Stream.Transcripts/twitch/2495535285 (2025-06-25) - Something Feels Crazy ACIP -- (25 June 2025)/2495535285 (2025-06-25) - Something Feels Crazy ACIP -- (25 June 2025).vtt

WEBVTT

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to be unmuted, please.

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Dr. Pepworth, I think you can unmute.

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Maybe we'll be able to hear you.

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Dr. Papsworth, can you hear us?

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If you can unmute.

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Hi, can you hear me now?

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Yes, we can hear you.

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Okay, sorry about that.

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My name is Vicki Pebsworth and I've worked in the healthcare field now for about 45 years.

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I have doctoral degrees in nursing and in public health from the University of Michigan.

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My public health background is in health services organization and policy.

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I previously served on the FDA's VRBPAC committee for quite a few years.

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I also served on two committees at the National Vaccine Advisory Committee.

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I currently am a volunteer as the director of research at the nonprofit National Vaccine Information Center.

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I'm also the Pacific Region Director of the National Association of Catholic Nurses.

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As it relates to conflicts of interest, I have been asked to read the following statement.

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As required under the ACIP policies and procedures, I am also disclosing that I own stock in a healthcare sector fund that includes holdings relevant to the ACIP, including vaccine manufacturers,

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However, the amount of that stockholding is under the Office of Government Ethics Regulatory De Minimis amount.

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I understand that I, therefore, can fully participate in the ACIP meeting.

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Thank you very much.

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I look forward to being of service and working hard to improve policymaking decisions for vaccines.

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Thank you.

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Thank you, Dr. Meissner.

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I apologize for the technical difficulty on my end.

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My name is Cody Meissner.

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I am currently a contractor supporting the Biomedical Advanced Research and Development Authority, that is BARDA.

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And I'm also a professor at Geisel School of Medicine

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at Dartmouth.

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I've had a long standing interest in vaccines and public health.

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I have previously served on ACIP, on VRBPAC.

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I was chair of the National Vaccine Injury Compensation Program.

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And I have worked in the past,

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extensively with the American Academy of Pediatrics.

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I am delighted to be able to present my perspective to the committee.

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Thank you.

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Thank you.

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And now I'll go through our ex-officio members.

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If you'd please let us know who's present from your agency and I'll try to go through this as fast as possible.

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Centers for Medicare and Medicaid Services.

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Good morning.

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Andrew Johnson, Senior Advisor, Centers for Medicare and Medicaid Services.

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Thank you.

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Food and Drug Administration.

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Present.

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Tracy Beth Hogue, Physician Scientist.

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I'm Senior Advisor for Clinical Sciences in the Office of the Commissioner and the Center for Biologics Evaluation and Research.

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Thanks.

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Thank you, Health Resources and Services Administration.

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Anyone online?

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I had my monitors on.

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Did she say Tracy Beth Hogue or something like that?

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Can somebody look that lady up?

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She's part of this weird network.

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She works at the FDA now?

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Holy shit.

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This is crazy.

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I didn't see her name come up.

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I'm trying to do something about the audio, but it's pretty soft.

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I don't want to get jacked later by something else.

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I don't want to put it up too high with the main game.

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I hope this is okay.

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Now I'm going to go through our liaison representatives, American Academy of Family Physicians.

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So any incompetence here doesn't look good for them, right?

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Any incompetence here doesn't look good for all of us.

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And there's an extreme amount of incompetence.

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You may have already seen it from the beginning.

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It's it's really remarkable what's going on here.

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They were supposedly going to start at 10 o'clock, but we're going to.

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We're going to go to the next section, which is the workgroup updates and then come back to roll call since we're having

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Difficulty.

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Thank you.

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Wow.

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I mean this is 2025 and the US government can't even do a live stream This is a foreigner

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Workgroups play a very important role in the work of the ACIP.

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Selected from around the country, workgroup members are experts on the vaccines, diseases, and safety issues under consideration.

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They investigate issues in detail and forward recommendations to the ACIP.

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Workgroups must be shared by an ACIP member, so new shares are currently being appointed to the existing workgroups.

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Other workgroup members have been retained.

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It's important that we build on the progress that has already been made, and we are very grateful for the work that has been done to date by these workgroups.

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There are currently 11 important workgroups looking at vaccines for chikungunya, COVID-19, cytomegalovirus, human papillomavirus, influenza, meningococcal disease, mpox, pneumococcal disease, and RSV, respiratory syncytial virus.

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We are looking forward to receiving reports from these workgroups at future ACIP meetings.

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When there are different views among working groups members, we want to hear both the majority and minority views.

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Some new work groups will also be established.

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The number of vaccines that our children and adolescents receive today exceed what children in most other developed nations receive, and what most of us in this room received when we were children.

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In addition to studying and evaluating individual vaccines, it is important to evaluate the cumulative effect of the recommended vaccine schedule.

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This includes interaction effects between different vaccines.

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the total number of vaccines, cumulative amounts of vaccine ingredients, and the relative timing of different vaccines.

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The Institute of Medicine, which is now the National Academy of Medicine, wrote an important report on these issues some years ago, arguing for more research on this topic.

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And it's now time to evaluate that new research.

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Towards that end, we will be establishing a workgroup

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that will look at the cumulative childhood vaccine schedule as well as the adolescent schedule.

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I don't really know how that works.

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I can.

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to keep up to date with scientific research to make sure that ACIP recommendations are optimal for both individuals and public health.

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Among other topics, this new vaccine group may look at the universally recommended hepatitis B vaccine at the day of birth.

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Is it wise to administer a birth dose of hepatitis B vaccine to every newborn before leaving the hospital?

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That's the question.

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Unless the mother is hepatitis B positive, an argument could be made to delay the vaccine for this infection, which is primarily spread by sexual activity and intravenous drug use.

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Vaccines are important for combating measles.

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For the first dose at age 12 to 15 months, a previous ACIP meeting recommended two alternative options equally with either separate MMR and varicella vaccines in two different needles.

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or the combined MMRV vaccine in one needle, even though the latter cause an excess number of febrile seizures.

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Aware of this, most pediatricians administer separate MMR and varicella vaccines, and CDC has also expressed a preference for that.

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To minimize vaccine adverse reactions,

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The ACIP may follow the lead of pediatricians and reevaluate its earlier recommendation concerning MMRV for one-year-old children.

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This working group may also look at new research concerning the optimal timing of the MMR vaccine to resolve religious objections that some parents have concerning the MMR vaccine being used here in the United States.

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It could also look at other MMR vaccines such as the one used in Japan.

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While we may bring different perspectives on some issues, we look very much forward to working collaboratively with the current members of the existing workgroups, as well as with scientists here at CDC.

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We share the same goal, the improvement of public health.

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That can only be achieved through close collaboration, open discussions, and most importantly, with evidence-based medicine.

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Thank you.

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Thank you for that update.

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Now we can start our presentations.

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Our first topic is COVID-19 vaccines.

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I'm going to turn it over to Dr. McNeil.

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Morning.

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Is this projecting?

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Great.

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Good morning.

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My name is Adam McNeil.

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I serve as acting director for the CDC's Coronavirus and Other Respiratory Viruses Division.

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The COVID session today will include information on the epidemiology of COVID-19, as well as COVID-19 vaccine effectiveness, safety, and implementation.

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These presentations include data from two evidence to recommendation domains that the COVID-19 workgroup has reviewed, which are the public health problem and benefits and harms.

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I want to upfront acknowledge and thank all the CDC employees and collaborators who contributed to the data and content of these presentations.

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Outlined on this slide is the agenda for the session.

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After a brief introduction, I will present on COVID-19 epidemiology and updates on COVID-19 vaccine effectiveness.

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Dr. Sarah Meyer will then give an update on vaccine safety.

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Dr. Georgina Peacock will present on COVID-19 vaccine coverage and implementation.

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And I'll wrap up the session by presenting a summary of the first two domains of the evidence to recommendations.

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Please note that PDF versions of these slides have all been posted on the ACIP website, which is available to the public.

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To recap events of the past year, last June, ACIP recommended 24, 25 COVID-19 vaccination for all people age six months and older.

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In August, FDA authorized Moderna, Pfizer, and Novavax COVID-19 vaccines, and in September,

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Okay, I'm just going to briefly speak over this.

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So what they started with was a general plan according to them to look into stuff.

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And the stuff they were going to look into was the accumulation of stuff or the interaction of stuff.

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And he listed a lot of more, you know, technical descriptions for essentially what is looking for stuff, looking at different stuff under the working assumption that vaccines are still the best invention since the airplane or the wheel.

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still under the assumption that vaccines are necessary and do lots of good things for lots of people and lots of diseases.

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The question is, we give a lot more in America, so maybe we should bring it back a little bit.

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And then he starts talking a little bit about other things like hepatitis B, and do we really need to give that to

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to women that aren't positive, as if it, you know, it's still accepting most or all of the limited spectrum of debate and giving you a question that doesn't get you out of the trap.

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The MMRV vaccine.

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How many people in the chat knew that the MMR was not the MMR anymore, but it was the MMRV vaccine?

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And so some doctors are making the very wise choice of

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using two needles and putting it in two different arms so that they get the varicella vaccine separate from the MMR.

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Boy, are they and other people are even suggesting we should use the Japanese version.

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And so this is all, it's all hocus pocus and bullshit.

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And it is extraordinary that after all this celebration that we got our guy there, we got our guys there, you know, it's Jay Bhattacharya and Robert F. Kennedy Jr.

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and Marty Makary to the rescue.

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and Robert Malone's on the ACIP, we're now gonna have a whole day's discussion about the virology of the vaccine schedule and maybe the nuances of, you know, how many shots do they really need?

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And are we giving them a little too early?

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It's remarkable.

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In vaccine using shared clinical decision-making.

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Adults aged 18 to 64 years should receive one dose of any 24, 25 COVID-19 vaccine.

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And those aged 65 and older should receive two doses of any 24, 25 COVID-19 vaccines based six months apart.

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The current recommendations for people with moderate or severe immunocompromised are shown on this slide.

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People who are moderately or severely immunocompromised and unvaccinated should receive a multidose vaccination series with an age appropriate 24-25 vaccine and receive one 24-25 vaccine dose six months after completing the initial series.

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Those who have previously completed an initial series should receive two doses of an age appropriate 24-25

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COVID-19.

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Somebody's cricket phone went off.

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And they may receive additional age appropriate 24-25 COVID-19 vaccine doses under shared clinical decision making.

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It's very important to note COVID-19 vaccines have had interim recommendations since 2020.

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These ACIP recommendations were made based on the best available information at the time with the understanding that these recommendations would be regularly revisited and potentially evolve over time.

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For the past several years, the workgroup has been considering non-universal recommendations for COVID-19 vaccination, meaning that only certain age or risk groups would be recommended.

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At the ACIP meetings in September 2023 and June 2024, the workgroup interpretations summary outlined discussions that the workgroup had around universal and non-universal policy options for the 2023-24 and the 2024-25 vaccines respectively.

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Ultimately, based on the totality of the evidence, including the epidemiology of COVID-19 and implementation considerations, the work group felt that a universal recommendation was the best option.

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Beginning in November 2024, the workgroup has discussed 25-26 COVID-19 vaccine recommendations.

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And at the April 25 ACIP meeting, ACIP members discussed considerations for the 2025-2026 recommendations, potentially moving to a non-universal recommendation.

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Between November 2024 and June 2025, the COVID-19 workgroup reviewed epidemiology and burden of COVID-19 disease, vaccine effectiveness, vaccine safety and implementation.

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At the most recent workgroup meeting on June 5th,

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And in polling after the meeting, the workgroup agreed to the following groups and recommendation types.

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Age-appropriate 2025-2026 COVID-19 vaccines for all infants and children age 6 to 23 months.

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Age-appropriate 2025-2026 COVID-19 vaccine for persons age 2 to 64 years for the following groups.

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Persons at high risk for severe COVID-19, including pregnant women.

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Persons at high risk of exposure shared clinical decision-making for persons desiring additional protection from COVID-19.

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And two doses of 20, 25, 26 COVID-19 vaccines for adults age 65 years and people six months and people less than or greater than six months with moderate or severe immunocompromised.

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Next, we will move to COVID-19 epidemiology.

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Remember that Robert Malone and Steven Hadfield and Jessica Rose and Tess Laurie and Claire Craig just released a paper that confirms everything, everything about COVID becoming endemic from a mud puddle in Wuhan.

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Including infants followed by adults and pregnant women.

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Finally, I'll give an update on current genomics of SARS-CoV-2.

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COVID-19 continues to impact American's health using COVID-net data.

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So there is a novel virus.

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It's still there.

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It is in fact endemic.

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So this is where I think we need to keep hammering.

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This is where I think the biology breaks down because Robert Malone is there specifically to make sure that no one can question the idea that this went endemic just like

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that that journalist named Garrett was on a CNN documentary right before the pandemic saying the scariest thing about any of these epidemics is should they go endemic.

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And that's what we're trying to avoid.

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That's what Robert Malone framed was at stake with regard to going to zero COVID and that Brett Weinstein was still optimistic we could reach zero COVID if we could just drug everybody in the world with ivermectin for a month.

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This idea that something is going endemic and there should be a collective effort to resist that process, that is what is being taught here.

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That is the enchantment that is being cast here as they talk about a novel virus that has started somewhere, maybe in a bat cave, or because Peter Daszak sprayed some shit, or maybe it's because Shang-Chi Lee put some fear and cleavage sites where they weren't supposed to be.

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You see, it's an illusion and it's more importantly, it's an enchantment.

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They are conjuring something that will be a monster in the minds of all of our children if we don't learn it ourselves as the illusion that it is and dispel this mythology wholesale gone.

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Respectively.

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COVID-NET is a population-based surveillance system that collects and reports data from more than 300 acute care hospitals in 185 counties across 13 states.

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The COVID-19 catchment area includes about 10% of the U.S.

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population.

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Hospitalizations reported to COVID-19 include all those where a positive COVID-19 test result was reported within 14 days prior to hospitalization.

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Testing for SARS-CoV-2 is driven by clinical judgment and facility policies.

