Captain Alan Dana is a highly experienced pilot with over 35 years of flying, now exceeding 23,000 flight hours. He holds the British, USA and Australian professional airline transport licenses, including an FAA Accident Prevention Counsellor Designation.

So when his employer, QUANTAS, suggested that he and his colleagues take a novel injection, this went against his core principle of bodily autonomy. When he refused, QUANTAS fired him. Now he, and other flight crew, are taking QUANTAS to court.

Movies released immediately prior to the pandemic gave us a preview of what was to come. A subliminal message.

If we assume that these movies were created by the engineers of the pandemic, then the content of the movies show a intriguing aspect of the psychology of those engineers.

The content is symbolic. For example Bill Gates movie "Pandemic", about the global introduction of a vaccine to cure an influenza outbreak, had 6 episodes and all were released on Jan 22nd 2020. The symbolic significance of 22 is that is represents the last letter of the Hebrew alphabet - TAU - signifying the End.

Aleph and Tau, Alpha and Omega, the beginning and the end.

Such content suggests that the engineers hold to a symbolic and spiritual view, and suggests that they are acting out a role , either consciously or un-consciously, as bringers of Judgement - bringing to conclusion an era - a world age.

In other words, they are not just acting as money-makers, or even as utilitarian depopulators or power-hungry elitists. They appear to be acting from a spiritual perspective in a symbolic role as judge and executioner.

As weird as this sounds, its as if they are different - performing a role so different from the ordinary human role - that it more closely resembles that of the priests and judges of the Old Testament.

Perhaps that's why their media content is like parable - with hidden meanings. Speaking on 2 levels.

Why does the Bible speak in parables? So that those with ears to hear and eyes to see can hear the hidden meaning and be saved. In other words, parables were a way of relaying information, the knowledge of which would lead to salvation - holding out a way of escape.

Others have noticed this same phenomenon at work in literature - somehow works preview and warn us - helping us to prepare - guiding us to a different path. It seems that only those without ears to hear end up perishing.

The phenomenon I am proposing here is that of a form of subliminal messaging. The physical message is just the surface. The hidden message consists of key words, phrases and themes planted into the stream of our perception - speaking to us - encouraging us - warning us - sometimes pointing to a future event.

The purpose of such messages appears to be to select based on awareness/perception - just as it was with the parables - and in so doing to warn us so that we might escape the destruction. Its the art of reading the signs.

I dont argue that this selection by awareness is justified, only that awareness appears to be the operating criteria.

Darwin proposed a law operating in nature - "survival of the fittest" - based on aggression, dominance of one individual over another. In contrast, here we see a different selection process - "survival of the wisest" - based on awareness and personal responsibility for decisions.

In this report, I look at the persistence of adverse reactions to COVID vaccines. Government and mass media narratives state that adverse effects are transient and short lived.

However, the Israeli Government commissioned an investigation of vaccine adverse effects following the introduction of a new vaccine reporting system in Israel. The results of this investigation were reported to the Israeli Government, who proceeded to cover up the findings, however the a video of the results was leaked by the researchers themselves.

They found that in 50% of the reported cases the adverse reactions persisted for more than 6 months.

They also found that there was a strong causal relationship between the vaccines and these adverse reactions - proven by a technique called "re-challenge". Rechallenge means that with each new dose there was a resurgence of the adverse reactions - i.e. when re-exposed ("rechallenged") to the same toxic stimulus, the same toxic reactions reemerged. This is the strongest possible proof that the vaccines are causally related to the subsequent reactions.

Prompted by the Israeli findings, I decided to reexamine VAERS in order to assess the degree of persistence of adverse reactions. Like many others, I had previously assumed that most of the adverse reactions were short lived.

So I decided to investigate.

Taking just the month of January 2021, I identified 44,046 reports where adverse reactions had begun in January 2021.

Next, I wanted to find out how long these reactions had persisted.

Each report has a REPORT DATE. Reports were submitted throughout 2021 for injuries that began in January. And each of these reports stated whether the person had recovered or not.

The results are contained in a table which I have published on the website at -

I found that 3553 reports submitted from June to December of 2021 were for injuries that began in January, but were still NOT RECOVERED.

In terms of percentages, if 44,046 people had an adverse reaction that began in January 2021, but 3553 people were still not recovered after 6 months, that's 8% or 1 in 12 not recovered.

Of course, I only looked at data up until December 2021. If I look at 2022 data, I will most likely find that there are reports of people injured in January 2021 who are STILL not recovered, even to this day. And this will obviously raise the percentage above 8%.

