emerging diseases. And with all the government backed research, there is no guarantee that pharma companies have enough incentive to continue working on research. Yet, broad-spectrum antivirals are not miracle drugs, but they can be a helpful addition to a toolbox that is currently sparse.

Remdesivir’s potential first drew public attention in October 2015 during an Ebola outbreak in West Africa that claimed more than 11,000 lives. Remdesivir subdues a virus by interfering with replication. First, the body changes remdesivir into an imposter. It becomes what’s called a nucleoside analog, a genetic doppelganger that resembles adenosine. When the virus replicates, it weaves this analog into the new strand of genetic material. Nevertheless, the analog’s molecular makeup differs from real adenosine just enough to grind the copying process to a halt.

As COVID-19 swept the globe, scientists led an international trial of remdesivir as a treatment option. EIDD-2801, another treatment option has demonstrated broad-spectrum antiviral potential, as well as an ability to defend cells from SARS-CoV-2. Yet, the best treatment for COVID-19 can be remdesivir, EIDD-2801 or any single antiviral at all. Even with that, broad spectrum antivirals can be invaluable in the short-term.
The early success of remdesivir suggests that broad-spectrum antivirals will get their moment in the scientific limelight. After a pandemic pass, though, the rush interest about a multipurpose treatment diminishes.

SOURCE

https://www.smithsonianmag.com/science-nature/remdesivir-works-against-many-viruses-why-arent-there-more-drugs-it-180974859/?utm_source=smithsoniandaily

https://www.gilead.com/news-and-press/press-room/press-releases/2020/4/gilead-announces-results-from-phase-3-trial-of-investigational-antiviral-remdesivir-in-patients-with-severe-covid-19

 

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The Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Partnership on May 18, 2020: Leadership of AbbVie, Amgen, AstraZeneca, Bristol Myers Squibb, Eisai, Eli Lilly, Evotec, Gilead, GlaxoSmithKline, Johnson & Johnson, KSQ Therapeutics, Merck, Novartis, Pfizer, Roche, Sanofi, Takeda, and Vir. We also thank multiple NIH institutes (especially NIAID), the FDA, BARDA, CDC, the European Medicines Agency, the Department of Defense, the VA, and the Foundation for NIH

Reporter: Aviva Lev-Ari, PhD, RN

May 18, 2020

Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) An Unprecedented Partnership for Unprecedented Times

JAMA. Published online May 18, 2020. doi:10.1001/jama.2020.8920

First reported in Wuhan, China, in December 2019, COVID-19 is caused by a highly transmissible novel coronavirus, SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). By March 2020, as COVID-19 moved rapidly throughout Europe and the US, most researchers and regulators from around the world agreed that it would be necessary to go beyond “business as usual” to contain this formidable infectious agent. The biomedical research enterprise was more than willing to respond to the challenge of COVID-19, but it soon became apparent that much-needed coordination among important constituencies was lacking.

Clinical trials of investigational vaccines began as early as January, but with the earliest possible distribution predicted to be 12 to 18 months away. Clinical trials of experimental therapies had also been initiated, but most, except for a trial testing the antiviral drug remdesivir,2 were small and not randomized. In the US, there was no true overarching national process in either the public or private sector to prioritize candidate therapeutic agents or vaccines, and no efforts were underway to develop a clear inventory of clinical trial capacity that could be brought to bear on this public health emergency. Many key factors had to change if COVID-19 was to be addressed effectively in a relatively short time frame.

On April 3, leaders of the National Institutes of Health (NIH), with coordination by the Foundation for the National Institutes of Health (FNIH), met with multiple leaders of research and development from biopharmaceutical firms, along with leaders of the US Food and Drug Administration (FDA), the Biomedical Advanced Research and Development Authority (BARDA), the European Medicines Agency (EMA), and academic experts. Participants sought urgently to identify research gaps and to discuss opportunities to collaborate in an accelerated fashion to address the complex challenges of COVID-19.

These critical discussions culminated in a decision to form a public-private partnership to focus on speeding the development and deployment of therapeutics and vaccines for COVID-19. The group assembled 4 working groups to focus on preclinical therapeutics, clinical therapeutics, clinical trial capacity, and vaccines (Figure). In addition to the founding members, the working groups’ membership consisted of senior scientists from each company or agency, the Centers for Disease Control and Prevention (CDC), the Department of Veterans Affairs (VA), and the Department of Defense.

Figure.

