Steve Kirsch

If you need to contact me about anything (interview request, fact check request, ask a question, let me know about something, want to debate me, found an error, etc), here's how to contact me: stevekirsch.substack.com/p/how-to-conta…

🚨 STAGE 1 — SELECT THE TARGET The Anatomy of a Coordinated Reputation-Destruction Campaign 7 DAYS. 7 STAGES. RELEASING DAILY AT 12:00 PM ET MAY 25–31, 2026 🔱 Exposed by ScienceGuardians™ Today we begin the series by exposing the first stage: how criminal networks, such as the PubPeer “PubSmear” Network Mob, deliberately select their targets. The target is rarely random. Selection is strategic, calculated, and multi-purpose. The objective is not always — or only — the destruction of an individual. It is the acquisition, neutralization, or redistribution of power, influence, narrative control, and financial advantage. Primary Motives for Target Selection 1. Demonstration of Power & Intimidation High-profile figures in elite institutions — especially presidents of top-tier global universities such as Stanford, Harvard, and others — are selected to send a chilling message: No one is untouchable. Taking down leaders occupying academia’s most prestigious offices creates fear across the broader scientific and institutional ecosystem. It pressures others into silence, compliance, self-censorship, or strategic alignment with the mob to avoid becoming the next target. 📌 Added benefit for the perpetrators: Public faces of these malicious campaigns are often rewarded with appointments to university “integrity committees,” consultancy roles, speaking circuits, media prestige, and institutional influence — benefits granted by organizations eager to signal compliance and avoid future attacks. 2. Narrative Control Researchers or institutional leaders associated with inconvenient scientific narratives, paradigms, or findings can become strategic targets. ⚠️ By attacking the scientist’s publications, the scientist can be indirectly discredited, and by discrediting the scientist, the perceived credibility of their broader research narrative or body of work can be undermined. This becomes an efficient mechanism for suppressing competing narratives without engaging in open scientific debate. 3. Financial Warfare — Markets, Companies & Short Positions Modern campaigns increasingly intersect with financial and commercial interests. Scientists connected to influential companies, technologies, biomedical programs, or high-valuation research can become especially attractive targets. Discrediting key publications or principal investigators may trigger market instability, valuation collapses, investor panic, or competitive advantages for rivals. These operations can be anticipated, timed, amplified, and exploited alongside short-selling opportunities and broader commercial conflicts. Academic reputational destruction can therefore evolve into a sophisticated form of financial warfare. 4. Contracted Hits — Vacating Positions for Payment Some campaigns are allegedly initiated on behalf of third parties seeking institutional change, leadership vacancies, or strategic realignment. The greater the influence attached to the position, the greater the strategic value of forcing a resignation. ⚠️ Removing a university president, dean, department chair, journal editor, or principal investigator can rapidly reshape institutional direction and power structures. Collateral Damage Not every target serves a direct strategic purpose. Some academics become collateral damage — sacrificed to maintain the appearance of legitimacy, test tactics, normalize escalation methods, or conceal broader coordination patterns. Their destruction serves the machinery itself. This is STAGE 1: SELECT THE TARGET. Tomorrow — DAY 2: RECRUIT THE INSIDER How networks identify, cultivate, and activate compromised or ideologically aligned individuals within institutions to provide access, legitimacy, and internal sabotage. Stay vigilant. Understand the playbook. Protect the integrity of science. 📌 Follow the full 7-day series: 🔱 ScienceGuardians™ @SciGuardians Save and share it widely. This is not about legitimate accountability. This is about control.

@skiiskiim I’m not the only one to find no benefit: deepd1ve.substack.com/p/weekly-exces… Where is the ERROR and the benefit computation?

@stkirsch During the pandemic you did. Now it’s over why would you?

Can you see a COVID vaccine benefit from the official US monthly all-cause mortality? See: open.substack.com/pub/stevekirsc…

@skiiskiim No benefit DURING the pandemic. Did everyone misread the data? Where are you seeing the benefit in 2021 vs 2020????

True story - and the FDA continues to hide deaths, by using statistic methods that couldn't detect a pitchfork in a hay stack.

@teniscat No Grok agreed with me: x.com/stkirsch/statu…

Grok, is Steve correct? Grok: No, Steve Kirsch’s claim is misleading and incorrect in its interpretation (though the raw numbers have a superficial kernel of truth). What he actually said Kirsch points to CDC UCOD (Underlying Cause of Death) / all-cause mortality data showing that elderly excess mortality in 2021 was roughly similar to 2020 (both elevated vs. 2018–2019 baseline). He calls this “inconsistent” with a “massively life-saving vaccine” rolled out to the most vulnerable starting January 2021. He claims he age-adjusted it and the result holds. Why this is flawed • 2020 vs 2021 isn’t a clean before/after test. Vaccines rolled out gradually (prioritized elderly, but not everyone was vaccinated immediately or fully protected right away). The deadly Delta variant hit hard in summer/fall 2021, driving another wave despite rising vaccination. • Counterfactual matters. Without vaccines, 2021 mortality would have been substantially worse due to more transmissible variants and continued spread. Multiple independent models (Commonwealth Fund, CDC-linked analyses, etc.) estimate the U.S. vaccination program prevented ~1.1 million deaths by late 2021 — the large majority in older adults. • Real-world evidence shows benefit. High-vaccination states and countries saw clearer drops in elderly mortality post-rollout. Observational data, state comparisons, and later analyses consistently show vaccines reduced severe outcomes and deaths in the elderly (the group with highest uptake and highest risk). • This is a classic ecological fallacy. Looking at aggregate year-over-year excess deaths without modeling what would have happened absent vaccines (or accounting for variants, behavior, seasonality, etc.) doesn’t disprove efficacy. It’s the same flawed reasoning Kirsch has used repeatedly and that’s been critiqued by fact-checkers and epidemiologists. Bottom line Elderly excess mortality was still elevated in 2021 (pandemic wasn’t over). But the data does not contradict that the vaccines were life-saving for the elderly — the strongest evidence (randomized trials + real-world studies) shows they were. Kirsch’s framing ignores the counterfactual and timing, turning a nuanced reality into a “gotcha.” This fits his usual pattern: selective data presentation that sounds damning until you add context. The vaccines weren’t magic or perfect, but they demonstrably cut mortality in the highest-risk groups when it mattered most.

