Like most people that become ex-vaxxers, Lauren was once pro-vax and readily complied with the recommended vaccine schedule. And like so many others, she learned the hard way that vaccines quite often induce the symptoms or illnesses that they claim to prevent, and can have detrimental effects on long-term health. She also speaks to a point that people often forget - we are all very unique individuals and not every…

Channel
Australian Vaccination-risks Network
@avninformedchoice
On this record: Also posting the same content · Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
6,354subscribers
-32 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
Register entry
| Telegram ID | -1001410894772 |
|---|---|
| Type | Channel |
| Username | @avninformedchoice |
| Created | 3 September 2020 — measured — cross-checked against a third-party dataset (ext.tg_channel) |
| First recorded | 6 August 2026 |
| Last confirmed live | 16 August 2026 |
| Measurements held | 5 |
| Confirmed unchanged | 1 time, most recently 16 August 2026 |
| On Telegram | t.me/avninformedchoice |
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 1 other registered channel, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 16 Aug 2026, 08:23 | 6,354 | -14 |
| 12 Aug 2026, 12:24 | 6,368 | -8 |
| 9 Aug 2026, 19:21 | 6,376 | -10 |
| 6 Aug 2026, 10:30 | 6,386 | no change |
| 6 Aug 2026, 09:51 | 6,386 | first reading |
Engagement
21 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 9 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 10.2%
- avg views ÷ 6,354 subscribers
- Avg views / post
- 651
- 10 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 10
- of 21 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.
| Window | Rolling 30 days · latest post in window 7 August 2026 |
|---|---|
| Posts held | 21 (3 July 2026 – 7 August 2026) |
| Views total | 6,510 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Aug 2026, 03:13 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
- 10m 52s
- Average length
- 1m 05s
Measured directly from 10 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.
Recent posts
https://youtu.be/k4rujVps4MQ?si=wuCe68higWwFHEPU
Photo, posted without a caption
Photo, posted without a caption
Photo, posted without a caption
Can we please just stop with the “Autism is genetic” argument. It’s a cop out, and it’s only half the story. 🎥 Watch Dr Judy Wilyman’s full presentation at The Vaccination Conversation: https://rumble.com/v7bigio-mandatory-vaccination-a-crime-against-humanity-dr-judy-wilyman-at-the-vacci.html
⚡️In Australia, you're more likely to get struck by lightning than die from meningitis, meningococcal or pneumococcal disease. Next thing you know they'll be developing a vaccine for lightning strikes 😆 Not only are they pushing vaccines for diseases that carry virtually no serious risk — those vaccines have been tested for less than 6 months with no placebo control. Not exactly the gold standard of science. And t…
💉 HOW & WHY IS ALUMINIUM USED IN HEALTHCARE? Most people have never heard the word "adjuvant." But it's in almost every vaccine a child will receive from birth. An adjuvant is a substance added to vaccines to amplify the immune response. Without it, many vaccines wouldn't produce enough antibody response to be considered 'effective'. The adjuvant is, in a sense, the engine of the vaccine. The most widely used adj…
“The COVID vaccine saved between 3 and 20 million lives." That claim has been debunked repeatedly — it was based on modelling built on assumptions that were simply not true. They assumed the vaccine was highly effective at preventing transmission. They assumed it prevented serious adverse effects. None of those assumptions held up. And when the evidence doesn't support their position, they don't acknowledge that. …
https://www.instagram.com/reel/Da8EcSexOkD/?igsh=dnd0cGNrNHB2anZi
When the science doesn't hold up, they don't bring better evidence (because they don’t have any) — they bring social pressure. If the claims they make about vaccines were actually true, the data would speak for itself and they wouldn't need to tell you what to think — that's not science. That's doctrine enforcement. And what do they do when they have no real evidence to back them up? The classic cult tactics of de…
One of the most common arguments we get from pro-vaxxers is that vaccines eradicated polio... when in reality, it just got rebranded. As "polio" numbers appeared to drop after the vaccine was rolled out, similar diagnoses like Guillain-Barré syndrome, acute flaccid paralysis, and aseptic meningitis quietly rose and were largely ignored. Remember when the flu seemed to disappear off the face of the earth with the ri…
Showing the 12 most recent of 21 posts we hold for @avninformedchoice. 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.
Citation-graph rank
Citation-graph rank — 333,133 of 1,481,306entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
@vaccinationdecisionsDrJudy · 2,4745 postsNSW HCWs United
@NSWHCWsUnited · 5822 postsChildren's Health Defense Australia
@AustraliansforCHD · 3,2391 postFriends of Truth
@friendsoftruth · 1,4661 postNoosa Freedom Gatherings
@NoosaFreedom · 1731 postTruth Seekers Collection
@truthseekerscollection · 631 post
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 1 registered channel — 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.
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.
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 16 August 2026 — this entry's latest reading, not the date you are reading this.
“Australian Vaccination-risks Network” (@avninformedchoice), 6,354 subscribers as measured 16 August 2026. Telegram Register, tgregister.com/channel/avninformedchoice.
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.