Accelerating COVID-19 Therapeutic Interventions and Vaccines

ACTIV’s 4 working groups, each with one cochair from NIH and one from industry, have made rapid progress in establishing goals, setting timetables, and forming subgroups focused on specific issues (Figure). The goals of the working group, along with a few examples of their accomplishments to date, include the following.

 

The Preclinical Working Group was charged to standardize and share preclinical evaluation resources and methods and accelerate testing of candidate therapies and vaccines to support entry into clinical trials. The aim is to increase access to validated animal models and to enhance comparison of approaches to identify informative assays. For example, through the ACTIV partnership, this group aims to extend preclinical researchers’ access to high-throughput screening systems, especially those located in the Biosafety Level 3 (BSL3) facilities currently required for many SARS-CoV-2 studies. This group also is defining a prioritization approach for animal use, assay selection and staging of testing, as well as completing an inventory of animal models, assays, and BSL 3/4 facilities.

 

The Therapeutics Clinical Working Group has been charged to prioritize and accelerate clinical evaluation of a long list of therapeutic candidates for COVID-19 with near-term potential. The goals have been to prioritize and test potential therapeutic agents for COVID-19 that have already been in human clinical trials. These may include agents with either direct-acting or host-directed antiviral activity, including immunomodulators, severe symptom modulators, neutralizing antibodies, or vaccines. To help achieve these goals, the group has established a steering committee with relevant expertise and objectivity to set criteria for evaluating and ranking potential candidate therapies submitted by industry partners. Following a rigorous scientific review, the prioritization subgroup has developed a complete inventory of approximately 170 already identified therapeutic candidates that have acceptable safety profiles and different mechanisms of action. On May 6, the group presented its first list of repurposed agents recommended for inclusion in ACTIV’s master protocol for adaptive clinical trials. Of the 39 agents that underwent final prioritization review, the group identified 6 agents—including immunomodulators and supportive therapies—that it proposes to move forward into the master protocol clinical trial(s) expected to begin later in May.

 

The Clinical Trial Capacity Working Group is charged with assembling and coordinating existing networks of clinical trials to increase efficiency and build capacity. This will include developing an inventory of clinical trial networks supported by NIH and other funders in the public and private sectors, including contract research organizations. For each network, the working group seeks to identify their specialization in different populations and disease stages to leverage infrastructure and expertise from across multiple networks, and establish a coordination mechanism across networks to expedite trials, track incidence across sites, and project future capacity. The clinical trials inventory subgroup has already identified 44 networks, with access to adult populations and within domestic reach, for potential inclusion in COVID-19 trials. Meanwhile, the survey subgroup has developed 2 survey instruments to assess the capabilities and capacities of those networks, and its innovation subgroup has developed a matrix to guide deployment of innovative solutions throughout the trial life cycle.

 

The Vaccines Working Group has been charged to accelerate evaluation of vaccine candidates to enable rapid authorization or approval.4 This includes development of a harmonized master protocol for adaptive trials of multiple vaccines, as well as development of a trial network that could enroll as many as 100 000 volunteers in areas where COVID-19 is actively circulating. The group also aims to identify biomarkers to speed authorization or approval and to provide evidence to address cross-cutting safety concerns, such as immune enhancement. Multiple vaccine candidates will be evaluated, and the most promising will move to a phase 2/3 adaptive trial platform utilizing large geographic networks in the US and globally.5 Because time is of the essence, ACTIV will aim to have the next vaccine candidates ready to enter clinical trials by July 1, 2020.

References

1.

Desai  A .  Twentieth-century lessons for a modern coronavirus pandemic.   JAMA. Published online April 27, 2020. doi:10.1001/jama.2020.4165
ArticlePubMedGoogle Scholar

2.

NIH clinical trial shows remdesivir accelerates recovery from advanced COVID-19. National Institutes of Health. Published April 29, 2020. Accessed May 7, 2020. https://www.nih.gov/news-events/news-releases/nih-clinical-trial-shows-remdesivir-accelerates-recovery-advanced-covid-19

3.

NIH to launch public-private partnership to speed COVID-19 vaccine and treatment options. National Institutes of Health. Published April 17, 2020. Accessed May 7, 2020. https://www.nih.gov/news-events/news-releases/nih-launch-public-private-partnership-speed-covid-19-vaccine-treatment-options

4.

