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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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The Seasonality of COVID-19

Reporter: Irina Robu, PhD

There are several similarities between SARS-CoV-2 and SARS-CoV, because both viruses share a high degree of homology to SARS-like coronaviruses isolated from bats. The entire genome of SARS-CoV-2 has 86% similarity with SARS-CoV. COVID-19, SARS-CoV-2 has a higher transmissibility than SARS-CoV, where more patients with COVID-19 have mild symptoms that contribute to spread because the patients are usually missed and not isolated.

Even in terms of disease dynamics, the similarities include transmission route via respiratory droplets. The angiotensin-converting enzyme 2 (ACE2), found in the lower respiratory tract of humans, has been identified as the receptor used for cell entry for both SARS-CoV and SARS-CoV-2.

So even though the viruses seem similar, there are some strong differences as well. Patients reports from China, Europe and United states show that some patients have also cardiac issues. The scientist do not truly understand what is happening at this point, whether people are having heart attacks (myocardial infarction) or whether the virus is actually invading the heart tissue to cause inflammation (myocarditis)

The great concern is that many people are asymptomatic with this condition, have no symptoms. This is what makes the virus so complicated is because you can have a group of patients severely sick and in the intensive care unit and in some cases, there are older individuals and some with underlying diabetes and heart disease, hypertension, renal disease.

Even though, the US has a large number of cases of over one million and at least 84,000 deaths, but due to undertesting, the true numbers of cases are probably far higher. The big unknown is that there is no clear understanding what is going to happen in the next coming months or years with the virus. However, the investigation models indicate that the virus has a probably of returning seasonally in the coming years.

Yet, people have to be mindful and recognize that even if we begin relaxing social distancing and transmission diminishes, that it could come back in these periodic waves, as suggested by the model.

SOURCE

https://www.medpagetoday.com/infectiousdisease/covid19/86049?xid=nl_mpt_DHE_2020-04-21

Seasonality of SARS-CoV-2: Will COVID-19 go away on its own in warmer weather?

 

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2020 World Medical Innovation Forum – COVID-19, AI and the Future of Medicine, Featuring Harvard and Industry Leader Insights – MGH & BWH, Virtual Event: Monday, May 11, 8:15 a.m. – 5:15 p.m. ET

Dialogue among principals is a World Forum’s signature. Expert moderators guiding discussion and questions in audience friendly exchanges. No slides – shared perspectives facilitated by Harvard faculty, leading journalists and Mass General Brigham executives.

Jeffrey Golden, MD

Chair, Department of Pathology, BH; Ramzi S. Cotran Professor of Pathology, Harvard Medical School

Hadine Joffe, MD

Vice Chair, Psychiatry, Executive Director, Mary Horrigan Connors Center for Women’s Health and Gender Biology, BH; Paula A. Johnson Professor, Women’s Health, Harvard Medical School

Thomas Sequist, MD

Chief Patient Experience and Equity Officer, Mass General Brigham; Professor of Medicine and Health Care Policy, Harvard Medical School

Erica Shenoy, MD, PhD

Associate Chief, Infection Control Unit, MGH; Assistant Professor, Harvard Medical School

Gregg Meyer, MD

Chief Clinical Officer, Mass General Brigham; Interim President, NWH; Professor, Harvard Medical School

Ravi Thadhani, MD

CAO, Mass General Brigham; Professor and Faculty Dean for Academic Programs, Harvard Medical School

Ann Prestipino

SVP; Incident Commander, MGH

Roger Kitterman

VP, Venture and Managing Partner, Partners Innovation Fund, Mass General Brigham

David Louis, MD

Pathologist-in-Chief, MGH; Benjamin Castleman Professor of Pathology, Harvard Medical School

Janet Wu

Bloomberg

Ron Walls, MD

EVP and Chief Operating Officer, BH; Neskey Family Professor of Emergency Medicine, Harvard Medical School