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Basic demographic data are collected on all patients while detailed clinical data are collected by trained surveillance officers from an age and sites stratified random sample.

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So they're talking about sampling people's genetic and medical data on the basis of something called a COVID net surveillance platform.

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Doesn't that, isn't that awesome?

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To present data for periods that are inclusive of both the typical respiratory virus season of October through April, as well as the increase in rates

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which we have experienced over the preceding summer for COVID-19.

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Clinical data are presented for the... None of the people that work for this project understand the molecular biology that underlies it.

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They're just using things that they can open and take out of the package and put where they're supposed to be and then put back and mix together and crack this tube and...

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And that's it.

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COVID-19 associated hospitalization rates peak both in the winter as well as the summer, as you can see with the large summer peak in the 2024 wave.

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This differs from RSV and influenza, which generally have a similar peak.

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and a

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These are probably modeled or predicted.

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That indicates ongoing new hospitalizations.

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For slopes that are flat, that indicates hospitalizations are minimal or slowed to zero.

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Cumulative rates of COVID-19 associated hospitalizations for the ongoing period of July 2024 through June 2025, shown in the solid red line, were higher during June to November

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lower during November through June compared to those observed in the prior season from July 2023 to June 2024.

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My assumption this is maybe being done by one of these tests that Mary Talley Bowden and Kevin McKernan and Jessica Rose and Mary Holland and Meryl Nass and Robert Malone will never question the usefulness of.

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will never question the fidelity of.

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And in fact, we'll never go back to 2020 and realize that the whole thing is based on this ridiculous now diagnostic standard.

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It's crazy.

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While the remainder of this presentation will focus mainly on COVID-19 hospitalizations, note that different respiratory viruses affect... This guy is reading.

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I mean, come on.

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Are we at that professional level where we're at, like, a senior in high school that's just trying to get done with his English homework?

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Like, this is shit.

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For July 2024 through April 2025, more infants aged less than one year and adults aged 75 years and older had hospitalizations associated with COVID-19 than influenza during a high severity influenza season.

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They can't even get their freaking menu bar off.

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Look at this.

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Similarly, rates among children aged 6 to 23 months are nearly equal to those among adults aged 50 to 64 months.

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The inset figure in the red box includes these same rates in addition to adults aged... This is the exact ACIP meeting that I expected Robert Malone and Itsef Levy and Martin Kildorff to volunteer to oversee.

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What a wonderful sort of honor it is to serve on the committee of the ACIP for the FDA.

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It's just such an honor that I can walk around this facility unhindered because I'm on the ACIP and I can be sitting in meetings or randomly show up at people's offices because I'm on the ACIP.

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But actuality, has anything changed since Donald Trump has been elected?

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Has anything changed since Donald Trump's been elected?

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How are we winning?

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Our gas prices?

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Where's the egg prices?

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How is butter doing for you?

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What are we doing with peace?

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And how about war?

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Got your Epstein files yet?

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Do we got any of those details?

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The flight logs are finally in everybody's phone?

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What has changed since Donald Trump's been elected?

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Nothing has changed.

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And believe it or not, the people who voted for Donald Trump, the people who are on X, the people who are on truth social, the people who are on Facebook and promoting Trump are all the laughing stock of the rest of the world.

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And if you're part of that group of people that thinks that Donald Trump is a sign of winning and that they're still playing 5D chess, you are the laughingstock of the world.

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Because nothing has changed since Donald Trump has been elected.

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They haven't even managed to pass a budget yet.

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The budget that they're trying to pass is going to sell millions of acres of our national land.

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Which is a net positive that actually earns us money every year.

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We're gonna sell it in a one-time sale.

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Potentially millions of acres if they get their way.

30:38.142 --> 30:41.205
Ladies and gentlemen, you need to wake up and apologize to your kids.

30:41.345 --> 30:43.187
America has been infiltrated.

30:43.267 --> 30:45.448
It's maybe been infiltrated for a long time.

30:45.488 --> 30:47.450
You are the victim of a long con.

30:48.811 --> 30:54.376
And if we don't wake up soon, we will be enslaved on our own soil.

30:58.672 --> 31:08.583
These data compare hospitalization rates due to COVID-19 in red and influenza in blue from July 2024 through March 2025.

31:09.324 --> 31:14.370
Hospitalization rates for both viruses are highest for those younger than six months old

31:15.134 --> 31:19.178
and generally decrease with an increasing age through age 17.

31:19.879 --> 31:25.105
For age groups younger than two, influenza and COVID-19 associated hospitalizations are similar.

31:25.786 --> 31:30.611
In those age two to 11 years, hospitalization rates were higher for influenza.

31:31.132 --> 31:34.135
And COVID-19 hospitalization rates for those.

31:34.577 --> 31:36.638
Don't forget that Robert F. Kennedy Jr.

31:36.678 --> 31:41.961
is probably going to provide you with an iWatch and a glucose monitor if you'd like one.

31:43.501 --> 31:51.125
And soon that will be, you know, we want all our kids at school also to be on wearables because that's the way forward.

31:51.145 --> 31:53.406
And then we're just going to share this data with everybody.

31:53.466 --> 31:58.449
It's going to be, you know, really just, just rampant transparency.

32:00.035 --> 32:11.643
hospitalizations among children and adolescents including infants younger than six months old who make up 27% of pediatric COVID-19 associated hospitalizations.

32:14.525 --> 32:18.748
COVID-19 causes severe disease in infants younger than six months.

32:19.348 --> 32:23.531
I'm gonna be really honest with you my back is hurting me worse than ever and so I'm kind of

32:24.605 --> 32:35.228
I'm kind of wussing out by just doing this ACIP meeting for a little while because putting together a whole slide deck and doing a two and a half hour show with energy and focus is actually really hard.

32:35.468 --> 32:43.730
And I could do it, but I'm trying to focus on keeping moving and not standing in one spot for too long.

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And so I can do this and occasionally, you know, move around a little bit over here.

32:48.532 --> 32:49.532
And so I hope you don't mind.

32:49.592 --> 32:51.312
This is not going to be a very formal show.

32:51.332 --> 32:53.433
That's why I didn't start with an opening or anything like that.

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I kind of need a day off, but I'm not trying not to take a day off.

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So anyway.

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We're clearly not missing anything here.

33:07.292 --> 33:09.454
...hospitalized recently for COVID-19.

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22% were admitted to the ICU, 71% had no underlying medical conditions, and only 3.5% had any record of maternal COVID-19 vaccination during pregnancy.

33:22.901 --> 33:29.311
No COVID-19 vaccine products are approved for infant ages younger than six months old.

33:29.852 --> 33:36.803
Any protection must come from maternal antibodies to the infant, either from vaccination during pregnancy or prior infection.

33:45.390 --> 34:00.902
Transitioning to vaccine eligible infants and older children, this figure shows the percent of weekly COVID-19 associated hospitalizations by age group from July 2024 through May 2025, limited to those children older than six months.

34:01.423 --> 34:09.049
Among them, children ages six to 23 months, shown in green, comprise 41% of all hospitalizations,

34:09.849 --> 34:17.653
One of the things that I think is unfortunate here is that they are very much not going to explain to you how exactly the COVID is identified.

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They're not going to tell you the exact

34:20.751 --> 34:22.492
you know, what tests are they using?

34:22.572 --> 34:24.434
What tests are they using?

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Or what criteria are they using?

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And so this is a remarkable thing, you have to just kind of accept that influenza is being accurately diagnosed differently from COVID-19.

34:36.363 --> 34:40.466
And that's something that I can only presume would be done with a molecular test.

34:40.606 --> 34:46.051
So the proposition that I am giving you again, is that one belief

34:47.512 --> 34:53.797
is that things go from a mud puddle or a bat cave or a chicken coop to endemic.

34:55.038 --> 35:06.107
Another possibility is that we have this irreducibly complex background and we have become ever better at molecularly characterizing signals in it.

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And as a result of being able to pull out signals from that background more reliably, we are able to claim things about those signals being there or traveling there or maybe even evolving there.

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Making those claims is one thing, but believing that those are facts and working under those assumptions to create a public health nightmare state is

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It's well dystopian.

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It's wrong.

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And it's a biological fallacy.

35:42.160 --> 35:45.822
And so again, let me say it again and try to maybe say it in a little better way.

35:45.842 --> 35:52.705
What I'm suggesting to you is that there's an irreducibly complex molecular background of genetic signals.

35:52.905 --> 36:06.091
And as we have become more sophisticated in our ability to amplify very small, difficult to detect genetic signals in that irreducibly complex background,

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we have been able to say more about what's there.

36:11.307 --> 36:21.033
And disingenuous claims can be made about what's there and what's happening and what signals that are found there mean relative to one another.

36:21.934 --> 36:23.875
And that's very different than pandemics.

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It's very different than tracking diseases.

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And so even if, even if there is something to this molecular signaling and molecular signals that they're following, they should have the scientific integrity and feel the moral imperative to explain to you how it is exactly at this moment in time that we are currently tracking this molecular signal.

36:56.093 --> 36:57.334
It's no other signal.

36:59.232 --> 37:03.996
It's not blue spots where people don't have blue spots unless they have COVID.

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It's not like that at all.

37:05.997 --> 37:08.099
It has to be a molecular signal.

37:08.139 --> 37:18.107
And so the way that is being detected, if it is PCR, essentially could be complete bullshit and likely is.

37:20.249 --> 37:28.676
The correlation could be with a bacteriophage signal that has come to be found to be highly correlated with

37:29.704 --> 37:33.991
bacterial activity in the lungs, pneumonia, etc.

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It could be correlated with an oral or intestinal bacterial signal, bacterial phage signal.

37:45.011 --> 37:52.053
that also shows up with stomach symptoms or respiratory symptoms or throat symptoms.

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And to differentiate one signal from another would require the acknowledgement of both of those signals.

38:00.155 --> 38:08.458
And in none of these diagnostic scenarios do we acknowledge that the background is dominated by genetic signals, which are bacteriophages.

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And so before we can make any claims about what we're finding,

38:12.742 --> 38:21.604
First and foremost, we have to make sure that we're not pulling up a bacteriophage signal that in one way or another is being assumed to be some kind of mammalian virus.

38:23.664 --> 38:30.965
And this is a very simple illusion that seems to be a very distinct possibility to me.

38:31.946 --> 38:38.587
That the big, giant books of virology that sit underneath my drafting table are actually the illusion.

38:39.730 --> 38:52.018
And that somewhere along the line, when these physicists were working on bacteriogenetics, and they were working on bacteriophages, excuse me, that the realization came that, you know what?

38:53.799 --> 38:56.041
This is all one big genetic mess.

38:56.161 --> 39:00.323
And we can't tell if these phages are also going, they're going in our body too.

39:00.383 --> 39:01.024
So we don't know.

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Maybe they started to see a picture of complexity that was beyond dissection.

39:10.322 --> 39:35.934
and so they had a choice and they had to draw the line of the individual somewhere and they drew the line of the individual at the epithelial barrier and everything else outside of us are microbes and invaders and pathogens and so the symbiosis at the heart of our existence is not acknowledged and

39:36.880 --> 40:04.849
Therefore, the possible molecular symphony that is our microbiome, that inside of us and outside of us and in our lungs and in our throat and in our mouths, that microbiome interacts with us specifically through our immune system because our immune system is governing what phages are allowed to pass freely and what phages are removed mechanically and electrochemically and immunologically.

40:06.707 --> 40:13.332
And that changes the way and what success and who has success in our microbiome.

40:15.514 --> 40:29.846
And I think that this is crucial to acknowledge as additional layers of complexity that are available for and likely part of the damage that's done by intramuscular injection.

40:31.206 --> 40:47.792
where the only thing that's really passing freely and supposed to be monitored there are bacteriophages and endosomes and exosomes and genetic signals that are there as part of a natural irreducibly complex background that we have to coexist with.

40:48.993 --> 40:57.379
and amplify parts of in order to sort of bring up the signal to noise that allows us to have all the emergent properties of life that we have.

40:58.040 --> 41:04.665
This meeting is based on the idea that intramuscular injection in principle is a wonderful methodology.

41:05.345 --> 41:11.089
Maybe we've just gone a little too far with it, with a combination of things or accumulation of things or an interaction of things.

41:11.129 --> 41:13.531
If we just put it in separate arms, maybe it'll be fine.

41:13.931 --> 41:17.314
My underestimate COVID-19 associated pediatric guests.

41:24.062 --> 41:28.845
In summary, most pediatric hospitalizations occur in children younger than two years.

41:29.626 --> 41:39.553
Most of these hospitalized children have no underlying medical conditions, including 71% of infants ages less than six months old and half.

41:39.653 --> 41:41.374
I mean, we're really not missing anything.

41:41.414 --> 41:44.456
They're just giving a lot of detail to the mythology.

41:44.536 --> 41:51.902
And a lot of detail is supposed to make the novel virus and the existence of it, you know, Mary Holla, it's strange.

41:52.742 --> 41:58.568
the existence of it cannot be dismissed if there's so much detail here.

42:00.850 --> 42:01.431
Four years.

42:02.071 --> 42:07.917
Notably, no COVID-19 vaccine products are approved for the youngest infants under six months.

42:08.377 --> 42:15.724
Any protection for them must come from transfer of maternal antibodies, either through vaccination during pregnancy or prior infection.

42:16.585 --> 42:22.148
Outcomes among hospitalized children can be severe with one in four admitted to the intensive care unit.

42:22.608 --> 42:26.290
COVID-19 deaths continue to occur among infants and children.

42:26.610 --> 42:36.514
The majority of COVID-19 vaccine eligible children and adolescents who are hospitalized had no recent record of receiving the most recently recommended vaccine.

42:41.837 --> 42:44.598
Onto COVID-19 associated hospitalizations in adults.

42:57.392 --> 43:10.859
As noted previously, adults comprise the vast majority of COVID-19 associated hospitalizations, with older adults being the most impacted, and rates are highest among adults aged 75 years and older.

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This figure shows the weekly percent of COVID-19 associated hospitalizations by adult age group from March 2024 through May 2025.