Its worth remembering that ANY adverse reaction that persists for months, even if it is as small as a headache, inflammation or pain, if it persists this long then it will be debilitating, and it will have a significant impact upon the quality of life.

Long term adverse reactions may be thought of as disabilities, since they reduce ones capacity in every arena of life - work, study, social, sport - everything.

Disability IS a permanent (long-term) adverse reaction. Previously I had looked at the frequency of disability following COVID vaccinations - see

I suppose we should not be surprised that something that causes death or permanent disability in many, will also cause long-term adverse reactions in others. In fact, if we all share a broadly similar physiology, then this would be expected.

Ivermectin has an excellent safety profile that has been established over decades, and is very effective in the treatment of COVID.

In contrast, the new bivalent booster being rolled out in September 2022 has been tested on only 8 mice over a period of a few weeks, and all the mice still got infected with COVID.

So why are they doing this?

As Edward Dowd states - the only reason they are restricting access to a cheap, safe and effective medicine, and instead pushing a dangerous and experimental one with a VAERS track record of significant harm, is because -

"they want you to die - they want you to get sick"

This video updates the previous one. Here I look at cardiac events in general - including brachycardia, pericarditis, tachycardia, cardiac arrest, myocardial infarction etc - rather than just myocarditis. I also look at elevated troponin levels.

The frequency of these symptoms is plotted against age, and it is found that young people are far more at risk than people over 30 years of age.

A link for the pdf -

In this study, I downloaded the VAERS data for the whole of 2021, and counted the number of cases where myocarditis was mentioned as a symptom, and the age of each recipient.
There were a total of 1054 cases where the age of the recipient was provided.
Then I created a pivot table to count the number of cases of myocarditis for each age.

The graph shows an exponential decline of myocarditis with age for COVID 19 vaccine recipients. For every 12 years that passes, the risk of myocarditis falls by half.
This means that babies will have –
• 2 x the risk compared to 12 year-olds
• 4 x the risk compared to 24 year-olds
• 8 x the risk compared to 36 year-olds
• 16 x the risk compared to 48 year-olds
It was pointed out that I should take into account the different population sizes for each age group, since if a smaller population produced a high case rate of myocarditis, then this would greatly increase the calculated risk of myocarditis for that population. Since young people had only recently begun vaccination, I suspected that their population was less than older age groups who began vaccination earlier in the year. Consequently, I expected the risk of myocarditis to be even higher in the young than calculated above.

In order to compensate for population size effects, I divided the number of cases for each age group by the total number of records (all adverse reactions) for that age group in VAERS.

The resulting graph shows that the risk of myocarditis starts jumping up to a very high level as age decreases. A very rough approximation is that myocarditis is halved for every 8 years that age increases. But we will need to take a closer look in order to calculate the incidence of myocarditis in babies.

Calculating the Incidence of Myocarditis for Babies
The incidence of myocarditis for babies would be the incidence at year 0, so I would need to extrapolate the graph backwards to see where it cuts the y-axis. As you can see, the graph is shooting up quite rapidly as age decreases, so I decided to create a log graph instead to better estimate the point of intersection.

It looks as if the point of intersection is at 10 3.1217 = 1323. This means that the estimated rate of myocarditis in babies following COVID-19 vaccination is 1323 cases per 100,000 = 7.43 times the rate for 15 year-olds (which was 178 cases per 100,000).
Of course, VAERS is under-reporting by an order of magnitude, but this calculation tells us that babies will get myocarditis 7.43 x more than adolescents.

The Thailand Study
The Thailand myocarditis study (Cardiovascular Effects of the BNT162b2 mRNA COVID-19 Vaccine in Adolescents[v1] | Preprints) found 7 cases of myocarditis in 301 adolescent subjects – a rate of 1 in 43 or 2.3%. Therefore, the incidence of myocarditis in babies will be 7.43 x this = 17%. So 1 in 6 babies exposed to the COVID-19 vaccine will get myocarditis.

You can find my full report at or at


I have created an updated report here -

The updated report looks at the frequency of cardiac events in general, and also looks at the frequency of elevated troponin for different age groups following Covid 19 gene therapy ("vaccination")

Funeral directors, coroners, doctors and nurses are aware of a 500-600% increase in thrombosis amongst the vaccinated.

Many chose to keep quiet in order to keep their jobs - just following orders.

