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Covid-19: Razvoj vakcine, imunitet i primena medikamenata


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Po Moderninim podacima, treća doza njihove originalne vakcine daje vrlo dobre rezultate protiv delte i drugih varijanti.








Izvor je prezentacija rezultata poslovanja Moderne u 2. kvartalu 2021:


Ako nekog zanima, ovde je dostupan transkript snimka prezentacije sa detaljnijim komentarom slajdova:

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U septembru se očekuju rezultati britanskog istraživanja koje podrazumeva davanje različitih bustera:



Volunteers from Southampton, Portsmouth and Bournemouth will soon be able to receive a third ‘booster’ COVID-19 vaccine through a new clinical trial launching this week...
The initial findings, expected in September, will help inform decisions by the Joint Committee on Vaccination and Immunisation (JCVI) on any potential booster programme from autumn this year, ensuring the country’s most vulnerable are given the strongest possible protection over the winter period.

The trial will look at seven different COVID-19 vaccines as potential boosters, given at least 10 to 12 weeks after a second dose as part of the ongoing vaccination programme. One booster will be provided to each volunteer and could be a different brand to the one they were originally vaccinated with. Vaccines being trialled include Oxford/AstraZeneca, Pfizer/BioNTech, Moderna, Novavax, Valneva, Janssen and Curevac, as well as a control group.


Edited by vememah
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2 hours ago, vememah said:

Po Moderninim podacima, treća doza njihove originalne vakcine daje vrlo dobre rezultate protiv delte i drugih varijanti.


Isto i kod Fajzera:








Izvor je prezentacija rezultata poslovanja Fajzera u 2. kvartalu 2021:


Ako nekog zanima, ovde je dostupan transkript snimka prezentacije sa detaljnijim komentarom slajdova:

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mRNA-1273 = Moderna
NVX... = Novavax
BNT162b2 = Pfizer/BioNTech
rAd26-s + ... = Sputnjik
Convalescent = preležali
Covaxin = Bharat Biotech (indijska s inaktiviranim virusom)
Ad26... = Johnson & Johnson tj. Janssen (jednodozna)
ChAdOx1... = Oxford/AstraZeneca
CoronaVac = Sinovac




a, Relationship between neutralization level and protection from SARS-CoV-2 infection. The reported mean neutralization level from phase 1 and 2 trials and the protective efficacy from phase 3 trials for seven vaccines, as well as the protection observed in a seropositive convalescent cohort, are shown (details of data sources are given in Supplementary Tables 1 and 2). The 95% CIs are indicated as vertical and as horizontal whiskers. The red solid line indicates the best fit of the logistic model and the red shading indicates the 95% predictive interval of the model. The mean neutralization level and protective efficacy of the Covaxin vaccine are indicated as a green circle (data from this study were available only after modeling was complete and did not contribute to fitting).

b, Schematic illustration of the logistic approach to identifying the protective neutralization level. The data for each study include the distribution of the measured in vitro neutralization titer against SARS-CoV-2 in vaccinated or convalescent subjects (as a proportion of the mean titer in convalescent subjects (dashed line)) (blue/red bell curve), accompanied by a level of protective efficacy for the same regimen. The efficacy is illustrated by the proportions of the bell curve ‘protected’ (blue) and ‘susceptible’ (red) for individual studies. The modeling fits the optimal 50% protective neutralization level (blue solid line, the shaded area indicates the 95% CI) that best estimates the correct levels of protection observed across the different studies.

c, Predictions of the leave-one-out analysis. Modeling was repeated multiple times using all potential sets of the seven vaccination studies and the convalescent study to predict the efficacy of the eighth study. The diagonal dashed line indicates the position of a 1:1 correlation (i.e., the relationship if the model were completely accurate). The horizontal whiskers indicate 95% CIs and the vertical whiskers indicate 95% predictive intervals.






a, Prediction of the effects of declining neutralization titer. Assuming that the observed relationship between neutralization level and protection is consistent over time, we estimate the decline in efficacy for vaccines with different levels of initial efficacy. The model assumes a half-life of the neutralization titer of 108 d over the first 250 d (as observed in a convalescent cohort5).

b, Modeling of the time for efficacy to drop to 70% (red line) or 50% (blue line) for scenarios with different initial efficacy. For example, for a group starting with an initial protective efficacy of 90%, the model predicts that 70% efficacy will be reached after 201 d and 50% efficacy will not be reached before 250 d.

c, Estimation of the impact of viral antigenic variation on vaccine efficacy. In vitro studies have shown that neutralization titers against some SARS-CoV-2 variants are reduced compared with titers against wild-type virus. If the relationship between neutralization and protection remains constant, we can predict the difference in protective efficacy against wild-type and variant viruses from the difference in neutralization level. The dashed line indicates equal protection against wild-type and variant strains. Details of the data and modeling are provided in the Methods.






a, The predicted relationship between efficacy against any symptomatic SARS-CoV-2 infection and the efficacy against severe infection. The black line indicates the best fit model for the relationship between protection against any versus severe SARS-CoV-2 infection. The shaded areas indicate the 95% CIs. Efficacy against severe infection was calculated using a threshold that was 0.15 times lower than that for mild infection (95% CI = 0.036–0.65) (see Methods and Supplementary Table 5).

b, Extrapolation of the decay of neutralization titers over time. This model uses the estimated half-life of SARS-CoV-2 neutralization titer in convalescent subjects of 108 d over the first 250 d5, after which the decay decreases linearly until it achieves a 10-year half-life (consistent with the long-term stability of antibody responses seen after other vaccines47,48). We simulate three scenarios, with decay of neutralization taking 1 year (blue dashed line), 1.5 years (purple dashed line) or 2 years (red dashed line) to slow to a 10-year half-life. For different initial starting levels the model projects the decay in neutralization titer over the subsequent 1,000 d (the gray shaded area indicates projections beyond the currently available data). The purple shaded region indicates being below the 50% protective titer for any symptomatic SARS-CoV-2 infection, and the orange shaded region indicates being below the 50% protective titer for severe SARS-CoV-2 infection. The model illustrates that, depending on the initial neutralization level, individuals may maintain protection from severe infection while becoming susceptible to mild infection (that is, with neutralization levels remaining in the purple shaded region).

c, Extrapolation of the trajectory of protection for groups with different starting levels of protection. The model uses the same assumptions for the rate of immune decay as discussed in b. The projections beyond 250 d (gray shaded region) rely on an assumption of how the decay in SARS-CoV-2 neutralization titer will slow over time. In addition, the modeling projects only how decay in neutralization is predicted to affect protection. Other mechanisms of immune protection may play important roles in providing long-term protection that are not captured in this simulation.





Kod vakcina sa početnom niskom efikasnošću novi sojevi dovode do većeg pada efikasnosti, pošto se ona izgleda manje-više kreće po ovoj krivoj.



Izvor slike: https://twitter.com/DavidLVBauer/status/1400582490490904581

Edited by vememah
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Opis zadnje slike:



Supplementary Figure 3. Schematic based on the model of Khoury et al. illustrating the relationship between measured neutralising antibody titres (NAbT) against SARS-CoV-2 and observed real-world vaccine efficacy (VE). When NAbTs begin at a high level (e.g. against variants with spike proteins similar to the Wild-type spike in first-generation vaccines), small changes in NAbsTs have a small effect on VE. However, when titres begin from a lower level (for example due to reduced activity against VOCs such as B.1.617.2 ‘B.1.617.2’), small subsequent changes in NAbTs that would not have greatly affected VE previously now have a larger effect on VE.






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