43:17.923 --> 43:21.045
For this period, July 2024 through May 2025, highlighted in the red box,

43:27.188 --> 43:35.977
Adults ages 65 and older comprise 72% of all adult COVID-19 associated hospitalizations captured in COVID-NET.

43:36.497 --> 43:45.346
Adults 75 years and older comprise half of all COVID-19 hospitalizations among adults, despite making up less than 10% of the population.

43:48.271 --> 43:54.176
This figure shows the number of underlying medical conditions reported among adults hospitalized for COVID-19.

43:54.896 --> 44:00.180
Most adults hospitalized with COVID-19 had at least one underlying medical condition.

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The majority had two or more underlying medical conditions.

44:04.103 --> 44:13.691
Even among the youngest adults, those ages 18 through 49 years, shown in light green, the prevalence of one or more underlying medical conditions is 86%, with 61% having- Six years later.

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Six years later, we are right here.

44:21.157 --> 44:33.320
A room full of monkeys with Apple computers, listening to some guy read a script, showing really shitty graphs about the novel virus.

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With Robert Malone, Retziv-Levy, and Martin Kulldorff in the room.

44:44.403 --> 44:45.203
That's where we are in 2025.

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That's why I'm pissed my back hurts and my knee hurts because I really want to... I really want to finish this.

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I really want to stop this.

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But America is under attack.

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America has been misled.

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America has been... I mean... These people sold us down the river.

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And they wanted to use me and my family to do it.

45:18.154 --> 45:41.269
This slide shows the proportion of adults hospitalized for COVID-19 by vaccination status among adult age groups for October, 2024 through March, 2025 among adults, 65 years and older highlighted in the box on the far right, 65% of adults hospitalized for COVID-19 received neither the 2023, 24 or 24, 25 formula.

45:41.349 --> 45:43.210
They're selling the vaccine again.

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Cause they, the guys, they were hospitalized.

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Didn't have it.

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Holy shit.

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Received the recommended at least one dose of the 2425 vaccine prior to admission.

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17% received two doses.

45:59.004 --> 46:02.386
Onto COVID-19 associated hospitalizations among pregnant women.

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This is the biggest day of this guy's life.

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In COVID-net, pregnancy status was collected from SARS-CoV-2 positive hospitalized women ages 15 to 49 years.

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28.5% of women aged 15 to 49 years hospitalized with laboratory confirmed SARS-CoV-2 infection were pregnant.

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50% of those had COVID-19 related signs or symptoms.

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Among 131 hospitalized pregnant women with a Labrador-confirmed SARS-CoV-2 positive test result and underlying COVID-19 related signs or symptoms, and COVID-19 related signs or symptoms, 50% had no underlying conditions.

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68% were no longer pregnant at discharge, among whom 83% had a healthy newborn, 11% had a preterm infant, 1% had an ill infant,

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and 5% had pregnancy loss.

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92% had no record of COVID-19 vaccinations since July 1st, 2023.

47:05.122 --> 47:06.723
5.8% received recommended 2425 COVID-19 vaccine dose.

47:06.763 --> 47:07.983
To summarize the adult data,

47:25.888 --> 47:30.931
Rates of COVID-19 associated hospitalization are highest among oldest adult age groups.

47:31.371 --> 47:43.879
Adults aged greater than 65 comprise 72% of adult COVID-19 associated hospitalizations, and those 75 years and older comprise 50% of adult hospitalizations.

47:44.827 --> 47:53.637
COVID-19 associated hospitalizations have decreased over time, but cumulative rates among adults aged greater than 75 years remain high.

47:54.398 --> 48:00.124
The risk of COVID-19 associated hospitalization continues year-round, peaking in winter and summer months.

48:01.105 --> 48:14.272
65% of adults age 65 years or older hospitalized with COVID-19 had no record of receiving greater than one dose of the recommended 24-25 COVID-19 vaccine prior to hospitalization.

48:14.992 --> 48:20.435
Most adults hospitalized for COVID-19 have at least one underlying medical condition and most have two.

48:21.315 --> 48:39.411
Among SARS-CoV-2 positive pregnant women admitted during April 24 to March 2025 with COVID-19 related symptoms on admission, 50% had no underlying medical conditions and most, 92%, had no record of COVID-19 vaccination since July 1, 2023.

48:39.952 --> 48:46.458
Next, we'll transition to SARS-CoV-2 genomics.

48:52.717 --> 49:06.006
Since SARS-CoV-2 emerged in late 2019, we observed evolution of the viruses with accumulating substitutions in the spike protein, which binds the H2 cellular receptor and is target for neutralizing antibodies.

49:06.806 --> 49:21.436
Looking at this timeline along the x-axis and looking at the timeline along the x-axis and number of spike protein amino acid differences on the y-axis, you can observe periods of both drift

49:22.406 --> 49:28.355
in accumulations of changes and shift when new lineage is emerged and had numerous changes.

49:28.455 --> 49:29.897
So really important stuff here.

49:30.238 --> 49:32.681
The first time we observed a shift was in late 2021 to 2022.

49:35.336 --> 49:40.379
and you can see by the jump from purple to orange dots, that was the shift from Delta to Omicron.

49:41.040 --> 49:52.187
We have also observed shifts from BA.45 viruses to XBB viruses, and then from XBB to JN.1 viruses.

49:52.607 --> 49:57.451
These shifts necessitated changing the formulation of the COVID-19 vaccine dose.

49:58.952 --> 50:01.313
It is a high school level presentation.

50:01.373 --> 50:02.934
The 23-24 formulation of the COVID-19 vaccine

50:04.884 --> 50:05.305
, god look at that

50:23.366 --> 50:36.068
December 2023 to January 2024, we observed a strain replacement of XBB1.5 to JN1 viruses, which evolved independently of XBB1.5 viruses.

50:42.253 --> 50:49.376
Since the emergence of JN1, SARS-CoV lineages have continued to evolve from JN1, and we've not observed a strain replacement.

50:49.756 --> 51:00.821
All the lineages that have predominated since the JN1... Remember, this is all based on spike protein changes, even though the spike protein is only 1,200 or so amino acids and the whole...

51:01.681 --> 51:22.478
virus is supposedly many other proteins and so we're not tracking any of the special parts like the furin cleavage site or the HIV inserts or the staphylococcus enterotoxin B homology and that's all part of the illusion that these people are apparently not aware of what Stephen Hatfield's aware of but Stephen Hatfield's not tracking it in the vaccine.

51:22.498 --> 51:25.040
I don't know if they left any of those things in there.

51:26.095 --> 51:27.515
It's all so stupid.

51:28.336 --> 51:31.457
And this has to be as stupid as the other side.

51:31.537 --> 51:35.118
That's why it's such a hard trap to escape.

51:35.698 --> 51:40.660
But this level of fidelity where they can tell you the percentage of all the different variants.

51:41.440 --> 51:48.022
Where are the other 30 proteins in this virus and how do they figure into the infectivity and the disease presentation?

51:48.482 --> 51:49.783
It's just so stupid.

51:51.107 --> 51:54.789
The N-protein is known to be one of the most antigenic proteins.

51:54.829 --> 52:00.933
It's gotta be made in high quantities in order to wrap up all that long RNA and package it in new coronaviruses.

52:01.493 --> 52:03.634
And so why aren't they talking about the N-protein?

52:03.654 --> 52:07.456
And when the N-protein is responsible for anything, why aren't they tracking that?

52:07.997 --> 52:14.040
Because this is a bullshit show about a bullshit spike protein.

52:16.221 --> 52:20.724
Changes in spike receptor binding domain in comparison to the vaccine formulation.

52:23.706 --> 52:23.866
of a

52:44.076 --> 52:58.579
To summarize the COVID-19 genomics, current viruses are JN1 descendants with two to three substitutions in spike receptor binding, in the spike receptor binding domain in comparison to KP2 spike.

52:59.159 --> 53:05.540
Current viruses are neutralized with sera from participants who received the 24-25 COVID-19 vaccine.

53:06.140 --> 53:09.761
Antigenic cartography indicates JN1 viruses are similar.

53:10.621 --> 53:23.010
FDA's VRBPAC reviewed genomic and phenotypic data in May 2025 and unanimously voted to recommend a monovalent JN1 lineage vaccine as its composition.

53:23.490 --> 53:29.114
FDA has advised manufacturers to use JN1-based COVID-19

53:30.686 --> 53:37.531
preferentially using the LP8.1 strain for the 25, 26 COVID-19 vaccines.

53:38.092 --> 53:41.675
I'll now move on to discussing COVID-19 vaccine effectiveness.

53:52.123 --> 53:53.384
This is the next set of slides, please.

53:57.196 --> 53:57.536
Thank you.

53:57.636 --> 54:04.962
I think we're going to continue with the presentations and the next presentation is on COVID-19 vaccine effectiveness.

54:04.982 --> 54:05.563
Dr. McNeil.

54:07.004 --> 54:07.264
Sorry.

54:08.625 --> 54:08.845
Go ahead.

54:09.626 --> 54:09.806
Okay.

54:12.788 --> 54:16.051
I will now move on to presenting COVID-19 vaccine effectiveness.

54:20.054 --> 54:23.376
COVID-19 vaccine effectiveness.

54:23.556 --> 54:35.162
I'll start today with methods and context for how we measure and interpret vaccine effectiveness or VE and then present estimates of COVID-19 VE in children and adults and overall conclusions.

54:36.962 --> 54:41.925
I'll start by summarizing VE methods and providing some context for interpretation of results.

54:53.575 --> 55:02.638
For respiratory viruses, CDC generally uses a case control design, often a test negative design or T and D to measure vaccine effectiveness.

55:03.499 --> 55:07.760
In the T and D, people who seek care for respiratory illness are included.

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Cases are those that test positive for SARS-CoV-2 and controls are those that test negative.

55:14.884 --> 55:19.167
Controls in these studies are meant to represent the population from which the cases arose.

55:19.607 --> 55:25.732
And here give us an understanding of COVID-19 vaccine coverage among people seeking care for respiratory illness.

55:26.312 --> 55:32.656
We then compare vaccination status in cases and controls to determine vaccine effectiveness or VE.

55:33.337 --> 55:40.522
If coverage is higher among controls than among cases, that indicates the vaccines are associated with protection against disease.

55:41.365 --> 55:52.194
Because both cases and controls are people seeking care for respiratory illness, we can reduce the impact of factors that can distort or confound the relationship between vaccination status and illness.

55:52.894 --> 56:01.481
Reducing the impact or adjusting for factors like age and geography helps to make the true relationship between vaccination status and illness clear.

56:08.697 --> 56:14.703
Today I'll be sharing VE results from three CDC platforms for children and adults.

56:15.303 --> 56:34.501
The first VE platform is the Vision Network, a multi-site network of over 200 electronic health records, a multi-site network of electronic health records at over 300 emergency departments and urgent care clinics and over 200 hospitals that include both children and adults.

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Vision uses a test negative design and includes eligible people of all ages with COVID-19-like illness and a clinical test within 10 days before or 72 hours after their encounter.

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Cases are those with a positive NAT or antigen test for SARS-CoV-2 and no positive RSV or influenza test result.

56:57.873 --> 57:02.695
Controls are those with a negative NAT test for SARS-CoV-2 and no positive NAT

57:03.297 --> 57:09.802
Hey Mark, at least you're at home and you're not, you know, you didn't leave your emus and your horses at home to volunteer for this show.

57:10.362 --> 57:12.064
I mean, I feel bad for Robert Malone.

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This must be really rough on him.

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The second B platform enrolls only children with enrollment at 26 pediatric hospitals in 20 States.

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The analysis I'll present today, uh, for this platform is designed to assess the effectiveness of COVID-19 vaccination and pregnant women.

57:32.133 --> 57:33.875
for prevention of COVID-19 related.

57:34.015 --> 57:36.857
I decided to overdose on baby aspirin.

57:37.458 --> 57:39.520
They're 81 milligrams a piece.

57:39.600 --> 57:40.761
They're little tiny things.

57:41.522 --> 57:48.729
And I took like, I don't know how many when I got up this morning and was thinking I wasn't even going to be able to stand here and do this stream.

57:49.629 --> 57:56.456
And after about an hour and a half, I got to really say that actually they have made a tremendous difference or something because

57:58.066 --> 58:01.428
When I got out of bed this morning it was worse than any day before it.

58:02.068 --> 58:03.930
The day I heard it or the day after I heard it.

58:03.970 --> 58:05.430
So that bothered me a lot.

58:06.351 --> 58:10.594
And now suddenly with... Did the light go out?

58:10.814 --> 58:13.255
Now suddenly I'm doing okay.

58:13.315 --> 58:14.056
This is great.

58:14.176 --> 58:18.178
So I just put in... I couldn't quite count how many more.

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So we'll see.

58:19.359 --> 58:20.980
Hopefully I don't reach toxic levels.

58:23.001 --> 58:33.848
Vaccination history is ascertained through electronic medical records, state and local vaccine registries, implausible self-report, and specimens are collected for central testing and sequencing.

58:38.512 --> 58:40.733
Here we've measured COVID-19 VE.

58:40.973 --> 58:41.634
Here's how

58:42.540 --> 58:46.645
COVID-19 VE measurements have been changed in terms of approaches by season.

58:47.225 --> 58:56.396
When COVID-19 vaccines were first released, we measured absolute VE, which compares the frequency of health outcomes in vaccinated versus unvaccinated people.

58:56.976 --> 59:01.762
During the bivalent era, however, we also measured relative VE.

59:02.418 --> 59:09.221
which compares the frequency of health outcomes in people who received one type of vaccine to people who received a different vaccine.

59:09.601 --> 59:16.543
For example, people who received a bivalent vaccine versus those who received only the original monovalent COVID-19 vaccine.

59:17.304 --> 59:28.788
Generally, for 2023-24 and 24-25 COVID-19 vaccines, we've combined absolute and relative VE, measured protection as the frequency

59:29.662 --> 59:37.750
in disease in those who received the current vaccine to those who did not, regardless of their past vaccination or infection history.