Even in those who show no sign of vaccine injury, micro-clotting in the capillaries has been found to occur in 52% of those vaccinated with mRNA Covid vaccines.

This results in reduction of blood flow to cells. Whilst this may not lead to major organ failure, it will lead to cell death and impaired functioning - a general fall in the level of health.

The mechanism of these clotting effects has been described here -
and here
and here
and here

It is important to point out though that in addition to blood clotting there may be an additional mechanism at work in the vaccinated that restricts blood flow. I refer to the progressive growth and formation of an elastic stringy material - which has been found by coroners in the blood vessels of covid vaccinated.

See here -

If this is the case, then the mRNA in the vaccines may not simply code for the spike protein. It may also cause cells to produce this elastic material which gathers together to form strings, resulting in loss of blood to the extremities.

In effect, the mRNA may program for a clot whose rate of manifestation is determined by the rate at which cells can manufacture the clotting material. This would produce a delayed clotting effect - which should be apparent as an increasing probability of clotting over time.

I wanted to preserve this video in case it's deleted by censors. Pharma was well aware of these adverse reactions from as early as January 2021, but did not release this study to the public until 17 months later. During that time governments did not warn the public and allowed the vaccine rollout to continue - repeating the mantra that they were "safe and effective".

This interview shows how real these adverse effects are. It also shows how long lasting the effects are. They can be temporarily suppressed by immune system suppressants like corticosteroids, but symptoms return once treatment ends.

Pharma declared that all subjects had full recovery, yet the subject in the video says that she is not recovered, and that she knows at least half of the subjects, and none of them are recovered.

In their conclusion, the study says that these neurological reactions are caused by an auto-immune attack upon nerve cells - I suppose that is why an immune system inhibitor like corticosteroids provided temporary relief.

When we look at the WHO database for adverse reactions to Covid vaccines - we find that neurological symptoms are the most prominent - records 1.5 million people suffering from nervous system disorders (and that's just for Pfizer's Comirnaty brand)

If these adverse reactions are under reported by a factor of 40 (a figure established by otherstudies), we might expect the real figure to be closer to 60 million for Comirnaty alone.

In this project I counted the frequency of occurrence of each of the 64 codons in Human Chromosome 8 and arranged these 64 frequencies in the form of a 4 x 4 x 4 cube. The arrangement was not contrived, but determined solely by the arrangement of the standard genetic code table.

I then summed the frequencies for the codons belonging to each face of the cube - left and right, top and bottom, front and back.

The result was a Rubik Cube!

The sum of opposite faces was always the same !

The pdf can be downloaded here -

Symptoms associated with immediate and delayed deaths following injection
with COVID-19 gene therapies.

I demonstrate that the most frequent cause of immediate deaths following vaccination is cardiac arrest.

The most frequent cause of delayed deaths (> 2 weeks after vaccination) is COVID 19.

The irony is that COVID 19 remains the dominant cause of death amongst the vaccinated for every week after weeks 1 and 2.

This suggests that the vaccine is failing to protect people from COVID 19. Why else would the main cause of death amongst the vaccinated be COVID 19?

NB. I am just saying what the data says. It says that the vaccinated die mostly from COVID 19

But what if COVID 19 does Not Exist or what if it is just like a mild flu?

I am not saying that people died because COVID 19 is dangerous, but rather because the vaccine makes people more susceptible to even a common cold. In other words, they become susceptible to everything. This is evidenced by the fact that viruses previously kept in check by the immune system suddenly proliferate after vaccination, e.g. Herpes. provides a list of infections that increase after COVID 19 injections -

COVID-19 (156459)
Influenza (39200)
Herpes zoster (32960)
Nasopharyngitis (22487)
Pneumonia (8657)
COVID-19 pneumonia (6717)
Oral herpes (6007)
Suspected COVID-19 (5749)
Urinary tract infection (4500)
Cellulitis (4409)
Vaccine breakthrough infection (3718)
Asymptomatic COVID-19 (3583)
Infection (3492)
Sinusitis (3471)
Rhinitis (3033)
Sepsis (2439)
Appendicitis (1942)
Lower respiratory tract infection (1754)
Conjunctivitis (1697)
Bronchitis (1660)
Ophthalmic herpes zoster (1463)
Ear infection (1419)
Cystitis (1350)
Vestibular neuronitis (1306)
Sweating fever (1226)
Herpes simplex (1218)
Tonsillitis (1101)
Herpes virus infection (1059)
Erysipelas (1052)
Pharyngitis (996)
Dysentery (946)
Viral infection (943)
Encephalitis (909)
Mastitis (896)
Genital herpes (854)
Diverticulitis (845)
Myelitis (783)
Labyrinthitis (739)
Septic shock (730)
Abscess (718)
Gastroenteritis (685)
Upper respiratory tract infection (657)
Pustule (649)
Post-acute COVID-19 syndrome (612)
Laryngitis (583)
Pneumonia aspiration (569)
Injection site cellulitis (565)
Post viral fatigue syndrome (539)
Rash pustular (504)
Localised infection (493)

Notice that, at the top of the list, we have COVID 19, Influenza, Herpes , Pneumonia.