Alice Park

Senior Writer, TIME

 

Jeffrey Golden, MD

Chair, Department of Pathology, BH; Ramzi S. Cotran Professor of Pathology, Harvard Medical School

Hadine Joffe, MD

Vice Chair, Psychiatry, Executive Director, Mary Horrigan Connors Center for Women’s Health and Gender Biology, BH; Paula A. Johnson Professor, Women’s Health, Harvard Medical School

Thomas Sequist, MD

Chief Patient Experience and Equity Officer, Mass General Brigham; Professor of Medicine and Health Care Policy, Harvard Medical School

Erica Shenoy, MD, PhD

Associate Chief, Infection Control Unit, MGH; Assistant Professor, Harvard Medical School

Gregg Meyer, MD

Chief Clinical Officer, Mass General Brigham; Interim President, NWH; Professor, Harvard Medical School

Ravi Thadhani, MD

CAO, Mass General Brigham; Professor and Faculty Dean for Academic Programs, Harvard Medical School

Ann Prestipino

SVP; Incident Commander, MGH

Roger Kitterman

VP, Venture and Managing Partner, Partners Innovation Fund, Mass General Brigham

David Louis, MD

Pathologist-in-Chief, MGH; Benjamin Castleman Professor of Pathology, Harvard Medical School

Janet Wu

Bloomberg

Ron Walls, MD

EVP and Chief Operating Officer, BH; Neskey Family Professor of Emergency Medicine, Harvard Medical School

Alice Park

Senior Writer, TIME

 

VIEW VIDEOS from the event

https://www.youtube.com/channel/UCauKpbsS_hUqQaPp8EVGYOg

 

From: “Coburn, Christopher Mark” <CMCOBURN@PARTNERS.ORG>

Date: Tuesday, May 12, 2020 at 6:48 AM

To: “Coburn, Christopher Mark” <CMCOBURN@PARTNERS.ORG>

Subject: REGISTRANT RECAP | World Medical Innovation Forum  

 

Dear World Forum Attendee, 

On behalf of Mass General Brigham CEO Anne Klibanski MD and Forum co-Chairs Gregg Meyer MD and Ravi Thadhani MD, many thanks for being among the nearly 11,000 registrants representing 93 countries, 46 states and 3200 organizations yesterday. A community was established around many pressing topics that  will continue long into the future. We hope you have a chance to examine the attached survey results. There are several revealing items that should be the basis for ongoing discussion. We expect to be in touch regularly during the year. Among the plans is a “First Look” video series highlighting top Mass General Brigham Harvard faculty as well as emerging Harvard investigators.  As promised, we  wanted to also share visual Forum session summaries.  You will be able to access the recordings on the Forum’s YouTube page . The first set will go up this morning

We hope you will join us for the 2021 Forum!  

Thanks again, Chris

e-Proceedings 2020 World Medical Innovation Forum – COVID-19, AI and the Future of Medicine, Featuring Harvard and Industry Leader Insights – MGH & BWH, Virtual Event: Monday, May 11, 8:15 a.m. – 5:15 p.m. ET

https://pharmaceuticalintelligence.com/2020/04/22/world-medical-innovation-forum-covid-19-ai-and-the-future-of-medicine-featuring-harvard-and-industry-leader-insights-mgh-bwh-virtual-event-monday-may-11-815-a-m-515-p-m-et/

Tweets & Retweets 2020 World Medical Innovation Forum – COVID-19, AI and the Future of Medicine, Featuring Harvard and Industry Leader Insights – MGH & BWH, Virtual Event: Monday, May 11, 8:15 a.m. – 5:15 p.m. ET

https://pharmaceuticalintelligence.com/2020/05/11/tweets-retweets-2020-world-medical-innovation-forum-covid-19-ai-and-the-future-of-medicine-featuring-harvard-and-industry-leader-insights-mgh-bwh-virtual-event-mond/

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