59:38.270 --> 59:53.124
In other words, the comparison group for the 23-24 VE analysis include people who are unvaccinated as well as those who- I mean, it's respiratory phage versus intestinal or oral phage, you know, that's all it is.

59:53.800 --> 01:00:02.224
where the comparison group is people who are unvaccinated or received original monovalent, bivalent, or 23-24 COVID-19 vaccines.

01:00:02.944 --> 01:00:07.466
Of note, this is similar to how influenza vaccine effectiveness is measured each year.

01:00:08.366 --> 01:00:16.910
This represents the added benefit of a seasonal vaccination for the respective season, regardless of previous vaccination or infection history.

01:00:24.192 --> 01:00:36.861
This graph shows the COVID-19 vaccination coverage from CDC's National Immunization Survey during the 23, 24, and 24-25 seasons among children age 6 months to 4 years in blue and among children and adolescents age 5 to 17 years in green.

01:00:42.693 --> 01:00:47.956
23, 24 uptake is shown in dotted lines and 24, 25 uptake is shown in solid lines.

01:00:48.357 --> 01:00:52.279
You can see that similar... I would be terrified to see what it was in 21 and 22.

01:00:52.399 --> 01:00:53.680
...remain quite low.

01:00:54.260 --> 01:00:59.984
The lowest coverage in youngest children occurred during the 24, 25 season.

01:01:01.765 --> 01:01:04.246
Here we see... Oh, let me show the rest of the years.

01:01:04.286 --> 01:01:06.087
Why don't they show us the rest of the years?

01:01:06.127 --> 01:01:10.130
Here we see data on uptake of COVID-19 vaccines among adults aged 18 years and up.

01:01:10.737 --> 01:01:11.678
I told you they struck out.

01:01:11.738 --> 01:01:12.618
I told you they struck out.

01:01:32.970 --> 01:01:48.760
Moving on to older adults, this slide uses data from Medicare fee-for-service beneficiaries aged 65 years and older to understand coverage for the 24-25 COVID-19 season by underlying medical condition status.

01:01:49.440 --> 01:01:53.903
The x-axis is calendar week and two-week periods and the y-axis is coverage.

01:01:54.603 --> 01:01:59.907
You can see in red the overall coverage was 28% for this group by January 2025.

01:02:01.388 --> 01:02:09.653
Coverage was highest among those with immunocompromising conditions at 32%, the lowest among those with no underlying medical conditions at 24%.

01:02:09.773 --> 01:02:16.237
I'll now share estimates for COVID-19 VE in children.

01:02:22.176 --> 01:02:31.543
This graph from CDC's COVIDNet surveillance platform shows cumulative rates of COVID-19 hospitalizations for 23, 24 and 24, 25.

01:02:32.624 --> 01:02:46.314
As the coverage graphs, as with coverage graphs, younger kids are again in blue and older kids are in green with 23, 24 rates in the dotted lines and 24, 25 rates in the solid lines.

01:02:47.035 --> 01:02:49.437
You can see that rates are higher in the younger children

01:02:50.763 --> 01:02:56.968
and that rates in the 24-25 season were lower in both age groups than in 23-24.

01:02:58.209 --> 01:03:03.013
As you'll see, this resulted in less statistical power for 24-25 analyses.

01:03:03.513 --> 01:03:10.119
It means that we are able to share, means that we are only able to share data for finite stratifications for 23-24.

01:03:15.765 --> 01:03:25.816
This slide shows the 23-24 COVID-19 vaccine effectiveness against emergency department and urgent care encounters, including data through August 24, which is when the 24-25 vaccines were released.

01:03:28.863 --> 01:03:36.148
Note that the reference group includes all individuals who did not receive a 2324 COVID-19 vaccine.

01:03:36.708 --> 01:03:48.475
For those aged greater than five years, this includes unvaccinated persons and persons who were vaccinated with greater than one original monovalent or bivalent COVID-19 doses.

01:03:49.076 --> 01:03:57.461
For those aged less than five years, both those in the reference group and those in the vaccinated group were required to have completed an initial series.

01:03:58.322 --> 01:03:59.585
The 23-24 dose.

01:03:59.826 --> 01:04:03.555
You know, I hear a lot of people talking about Coke, but, uh...

01:04:04.637 --> 01:04:10.902
I have the feeling that there are a lot more people that if they have all the money in the world, they're using something other than coke.

01:04:10.962 --> 01:04:20.889
They might use a better version of Adderall or some other methamphetamine-derived substance.

01:04:22.090 --> 01:04:27.053
I think there's lots of other things that people would use besides cocaine, although I get it.

01:04:28.394 --> 01:04:32.199
But I think cocaine is something that they can use on lesser individuals.

01:04:32.279 --> 01:04:38.928
I think, you know, it's it's that's still that's still peasant stuff control for for other people.

01:04:39.429 --> 01:04:40.690
From days 60 to 299 with positive.

01:04:44.580 --> 01:04:51.989
SARS-CoV-2 tests to split the 60 to 299 day block in children with more granularity.

01:04:52.489 --> 01:04:58.556
You can see that VE is estimated to be as good or better among children as it is among adults.

01:04:59.077 --> 01:05:03.682
This aligns with previous seasons showing generally comparable VE across age groups.

01:05:09.619 --> 01:05:15.466
This slide is similar to the previous one, though now showing VE during the 24-25 season.

01:05:15.887 --> 01:05:23.577
As mentioned, lower numbers of COVID-19 cases in 24-25 resulted in less statistical power during the season.

01:05:23.977 --> 01:05:27.301
So we're not able to estimate VE by a time since dose for 24-25.

01:05:28.993 --> 01:05:37.917
Instead we've shown overall VE for the 7 to 179 days since receipt of a 24-25 COVID-19 vaccine dose.

01:05:38.377 --> 01:05:45.020
You can see that as with 2023-24, VE is the same or higher in children and adults.

01:05:47.421 --> 01:05:48.461
I'm going to keep swaying then.

01:05:52.383 --> 01:05:55.744
Now we'll move on to estimates of effectiveness of maternal COVID-19 vaccine.

01:05:57.355 --> 01:06:06.817
receipt for protection of COVID-19 associated hospitalization among infants from the overcoming COVID-19 network during 2023, 2022, 2023.

01:06:07.558 --> 01:06:18.060
Maternal VE is particularly important because infants under six months of age are not eligible for COVID-19 vaccination and have higher rates of severe COVID-19 disease.

01:06:18.180 --> 01:06:19.921
Vaccine efficacy.

01:06:20.021 --> 01:06:24.162
It means, believe it or not, they're talking about a big myth and they're abbreviating it VE.

01:06:24.782 --> 01:06:27.703
to protect their infants from severe disease.

01:06:29.823 --> 01:06:39.706
This analysis included mothers who received their last dose of COVID-19 mRNA vaccine between the first day of pregnancy and 14 days before delivery.

01:06:40.266 --> 01:06:47.168
The comparison group was mothers who did not receive any COVID-19 vaccination either before or during pregnancy.

01:06:47.688 --> 01:06:53.313
As you can see, VE... I just realized I'm like an ARC character with my arms up like this.

01:06:53.433 --> 01:07:00.158
...at 54% during the first two months of life and 35% during the first zero to five months of life.

01:07:00.719 --> 01:07:08.045
This mirrors patterns in older children and adults where VE drops with more time since dose.

01:07:15.626 --> 01:07:19.492
I'll now share results for COVID-19 VE in adults.

01:07:22.476 --> 01:07:22.797
Really?

01:07:22.857 --> 01:07:23.959
Now we're gonna do adults?

01:07:24.039 --> 01:07:24.860
Holy shit.

01:07:24.940 --> 01:07:26.523
I hope there are not many age groups.

01:07:28.032 --> 01:07:47.248
This dude's earning is, well, probably not, but he's... This slide shows absolute VE of original monovalent and bivalent doses received prior to or during pregnancy against COVID-19 associated emergency department or urgent care visits in pregnant women aged 18 to 45 years.

01:07:47.869 --> 01:07:52.573
Note that although these are older vaccines, the data were collected during 2023

01:07:54.284 --> 01:07:56.244
during 2022 and 2023, when Omicron was the dominant variant.

01:07:56.624 --> 01:08:16.968
As you can see, a dose during pregnancy in this population administered a median of 91 days before the encounter provided 52% protection, while a dose administered less than six months before pregnancy, a median of 267 days.

01:08:17.008 --> 01:08:21.209
I mean, this is no different than the bullshit that they pulled with Zika in South America.

01:08:21.249 --> 01:08:22.229
This is just gross.

01:08:23.189 --> 01:08:33.673
All of these women should be got together in a class action lawsuit and any medical problems that they or their children have should be blamed on this.

01:08:33.753 --> 01:08:34.754
It's just gross.

01:08:34.934 --> 01:08:40.016
It's absolutely gross that they are presenting this as data.

01:08:40.976 --> 01:08:42.378
Data on effectiveness.

01:08:42.398 --> 01:09:00.699
If we were to look at the time since dose, we can see that protection in pregnant women, a median 77 days after COVID-19 vaccination, shown on the top, was similar to protection in non-pregnant women of the same age group, a median of 83 days after COVID-19 vaccination.

01:09:04.363 --> 01:09:09.986
This slide shows the characteristics of the patient populations included in the next analysis I'll present.

01:09:10.626 --> 01:09:30.998
First, above the top you see each of the three analyses, vision emergency department urgent care encounters in adults aged 18 years and up, vision hospitalizations in adults aged 65 and up, which include estimates against critical illness, and IV hospitalizations in adults aged 65 years and up.

01:09:31.818 --> 01:09:45.638
First, you can see that median age for the emergency department urgent care encounters was low, in the low to mid 50s, compared to hospitalization analysis in both platforms, which had median ages in the mid to high 70s.

01:09:47.080 --> 01:09:57.063
Keep in mind that the only analysis we'll share today that included adults age 18 to 64 was the VISION-ED urgent care analysis.

01:09:57.543 --> 01:10:11.528
Younger adults were excluded from hospitalization analyses for both VISION and IVY because of lack of statistical power due both to lower baseline hospitalization rates and lower COVID-19 vaccine uptake in younger adults.

01:10:12.208 --> 01:10:20.253
However, we've seen in previous seasons that VE is similar among those age 18 to 64 and those age 65 and up.

01:10:20.894 --> 01:10:25.517
Finally, both platforms include VE for adults with immunocompromising conditions.

01:10:34.059 --> 01:10:36.521
I swear to God, if this aspirin works, I'm going to the gym.

01:10:36.541 --> 01:10:38.242
That could be my sound because I have it so turned up.

01:10:38.282 --> 01:10:39.443
I have it so turned up.

01:10:39.483 --> 01:10:43.206
Catherine, if I turn it down like this, do you still hear it so loud?

01:10:43.226 --> 01:10:47.069
Because it could be that I have to turn it up so loud because their audio is so low.

01:10:59.486 --> 01:11:05.968
And it could also be my stream making that noise, because I've had a noise that I can't get rid of, and it's, I can only hear it sometimes.

01:11:06.048 --> 01:11:10.250
So if it's gone now and comes back when I turn this guy up, then it's from them.

01:11:10.690 --> 01:11:13.091
The first column shows COVID-19 cases.

01:11:13.771 --> 01:11:16.532
The second column shows COVID-19 controls.

01:11:16.992 --> 01:11:20.813
The third column shows median time since the last dose among vaccinated.

01:11:21.173 --> 01:11:25.215
And then finally, the last column of four supply shows vaccine effectiveness.

01:11:27.660 --> 01:11:34.624
I really appreciate that concern Reginald but last week I dunked for the first time with two hands and my sons saw it.

01:11:35.224 --> 01:11:43.389
I didn't hang on the rim but it happened and so all the work has paid off and I'm definitely not stopping but you're right.

01:11:43.949 --> 01:11:44.890
I'm gonna be careful.

01:11:44.910 --> 01:11:48.492
I'm gonna try to recover as quick as possible because I'm having so much fun.

01:11:49.492 --> 01:11:51.733
I've come so far in the last 90 days.

01:11:51.753 --> 01:11:58.375
I don't know if it's visible from the outside, but it's definitely, I feel it from the inside.

01:11:58.495 --> 01:12:02.296
And it's going to change the way that this stream manifests.

01:12:02.336 --> 01:12:04.836
It's going to change the way that I teach the biology.

01:12:04.896 --> 01:12:07.437
It's going to change the amount of stuff I can do for you.

01:12:07.977 --> 01:12:10.558
And it's also helping me to earn a little bit of money because

01:12:11.178 --> 01:12:15.020
I've made a relationship with my gym now as a photographer, and that's helped a little bit.

01:12:15.800 --> 01:12:16.920
And all of this is great.

01:12:17.000 --> 01:12:20.342
So I'm just frustrated because I so love it.

01:12:20.422 --> 01:12:24.163
And I haven't taken very many days off because I love it so much.

01:12:24.223 --> 01:12:25.704
And so I could be overdoing it.

01:12:25.764 --> 01:12:26.624
I'm going to be careful.

01:12:26.684 --> 01:12:27.224
Don't worry.

01:12:27.244 --> 01:12:29.325
I really want to make something of this.

01:12:35.182 --> 01:12:46.610
This slide shows VA against COVID-19 associated hospitalization among adults age 65 years and up without documented immunocompromising conditions in the vision and IV networks.

01:12:47.050 --> 01:12:55.336
This slide is laid out the same as the previous slide, except instead of age groups, it shows vision adults in the top block.

01:12:55.596 --> 01:12:57.898
Just so you know, I know that overtraining is not good.

01:12:57.958 --> 01:13:04.423
And in fact, I think I've been very careful up until now to train every day in a way that I'm never sore.

01:13:05.347 --> 01:13:08.690
I can feel my muscles are working, but I'm not sore.

01:13:09.671 --> 01:13:19.779
And I really think I just blew it by going into a full speed jump shot the other day and doing it repeatedly before I had warmed up.

01:13:21.040 --> 01:13:27.405
I just jumped 100 jumps with my rope and did a little ball handling and then just started shooting.

