/Summary_of_knowledge_gaps_related_to_quality_and_efficacy_of_current_influenza_vaccines and 5g, Depopulation tactics of the EUgenicist Platonists.

 

https://www.gov.uk/government/statistics/annual-flu-reports

Surveillance of influenza and other respiratory viruses in the UK Winter 2018 to 2019

Influenza vaccine (LAIV) programme for children England The Immform survey was used to monitor influenza vaccine uptake in 2 and 3 olds in primary care in England. The cumulative uptake for all GP-registered 2 year olds up to 28 February 2019 was 43.8% (compared to 43.3% in 2017 to 2018) and was 45.9% in 3 year olds (compared to 44.7% in 2017 to 2018) in England. This was reported from 96.2% of GP practices in England. The combined uptake for 2 and 3 year olds was 44.9% compared to 44.0% in 2017 to 2018. The seasonal influenza vaccine programme for children school year reception, 1,2, 3, 4 and 5 (4 years rising to 10 years of age) was mainly delivered via a school-based programme, although 1 area delivered vaccinations through general practice. Vaccine uptake was monitored through manual returns by local teams for their responsible population. An estimated 2,461,563 children in school years’ reception, 1, 2, 3, 4 and 5 (4 years rising to 10 years of age) in England received at least 1 dose of influenza vaccine during the period 1 September 2018 to 31 January 2019. With an estimated total target population of 4,051,698; the overall uptake was 60.8%. Total uptake in children in reception and school years 1, 2, 3, 4 and 5 was 64.3%, 63.6%, 61.5%, 60.4%, 58.3% and 56.5%, respectively. Uptake by local NHS England Team ranged from 49.4% to 68.9% in London and the Hampshire, Isle of Wight and Thames Valley team, respectively (Table 4). Overall uptake for children in school years’ reception, 1, 2, 3, 4 and 5 age combined by LA (not shown here) ranged from 30.1% (6,138/20,399) in Tower Hamlets to 80.6% (17,174/21,309) in East Riding. Uptake by year group by LA ranged from 32.2% to 89.1% in reception, 34.2% to 82.3% in year 1, 31.4% to 80.3% in year 2, 31.3% to 80.7% in year 3, 26.3% to 78.3% in year 4 and 24.9% to 77.3% in year 5. A more detailed PHE report on influenza vaccine uptake in England in primary school age children is publicly available 15 .

The 2018 to 2019 season also saw the continuation of the primary school-age vaccination programme in 5 pilot areas (11 Local Authorities) that have been piloting the programme since the 2013 to 2014 season (for pilot areas see Appendix A). Influenza vaccine was offered to all primary school age children aged 4-11 years (school years’ reception to year 6) through a school based delivery model. The extension to the pilot programme to include reception aged children (aged 4 rising to 5) was made in September 2017. An estimated 214,977 primary school children aged 4-11 years in 5 pilot areas received at least 1 dose of influenza vaccine during the period 1 September 2018 to 31 January 2019. With an estimated total target population of 343,280, this results in an overall uptake of 62.6% (ranging by pilot site from 44.6% in Leicester to 80.6% in Rutland) (Figure 29).

Paediatric mortality Fatal case reports from local health protection teams and the Office for National Statistics (ONS) were received for influenza-related deaths in children in England. Provisional data shows that during the 2018 to 2019 winter influenza season between 1 October 2018 and up to 18 April 2019, 13 influenza-related fatal cases were reported in children aged between 0 to 17 years. There were 7 female and 6 male cases. 12 of the 13 cases had influenza A infection (including 7 influenza A(H1N1)pdm09 and 5 influenza A(not subtyped)) and the remaining case had influenza infection (no type/subtype information available) recorded as part of their cause of death. Information available shows that underlying medical conditions were reported from 10 of the 13 cases. Information on influenza vaccination history during the 2018 to 2019 season were available from 5 out of the 13 fatal cases with 4 cases not having had the influenza vaccine.