(There is also listed 909 cases of encephalitis (mad cow disease) !)

Pfizers own study, published released on Feb 28th 2021 stated that within the first 90 days of vaccine deployment the Pfizer company received 8000 reports of Herpes outbreak in the vaccinated.

I have published documents and research here -

The vaccines have a delayed effect. Analysis by state shows massive increase in mortality in 7 states in the third quarter of 2021 (Q3). I demonstrate that this is due to the vaccines deployed in Q1 and Q2. So the vaccines act like a bomb with a 100 day fuse. Pharma tested this delayed effect in 7 states only - all in the south east of the USA, and they tested it on working age adults - not on the aged.

For more information please visit -

Since creating this video several prominent researchers have confirmed that a 5 month delayed death effect does exist. Please see - where you can find a list of this research on the home page.

The numbers vaccinated follows a 7 day cycle each week - with a minimum number of vaccines being given on a Sunday, progressively more vaccines being administered on Monday, Tuesday and Wednesday, reaching a maximum on Thursday, then declining on Friday and Saturday down to a Sunday minimum.

This pattern is repeated every week.

I was curious to see if the number of deaths resulting from the vaccines followed a similar pattern.

So I counted the number of deaths associated with vaccines given on each day of the week. To do this I looked at each vaccination date and counted the total number of reports for that date which ended in a fatality.

I found that the number of deaths correlated very strongly with the number vaccinated on a particular day. The correlation was 0.99 with a probability of 0.046.

So, every week, as the number vaccinated rose and fell in a 7 day cycle, the number of deaths also rose and fell in a 7 day cycle, and this pattern persisted throughout the whole of 2021.

Perhaps we should ask a question -

"If the vaccine is meant to reduce mortality and protect our health, then why do deaths rise as the number of vaccinated rises, and fall as the number of vaccinated falls, in a weekly cycle that repeats over and over again?"

Belgium exhibits extremely high % of severe adverse reactions compared to the other European countries.

The hypothesis being put forward here is that Belgium is the site for the finishing plant for all European vaccines, so the people of Belgium receive the vaccine batches first after manufacture.

The mRNA in the vaccines seems to degrade quickly over the first 30 days, and there is a corresponding decrease in toxicity over that period. The % of reports that are severe is three times higher for vaccine deployed within that 30 day window.

So, in consequence, the people of Belgium are receiving the vaccines first, possibly even within the 30 day window, and suffering the consequences.

This is one of those instances where its good to be last - or at least as far past the expiry date as is possible.

For each Pfizer lot I counted the number of deaths, disabilities and life threatening illnesses. I summed these counts to get a total severity -

Total severe = deaths + disabilities + Life Threatening Illnesses

Then I calculated the % of reports for each lot that were severe

% Severe = Total severe/Total number of adverse reaction reports

I reasoned that if a lot was more toxic, then a greater % of its reports would result in death, disability or life threatening illness. Conversely. if a lot was more harmless, it would result in a significantly smaller number of deaths, disabilities and life threatening illnesses. This seems like common sense.

The results were interesting.

Pfizer lots vary in % severity by 40 fold.

They also vary alphabetically. As the alphabetic identifier of the batch code ascends, the % severity decreases.

It is also observable that the pattern of variation between the alphabetic groups for Pfizer is very similar to the pattern found between the alphabetic groups for Moderna.

Extraordinarily, they even embody a similar coding system.

The following analysis uses lot numbers that are validated by the CDC - these are 339 lots with expiry dates published on the CDC expiry list. As such, the lots do not contain any spelling mistakes.