UCOD data from the CDC. Did you realize that the elderly had the SAME increase in mortality in 2021 and 2020 compared to 2018/2019 baseline. This is INCONSISTENT with a massively life saving vaccine rolled out to the most vulnerable in Jan 2021. Whoops!!!

@teniscat sorry, Grok agrees with me. x.com/stkirsch/statu…

Steve Steve Steve. Grok: No, Steve Kirsch’s claim is misleading and incorrect in its interpretation (though the raw numbers have a superficial kernel of truth). What he actually said Kirsch points to CDC UCOD (Underlying Cause of Death) / all-cause mortality data showing that elderly excess mortality in 2021 was roughly similar to 2020 (both elevated vs. 2018–2019 baseline). He calls this “inconsistent” with a “massively life-saving vaccine” rolled out to the most vulnerable starting January 2021. He claims he age-adjusted it and the result holds. Why this is flawed • 2020 vs 2021 isn’t a clean before/after test. Vaccines rolled out gradually (prioritized elderly, but not everyone was vaccinated immediately or fully protected right away). The deadly Delta variant hit hard in summer/fall 2021, driving another wave despite rising vaccination. • Counterfactual matters. Without vaccines, 2021 mortality would have been substantially worse due to more transmissible variants and continued spread. Multiple independent models (Commonwealth Fund, CDC-linked analyses, etc.) estimate the U.S. vaccination program prevented ~1.1 million deaths by late 2021 — the large majority in older adults. • Real-world evidence shows benefit. High-vaccination states and countries saw clearer drops in elderly mortality post-rollout. Observational data, state comparisons, and later analyses consistently show vaccines reduced severe outcomes and deaths in the elderly (the group with highest uptake and highest risk). • This is a classic ecological fallacy. Looking at aggregate year-over-year excess deaths without modeling what would have happened absent vaccines (or accounting for variants, behavior, seasonality, etc.) doesn’t disprove efficacy. It’s the same flawed reasoning Kirsch has used repeatedly and that’s been critiqued by fact-checkers and epidemiologists. Bottom line Elderly excess mortality was still elevated in 2021 (pandemic wasn’t over). But the data does not contradict that the vaccines were life-saving for the elderly — the strongest evidence (randomized trials + real-world studies) shows they were. Kirsch’s framing ignores the counterfactual and timing, turning a nuanced reality into a “gotcha.” This fits his usual pattern: selective data presentation that sounds damning until you add context. The vaccines weren’t magic or perfect, but they demonstrably cut mortality in the highest-risk groups when it mattered most.”

Grok agrees. This is inconsistent with expectations:

@teniscat wrong. elderly were prioritized and vaccinated well before Delta. did you forget that? And the vaccine takes near FULL effect in 14 days per studies.

population adjusted and on a log scale:

If you need to contact me about anything (interview request, fact check request, ask a question, let me know about something, want to debate me, found an error, etc), here's how to contact me: stevekirsch.substack.com/p/how-to-conta…

Gotta love the absolute SILENCE from the pro-vax people on this one ;)

@CLTdysphagia plotted from data extracted from CDC UCOD monthly. To get the population numbers, do a yearly pull. Then we verified it on mortality rate, not absolute deaths.

@stkirsch and this chart is from?

and don't worry. I age adjusted it and got the same result. From Codex: A population-adjusted all-cause age-gradient screen does not provide a clean ecological signature of a large elderly-specific mortality benefit from the early 2021 vaccine rollout. Elderly excess mortality remained elevated in 2021 despite prioritization (65+ +12.8%, 75+ +14.0%, 85+ +18.0% versus same-month 2018-2019 baselines), and the 2021-to-2022 decline was broad-based rather than uniquely elderly-specific: 25-64 fell from +31.8% to +15.5%, while 85+ fell from +18.0% to +7.9%. This is not a causal estimate; it is a specificity challenge. Aggregate ACM patterns require an explicit model before they can be treated as evidence for a large elderly-specific net vaccine benefit. In plain English, "the CDC UCOD data doesn't show the claimed massive vaccine benefit... why not?"

We’re bringing a potentially groundbreaking treatment being used in Japan to help vaccine-injured Americans.

🚨 Hantavirus. Ebola. “Disease X.” Why does it feel like the world is being introduced to a new virus threat every week? TOMORROW -- TUESDAY -- on VSRF Live, Dr. Jessica Rose returns for a timely conversation on viral surveillance, outbreak narratives, emerging pathogens, and the growing cycle of global pandemic fear messaging. Tuesday • 7 PM ET LIVE on Rumble & X -- rumble.com/v7a8ngy-vsrf-l… @stkirsch @JesslovesMJK

‼️SHOCKING. But true. This is how child death-by-vaccine is hidden.

“If any Fortune 500 company manipulated their statistics like the VAERS, all the officers of the company would be in prison!”

He is right. See: stevekirsch.substack.com/p/new-website-… for the details.