Surveillance of influenza and other respiratory viruses in the UK: Winter 2017 to 2018

Paediatric mortality Fatal case reports from local health protection teams and the Office for National Statistics (ONS) were received for influenza-related deaths in children in England. Provisional data shows that during the 2017 to 2018 winter influenza season between 1 October 2017 and up to 10 May 2018, 16 influenza-related fatal cases were reported in children aged between 0 to 17 years. There were 8 female and 8 male cases. 10 of the 16 cases had influenza A infection (including 4 influenza A(H1N1)pdm09) and the remaining 6 cases had influenza B infection recorded as part of their cause of death. Information available shows that underlying medical conditions were reported from 7 of the 16 cases. Influenza vaccination history was available from 6 of the 16 cases and none of the 6 cases had received the 2017/18 influenza vaccine.

Surveillance of influenza and other respiratory viruses in the UK: Winter 2016 to 2017

Excess all-cause mortality surveillance The UK uses the European monitoring of excess mortality (EuroMOMO) algorithm to estimate weekly all-cause excess mortality9 . This algorithm allows for direct comparison between excess mortality estimation in the countries of the UK. The number of deaths is corrected by reporting delay and excess determined by week of death, avoiding the impact of bank holidays as illustrated above. During 2016 to 2017, up to week 14 2016, significant excess mortality was seen in England predominantly in all ages and in 65+ year olds between week 52 2016 and week 5 2017 for six weeks (Figures 30). In other age groups, significant excess was seen in 15-64 year olds (Table 4).

Surveillance of influenza and other respiratory viruses in the United Kingdom: Winter 2015 to 2016

Excess all-cause mortality surveillance Mortality by week of death registration The Office for National Statistics (ONS) provides estimated numbers of weekly all-cause registered deaths in England and Wales11. PHE uses this data to statistically estimate through Serfling regression the expected number of weekly death registrations for a given week in the year. Allowing for variation, we can then determine if the number of deaths is higher than expected, resulting in excess all-cause mortality. In contrast to 2014 to 2015 season when a large number of excess all-cause death registrations was seen, the size of the excess was much smaller in 2015 to 2016; with a total of 2,291 excess all-age death registrations above baseline estimated to have occurred. Only 7/31 (up to week 17 of 2016) weeks were above the upper limit compared to 15/33 weeks in excess in 2014 to 2015.

https://webarchive.nationalarchives.gov.uk/20140629102650/http://www.hpa.org.uk/Publications/InfectiousDiseases/Influenza/

https://webarchive.nationalarchives.gov.uk/20140714113122/http://www.hpa.org.uk/webc/HPAwebFile/HPAweb_C/1284475321350

https://www.academia.edu/25977487/Summary_of_knowledge_gaps_related_to_quality_and_efficacy_of_current_influenza_vaccines

Summary of knowledge gaps related to quality and efficacy of current
influenza vaccines
Michael Pfleiderer a,b , Jean-Hugues Trouvin c , Daniel Brasseur a,d,e , Marta Gränstrom a,f,g ,
Ragini Shivji h , Manuela Mura h,∗ , Marco Cavaleri h

a b s t r a c t
Influenza viruses are a public health threat, as they are pathogenic, highly transmissible and prone
to genetic changes. For decades vaccination strategies have been based on trivalent inactivated vac-
cines, which are regulated by specific guidelines. The progress in scientific knowledge and the lessons
learned from the A(H1N1)2009 pandemic have highlighted further the need to improve current guide-
lines, including the immunogenicity criteria set by the CHMP in 1997, and to promote the discussion
on the shortcomings encountered, e.g. the evaluation of vaccine efficacy in the paediatric and elderly
populations, the measurement of the naivety of a population, the impact of prior immunity on subse-
quent vaccinations, and the technical issues with the serological assays for detection of immunity and
immunogenicity.
The authors attempted to summarise and tackle key gaps in the existing evidence concerning qual-
ity and efficacy of influenza vaccines, aiming at favouring a common understanding and a coordinated
approach across stakeholders.
© 2014 Elsevier Ltd. All rights reserved.

