Please Learn Math - Conspiracies - Conspiracy Theories & Facts

Please Learn Math

posted 2 years ago by GnarlyToad 2 years ago by GnarlyToad +5 / -10

I continually see memes quoting statistics that claim to show the ineffectiveness of vaccines.

Anybody with even middle school level math competency should be able to see through the misrepresentation of these statistics.

A recent example stated that 85.7% of deaths over a particular week in Scotland were vaccinated people. The conclusion drawn was that the vaccines don't work because the vast majority of people dying were vaccinated.

What was left out in the post was that 94% of Scotland has received at least 1 dose and 74% has received 3 doses. That leaves only less than 6% of the population unvaxxed accounting for 12% of the deaths. This data suggests (suggests, doesn't prove anything), just the opposite of the conclusion drawn.

Misuse of statistics makes people look either stupid or dishonest. If you see something posted like this, you should immediately question your source. Anybody passing off this kind of stuff isn't vetting their sources or their numbers either through actual intent to mislead or sheer stupidity. Either way, the source cannot be trusted. Trusting such a source is just allowing yourself to be duped (which makes you a dupe) or a liar yourself.

Hold yourself to higher standards of integrity, please, everybody. It doesn't help anybody to lie about facts or pass on lies about facts.

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– GnarlyToad [S] 0 points 2 years ago +1 / -1

I am not an expert in sequencing techniques. Are you? Here's the thing: scientists publish studies in scientific journals that are peer reviewed. So if their sequencing techniques are flawed, they get called out. It's not a perfect system, but when there are experts reviewing sequencing techniques I'm going to trust them much more than someone on the internet who, for no stated reason, doesn't trust their sequencing techniques. I'd love to see you walk into a lab and say, "I don't trust your sequencing techniques." It's laughable.

You tell me: what's wrong with their sequencing techniques? They lay it all out there for anyone to replicate. Your experts could publish a study demonstrating that the sequencing techniques do not work.

Here is a description in that last study I cited:

SARS-CoV-2 positive samples were randomly selected and tested with primers targeting the E gene, which has been previously demonstrated in our reports to be the most sensitive target [10,11].

Is this a step in sequencing that you do not agree with? Why or why not?

Samples with Ct value [less than or equal to] 28 were chosen for further analyses.

What criticism of this step do you have?

Total nucleic acids were extracted from 500 [mu]L UTM-medium on the QIAsymphony SP using the QIAsymphony DSP Virus/Pathogen Midi Kit (Qiagen), following manufacturer's instructions.

Can you pinpoint for me what is wrong with this sequencing step?

High resolution melting was used for the qualitative detection of p.N501Y and p.E484K mutations in the SARS-CoV-2 genome.

How about these steps?

Briefly, extracted RNA was used as a template for the VirSNiP SARS B1351 assay on the LightCycler ® 480 Real-Time PCR System (Roche Diagnostics). Positive and negative control (NTC) were included in all experiments.

4 [mu]L Roche master mix, 0.5 [mu]L reagent mix (containing primers and probes), 5.5 [mu]L PCR-grade water and 10 [mu]L of template were mixed to a total volume of 20 [mu]L. Amplification was performed following manufacturer's instruction.

After normalization and temperature shift determination, the different melting curves were generated.

p.E484K is associated with a shift from 52°C to 57°C while p.N501Y is associated with a shift from 60°C to 65°C. LightCycler® 480 Software was used to analyze all data.

Samples were randomly selected from the 1508 specimens that underwent HRM screening. 479 barcoded libraries were prepared using the Ion AmpliSeq SARS-CoV-2 Research Panel (Thermo Fisher Scientific) and the Ion AmpliSeq Library Kit Plus (Thermo Fisher Scientific), following manufacturer's protocol.

The panel consists of 237 amplicons that allows for the sequencing of 99% of the SARS-CoV-2 reference genome (NC_045512.2), covering from position 43 to position 29,842. All the reactions were performed in a Veriti[TM]Dx 96-Well Thermal Cycler (Applied Biosystems[TM]). Libraries were quantified with the Qubit dsDNA HS Assay kit (Life Technologies) and then diluted to 30 pM. Libraries were loaded into the Ion Chef[TM] Instrument (Thermo Fisher Scientific) for template enrichment and chip loading. Sequencing was performed with the Ion S5 GeneStudio Sequencer using the Ion 510 & Ion 520 & Ion 530 Kit-Chef and the Ion 530[TM] chip-kit (all Thermo Fisher Scientific).