Corey  L , Mascola  JR , Fauci  AS , Collins  FS .  A strategic approach to COVID-19 vaccine R&D.   Science. Published online May 11, 2020. doi:10.1126/science.abc5312PubMedGoogle Scholar

5.

Angus  DC .  Optimizing the trade-off between learning and doing in a pandemic.   JAMA. Published online March 30, 2020. doi:10.1001/jama.2020.4984
ArticlePubMedGoogle Scholar

6.

Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) portal. National Institutes of Health. Accessed May 15, 2020. https://www.nih.gov/ACTIV

7.

Accelerating Medicines Partnership (AMP). National Institutes of Health. Published February 4, 2014. Accessed May 7, 2020. https://www.nih.gov/research-training/accelerating-medicines-partnership-amp
SOURCE

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Race to develop antibody drugs for COVID-19

Reporter: Irina Robu, PhD

Even at the record pace vaccines are moving, the first vaccine for COVID-19 might not be available until next year. And even if it is available, it will take longer for enough people within the population to be vaccinated in order to achieve herd immunity and curb the spread. Companies such as Regeneron, Eli Lily, Amgen and Vir Biotechnology are leading the race to produce therapies that could give patients infected with COVID-19 short term protection. However, several experts believe that developing antibody drugs are vital.
At this time, Gilead’s antiviral drug remdesivir, which seems to help hasten recovery from COVID-19, but not entirely. There is no guarantee that these injectable biologic drugs won’t solve the pandemic. Yet, many believe that in combination with mass testing and tracing measures, these injectable biologic drugs could be a critical tool for keeping the disease in check.

When fighting off foreign invaders, our bodies make antibodies precisely produced for the task. The reason vaccines offer such long-lasting protection is they train the immune system to identify a pathogen, so immune cells remember and are ready to attack the virus when it appears. Monoclonal antibodies for coronavirus would take the place of the ones our bodies might produce to fight the disease. The manufactured antibodies would be infused into the body to either tamp down an existing infection, or to protect someone who has been exposed to the virus.

However, these drugs are synthetic versions of the convalescent plasma treatments that rely on antibodies from people who have recovered from infection. But the engineered versions are easier to scale because they’re manufactured in rats, rather than from plasma donors.

Yet, what brands antibodies unique in comparison to vaccines or antiviral drugs is their potential to both treat and protect against viral infections and could work as a short-term preventative for healthcare workers who are at high risk of contracting COVID-19 or as a treatment for people who are already sick. But it is up to creators to figure out exactly when is the best time is to interfere with an antibody drug. More persuasively, antibodies will deliver the greatest value for the people at the highest risk like healthcare workers or people who are old or immuno-compromised.

Over the years of research, it is shown that some vaccines are only effective in a part of population. But making a vaccine takes time, and they don’t kick in immediately. So, proving the monoclonal antibodies can treat patients with COVID-19 disease can be much faster and easier than showing a preventive benefit. As with vaccines, antibodies would have to succeed in much longer tests to fully show they can prevent infections. Vaccine aside, the only treatments granted emergency use by the FDA thus far are the antiviral remdesivir and the generic malaria pill hydroxychloroquine.

Regeneron, Amgen, Vir and Eli Lilly are each using different methods to screen for and develop their antibodies. The initial experiments may lead to different type of products where one type of antibody versus a cocktail of two or three. The antibodies are designed to mimic the ones our bodies make versus those that are modified in some way to improve their properties. Modifying an antibody could help it last longer, but make it look more foreign to the immune system, which could lead to potential problems.
What makes antibodies unique compared to vaccines or antiviral drugs is their potential to both treat and protect against viral infections. The idea is that an antibody drug will bind to the “spike” protein SARS-CoV-2 uses to crack open cells, and prevent the virus from entering. The fastest path to success for an antibody is possible through a drug that has to be given intravenously in a hospital or clinic, rather than through an auto-injector a patient could self-administer.

SOURCE

https://www.biopharmadive.com/news/coronavirus-antibody-drug-trials/577778/

As We Wait For a Vaccine, Scientists Eye Antibodies

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Vaccinology in the Age of Pandemics:
Strategies Against COVID-19 & Other Global Threats

June 15–16, 2020 | 11:00AM–3:30PM ET | 3:00–7:30PM UTC | 5:00–9:30PM CEST*
*Program is subject to change


As the world faces the greatest global pandemic of our lifetimes, the critical importance of vaccine development has come to the forefront of scientific and public audiences alike. Over the course of history, vaccination has enabled us to conquer devastating diseases from measles to smallpox, but new challenges arise when addressing an emerging pandemic in real time. This virtual meeting will assemble the world’s leading vaccinology and global health experts to present the latest advances in vaccine design and development. Finally, this virtual conference will discuss how to best apply these strategies in the context of the current pandemic.