11. Efficacy data for influenza vaccines in children particularly
of 6–36 months is lacking

Area of paediatrics
Conduct clinical efficacy trial in the context of Paediatric
Investigational Plans

12. A gap in knowledge currently prevents the definition of the
age range for children that need to be primary immunised by
vaccination (i.e. primed).

Explore epidemiology of influenza across the EU or through clinical
trials in order to gather sufficient evidence for the definition of an age
threshold as of which primary vaccination of children is no longer
required and booster vaccination is sufficient. 2 Cooperative effort (industry governmental institutions,
academia)
13. The influenza disease burden and severity in pregnant
women and in infants up to 6 months of age in the EU countries
should be better defined, including the effect of maternal
immunisation on priming of children and the characteristics of
protection in neonates and infants (e.g. duration of antibodies).

(a) Background data on women/infants should be gathered if available,
not limited to the studies performed in the USA and in Bangladesh.
(b) Efficacy trials in infants following vaccination of the mothers
during pregnancy should be considered

4. Vaccine efficacy
Substantial gaps in evidence are identifiable for some age
groups with regard to efficacy data for TIVs generated by RCTs
with relevant endpoints, such as virally confirmed influenza infec-
tions (RT-PCR or viral culture). There is a limited number of RCTs
assessing efficacy of TIVs in subjects aged 6 months–17 years and
65 years or older [23]. Efficacy data on the contrary exist for LAIV
vaccines in various age groups, albeit limited and/or of difficult
evaluation due to variability across studies in adults and in elderly
above 60 years of age [20,23]. Overall the elderly are the age group
with the least supportive data, including evaluation of impact on
morbidity and mortality, whereas this group represents one of the
main targets for influenza vaccination. Data are limited also in
infants and toddlers (6–36 months).
The immune responses in at risk groups such as immunocom-
promised individuals would also need to be better characterised,
which may help to identify new vaccines or vaccination schedules
suited specifically for this population.
The consequences of previous immunity to the virus, induced
by repeated exposure to circulating or vaccine’ seasonal strains,
on vaccine efficacy should be further elucidated both for LAIVs and
TIVs. For example the lower and highly variable protection induced
by LAIV in adults vs. children led to the hypothesis that previous
immunity may scavenge LAIV viruses before a specific immune
response to seasonal HA and NA could effectively be mounted
[20,21]. Correspondingly, previous exposure to seasonal TIVs could
influence susceptibility to pandemic viruses of the same HA or NA
type, although divergent results are reported [22]. Further investi-
gation is required in order to draw evidence-based conclusions and
to consequently revise existing regulatory criteria appropriately.
Concerning pandemic vaccines, the reported poor immuno-
genicity of H5 virus vaccines, for example, is still unclear and
divergent results have been reported from pre-clinical studies in
terms of correlation between HI titres and protection against avian
virus challenge [3,7]. The validity of using an HI titre of 40 or higher
as 50% protective titre against H5 and H7 or any other HPAIV based
on experience with seasonal strains should be substantiated more
robustly. Moreover additional immune markers testing increased
spectrum of responses (e.g. anti-NA and anti-M2/NP antibodies,
phenotypic and functional CD4+ and CD8+ T-cells, depending on
the vaccine) and estimating priming in a population would be use-
ful for dosing recommendations at the start of a pandemic [7]. The
complexities that arose due to assay variability during the pan-
demic are not reviewed here; the lesson learned is that there is a
great need to reach a consensus on the relative value of HI/SRH vs.
VN data [3].
The overall safety record of influenza vaccines is considered
well-established and in general quite reassuring, despite very few
notable and vaccine-specific exceptions that will not be covered
here.