01:13:28.459 --> 01:13:32.163
Now the way that I shoot with a full jump shot, it's a pretty impactful thing.

01:13:33.024 --> 01:13:38.370
Um, and so my back is still not, you know, I mean, it's still, I'm still a skinny guy.

01:13:38.450 --> 01:13:38.650
Right.

01:13:38.690 --> 01:13:41.593
And I still don't have the strong stomach that Bruce Lee had.

01:13:41.693 --> 01:13:44.216
So there's a lot of stuff I still have to build up.

01:13:44.356 --> 01:13:45.217
I'm going to be fine.

01:13:45.237 --> 01:13:45.277
Um,

01:13:46.940 --> 01:13:48.002
I'm not going to overdo it.

01:13:48.102 --> 01:13:50.546
I assure you the basketball and biology is coming.

01:13:50.586 --> 01:13:51.568
It's going to be so fun.

01:13:51.588 --> 01:13:52.530
It's going to be so great.

01:13:52.550 --> 01:13:53.311
I'm so excited.

01:14:01.784 --> 01:14:06.010
Estimates are shown by time since dose among those 65 years and up.

01:14:06.751 --> 01:14:14.182
You can see that point estimates do not change much over time, even in the longest time since dose strata, 120 to 179 days since the dose.

01:14:17.506 --> 01:14:21.249
indicating relatively durable protection.

01:14:21.770 --> 01:14:24.212
This mirrors what we've seen in previous years.

01:14:24.732 --> 01:14:33.379
VE against the most severe outcomes remains the most durable over time, with little evidence of waning in the longest time since dose period.

01:14:34.020 --> 01:14:46.370
In IV, shown on the bottom, we have VE against three separate outcomes, all shown for the 7 to 179 days since a dose, shown generally by increasing severity.

01:14:46.860 --> 01:14:52.982
including acute respiratory failure, ICU admission or death, and invasive mechanical ventilation.

01:14:53.582 --> 01:15:03.325
Here, again, we see indications of higher VE for the most severe outcomes at 70% for invasive mechanical ventilation or death.

01:15:04.505 --> 01:15:05.185
No shit.

01:15:07.326 --> 01:15:08.346
That's hilarious.

01:15:10.646 --> 01:15:19.957
This slide shows VE against COVID-19 associated hospitalizations among adults aged 65 years and up with immunocompromising conditions and vision and IV.

01:15:20.237 --> 01:15:21.579
This is really awful, isn't it?

01:15:21.779 --> 01:15:22.740
I mean, it's just really awful.

01:15:26.504 --> 01:15:28.325
since dose in this group.

01:15:29.005 --> 01:15:36.329
In vision, VE appears to be increasing over time, which is something we've seen previously in adults with immunocompromised conditions.

01:15:36.869 --> 01:15:54.218
And it's likely due to faster waning of infection-induced immunity in immunocompromised people, which would make the referent group, those who did not receive a 24-25 vaccine, have less protection over time since the summer surge, thereby appearing to increase VE.

01:15:54.958 --> 01:16:07.625
VE for the overall time period, 38% in vision and 36% in IV, is close to VE in non-immunocompromising adults, providing assurance that vaccine is working in immunocompromised adults.

01:16:10.266 --> 01:16:13.808
I'll next share VE by strain from the IV network.

01:16:14.328 --> 01:16:17.770
In this sub-analysis, IV conducted whole genome sequencing.

01:16:18.160 --> 01:16:29.466
and restricted to patients with sequence confirmed KP3.1.1 or XCC lineage viruses and calculated VE against hospitalization separately for each lineage.

01:16:30.306 --> 01:16:34.249
As with the main analysis, controls were those with COVID-like illness.

01:16:35.229 --> 01:16:39.272
and test negative tests for SARS-CoV-2 influenza.

01:16:39.453 --> 01:16:43.116
It was successful 49% of the time to get the whole genome it said.

01:16:43.136 --> 01:16:50.662
This slide shows the results of the VE by lineage analysis with kp3.1.1 on the top.

01:16:53.624 --> 01:17:03.430
And so whole genome sequencing is only good enough to confirm whether it's in this clade or that clade, which seems kind of to defeat the purpose of whole genome sequencing.

01:17:04.091 --> 01:17:08.694
But, you know, I'm just I'm just an armchair molecular biologist, virologist here.

01:17:08.934 --> 01:17:19.601
on time since those for the XCC cases who had received a 24 or 25 dose was 87 days, likely accounting for the slightly different point estimates, 45% for KP3.1.1 and 34% for XCC.

01:17:19.641 --> 01:17:22.143
For the respective year compared to no in-season COVID-19 vaccination,

01:17:35.373 --> 01:17:47.885
For this respective year, compared to no in-season dose, COVID-19 vaccination provided additional protection from COVID-19 associated emergency department and urgent care visits among children.

01:17:48.205 --> 01:17:52.189
Projection was generally similar across all these age groups.

01:17:52.530 --> 01:17:54.972
Unfortunately, I think this whole meeting is going to be a bust.

01:17:55.012 --> 01:17:56.854
And I think right now they're going to go to lunch.

01:17:59.713 --> 01:18:05.436
I didn't think it was going to be that bad, and I was actually hoping that Robert Malone might open the meeting, but I didn't catch the very beginning.

01:18:05.457 --> 01:18:07.918
I don't know.

01:18:08.558 --> 01:18:15.663
Like I said, I'm kind of coping with the back problem right now, so I'm kind of copping out on this show today.

01:18:16.683 --> 01:18:21.806
But tomorrow I'll be back in full swing, especially if this aspirin is actually something that's working for me.

01:18:22.647 --> 01:18:24.828
I usually don't put anything in my mouth like that.

01:18:26.485 --> 01:18:29.710
But this morning, it just it was just a lot all of a sudden.

01:18:29.730 --> 01:18:31.253
And I didn't expect it to get worse.

01:18:31.313 --> 01:18:32.375
I thought it was going to get better.

01:18:32.415 --> 01:18:34.758
That's why I went to the gym yesterday and moved around.

01:18:35.139 --> 01:18:40.568
Protection against future disease, though protection, like with vaccination, wanes over time.

01:18:41.331 --> 01:18:51.957
An increase in SARS-CoV-2 circulation in the United States occurred in late summer 2024, just before the 24-25 COVID-19 vaccines were approved and authorized.

01:18:52.697 --> 01:18:58.481
This may have resulted in a higher proportion of population-level immunity... Has this guy taken a drink?

01:18:58.801 --> 01:19:04.824
...strains, which could have resulted in lower VE measured than in a population with less recent infection.

01:19:04.864 --> 01:19:06.705
I mean, there's a guy with a big camera there.

01:19:06.785 --> 01:19:07.786
Come on, seriously?

01:19:09.232 --> 01:19:17.179
I'd like to thank the numerous colleagues from CDC and collaborators with Vision, HIV, and Overcoming Networks who contributed to this presentation.

01:19:17.900 --> 01:19:21.282
I'll now hand it off to Captain Meyer, who will present on vaccine safety.

01:19:21.463 --> 01:19:21.703
Thank you.

01:19:21.783 --> 01:19:24.025
Captain Meyer on vaccine safety.

01:19:24.065 --> 01:19:25.166
Thank you, Dr. McNeil.

01:19:25.206 --> 01:19:31.391
Before we go to the next presenter, we're going to take some questions from committee members.

01:19:31.411 --> 01:19:31.892
It was Martin.

01:19:34.114 --> 01:19:36.337
Now I understand why I heard a foreigner.

01:19:36.377 --> 01:19:40.101
That's Martin Kulldorff of the Great Barrington Declaration.

01:19:40.162 --> 01:19:49.253
He's a Dutch guy who one of our supporters is actually in contact with and was thinking would eventually be able to sway him to talk to me.

01:19:50.294 --> 01:19:53.097
And is pretty sad that that's not happening.

01:19:53.157 --> 01:19:54.359
And that's the truth.

01:19:54.419 --> 01:19:55.260
That's where we are.

01:19:55.981 --> 01:20:01.867
I've been in almost direct contact with two of the three great Barrington people.

01:20:03.208 --> 01:20:06.572
And we are being, you know, just, it's nothing.

01:20:06.893 --> 01:20:07.333
Zero.

01:20:07.573 --> 01:20:08.014
Crickets.

01:20:11.089 --> 01:20:13.510
to my SMEs here to comment.

01:20:13.770 --> 01:20:19.773
But I think it's also important to remember a lot of the randomized controlled trials were done in largely naive populations.

01:20:19.953 --> 01:20:31.458
And what we're looking at in these couple of recent years is basically the added value in a population that's had multiple exposures to vaccines or infections.

01:20:31.598 --> 01:20:37.161
So randomized clinical trials are not necessarily comparable to what we're,

01:20:37.461 --> 01:20:39.302
currently seeing with the vaccine.

01:20:39.342 --> 01:20:46.087
And, you know, we've seen across these different ages, we're seeing ballpark that the added benefit is in the range of 30 to 50%.

01:20:46.127 --> 01:21:00.777
So it's, you know, I think it's where we're trying to now monitor is the world impact of these vaccines as opposed to clinical trial data, which was certainly extensively documented.

01:21:03.519 --> 01:21:05.280
And in terms of observational studies,

01:21:07.003 --> 01:21:13.504
it's important that the control group is sort of representative of the population at large.

01:21:14.625 --> 01:21:18.425
Um, and that's usually best accomplished with the cohort study.

01:21:18.445 --> 01:21:31.168
Um, if doing a case control study, I got a, uh, really good tip from, um, the knees over toes guy combined with some other dude on the internet about, um,

01:21:32.247 --> 01:21:37.390
I was going to switch over to the other side here just quick like this, um, about my shoulder.

01:21:37.470 --> 01:21:42.573
I've had, I had long story short, I've always had a bad shoulder on my left side.

01:21:43.134 --> 01:21:57.923
Um, but when we got Mike, there was like a first few weeks where he was, you know, sleeping on the floor and I slept with him on the floor and, and I slept on this shoulder a couple of times all night and I made it real bad.

01:21:58.960 --> 01:22:02.966
And so I got this exercise that I combined with my full squats.

01:22:03.206 --> 01:22:11.216
And it's, it's really a great thing because the exercise you do is this you, you're really lifting like that.

01:22:11.277 --> 01:22:12.118
So you could do it with

01:22:13.001 --> 01:22:16.724
You could do it with two dumbbells or one dumbbell and you can just lift like this.

01:22:16.884 --> 01:22:18.785
You're just kind of punching up like that.

01:22:19.686 --> 01:22:24.569
And so I use a light one, which is just enough for me to get extra on my full squat.

01:22:24.749 --> 01:22:28.972
And then again, I, full squats are from that knees over toes guy.

01:22:28.992 --> 01:22:30.133
And I think they're really good.

01:22:31.414 --> 01:22:34.376
I swear that they're not, they're not what I thought they were.

01:22:34.416 --> 01:22:35.297
They're really good for you.

01:22:35.337 --> 01:22:41.281
And so then I just go up and over like that and I get both, sorry, you can hear my knees.

01:22:42.441 --> 01:22:43.422
If I go too fast.

01:22:44.723 --> 01:22:46.164
You're supposed to go slow anyway.

01:22:47.665 --> 01:22:50.568
And that's a really good exercise for your shoulder too.

01:22:50.628 --> 01:22:56.032
It really helped me a lot over the last few weeks.

01:22:56.072 --> 01:22:58.314
That shoulder was awful for a couple weeks.

01:22:58.394 --> 01:22:59.275
I couldn't even sleep.

01:23:01.937 --> 01:23:04.179
My knee is making a lot of noise in the last few days.

01:23:04.219 --> 01:23:06.260
And I think it's because I became dehydrated.

01:23:07.421 --> 01:23:09.003
And so I got to keep dumping water in.

01:23:16.115 --> 01:23:20.757
Provided by the CDC many people in generating this data.

01:23:20.877 --> 01:23:25.699
That's Robert Malone right there And that's Rex's Levy But Roberts definitely there I also want to thank

01:23:36.135 --> 01:23:52.298
Dr. McNeil for presenting a huge amount of data in a short period of time, a very difficult task, and you deserve a promotion for presenting that so clearly and effectively.

01:23:52.638 --> 01:23:56.339
I'm going to interrupt you and look over to Dimitri with a little nod right there.

01:23:56.699 --> 01:23:57.139
Thank you.

01:23:57.159 --> 01:23:58.219
Another exercise that I do,

01:24:05.518 --> 01:24:20.752
Over there by the small Star Wars machine, I have three invisible rainbow books next to each other that I can do calf raises on in varying positions of my feet.

01:24:21.856 --> 01:24:23.918
So, I do a lot of calf raises every day.

01:24:23.958 --> 01:24:32.085
Calf raises, jump rope are the two best exercises for speed and explosiveness that I know of as an athlete of old.

01:24:32.826 --> 01:24:37.310
And so, in getting myself back in shape, I defaulted to those things.

01:24:37.370 --> 01:24:47.719
If I had a staircase like I had at DePaul University at Alumni Hall, I would run a staircase over and over every day too, but I don't have that.

01:24:49.353 --> 01:25:10.671
But I do do calf raises and so for all the books that I've been sent the invisible rainbow I've been sent three times and I don't think it's a very good book, but it's they're all the same thickness and they're great for for calf raise Platform, so I they're very useful books in that sense How many patients who had a positive

01:25:12.229 --> 01:25:17.924
PCR assay were actually being treated for COVID, and it turned out that less than half of them were.

01:25:20.382 --> 01:25:26.584
I think many of the numbers that have been presented... All of my delts are underdeveloped.

01:25:26.604 --> 01:25:27.204
Trust me.

01:25:27.264 --> 01:25:28.184
I mean, you can see it.

01:25:29.005 --> 01:25:34.566
When people grab my shoulders or my arms, other men are usually kind of like, whoa, dude, you're thin.

01:25:34.746 --> 01:25:35.907
And, and it's true.

01:25:35.947 --> 01:25:37.147
I've been thin my whole life.

