Pfizer COVID Vaccines Delivering Promised Rate of Protection, Israeli Data Shows

Statistical model from theoretical physics in Israel finds that 28 days after the second shot the COVID vaccine is 95 percent effective

Asaf Ronel
Asaf Ronel
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A COVID vaccination center in Jerusalem, a month ago.
A COVID vaccination center in Jerusalem, a month ago. Credit: Ohad Zwigenberg
Asaf Ronel
Asaf Ronel

The coronavirus vaccine developed by Pfizer and BioNTech provide those vaccinated with at least a 50 percent protection 10 days after the first shot and is 95 percent effective a week after the second shot, new data from Israel reveals. 

The data from Israel is very similar to the conclusions reached in Pfizer’s own Stage III clinical trials.

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The conclusions from the new study are based on a probabilistic statistical model used to analyze the rates of vaccination and COVID-19 patients in moderate to serious condition – based on a breakdown according to age groups in Israel. The study has not yet undergone peer review.

The model is based on principles taken from statistical physics, and shows that since the second week of January it is possible to see a drop in the rate of new patients in moderate to serious condition among the age group over 60 – which cannot be explained using other variables.

The research was conducted by Dr. Hilla De-Leon, who is doing post-doctoral research at The Trento Institute for Fundamental Physics and Applications under Prof. Francesco Pederiva of Trento University in Italy, and professors Doron Gazit, Ronit Calderon-Margalit and Yinon Ashkenazy of the Hebrew University of Jerusalem.

De-Leon, a theoretical physicist, says she began to work on the model used in the study in March last year when the pandemic began to spread throughout the world and the situation in Italy deteriorated. Her research originally was on calculating multi-body systems that include interactions between all pairs of particles which weaken the farther the two particles are from each other.

When COVID-19 began to spread, De-Leon and Pederiva began to adapt their model for epidemiological use. But in this case, the distance between any two particles in the model determines the probability of one of them being infected by the other. De-Leon and Pederiva published their first theoretical model in August in the scientific journal Physics of Fluids.

A COVID vaccination center in Tel Aviv, last month. Credit: Hadas Parush

When Pfizer and Moderna announced the success of their clinical trials, and along with the cases of reinfection at the same time, De-Leon and Pederiva upgraded their model to include the possible influence of the vaccination campaigns and the possibility of reinfection. The second article, “Statistical mechanics study of the introduction of a vaccine against COVID-19 disease,” was originally published on the medRxiv preprint server for health sciences before peer review.

In late December, “Doron (Gazit) called me and asked if I could adapt the model to the real data from Israel and the efficacy that Pfizer is reporting in its trials,” said De-Leon. Adapting the model for the real data from the field took a bit of work. “Now, for every one of the particles in the model there is a name – its age. This allows for an analysis of the infection according to age and adaption of the model to the vaccination data in Israel,” she said.

One problem De-Leon and her colleagues were required to solve was that the scenarios the model presented went wrong in the vicinity of 1,200 patients in serious condition. De-Leon says the solution to this obstacle was in understanding that this number was the upper limit for the number of patients in serious condition the hospitals in Israel were able to treat.

To discover this, De-Leon and her colleagues tweaked the model with the help of the infection figures from the second wave of the outbreak. At this stage, they saw that a relationship exists between the daily number of patients in serious and moderate condition and the load on the health system.

This is why the drop in the number of patients in serious condition that came at the end of January can also be explained by crossing this limit on the way down, says De-Leon. The places that opened up in the hospitals by patients over 60 in serious condition were filled by other patients who had previously not been considered to be in serious condition. In the third wave, the number of patients in serious condition over 60 began to fall as of January 15 – only a week after the lockdown was tightened. “The sole explanation for the drop is the vaccinations,” she said.

As of the latest update of the data from the beginning of the week, the curve of the change in the number of patients in moderate and serious condition matches exactly the scenario in which the Pfizer vaccine offers 95 percent protection from serious illness after 28 days. “The decrease appears exactly where the model predicts it will come,” said De-Leon.

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