After alignment, the following plugins were run on the Torrent Suite[TM] Server (Thermo Fisher Scientific): the SARS_CoV_2_variant caller, the SARS_CoV_2_CoverageAnalysis, the SARS_CoV_2_annotateSnpEff and the generateConsensus. Sequences kept for further investigations were the ones possessing a mean depth of coverage [greater than or equal to] 500 and a percentage of gaps [less than or equal to] 20% of the entire sequence. For variant calling, variants with a genotype quality (GQ) score [greater than or equal to] 30, a coverage (FDP) [greater than or equal to] 500 and a minimum alternate allele frequency of 70% (AF [greater than or equal to] 70%) were kept for further investigations.

Clade and lineages of 479 specimens were defined with the Nextclade v2.29.1 web application (https://clades.nextstrain.org/), the GISAID CoVsurver mutation App (https://www.gisaid.org/epiflu-applications/covsurver-mutations-app/), the pangolin web app developed by the Centre for Genomic Pathogen Surveillance-version v.3.1.11 - (https://pangolin.cog-uk.io/) and the Ultrafast Sample placement on Existing tRee (UShER) web tool by UCSC (https://hgwdev-angie.gi.ucsc.edu/cgi-bin/hgPhyloPlace). SNPs and INDELs frequencies were evaluated in the CovidMiner data portal (https://covid-miner.ifo.gov.it/app/home) and in the GISAID database (https://www.gisaid.org/).

FASTA sequences have been uploaded in the GISAID database. S2 Table enlists Accession IDs and virus names.

FASTA sequences were aligned with ClustalW. The Maximum Likelihood (Tamura-Nei method) method was used to generate a phylogenetic tree of the 479 sequences. Alignment and tree were computed with Molecular Evolutionary Genetics Analysis (MEGA) v.11.

What part(s) do you determine are flawed and untrustworthy? Do you have some suggestions to improve their sequencing methods?

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– KiloRomeo 1 point 2 years ago +1 / -0

What's the reliability of this? The PCR sequencing techniques multiply false positives. There's also needs to be a random sample in order to be valid. I find it hard to believe that we know the variant with reliability. I think the idea of variant is just random mutation and they've fit the data to it. For example, more vulnerable population getting sick first so this must be a different variant even though the sampling was insufficient to determine such.

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– GnarlyToad [S] 0 points 2 years ago +1 / -1

What's the reliability of this? The PCR sequencing techniques multiply false positives. There's also needs to be a random sample in order to be valid.

You should write a letter to the New England Journal of Medicine with your suggestions.

If you're really interested, you could look up this: Mio C, Cifù A, Marzinotto S, Marcon B, Pipan C, Damante G, et al. Validation of a One-Step Reverse Transcription-Droplet Digital PCR (RT-ddPCR) Approach to Detect and Quantify SARS-CoV-2 RNA in Nasopharyngeal Swabs. Disease Markers. 2021;2021: e8890221. doi: 10.1155/2021/8890221

or this: 10. Mio C, Cifù A, Marzinotto S, Bergamin N, Caldana C, Cattarossi S, et al. A Streamlined Approach to Rapidly Detect SARS-CoV-2 Infection Avoiding RNA Extraction: Workflow Validation. Dis Markers. 2020;2020. doi: 10.1155/2020/8869424

or this: 13. Washington NL, Gangavarapu K, Zeller M, Bolze A, Cirulli ET, Barrett KMS, et al. Genomic epidemiology identifies emergence and rapid transmission of SARS-CoV-2 B.1.1.7 in the United States. medRxiv. 2021 [cited 11 Apr 2021]. doi: 10.1101/2021.02.06.21251159

or this: 14. Lo Menzo S, Marinello S, Biasin M, Terregino C, Franchin E, Crisanti A, et al. The first familial cluster of the B.1.1.7 variant of SARS-CoV-2 in the northeast of Italy. Infection. 2021; 1-5. doi: 10.1007/s15010-021-01609-6

It's all cited in the study itself, because that's what science does.

I find it hard to believe that we know the variant with reliability

You're just naysaying the science. And that was just one study and there have been literally hundreds of studies.

I think the idea of variant is just random mutation and they've fit the data to it.

You're looking for ways out to protect your cherished and firmly held dogma.

For example, more vulnerable population getting sick first so this must be a different variant even though the sampling was insufficient to determine such.

Was it insufficient though? What makes you think so? To think they can't fully sequence this virus is another ridiculous position.

Where are your studies?

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