01:25:37.267 --> 01:25:44.109
So, uh, I got one blessing and that is that I can only add, you know, it's not like I've got to lose stuff first.

01:25:44.129 --> 01:25:46.230
So that's one, one blessing of being thin.

01:25:46.330 --> 01:25:47.490
So, uh,

01:25:48.542 --> 01:25:51.184
First of all, I'll ask you, and I'll stop there.

01:25:51.904 --> 01:25:56.427
If Dr. Kildorff will permit, I have some other questions, but I'm interested in your response to that.

01:25:56.547 --> 01:25:57.587
I'm barefoot right now.

01:26:00.209 --> 01:26:09.514
Yeah, if you give me one second, we have, you know, this has certainly been a very commonly discussed question.

01:26:09.814 --> 01:26:13.977
I don't jump rope barefoot because it hurts if you miss, but I could do that.

01:26:14.017 --> 01:26:15.317
But I'm barefoot most of the time.

01:26:17.415 --> 01:26:25.339
not for grounding but because it's really good for my back and it's really good for me not tripping and it's really good for me not hitting the ceiling in my garage actually.

01:26:29.802 --> 01:26:31.623
He can't find the answer in his script.

01:26:36.019 --> 01:26:40.860
50% of the pregnant women who were hospitalized had signs and symptoms of a respiratory.

01:26:41.280 --> 01:26:42.541
Oh, they're playing him.

01:26:42.881 --> 01:26:44.561
They're playing him over the PA.

01:26:44.621 --> 01:26:45.681
That's why it's echoing.

01:26:45.701 --> 01:26:48.962
And that's why they had problems with echoes before those retards.

01:26:49.522 --> 01:26:53.503
Colonized, if that's the right word, with this coronavirus.

01:26:53.803 --> 01:26:55.883
So we're hearing him through the other mic, you see?

01:26:58.444 --> 01:27:01.344
Meena, are we able to jump over to our SME line?

01:27:03.105 --> 01:27:03.625
We should have

01:27:05.020 --> 01:27:07.222
an SME online who knows.

01:27:07.722 --> 01:27:11.004
We do have an SME who's trying to chime in.

01:27:11.044 --> 01:27:13.266
So if that line could be turned on, that would be great.

01:27:21.412 --> 01:27:22.113
Hi, can you hear me?

01:27:22.413 --> 01:27:23.974
Oh boy, this is really awesome.

01:27:25.015 --> 01:27:30.659
Hi, my name is Dr. Christopher Taylor and I'm an SME with the Covenant system.

01:27:31.500 --> 01:27:36.005
And that's an excellent question you asked Dr. Meisner, and thank you for allowing me to address it.

01:27:38.507 --> 01:27:40.649
There are two sort of components.

01:27:40.669 --> 01:27:42.951
He's got a funny shaped head there.

01:27:42.991 --> 01:27:44.753
Doesn't look like the Robert Malone I know.

01:27:44.813 --> 01:27:46.415
I think that could be a clone.

01:27:46.435 --> 01:27:48.557
This might not be the real Robert Malone.

01:27:48.577 --> 01:27:52.280
The clinical data that's based on a sample of those hospitalizations.

01:27:53.121 --> 01:27:54.843
The rates that are presented

01:27:55.447 --> 01:28:01.952
Again, our population-based rates, and as you correctly said, are based on lab-confirmed SARS-CoV-2 positive tests.

01:28:03.873 --> 01:28:22.868
The clinical data that we present are limited to a sample, and that sample is further filtered, and the results, and you'll note if you go back into the slides on the footnotes, those results are limited to those where COVID-19 was identified as the likely reason for admission.

01:28:23.430 --> 01:28:25.310
Yeah, I guess subject matter expert.

01:28:26.451 --> 01:28:28.031
I was trying to figure that out too.

01:28:28.111 --> 01:28:28.491
Thank you.

01:28:28.531 --> 01:28:39.073
Published a peer reviewed paper in influenza and other respiratory viruses, looking at the trends in COVID-19 attributable hospitalizations among adults with lab confirmed SARS-CoV-2.

01:28:39.753 --> 01:28:49.055
And what we found was that looking again, just at adults, 18 years of age and older, 86% of hospitalizations during the most recent period, which for that

01:28:49.713 --> 01:29:04.194
manuscript includes 2022 and 22, 23, 86% of populations we could define as COVID attributable, which includes cases that were identified as being

01:29:05.853 --> 01:29:13.519
having a reason for admission likely attributable to COVID-19, meaning that it was identified that they had COVID-19 related illness on admission.

01:29:14.100 --> 01:29:24.769
They received a course of medicine during their hospitalization for persons with severe disease among hospitalized persons with COVID-19, or they had a

01:29:26.630 --> 01:29:29.613
select subset of discharge diagnoses.

01:29:29.733 --> 01:29:31.915
Questionable backpack there for that lady.

01:29:32.615 --> 01:29:33.496
That's not his wife.

01:29:33.656 --> 01:29:35.898
Otherwise, they'd be sitting next to each other, I presume.

01:29:35.938 --> 01:29:36.498
Something like that.

01:29:36.859 --> 01:29:42.584
So again, we found 86 percent of adult hospitalizations during that time period were somehow.

01:29:42.704 --> 01:29:45.586
Retzif Levy does not have a computer with him.

01:29:46.847 --> 01:29:50.630
Well, thank you for that very helpful information.

01:29:51.091 --> 01:29:53.713
I guess my only response is that

01:29:55.342 --> 01:29:56.682
the severity of disease.

01:29:56.722 --> 01:30:01.684
And they have this guy hosting the meeting from a remote location, which is genius.

01:30:01.864 --> 01:30:03.324
I mean, that's genius.

01:30:03.544 --> 01:30:05.205
2223 makes total sense.

01:30:06.405 --> 01:30:22.090
We know that there are many fewer hospitalizations now than there were then, whether that reflects mutations in the virus that lead to less severe disease or whether we all have a baseline immunity from the vaccine and or infection.

01:30:22.580 --> 01:30:23.521
I guess it's hard.

01:30:24.443 --> 01:30:27.287
Either way, you accept that something is now endemic.

01:30:27.347 --> 01:30:28.729
That's how stupid this is.

01:30:28.929 --> 01:30:31.593
Either way, you accept now that something is endemic.

01:30:31.633 --> 01:30:32.334
Think about that.

01:30:33.055 --> 01:30:38.944
Also, I guess it would also apply to the question of death.

01:30:39.554 --> 01:30:39.994
to SARS-CoV-2.

01:30:40.094 --> 01:30:42.575
Now somebody turned on their microphone.

01:30:42.655 --> 01:30:56.822
How many of the deaths occurred people who had respiratory symptoms or other symptoms, referral to a viral infection, and how many simply had a positive throat swab?

01:30:56.862 --> 01:31:08.708
Because many hospitals have required a throat swab on anybody who's admitted and then classified as SARS infection.

01:31:10.254 --> 01:31:10.834
Yes, thank you.

01:31:10.854 --> 01:31:14.757
That's an excellent question and we actually have an ongoing analysis looking at deaths.

01:31:14.897 --> 01:31:29.346
We're compiling the most recent years of death certificate data and it will be, we're actually in the sort of the mid-stages of that now and we hope to present it to ACIP when we have findings in the future.

01:31:29.826 --> 01:31:34.529
One thing I would also note... I mean the sound in that room, it just makes it such a joke.

01:31:35.490 --> 01:31:36.830
It's such a joke.

01:31:36.911 --> 01:31:38.471
The empty chairs are a joke.

01:31:40.287 --> 01:31:44.109
The laptops, the screen here, it's a joke.

01:31:45.549 --> 01:31:47.310
This is all a giant joke.

01:31:47.990 --> 01:32:06.438
What we have seen at least preliminarily with the 21, 22, 23 data in our published COVID hospitalization paper is that the proportion of hospitalizations attributable to COVID has actually increased slightly over time.

01:32:07.091 --> 01:32:09.892
likely as a result of decreased screening.

01:32:09.952 --> 01:32:14.612
So the number of asymptomatic people being screened has decreased.

01:32:14.632 --> 01:32:22.534
So the people that are being tested for COVID-19 are more likely to be those that come in and have some sort of symptom of COVID-19 related illness.

01:32:25.814 --> 01:32:27.675
Dr. Meissner, you said you had one more question?

01:32:29.175 --> 01:32:31.395
All right, let me ask.

01:32:32.355 --> 01:32:35.116
Okay,

01:32:36.236 --> 01:32:55.453
A quick point I want to make is that looking at the most recent CDC data on hospitalization rates among children zero to four years of age, it's less than one hospitalization per 100,000 children.

01:32:56.534 --> 01:33:03.520
And I think that even if we look at children under six months of age, looking at that same table,

01:33:04.348 --> 01:33:12.296
it's 1.6 hospitalizations per 100,000.

01:33:12.797 --> 01:33:14.498
Is that a correct interpretation?

01:33:18.462 --> 01:33:26.450
So my point is, this is a very rare illness in young children, as well as in adults now, I think.

01:33:28.786 --> 01:33:45.414
I mean, I would also just make sure we also think and point to overall cumulative numbers that there, you know, cumulative numbers, this does remain a substantial burden, particularly among the youngest and oldest age groups.

01:33:46.795 --> 01:33:56.339
To me, I think some of the comparisons to influenza, if you go back to the slides there, I think quite telling that it, there are,

01:33:57.987 --> 01:34:01.590
there are still areas for concern with COVID-19.

01:34:04.133 --> 01:34:08.416
Okay, but are those, do you think those rates are accurate?

01:34:10.678 --> 01:34:23.910
Yeah, so the rates from COVID-NET has been, you know, really a very robust platform that captured, it's captured about 10% of the U.S.

01:34:23.950 --> 01:34:24.571
population.

01:34:25.666 --> 01:34:30.248
allows very well characterization of illness.

01:34:30.489 --> 01:34:34.851
And then from there are modeled rates to the entire country.

01:34:36.091 --> 01:34:43.095
Obviously, there's a certain degree of broadness of the confidence intervals.

01:34:43.135 --> 01:34:49.719
But I think we're really talking about a pretty comfortable ballpark in terms of the burden estimates.

01:34:49.739 --> 01:34:51.960
OK.

01:34:55.987 --> 01:35:00.629
And let me just, I mean, make a comment about the reference to influenza.

01:35:00.689 --> 01:35:16.598
I think early on, many people, including myself, made comparisons with influenza, but I think we've come to find that that's probably not, that the orthomixaviruses behave quite differently than this coronavirus.

01:35:17.238 --> 01:35:21.440
And that's why you mentioned shift versus drift.

01:35:22.681 --> 01:35:24.422
I think many people have suggested,

01:35:26.510 --> 01:35:36.541
not continuing with that comparison with influenza because it's a very different virus.

01:35:36.861 --> 01:35:40.405
So I have a bunch more questions, but I don't want to hold up.

01:35:41.084 --> 01:35:48.107
Yeah, I mean, so I would say I think when we compared rates, I think your point is well taken.

01:35:48.167 --> 01:35:55.670
The goal is not to imply that the pathophysiology of influenza is the same as COVID-19.

01:35:55.770 --> 01:35:58.812
It's more a sense of the population burden.

01:36:01.395 --> 01:36:12.674
One of the things that's going around on the internet right now is that they're going to go forward with vaccinating all the chickens in America and that's going to make the bird flu mutate and even Robert Malone and the

01:36:13.729 --> 01:36:24.901
The guy with Kermit the Frog's voice that is now posing as part of Peter McCullough's health network is also talking about how vaccinating birds will make them virus factories.

01:36:25.141 --> 01:36:29.385
It is right now that this narrative is being laid down.

01:36:29.466 --> 01:36:32.489
It's right now on both sides that this is being laid down.

01:36:32.549 --> 01:36:34.210
So listen carefully because it's coming.

01:36:34.331 --> 01:36:36.313
Different terminology should be used for

01:36:36.853 --> 01:36:50.225
large rapid changes in the dominant COVID-19 variant that circulates.

01:36:50.305 --> 01:36:53.568
So thank you for that very interesting discussion.

01:36:53.748 --> 01:36:56.351
And I think we have a question from Dr. Levi.

01:36:56.971 --> 01:36:57.372
Here we go.

01:36:57.392 --> 01:36:57.972
In the room.

01:37:00.915 --> 01:37:03.517
I have multiple questions, but I'm going to focus on two.

01:37:03.537 --> 01:37:08.460
One, the first one is building on what Dr. Koldorf asked about the method.

01:37:09.701 --> 01:37:13.344
So, I'm just looking at the previous slides.

01:37:14.064 --> 01:37:25.672
Am I understanding correctly that if I look on the over 65, and I look on the percentage of people hospitalized for COVID, about 65% of them did not,

01:37:28.650 --> 01:37:31.152
were not updated on their, uh, COVID dose.

01:37:31.812 --> 01:37:39.477
But at the same time, when I look on the vaccination rates... I mean, he's debating about something that he's... he's accepting the premises.

01:37:39.598 --> 01:37:55.308
The premises are that there is a virus, that it's trackable, that it's sequencable, that those things are high-fidelity measurements, and therefore, measuring them in quantity is worth talking about in terms of a process and an endpoint.

01:37:55.649 --> 01:37:56.409
Stop lying!

01:37:56.829 --> 01:37:57.650
That's where we are.

01:37:59.849 --> 01:38:14.854
in the COVID arm, but also slightly less overrepresented in the other arm, we might conclude that the vaccine is effective based on this method because it's just a relative comparison.

01:38:16.761 --> 01:38:20.144
Would that be really the real conclusion?

01:38:20.184 --> 01:38:34.455
So I guess my question is, did we kind of scrutinize what are alternative explanations to the analysis that was conducted about the efficacy that might not point to an efficacy of the vaccine?

01:38:34.475 --> 01:38:36.317
Look at the ACIP logo down there.

01:38:36.337 --> 01:38:37.838
It's like vertical.

01:38:38.639 --> 01:38:40.700
It's like slanted like the Wisconsin W.

01:38:44.628 --> 01:38:57.472
If I think I am following your question, it's probably a question about how much we can control for certain compounding variables.