The field of vaccinology has made great leaps in recent years, providing novel technologies and approaches that can be leveraged to our advantage against the novel coronavirus, COVID-19. Incredible advances in science and technology now make it technically possible to develop vaccines against many new targets. Meanwhile, innovative approaches to vaccine development are tackling challenges of emerging infections and implementation in low-income countries. These advances, among many others, will guide the way towards a safe and effective COVID-19 vaccine. Additionally, these new scientific advances will set the stage for success against this pandemic, as vaccinologists race against the ever-rising global death toll.

This virtual meeting program will cover many important facets of vaccine science, technology and strategy, including:

  • transformative new technologies, including structure-based design, adjuvants, nucleic acid vaccines (especially RNA), viral vectors, systems biology, and controlled human infections
  • scientific underpinnings of new vaccinology strategies, including advances in the fields of human immunology, genomics, synthetic biology, molecular structure of antigens and antigen-antibody complexes, germinal centers, and microbiome
  • multidisciplinary technologies and strategies, including efforts of Coalition for Epidemic Preparedness Innovations (CEPI), Bill & Melinda Gates Foundation and Wellcome Trust, which will change the way vaccines are developed

Program is intended for scientific researchers and clinical audiences.

Join us for this landmark virtual event, brought to you by Keystone Symposia.

Regular Registration Rate: $50 USD

#VKSvaxcovid19

SPEAKERS

Program Details

Keynote Speaker


Anthony S. Fauci, MD
Anthony S. Fauci, MD
NIAID, National Institutes of Health
Transforming Vaccinology: Considerations for the Next Decade

Speaking at this eSymposia


Galit Alter

MIT and Harvard University

Yasmine Belkaid

NIAID, National Institutes of Health

Anthony S. Fauci, MD

Anthony S. Fauci

NIAID, National Institutes of Health

Barney S. Graham

NIAID, National Institutes of Health

Richard Hatchett

Coalition for Epidemic Preparedness Innovations, CEPI

Neil P. King

University of Washington

Antonio Lanzavecchia

Institute for Research in Biomedicine

Ulrike Protzer

Technische Universität München

Bali Pulendran

Stanford University School of Medicine

Rino Rappuoli

GlaxoSmithKline Vaccines

Federica Sallusto

Università della Svizzera Italiana & ETH Zurich

Robert A. Seder

NIAID, National Institutes of Health

Christine Shaw

Moderna

Gabriel D. Victora

Gabriel D. Victora

Rockefeller University

Hedda Wardemann

German Cancer Research Center

Catherine J. Wu

Dana-Farber Cancer Institute

SOURCE

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The COVID-19 Recovery will be digital: A plan for the First 90 Days

Report: Joel T. Shertok, PhD

 

“McKinsey Digital” – 5/14/20

By Aamer Baig, Bryce Hall, Paul JenkinsEric Lamarre, and Brian McCarthy

 

1 – Most C-suite executives have led their companies to digitize some part of their business to protect employees and serve customers facing mobility restrictions.

2 – We have vaulted five years forward in consumer and business digital adoption in a matter of around eight weeks. 

3 – WE need to confront three structural changes that are playing out: a – customer behaviors and preferred interactions have changed significantly; b -as the economy lurches back, demand recovery will be unpredictable; c – many organizations have shifted to remote-working models almost overnight.

4 – Customers have already migrated to digital. Employees are already working fully remotely and are agile to some degree. Companies have already launched analytics and artificial-intelligence (AI) initiatives in their operations.

5 – Companies must adapt: they must reimagine customer journeys to reduce friction, accelerate the shift to digital channels, and provide for new safety requirements.

6 – CEOs should ask their business leaders to assess how the needs and behaviors of their most important customers have changed and benchmark their digital channels against those of their competition.

7 – Modern businesses have several forecasting and planning models to guide such operational decisions. Organizations will need to validate these models.

8- As companies construct these models, analytics teams will likely need to bring together new data sets and use enhanced modeling techniques to forecast demand and manage assets successfully.

9 – The chief analytics officer should mobilize an effort to inventory core models and work with business leaders to prioritize them based on key operations and their efficacy drift.