6. Concluding remarks
Licensed influenza vaccines have generally shown over the last
seven decades a positive benefit-risk profile and an important role
in reducing influenza morbidity, particularly in the adult pop-
ulation. Therefore it is crucial from a public health perspective
to reinforce the concept that these vaccines represent the best
intervention currently available against influenza outbreaks (sea-
sonal or pandemic) [23]. However there is also an urgent need to
address the gaps in knowledge summarised in Table 1 for currently
licensed influenza vaccines, which may assist in defining innova-
tive evaluation criteria and in developing new more effective and
cross-protective vaccines.

3 thoughts on “/Summary_of_knowledge_gaps_related_to_quality_and_efficacy_of_current_influenza_vaccines and 5g, Depopulation tactics of the EUgenicist Platonists.

  1. https://notthegrubstreetjournal.com/2020/03/21/summary_of_knowledge_gaps_related_to_quality_and_efficacy_of_current_influenza_vaccines-and-5g-depopulation-tactics-of-the-eugenicist-platonists/ /Summary_of_knowledge_gaps_related_to_quality_and_efficacy_of_current_influenza_vaccines and 5g, Depopulation tactics of the EUgenicist Platonists.
    Dr. David Ahn7 days ago
    A rational, well-thought out post. Thank you. I agree COVID-19 is to be respected, especially in you are over 60. And epidemic spread of COVID-19 superimposed on our influenza season WILL overwhelm our healthcare system (heck, a bad flu season ALONE can do that).

    I credit the mess we’re in to the irresponsible early reporting of the (very) crude fatality rate of 18%, which combined with the admittedly rapid spread of the virus is to blame for the wholesale panic we’re seeing. Even as lower CFRs are continuing to be issued, it’s too late. People are too panicked to calm down now.

    I’d like to go even further than Dr. Fauci in predicting an overall mortality rate well under 0.5%. An accurate case fatality rate requires both death numbers AND an accurate total case count. Sadly, hospital based testing gives you a very small subset of the total cases, as you’re only testing the more severe cases. (Half of the cases on Diamond Princess were asymptomatic.)

    1. Witness the precipitous drop in case fatality rates from 17.3% in January to 3.8% in February to now approximately 0.5-1% in early March, with further drops to come. That’s not due to better therapeutics, that’s due to better data (expanded testing). (Sadly, it’s too late to put the genie back in the bottle.)

    2. In South Korea, where testing is occurring on a massive scale, a CFR of 0.5% seems closer to the true rate than anywhere else where only the more severely affected are tested.

    3. The Diamond Princess – while limited due to the small population and non-random selection – is revealing. Out of 3711 passengers and crew, 705 tested positive, approximately half of those were asymptomatic, and to date, 7 have died, or 1%. I could not find the ages of the deceased, but a cruise ship skews QUITE mature, so a more evenly stratified population would have a MUCH lower CFR. How much lower? Looking at China’s age banding data, 70-79 year olds have 100 TIMES the CFR as 20-29 year olds (9.8% vs 0.09%), and 80+ 100 times the CFR of 30-39 year olds (18% vs 0.18%). But more telling, going up from 40-49 to 60-69 is a 10-fold jump in CFR (0.4% to 4.6%), so if the Diamond Princess’s average age is 20 years older than the general population, we could very well be looking at an overall CFR of 0.1% rather than 1%.

    Now if Korea’s 0.5% overall CFR is accurate and you scale China’s age banded CFRs based on 3.8% overall CFR to 0.5%, the CFR for 20-29 drops from 0.09% to 0.01% (13% of 0.09%), and for 80+ goes from 18% to 2.4%. This is huge. But if the Diamond Princess’s universal testing plus my admittedly rough age adjusted risk of 0.1% CFR is more accurate, this would be even HUGER (CFR for 80+ goes from 18% to 0.5% CFR). I know this is speculative, but I firmly believe once we have more data, COVID-19 will turn out to be much closer to seasonal flu in CFR than the current thinking of 10 times worse.
    https://www.medscape.com/viewarticle/926089

    Like

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