01:38:58.472 --> 01:39:00.433
So, let me be more precise.

01:39:00.473 --> 01:39:11.977
So, the method that you're currently using is comparing the relative fraction of people that are updated with their vaccinations between people that came and were tested positive versus people that came and tested negative.

01:39:14.532 --> 01:39:26.821
a possible scenario to conclude that the vaccine is effective if they are over-represented in both scenarios, but just slightly less on the one in which they tested negative.

01:39:27.261 --> 01:39:33.466
In that case, you will assume that they are, that the vaccine is protective.

01:39:34.026 --> 01:39:45.451
But the only thing, but an alternative explanation would be that the vaccine is actually making you more vulnerable for multiple viruses, including COVID, but maybe more so on other viruses than COVID.

01:39:45.671 --> 01:39:47.892
And the perception is that it's effective.

01:39:48.952 --> 01:39:51.013
And there are other scenarios.

01:39:51.714 --> 01:40:02.058
I think that there are other scenarios that you can take the same results that are presented and potentially think about alternative explanations that do not point out to vaccine efficacy, but maybe to

01:40:03.406 --> 01:40:06.069
vaccine lack of efficacy or deficiency.

01:40:06.089 --> 01:40:09.852
No, that's still one of the weaknesses with the test negative design.

01:40:10.112 --> 01:40:17.980
Yeah, so I just wanted to make it more precise because some of the data here suggests that maybe actually that's actually happening because the rate of

01:40:18.968 --> 01:40:30.374
It seems that the rate of people that are hospitalized with updated vaccination is actually higher than their relative proportion in the population.

01:40:30.615 --> 01:40:33.676
And that's kind of should make you at least concerned about these options.

01:40:34.137 --> 01:40:41.161
Let me link over to, I think Dr. Link Gales, who's our SME on methodology.

01:40:43.582 --> 01:40:44.703
Wow, that's pathetic.

01:40:45.723 --> 01:40:46.844
I just read the script.

01:40:46.864 --> 01:40:48.545
So I'm going to defer to somebody else.

01:40:51.300 --> 01:40:52.321
Hi, yes, thank you.

01:40:53.401 --> 01:40:56.182
So the- Look at Robert Malone.

01:40:56.202 --> 01:41:04.266
The test negative design is to use the controls to represent the vaccination coverage in the population that gave rise to the cases.

01:41:04.887 --> 01:41:15.912
So one of the benefits of the test negative design is that these are individuals who have the same symptoms as the cases and sought testing and medical care at the same facilities as the cases.

01:41:16.372 --> 01:41:19.554
And so in that sense, these are population-based controls.

01:41:20.294 --> 01:41:23.317
even though it is a test negative case control design.

01:41:23.837 --> 01:41:36.549
And then I would add that the over, the representation of the controls of this case, these are not the general population in that they are elderly people who are hospitalized with COVID-19.

01:41:38.170 --> 01:41:47.433
acute respiratory illness, and therefore we would not expect them to have the same vaccination coverage as in the unhospitalized, likely healthier general U.S.

01:41:47.493 --> 01:41:48.213
population.

01:41:48.593 --> 01:41:57.976
They are really meant to be representative as much as possible of people who, if they had COVID, would have sought medical care or been hospitalized at the same location.

01:41:58.416 --> 01:42:07.179
And so for that reason, we think that the controls here are exactly what we want to understand the relative impact of the vaccination.

01:42:15.714 --> 01:42:18.341
I think we have a question from Dr. Bethel.

01:42:20.407 --> 01:42:21.147
Yes, hi.

01:42:21.327 --> 01:42:35.010
I'm sorry to ask a question as the FDA ex officio, but I'm very excited to be able to talk with the first author of this study, looking at the test negative design.

01:42:35.090 --> 01:42:41.912
And I share Dr. Kulldorff and Dr. Levy's concerns about the potential for confounding.

01:42:42.772 --> 01:43:01.558
I'm wondering, you know, if the goal is to really have comparable groups with comparable symptoms, you know, one that happens to test positive for COVID and one that doesn't, why exclude the patients that test positive for influenza and then those over 60 that test positive for RSV?

01:43:01.778 --> 01:43:12.061
And, you know, are we not concerned that these may be fundamentally different groups of people that are, you know, seeking medical care but happen to test positive for COVID-19 versus

01:43:12.501 --> 01:43:17.966
something else, and it's really difficult to say their symptoms are exactly comparable.

01:43:18.106 --> 01:43:35.361
And so, you know, just to get my point in, I think I share a lot of people on this panel's desire to see randomized control trials to minimize these types of bias so we aren't sitting here saying, you know, wondering, are we being misled by these data?

01:43:36.362 --> 01:43:39.265
So, thanks for your response to that.

01:43:42.952 --> 01:43:44.115
Yeah, thank you for that.

01:43:44.175 --> 01:43:48.888
So I would add to my previous answer that I think

01:43:50.071 --> 01:43:58.733
If you include controls or cases that test positive for another vaccine-preventable disease, you are actually going to add bias to your study.

01:43:59.173 --> 01:44:05.195
And there's been quite a lot of published literature by Dahl, et al., and others showing that this would happen.

01:44:05.575 --> 01:44:14.717
And so for that reason, we dropped controls that tested positive for flu or RSV because the vaccine status is actually correlated.

01:44:15.097 --> 01:44:29.387
And so if you had a positive control for influenza, they would be less likely to be influenza vaccinated, also would mean they'd be less likely to be COVID vaccinated, because we know that COVID and flu vaccine status are highly correlated.

01:44:30.148 --> 01:44:37.173
We also do quite a lot of work with the study sites to make sure that the cases and controls have similar symptoms.

01:44:37.613 --> 01:44:39.455
And we have looked at a number of cases

01:44:40.195 --> 01:44:50.805
and published looking at number of symptoms among cases and controls, severity of symptoms among cases and controls to ensure that our case and control populations are balanced in that respect.

01:44:51.546 --> 01:44:56.591
As far as the question about clinical trials, I would actually defer that back to you all at FDA.

01:44:57.812 --> 01:44:58.873
Yeah, we're working on that.

01:44:58.913 --> 01:44:59.213
Thanks.

01:44:59.814 --> 01:45:00.775
Thanks for the response.

01:45:01.688 --> 01:45:13.437
And I would actually maybe weigh in on one other aspect of this with clinical trials, just realizing some of the real-world realities of the time and cost it takes to do clinical trials.

01:45:13.637 --> 01:45:21.323
And I think the test-negative design has provided a robust way to, in a very timely manner,

01:45:22.163 --> 01:45:23.405
get real-world data.

01:45:23.445 --> 01:45:35.337
I mean, to realistically say that, you know, this is June and we're looking at VE data from this last season as the timing would not be

01:45:36.428 --> 01:45:44.190
possible from a temporal or a cost standpoint to be able to, for CDC to be able to do randomized clinical trials with that.

01:45:44.210 --> 01:45:50.351
So, I think this is, for us, it's sort of a robust way to be able to rapidly get real-world data very efficiently.

01:45:51.191 --> 01:45:51.712
Dr. Levi?

01:45:52.952 --> 01:45:56.553
Yeah, I guess my second question is maybe on a completely different topic.

01:45:56.573 --> 01:46:01.234
So, I was looking on the evolution, the genome evolution of the variants.

01:46:03.237 --> 01:46:05.721
And there are two striking jumps.

01:46:07.203 --> 01:46:10.849
You see continuous kind of evolution and then two major jumps.

01:46:13.320 --> 01:46:15.541
And I have two questions related to that.

01:46:15.641 --> 01:46:25.587
One of them is, did we do any analysis to compare that to other viruses like influenza, for which we have similar data, to see if that's kind of a common pattern?

01:46:25.668 --> 01:46:29.850
Or these jumps, how common these jumps are at once, almost at once?

01:46:30.030 --> 01:46:35.473
And if they are not common, what could be some evolutionary pressures?

01:46:36.934 --> 01:46:39.456
Because usually these jumps come from some pressure.

01:46:41.836 --> 01:46:43.137
of evolutionary pressure.

01:46:43.338 --> 01:46:58.171
So, to what extent that was analyzed and maybe also to see if there is, are there any connections to the vaccination policy that we have in that evolution of, in the evolution of the variants.

01:46:58.311 --> 01:47:02.314
That seems at least kind of striking in terms of the shape, the pattern, so.

01:47:03.655 --> 01:47:07.479
I think we have one more comment from Dr. Meissner and then maybe I think we should move on.

01:47:09.773 --> 01:47:13.896
Do you want me to quickly comment on the evolutionary aspect?

01:47:14.256 --> 01:47:22.781
Yeah, I mean, this has been, I think it has been, it's a field we've been continuing to learn.

01:47:23.401 --> 01:47:25.723
COVID-19 has thrown us many surprises.

01:47:25.843 --> 01:47:31.186
Omicron, I think, is a classic example of that, where it was a massive change.

01:47:31.246 --> 01:47:33.728
It came out of nowhere and caused an incredible,

01:47:35.168 --> 01:47:37.350
I think we've also seen these other punctuated changes.

01:47:37.370 --> 01:47:49.219
There are likely aspects of selective pressure within the human population due to, say, preexisting immunity.

01:47:50.619 --> 01:47:55.540
You know, I think there are also unusual aspects of the virus.

01:47:55.900 --> 01:47:57.640
So, I think it's a complex dynamic.

01:47:57.660 --> 01:48:09.882
There's obviously been a ton of work in the space of monitoring variants, being able to provide sequencing data real time.

01:48:09.962 --> 01:48:18.744
So, you know, I think it's crucial that we continue to have the capacity to be able to monitor for if and when these surprises occur.

01:48:21.495 --> 01:48:22.796
Thank you, and Dr. Meissner?

01:48:24.418 --> 01:48:26.119
Thank you very much.

01:48:27.100 --> 01:48:37.228
I just want to add to the complexity of what was just being said, because we're now seeing convergent evolution.

01:48:37.368 --> 01:48:50.179
That is, various strains are developing the same mutations in certain areas of the spike protein.

01:48:52.376 --> 01:48:56.118
this is a really tough issue to sort out.

01:48:58.959 --> 01:49:17.548
But the one point I wanted to say in regard to the case control design, it isn't perfect, and I think that's what we're hearing, but it's the best we can do in a limited time period.

01:49:17.568 --> 01:49:20.730
For example, that's what we use

01:49:21.417 --> 01:49:24.719
to assess influenza vaccines, which change every year.

01:49:25.299 --> 01:49:39.909
So I mean, a case control, as Dr. Link-Ellis pointed out, I mean, sure, it has biases in favor of a person who's more likely to seek medical attention.

01:49:41.270 --> 01:49:42.090
So there are problems.

01:49:42.791 --> 01:49:49.655
But it is a pretty well-established design for looking at vaccines over

01:49:54.200 --> 01:49:54.521
Thank you.

01:49:54.541 --> 01:50:04.970
And I think we have to distinguish between a traditional case control study versus a test negative design, because methodologically, I think those are very different in terms of the quality of the information.

01:50:05.551 --> 01:50:17.381
But we will now have to move on with Dr. Sarah Meyer from CDC, who will talk about COVID-19 vaccine safety issues.

01:50:17.581 --> 01:50:17.862
Thank you.

01:50:22.762 --> 01:50:23.443
Good afternoon.

01:50:23.883 --> 01:50:24.985
My name is Sarah Meyer.

01:50:25.165 --> 01:50:28.549
I'm a pediatrician and the director of the Immunization Safety Office.

01:50:29.149 --> 01:50:33.614
Today I'll be sharing an update on CDC's COVID-19 vaccine safety monitoring.

01:50:34.235 --> 01:50:44.066
The goal of this presentation is to share with the committee how CDC monitors COVID-19 vaccine safety and what we have found through four and a half years of monitoring these vaccines.

01:50:46.397 --> 01:50:49.740
Before I get into the details, I want to state the bottom line up front.

01:50:50.380 --> 01:50:57.085
CDC and interagency partners launched an extensive vaccine safety monitoring program for COVID-19 vaccines.

01:50:57.926 --> 01:51:03.410
Many potential safety outcomes were rigorously assessed through complementary passive and active systems.

01:51:04.211 --> 01:51:07.233
Myocarditis has been causally associated with mRNA COVID-19 vaccines.

01:51:09.560 --> 01:51:17.465
In addition, adverse events common to all vaccines such as local and systemic reactions and allergic reactions have been observed.

01:51:18.265 --> 01:51:21.787
CDC continues to monitor the safety of COVID-19 vaccines.

01:51:22.768 --> 01:51:23.348
I apologize.

01:51:25.309 --> 01:51:26.410
Let me get the slide to move.

01:51:31.926 --> 01:51:36.347
Vaccine safety monitoring is a key component of the entire vaccine life cycle.

01:51:36.647 --> 01:51:36.887
Awesome.

01:51:36.967 --> 01:51:46.150
From the preclinical research and development to clinical trials and the reviews by regulatory agencies and advisory groups, safety is evaluated at every step.

01:51:47.010 --> 01:51:59.413
After a vaccine has been authorized or approved, CDC safety monitoring begins alongside our interagency partners, FDA, Indian Health Service, Department of Defense and Department of Veterans Affairs.

01:52:09.130 --> 01:52:20.695
CDC uses strong complementary systems in a layered approach to rapidly detect and assess potential safety concerns in order for public health officials and policy makers to take appropriate action.

01:52:21.475 --> 01:52:30.599
Most of these systems have been in place for decades, but we are continuing to improve the existing systems as well as identify new systems that are needed to fill gaps.

01:52:30.819 --> 01:52:35.923
This can be kept on the, I mean, they can keep this cruise ship going exactly the direction it's going.

01:52:36.023 --> 01:52:40.826
Robert Malone and the new ACIP meeting is not going to do shit diddly about it.

01:52:41.667 --> 01:52:42.767
It's, it's all the same.

01:52:43.708 --> 01:52:47.371
Nothing has changed since Trump has come in office.

01:52:47.411 --> 01:52:48.271
There's no peace.