See -

We find 5-12 times higher variability between C19 lots compared to flu vaccine lots

Flu Vaccines - Average is 7 severe adverse reactions per lot
C19 Vaccines - Average is 340 severe adverse reactions per lot

Minimum number of severe adverse reactions = 1
Maximum number of severe adverse reactions = 24

Minimum number of severe adverse reactions = 1
Maximum number of severe adverse reactions = 1544

All pharmaceutical products are subject to the same regulatory requirements for manufacturing quality control. EUA and novelty of the tech is no excuse for killing thousands of people.

We have the exact lot sizes for 33 Pfizer lots, and have correlated these with the number of adverse reports for those lots in VAERS.

Two strong correlations emerge -
11 out of 33 of the lots were deployed in the USA
USA lots - correlation between lot size and number of adverse reactions = 0.86

22 out of 33 of the lots were deployed in other countries
Foreign lots - correlation between lot sizes and number of adverse reactions = 0.7

The USA lots appear to be a much more poisonous product - as evidenced by the higher number of adverse reaction reports when compared to same size lots for the foreign lots. Also, as lot size increases for USA lots, the number of adverse reactions increases with a steeper gradient compared to foreign lots.

This phenomenon also manifests in the difference between numbers of deaths and disabilities for US vs foreign batches. In the US, batches produce more death, whilst in foreign countries batches produce more disability. See

We have an extremely strong correlation between number vaccinated in each US state, and deaths in each state following vaccination. The more doses you give, the more deaths you get. This is strong evidence of a causal relationship.


We have an extremely strong correlation between number vaccinated in each US state, and disabilities in each state following vaccination. The more doses you give, the more disabilities you get. This is strong evidence of a causal relationship.


When deaths were correlated with numbers vaccinated for all states, the result was a strong correlation forming a straight line. However there were 5 outlier states showing much higher deaths than expected for the numbers vaccinated - these were Kentucky, Tennessee, Minnesota, Michigan and Georgia. Kentucky had 6 x the expected number of deaths.

When we measure the toxicity of a snake venom, we do so by the number of severe reactions following a bite as a percentage of the total number of people bitten.

So if 100 people were bitten by a snake, and 90% died, we would say that the snake venom was very toxic. However if only a 10% died, we would say it was less toxic.

Pharma use the same method to determine a lethal dose - if it kills over 50% of the recipients then that is the LD50 level for a drug.

So the measure we are using is the % of adverse reaction reports that were severe.
A severe reaction is one that results in death, disability or life threatening illness - and is identified in the VAERS database by having a Y in one or more of those columns.

Measure of Toxicity

= Percentage of adverse reaction reports that are severe

= (deaths + disabilities + life threatening illnesses)/total number of adverse reaction reports


I looked at all the Moderna lots generating over 100 adverse reaction reports for USA 2021.

I found that the lots varies in toxicity by from 0.4 % to 15% - in other words by 30 fold.

Moderna lots have alphabetic lot numbers and can be gathered together into alphabet groups - each group characterised by a different letter of the alphabet. When I did this, I found that the toxicity of the groups decreased as the alphabet ascended.

If you are interested to read more, I have published additional material at and also at

My current project is to update all the charts on the website to include a "lethality" rating based on the above measure.

Craig Paardekooper

I was asked to analyse differences in adverse reactions for each state in the USA. So I looked at deaths following vaccination.

I looked at all COVID 19 vaccines together, and filtered the results so I had only the adverse reactions resulting in death.

Then I used a pivot table to count the number of deaths for each state.

Then I obtained the number vaccinated in each state as of 14th January 2022. This gave me the number of deaths per 100,000 vaccinated.

All the red states clustered at the top with up to 19 x the number of deaths per 100,000 vaccinated.

I invite you to see the results yourself at

When I looked at disability, the pattern was reversed with blue states being at the top.

On the page I have looked at the effect of age of recipients.

Please also look at

Many people have wanted to see if they can replicate my figures as displayed on In order to clearly outline the steps I take, I have created a video .

I wanted to see if there was any temporal relationship between the date of vaccination and the date of death. The government and media assert that people are just dying of old age or comorbidities that have nothing to do with the vaccine.

If the vaccination had nothing to do with their deaths, then there should be no relationship between the date of vaccination and the subsequent date of death. The dates of death should NOT cluster around the date of vaccination.

So I did the following
1. I downloaded the VAERS database for the USA for 2021, and
2. filtered the table so I just had COVID 19 vaccines. Then
3. I filtered it just for records where people had died. Then
4. I subtracted the date of vaccination from the date of death to get the difference in days
6. I plotted a histogram of the days between death and vaccination

Death was found to cluster very strongly around the date of vaccination, with 12% dying in the first 2 days, and 18% in the first 4 days and 22% in the first 6 days.

