Other / unclassifiable — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 12 September 2026 and assigned it the closest of 31 fixed categories, at 84% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
14 measurements spanning 44 days, net -21. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 7,874–7,901 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
19 Sept 2026, 01:55
7,877
-4
14 Sept 2026, 07:37
7,881
+2
10 Sept 2026, 18:14
7,879
-10
5 Sept 2026, 08:15
7,889
-1
1 Sept 2026, 10:47
7,890
-4
29 Aug 2026, 08:35
7,894
+1
26 Aug 2026, 07:53
7,893
-2
23 Aug 2026, 10:57
7,895
-3
20 Aug 2026, 03:33
7,898
+16
16 Aug 2026, 19:54
7,882
-2
13 Aug 2026, 08:48
7,884
-11
10 Aug 2026, 04:35
7,895
-3
6 Aug 2026, 10:19
7,898
no change
6 Aug 2026, 09:59
7,898
first reading
Engagement
49 posts held, back to 3 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 19 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
12.2%
avg views ÷ 7,877 subscribers
Avg views / post
964
11 posts measured
Reaction rate
4.34%
reactions ÷ views · ER floor
Posts in window
11
of 49 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 28 August 2026
Posts held
49 (3 July 2026 – 28 August 2026)
Views total
10,601
Reactions total
460
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
28 Aug 2026, 20:00 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Video runtime
1h 18m
Average length
1m 37s
Measured directly from 49 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
3,164 reactions across 49 posts, in 23 distinct kinds. The most used accounts for 32.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
💯
1,018
32.2%
🤬
526
16.6%
🙏
354
11.2%
🔥
336
10.6%
👍
293
9.26%
😈
287
9.07%
👏
133
4.20%
❤
88
2.78%
😢
41
1.30%
🤔
13
0.411%
😨
12
0.379%
💔
11
0.348%
🖕
9
0.284%
⚡
7
0.221%
😱
7
0.221%
🤡
6
0.19%
🤮
5
0.158%
🏆
4
0.126%
🤣
4
0.126%
🤯
4
0.126%
3 further kinds
6
0.19%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 49 of the 49 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 3,164 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 49 most recent posts we hold, published 3 July 2026 to 28 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Bill Gates is now warning of imminent AI bioterror attacks... right after he funded the first-ever use of AI to create synthetic viruses capable of replicating.
He's “sounding the alarm” over the very capability his own foundation helped bring into existence.
Subscribe to http://t.me/TruthAboutCOVID
It's NOT just ticks... VACCINES are also driving the explosion of Alpha-Gal Syndrome.
Our study found that over 90% of children are injected with 54 mg of alpha-gal-bearing gelatin through MMR and chickenpox vaccines before they start school.
Subscribe to http://t.me/TruthAboutCOVID
BILL GATES WARNS OF AI BIOTERRORISM JUST WEEKS AFTER HE FUNDED THE FIRST-EVER CREATION OF 16 SYNTHETIC VIRUSES USING AI
BILL GATES: “AIs are now capable of causing BIOTERRORISM, and we need to monitor things like creating a dangerous virus to see if that’s happening.”
ALSO BILL GATES: Literally funded the FIRST-EVER creation of 16 synthetic viruses using AI, published in the journal Science.
Subscribe to http://t…
Former ABC News correspondent Terry Moran says Dr. Anthony Fauci shut down a story he was preparing on the COVID-19 lab-leak.
According to Moran, he was ready to go on air when he was suddenly told the story wasn’t happening. Why? Moran says his team had spoken with Fauci, and Fauci told them they couldn’t do the story.
“I was livid,” Moran recalled.
For years, Americans were told the lab-leak theory was misinforma…
Catherine Austin Fitts says MAHA has "proven beyond a shadow of a doubt" working with "the enemy" in the fed gov't is "hopeless"
"CDC just awarded $1.2 billion to Pfizer for Covid shots... to murder more children... They are depopulating the American people"
"We have watched the most unbelievable bipartisan commitment to poisoning the American people. It's unbelievable"
"and the process of people trying to get the…
Documentary evidence that the US government pandemic response led by now disgraced Dr Anthony Fauci knew about damage to the fetus from genetic COVID-19 vaccination. Dr Peter McCullough® and investigative journalist John Leake from 2021 to 2026 expose the chain of evidence. McCullough® warned against this from the very beginning.
Subscribe to http://t.me/TruthAboutCOVID
NIH Director Dr. Jay Bhattacharya shares truly DISTURBING statistics on myocarditis in young men after the COVID vaccine.
“Somewhere between 1 in 2,000 and 1 in 10,000 young men who got the COVID vaccine got myocarditis.”
“That’s too many.”
“Especially since the benefit from the vaccine for them was minuscule.”
Subscribe to http://t.me/TruthAboutCOVID
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AG Todd Blanche confirms DOJ received the Senate referral involving Dr. Fauci.
He says the matter is being handled as an “ongoing investigation.”
Now the question is what DOJ does next.
Subscribe to http://t.me/TruthAboutCOVID
“The World Health Organization” now states on its website:
“Vaccination against COVID-19 can trigger multiple sclerosis through cross-reactive CD4+-T cells that recognize the spike protein of SARS-CoV-2 and myelin peptides.”
In other words: Your own immune system destroys the nerve pathways and then attacks your brain and spinal cord.
This data was available during the lockdowns but was labeled as “conspiracy theo…
Is the MMR safer if it’s split into three separate vaccines? Not necessarily.
@ BrianHookerPhD: "I do not see these viruses really as a strong threat."
Hooker explains why he believes the risks of the individual vaccines still outweighs the benefits, even when the combination shot is separated.
The bigger message for parents: do your own research and make the decision for your own child.
Don’t blindly accept any …
Former NFL MVP Cam Newton confirms Aaron Rodgers was RIGHT: players, coaches, and even executives bought FAKE vax passes to dodge the NFL’s COVID rules.
“If we're being honest, going back to 2020, there were multiple players, coaches, and executives that fraudulently got their COVID shot. Yes, I said it.”
“I knew multiple people in that locker room didn't get the COVID shot. But they got a card that they paid for.”…
💯55👏9❤3🙏2🤮1
Showing the 12 most recent of 49 posts we hold for @TruthAboutCOVID. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 17 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
COVID VACCINE VICTIMS AND FAMILIES @covid19vaccinevictims · 38,415 Telegram ranks this channel #21 of 69 here — alongside 68 others — read 31 August 2026
Mikki Willis Official @OfficialPlandemic · 33,413 Telegram ranks this channel #22 of 85 here — alongside 84 others — read 4 September 2026
Dr David Martin @DrDavidMartin · 50,651 Telegram ranks this channel #32 of 82 here — alongside 81 others — read 25 August 2026
Dr Mike Yeadon @DrMikeYeadon · 27,285 Telegram ranks this channel #39 of 87 here — alongside 86 others — read 11 September 2026
Covid BC (Excess Deaths) @covidbc · 31,420 Telegram ranks this channel #52 of 64 here — alongside 63 others — read 6 September 2026
Lara Logan @NoAgendaLara · 26,102 Telegram ranks this channel #70 of 84 here — alongside 83 others — read 13 September 2026
This channel appears in 6 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 19 September 2026 — this
entry's latest reading, not the date you are reading this.
“TruthAboutCOVID” (@TruthAboutCOVID), 7,877 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/TruthAboutCOVID.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.