01:52:48.331 --> 01:52:49.492
There's no cheap eggs.

01:52:49.532 --> 01:52:50.793
There's no cheap gas.

01:52:51.974 --> 01:52:53.375
There's no, you know,

01:52:55.089 --> 01:53:16.919
changing of the immigrant problem whatever that is there's no nothing nothing is happening other than the continued controlled demolition of america and this ridiculous theater that something is happening called public health and it's an answer for stuff events and vaccines however reports are encouraged from anyone such as patients or their family member

01:53:18.072 --> 01:53:23.494
An important point to stress is that a report to VAERS does not mean that a vaccine caused an adverse event.

01:53:24.335 --> 01:53:31.117
VAERS is used for signal detection and hypothesis generation and in most situations is not able to assess for causality.

01:53:36.199 --> 01:53:42.522
The Vaccine Safety Data Link or VSD is a collaborative model for generating high quality vaccine safety data.

01:53:43.644 --> 01:53:44.145
13 integrated.

01:53:44.165 --> 01:53:49.393
It's really hard to imagine that this is 2025 and not 2021 or 2019 or 2015 with a meeting where, where I don't know where Mary Holland might speak.

01:53:49.413 --> 01:53:49.874
This is just stupid.

01:53:57.760 --> 01:54:02.462
for pre-specified events of interest, as well as for monitoring for unexpected events.

01:54:03.282 --> 01:54:09.825
As opposed to VAERS, which is used for signal detection, VSD can both detect as well as assess safety signals.

01:54:10.646 --> 01:54:18.629
Another hallmark of the VSD is the strong expertise in this network, which has allowed for the development of innovative methods for monitoring safety.

01:54:24.005 --> 01:54:26.086
The clinical immunization safety assessment.

01:54:26.147 --> 01:54:31.170
The extent to which this has advanced is that they are no longer saying next slide.

01:54:31.710 --> 01:54:35.913
That's the progress we've made in the last five years at this bullshit show.

01:54:35.933 --> 01:54:38.615
Vaccine safety experts and subspecialists.

01:54:39.356 --> 01:54:46.461
CISA consultants provide individual clinical consultations on complex immunization issues to help guide patient care.

01:54:47.338 --> 01:54:54.925
CISA investigators also conduct clinical research on vaccine safety geared towards real-world issues not assessed in pre-licensure trials.

01:54:55.786 --> 01:55:02.232
Finally, CISA consultants help to inform CDC public health guidance on clinical immunization safety issues.

01:55:06.894 --> 01:55:14.440
Lastly, the V-safe after vaccination health checker is CDC's newest tool and involves direct-to-consumer vaccine safety monitoring.

01:55:15.061 --> 01:55:22.146
V-safe is a smartphone and computer-based self-reported active monitoring system established during the COVID-19 pandemic.

01:55:22.807 --> 01:55:31.313
It can serve as the earliest source of information on reactogenicity and other health events for new vaccines and in populations excluded from clinical trials.

01:55:32.054 --> 01:55:43.603
For example, v-safe provided a conduit to enroll more than 23,000 pregnant women into a voluntary registry to monitor maternal and neonatal outcomes after COVID-19 vaccination.

01:55:44.804 --> 01:55:51.570
Because it is flexible and able to be rapidly deployed, v-safe is an important tool for emergency preparedness and response.

01:55:52.370 --> 01:55:57.815
In addition, v-safe is integrated with VAERS to help streamline reporting of serious adverse events.

01:56:03.697 --> 01:56:09.782
These systems serve as the foundation for CDC's comprehensive approach to studying COVID-19 vaccine safety.

01:56:10.903 --> 01:56:28.978
This approach includes surveillance to analyze spontaneously reported events, epidemiologic studies to assess specific safety questions, clinical research to help guide clinical practice, a pregnancy registry for a longitudinal assessment of maternal and infant outcomes after COVID-19 vaccination,

01:56:30.188 --> 01:56:35.751
Rapid cycle analyses to quickly detect potential concerns that require further investigation.

01:56:36.571 --> 01:56:43.254
Data mining to assess for over 60,000 potential outcomes in order to detect unexpected events after vaccination.

01:56:43.374 --> 01:56:47.656
I don't expect that they're doing placebos with COVID vaccines anymore.

01:56:47.676 --> 01:56:50.478
I don't know if they're doing placebos with anything anymore.

01:56:51.358 --> 01:56:53.160
simply because the uptake is so low.

01:56:53.280 --> 01:56:54.721
So I don't know if they have to.

01:56:54.761 --> 01:57:03.649
What they had to do it for was the initial, if you want it, we want to make sure we can get it in your arm part of the military exercise.

01:57:03.709 --> 01:57:07.852
So that, that for sure was almost exclusively placebo.

01:57:08.453 --> 01:57:10.855
Not AstraZeneca, I mean the mRNA.

01:57:11.135 --> 01:57:11.655
One billion, okay.

01:57:36.553 --> 01:57:42.237
To quickly recap, there were three types of COVID-19 vaccines that were authorized or approved in the United States.

01:57:43.118 --> 01:57:51.504
mRNA vaccines by Pfizer, BioNTech, and Moderna, a protein-based vaccine by Novavax, and a viral vector-based vaccine by Janssen.

01:57:55.526 --> 01:57:58.147
However, Janssen use was limited in the United States.

01:57:58.608 --> 01:58:02.530
By April, 2021, VAERS detected six reports of thrombosis.

01:58:02.630 --> 01:58:08.273
So we're just retelling the story to make sure that you know that they did everything they could to be safe.

01:58:08.333 --> 01:58:10.174
When they saw a signal, they took it off.

01:58:10.714 --> 01:58:12.115
They evoked the EUA.

01:58:12.555 --> 01:58:13.836
That means they're good guys.

01:58:13.896 --> 01:58:16.297
And that means that these didn't have a signal.

01:58:16.337 --> 01:58:24.982
That's the same illusion that Jessica Rose created about the previous vaccines, because we've never seen a signal like this in VAERS before.

01:58:27.642 --> 01:58:35.375
The Janssen experience highlights an example of federal safety systems working together to rapidly identify and mitigate a vaccine safety issue.

01:58:35.996 --> 01:58:40.503
I won't be discussing safety of Janssen's COVID-19 vaccine any further in this presentation.

01:58:43.919 --> 01:58:48.864
For Novavax, there are currently limited post-authorization safety data available in the US.

01:58:49.465 --> 01:58:56.672
This product was authorized later than the mRNA vaccines in July, 2022, and there has been limited uptake in the United States.

01:58:57.232 --> 01:58:59.595
Therefore, I won't be discussing Novavax.

01:58:59.615 --> 01:59:01.917
There might've been a lot of uptake in India.

01:59:01.957 --> 01:59:03.719
They might have a lot of data from India though.

01:59:05.387 --> 01:59:13.935
Thus, I will focus the remainder of this talk on the safety of mRNA COVID-19 vaccines for which a large body of evidence has accrued over the past few years.

01:59:16.097 --> 01:59:22.883
Here comes the large body of evidence monitoring the safety of COVID-19 vaccines at CDC.

01:59:23.043 --> 01:59:23.604
Sweet.

01:59:24.084 --> 01:59:24.965
What have we learned?

01:59:28.109 --> 01:59:37.738
CDC has evaluated at least 65 specific outcomes to assess COVID-19 vaccine safety using a variety of systems and epidemiologic methods.

01:59:42.281 --> 01:59:56.265
We have conducted weekly sequential monitoring through rapid cycle analyses or RCA's in the VSD since the start of the vaccine rollout in December 2020 of up to 23 pre-specified outcomes among over 12 million people.

01:59:57.086 --> 02:00:04.308
These outcomes were selected based on clinical trial data, known safety findings with other vaccines or biological plausibility.

02:00:05.171 --> 02:00:17.943
Sequential statistical testing using automated ICD-10 codes is used to compare incidence of an outcome in vaccinated people during a post-vaccination risk interval versus vaccinated people in a comparison interval.

02:00:18.724 --> 02:00:24.849
If a potential statistical signal is detected, additional analyses and or chart reviews are conducted.

02:00:25.610 --> 02:00:27.472
The system is designed to be sensitive.

02:00:27.772 --> 02:00:30.935
Not all detected signals represent a true safety concern.

02:00:35.609 --> 02:00:42.732
From 2020 to 2025, eight statistical signals have been detected through VSD's weekly rapid cycle analyses.

02:00:43.433 --> 02:00:55.879
These include acute myocardial infarction, venous thromboembolism, immune thrombocytopenic purpura, ischemic stroke, seizure, Guillain-Barre syndrome, Bell's palsy, and myocarditis.

02:00:56.339 --> 02:00:57.760
So they're going to start paying for these.

02:00:59.969 --> 02:01:10.354
After a signal is detected, CDC undertakes further investigations to determine whether a true safety concern is present or whether the statistical signal represents a false positive.

02:01:11.114 --> 02:01:27.362
These include chart reviews, a trend analysis of the reported rate ratios, cluster analyses, additional studies, such as self-controlled case series, and querying other monitoring systems, such as VAERS or databases managed by interagency partners, including the FDA and VA.

02:01:31.590 --> 02:01:39.313
After completing these investigations, CDC assess that there is an increased risk for myocarditis following mRNA COVID-19 vaccines.

02:01:39.933 --> 02:01:44.595
There's been no clear or consistent evidence of a safety concern for the other outcomes I mentioned.

02:01:44.695 --> 02:01:45.876
That's fantastic.

02:01:46.036 --> 02:01:49.617
No other consistent evidence of any of that other shit.

02:01:49.657 --> 02:01:51.278
It's just myocarditis.

02:01:51.298 --> 02:01:51.738
Stop lying!

02:01:51.758 --> 02:01:52.779
Stop lying!

02:01:53.059 --> 02:02:01.122
This figure shows the incidence of myocarditis per million doses administered within seven days of vaccination among 12 to 39 year olds.

02:02:01.562 --> 02:02:02.703
by season and dose.

02:02:03.944 --> 02:02:08.809
In general, rates of myocarditis peak in 16 to 17 year olds and are higher in males.

02:02:09.730 --> 02:02:15.475
Myocarditis is rare in children aged less than 12 years or in adults greater than 50 years of age.

02:02:16.296 --> 02:02:23.283
As you can see, the risk was highest after the second dose in the primary series, but remained elevated after the first monovalent booster.

02:02:25.171 --> 02:02:32.422
In subsequent seasons, the incidence has been lower and is more similar to the background rate of less than two cases per million population.

02:02:33.443 --> 02:02:36.287
We have seen similar patterns with VAERS reports as well.

02:02:37.469 --> 02:02:41.535
There are a few possible reasons for these lower myocarditis rates in recent years.

02:02:42.273 --> 02:02:46.458
At this stage, adolescents and adults have been eligible for multiple vaccine doses.

02:02:47.199 --> 02:02:54.629
In addition, the longer inter-dose interval, where most people are getting a dose only once per year at most, is another potential factor.

02:02:55.229 --> 02:02:58.754
There may be others, like higher levels of overall population immunity.

02:03:04.449 --> 02:03:18.375
FDA has also recently shared updated data on myocarditis and pericarditis following mRNA COVID-19 vaccination from the Biologics Effectiveness and Safety System, or BEST, from the 2023-2024 season.

02:03:19.335 --> 02:03:28.719
FDA issued safety labeling change notification letters to the manufacturers in April to include new safety information on myocarditis and pericarditis.

02:03:29.554 --> 02:03:35.941
And today, FDA approved safety labeling changes for Comirnaty and Spikevax to include this new safety information.

02:03:41.467 --> 02:03:44.330
New safety information in the foldout.

02:03:44.430 --> 02:03:45.391
I think this is a good

02:03:46.294 --> 02:03:52.059
CDC has conducted follow-up studies that show most adolescents and young adults have recovered from myocarditis.

02:03:52.359 --> 02:03:53.320
Oh my god.

02:03:53.400 --> 02:03:55.822
Okay, that's it.

02:03:56.162 --> 02:04:00.746
So they're basically telling you that it's only myocarditis and most of them recover anyway.

02:04:01.327 --> 02:04:02.628
So Robert F. Kennedy Jr.

02:04:02.648 --> 02:04:04.209
doesn't even have anything to fix.

02:04:05.790 --> 02:04:07.392
This is again running slow.

02:04:07.412 --> 02:04:07.932
It should be 97.

02:04:10.959 --> 02:04:11.659
I don't know what to say.

02:04:11.679 --> 02:04:14.701
I apologize for not having an organized show this morning.

02:04:15.542 --> 02:04:19.664
Again, I'm trying to figure out how to move and get moving again.

02:04:21.085 --> 02:04:22.525
But I will be here tomorrow for sure.

02:04:22.565 --> 02:04:26.668
I have the slide deck done and there's so much to watch, so much to work on.

02:04:27.328 --> 02:04:30.050
and so much Biology 101 to learn together.

02:04:30.110 --> 02:04:38.416
So I'm very excited about this slowly moving change after the summer equinox.

02:04:38.956 --> 02:04:42.379
I hope my listeners are not suffering too much from the heat.

02:04:42.459 --> 02:04:43.780
If you're in America, you might be.

02:04:45.201 --> 02:04:53.126
And I hope you have a little swimming pool like I do that you can hang out with with your kids or something equivalent to that.

02:04:54.895 --> 02:05:01.799
I don't know what to say, but you got to enjoy the little plastic pool moments at this point, because who knows when we won't even have those.

02:05:02.439 --> 02:05:04.361
Thank you very much for being here, ladies and gentlemen.

02:05:04.401 --> 02:05:05.661
Thank you very much for sharing.

02:05:05.681 --> 02:05:07.542
Thank you very much for supporting the stream.

02:05:08.703 --> 02:05:09.904
I'll beg for money tomorrow.

02:05:09.924 --> 02:05:10.664
Thank you very much.

02:05:10.944 --> 02:05:11.705
I'll see you again soon.

02:05:44.727 --> 02:05:45.270
Thanks, guys.

02:05:45.290 --> 02:05:46.455
See you tomorrow.