10 – Two features of a modern technology environment are particularly important and can be rapidly implemented: a cloud-based data platform and an automated software-delivery pipeline.

11 – Companies that have led the way in adopting flatter, fully agile organizational models have shown substantial improvements in both execution pace and productivity. 

12 – Leaders who want to succeed in the digital-led recovery must quickly reset their digital agendas to meet new customer needs, shore up their decision-support systems, and tune their organizational models.

SOURCE

https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/the-COVID-19-recovery-will-be-digital-a-plan-for-the-first-90-days?cid=other-eml-alt-mbl-mck&hlkid=ffa7f7dace64429f82c354ddf40accb6&hctky=2071733&hdpid=dfb4c609-2604-4df3-aa42-ae7ed2aff045

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Crowdsourcing Difficult-to-Collect Epidemiological Data in Pandemics: Lessons from Ebola to the current COVID-19 Pandemic

 

Curator: Stephen J. Williams, Ph.D.

 

At the onset of the COVID-19 pandemic, epidemiological data from the origin of the Sars-Cov2 outbreak, notably from the Wuhan region in China, was sparse.  In fact, official individual patient data rarely become available early on in an outbreak, when that data is needed most. Epidemiological data was just emerging from China as countries like Italy, Spain, and the United States started to experience a rapid emergence of the outbreak in their respective countries.  China, made of 31 geographical provinces, is a vast and complex country, with both large urban and rural areas.

 

 

 

As a result of this geographical diversity and differences in healthcare coverage across the country, epidemiological data can be challenging.  For instance, cancer incidence data for regions and whole country is difficult to calculate as there are not many regional cancer data collection efforts, contrasted with the cancer statistics collected in the United States, which is meticulously collected by cancer registries in each region, state and municipality.  Therefore, countries like China must depend on hospital record data and autopsy reports in order to back-extrapolate cancer incidence data.  This is the case in some developed countries like Italy where cancer registry is administered by a local government and may not be as extensive (for example in the Napoli region of Italy).

 

 

 

 

 

 

Population density China by province. Source https://www.unicef.cn/en/figure-13-population-density-province-2017

 

 

 

Epidemiologists, in areas in which data collection may be challenging, are relying on alternate means of data collection such as using devices connected to the internet-of-things such as mobile devices, or in some cases, social media is becoming useful to obtain health related data.  Such as effort to acquire pharmacovigilance data, patient engagement, and oral chemotherapeutic adherence using the social media site Twitter has been discussed in earlier posts: (see below)

Twitter is Becoming a Powerful Tool in Science and Medicine at https://pharmaceuticalintelligence.com/2014/11/06/twitter-is-becoming-a-powerful-tool-in-science-and-medicine/

 

 

 

 

 

Now epidemiologists are finding crowd-sourced data from social media and social networks becoming useful in collecting COVID-19 related data in those countries where health data collection efforts may be sub-optimal.  In a recent paper in The Lancet Digital Health [1], authors Kaiyuan Sun, Jenny Chen, and Cecile Viboud present data from the COVID-19 outbreak in China using information collected over social network sites as well as public news outlets and find strong correlations with later-released government statistics, showing the usefulness in such social and crowd-sourcing strategies to collect pertinent time-sensitive data.  In particular, the authors aim was to investigate this strategy of data collection to reduce the time delays between infection and detection, isolation and reporting of cases.

The paper is summarized below:

Kaiyuan Sun, PhD Jenny Chen, BScn Cécile Viboud, PhD . (2020).  Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study.  The Lancet: Digital Health; Volume 2, Issue 4, E201-E208.

Summary

Background

As the outbreak of coronavirus disease 2019 (COVID-19) progresses, epidemiological data are needed to guide situational awareness and intervention strategies. Here we describe efforts to compile and disseminate epidemiological information on COVID-19 from news media and social networks.

Methods

In this population-level observational study, we searched DXY.cn, a health-care-oriented social network that is currently streaming news reports on COVID-19 from local and national Chinese health agencies. We compiled a list of individual patients with COVID-19 and daily province-level case counts between Jan 13 and Jan 31, 2020, in China. We also compiled a list of internationally exported cases of COVID-19 from global news media sources (Kyodo News, The Straits Times, and CNN), national governments, and health authorities. We assessed trends in the epidemiology of COVID-19 and studied the outbreak progression across China, assessing delays between symptom onset, seeking care at a hospital or clinic, and reporting, before and after Jan 18, 2020, as awareness of the outbreak increased. All data were made publicly available in real time.