When I carried out a similar study in February 2021 with 456 deaths, the % dying in the first two days was much higher - it was 27.8% in the first day. I surmise from this that pharma are endeavouring to reduce the speed of death, since it would be too noticeable - especially amongst the young.

For future research, I intend to measure the speed of death for each vaccine lot, in order to determine if some lots are more potent than others. The analogy is a snake bite. The toxin of a more poisonous snake is faster acting and might kill you in hours rather than days.

I look at data from -
1. Vigiaccess
2. Vaers
3. Eudraviligance
4. Pfizer's own reports

and demonstrate that the covid vaccines of Pfizer, Moderna, and Astrazeneca cause 2 - 3 times the number of injuries in women compared o men.

This is a huge safety signal, showing that the vaccines are not consistent in their effects upon different groups of the population. One group (women) suffer 3 times more adverse effects than another group (men).

The vaccine was only granted EUA on the basis that its effects would be consistent. This gender disparity negates its EUA authorisation.

Has the government acknowledged this safety signal? No
Has the government carried out an investigation? No
Has the government suspended the roll out until this issue is resolved? No

It is therefore apparent that the government is ignoring the safety signals.

If the governments intention is to ignore safety signals, then their intention is not to protect you from harm. However, it is the government that is actually pushing the thing that is causing the harm. My conclusion is that they are causing harm intentionally.

Once we establish that they are intending harm, then it is natural to ask WHY, what is the purpose?
Why are the vaccines targeting the female gender? I would suggest that this has something to do with reducing reproduction.

Pfizer produced 33 batches of vaccine between July and November of 2020. However, the regulators wrote to Pfizer informing them that they were not GMP compliant in 117 different ways.

Despite these batches being non-compliant, they were shipped anyway within a week, and resulted in over 1000 deaths.

The batches are from Pfizer's EJ, EK, and EL series.

Under emergency use authorisation, GMP compliance must still be upheld.
The extreme variation in toxicity between batches of equal size is evidence of the breakdown of manufacturing compliance which resulted in high levels of death and disability.

Part 1 - Getting your data
1. Download main table and batches table from VAERS website
2. Import batches table into same workbook as main table
3. Make sure both tables are in Table format, and named simply
4. Use vLookup() function to copy batch/lot numbers from batch table to main table
5. Use vLookup() function to copy vaccine names from batch table to main table
6. Save the main table with the columns that you have added.

Part 2 - Filtering the data
7. Use the dropdown filter to select a particular manufacturer in the vaccine name column
8. Use the dropdown filter to select a particular date range in the vaccine date column
9. Select columns for Lot Number, Died, L-Threat and Disability . Copy these using Control C
10. Paste into a new worksheet

Part 3 Counting your data
11. Create a pivot table to count the number of adverse reactions for each batch
12. Copy and paste the rows of the pivot table to a new worksheet
13. Name and order the columns


Each range of toxicity (indexed by levels of adverse reactions) has a distinct alpha numeric batch code. As the alphabet ascends, the toxicity appears to decrease in a linear step-wise fashion.

Was Pfizer testing out different concentrations of vaccine - and labelling each dosage level with a particular code? Scientists normally label each experimental condition carefully, so they can record and monitor the effects of that condition. Is that what is happening here?

Certainly, the batch codes within a particular toxicity range are not random between one range and another, but seem to ascend alphabetically as the toxicity falls.

And within each range, all the batch codes form a sequential mathematical series !

It appears that the adverse reactions may not be so much the product of the ill health of the vaccine recipients, but rather may simply be dependent upon the particular batch code series administered.

Seeing that there is such a wide variation in the number of adverse reactions, number of deaths and number of disabilities associated with different batches, it made sense to create an app/ website where people could look up a batch code and see if that batch was on record for causing problems.

The website is available here -

How Bad is My Batch is quite simple to use, and is recommended for doctors and nurses - so they can see if a batch is bad before administering it.

For the same reason, it is recommended for parents and teachers - who are responsible for the welfare of the children. Parents and teachers can check the historical records for the safety of a particular batch here -

If you would like to host this app on your own website, then you can download the source code as a compressed file directly from the website.

It is hoped that this app will raise awareness of the variability between batches, and also help people to make a more informed decision as to whether they want vaccine from any particular batch - based upon the number of deaths, disabilities and life threatening illnesses associated with that batch historically.


Created 1 year, 7 months ago.

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