Findings

We collected data for 507 patients with COVID-19 reported between Jan 13 and Jan 31, 2020, including 364 from mainland China and 143 from outside of China. 281 (55%) patients were male and the median age was 46 years (IQR 35–60). Few patients (13 [3%]) were younger than 15 years and the age profile of Chinese patients adjusted for baseline demographics confirmed a deficit of infections among children. Across the analysed period, delays between symptom onset and seeking care at a hospital or clinic were longer in Hubei province than in other provinces in mainland China and internationally. In mainland China, these delays decreased from 5 days before Jan 18, 2020, to 2 days thereafter until Jan 31, 2020 (p=0·0009). Although our sample captures only 507 (5·2%) of 9826 patients with COVID-19 reported by official sources during the analysed period, our data align with an official report published by Chinese authorities on Jan 28, 2020.

Interpretation

News reports and social media can help reconstruct the progression of an outbreak and provide detailed patient-level data in the context of a health emergency. The availability of a central physician-oriented social network facilitated the compilation of publicly available COVID-19 data in China. As the outbreak progresses, social media and news reports will probably capture a diminishing fraction of COVID-19 cases globally due to reporting fatigue and overwhelmed health-care systems. In the early stages of an outbreak, availability of public datasets is important to encourage analytical efforts by independent teams and provide robust evidence to guide interventions.

A Few notes on Methodology:

  • The authors used crowd-sourced reports from DXY.cn, a social network for Chinese physicians, health-care professionals, pharmacies and health-care facilities. This online platform provides real time coverage of the COVID-19 outbreak in China
  • More data was curated from news media, television and includes time-stamped information on COVID-19 cases
  • These reports are publicly available, de-identified patient data
  • No patient consent was needed and no ethics approval was required
  • Data was collected between January 20, 2020 and January 31,2020
  • Sex, age, province of identification, travel history, dates of symptom development was collected
  • Additional data was collected for other international sites of the pandemic including Cambodia, Canada, France, Germany, Hong Kong, India, Italy, Japan, Malaysia, Nepal, Russia, Singapore, UK, and USA
  • All patients in database had laboratory confirmation of infection

 

Results

  • 507 patient data was collected with 153 visited and 152 resident of Wuhan
  • Reported cases were skewed toward males however the overall population curve is skewed toward males in China
  • Most cases (26%) were from Beijing (urban area) while an equal amount were from rural areas combined (Shaanzi and Yunnan)
  • Age distribution of COVID cases were skewed toward older age groups with median age of 45 HOWEVER there were surprisingly a statistically high amount of cases less than 5 years of age
  • Outbreak progression based on the crowd-sourced patient line was consistent with the data published by the China Center for Disease Control
  • Median reporting delay in the authors crowd-sourcing data was 5 days
  • Crowd-sourced data was able to detect apparent rapid growth of newly reported cases during the collection period in several provinces outside of Hubei province, which is consistent with local government data

The following graphs show age distribution for China in 2017 and predicted for 2050.

projected age distribution China 2050. Source https://chinapower.csis.org/aging-problem/

 

 

 

 

 

 

 

 

 

 

 

 

The authors have previously used this curation of news methodology to analyze the Ebola outbreak[2].

A further use of the crowd-sourced database was availability of travel histories for patients returning from Wuhan and onset of symptoms, allowing for estimation of incubation periods.

The following published literature has also used these datasets:

Backer JA, Klinkenberg D, Wallinga J: Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20-28 January 2020. Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin 2020, 25(5).

Lauer SA, Grantz KH, Bi Q, Jones FK, Zheng Q, Meredith HR, Azman AS, Reich NG, Lessler J: The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Annals of internal medicine 2020, 172(9):577-582.

Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, Ren R, Leung KSM, Lau EHY, Wong JY et al: Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia. The New England journal of medicine 2020, 382(13):1199-1207.

Dataset is available on the Laboratory for the Modeling of Biological and Socio-technical systems website of Northeastern University at https://www.mobs-lab.org/.

References

  1. Sun K, Chen J, Viboud C: Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study. The Lancet Digital health 2020, 2(4):e201-e208.
  2. Cleaton JM, Viboud C, Simonsen L, Hurtado AM, Chowell G: Characterizing Ebola Transmission Patterns Based on Internet News Reports. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 2016, 62(1):24-31.

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