Peter Chew Formular for calculate Covid-19 Vaccine eciency

Background: The World Health Organization (WHO) said the situation in India was a "devastating reminder" of what the coronavirus could do. India shifts from mass vaccine exporter to importer, worrying the world. Every country needs to vaccinate its citizens faster, vaccination can reduce viral load. This results in vaccination that can reduce transmission, preventing serious illness and death'. Therefore, Countries with higher levels of vaccination can prevent them from becoming "Second India". study, shows that take the because they question the and The purpose of creating this calculation formula is to allow the public to calculate the efficiency of the covid-19 themselves, so that they can understand the effectiveness of the vaccine and decide to take the This helps to get a high response to COVID vaccination Methods: for the public to know that people who are not vaccinated with Pfizer BioNTech's COVID-19 vaccine are 22 times more likely to be infected than people who are fully vaccinated. The above results can convince those who easily question the effectiveness of vaccination. Conclusions: Peter Chew Formular easy to calculate, and the data required for the Peter Chew Formular calculation easy to obtain from public news. This is to ensure that the public can calculate the efficacy of the vaccine by themselves. The information on the calculation can let public compare the average target group get infected every day before and after fully vaccination is also an advantage to let public know the effectiveness of vaccination. One of the advantage of Peter Chew formulator is that we can assume a high target population of vaccination with k = 100, such as the medical worker group . When k = 100, the Peter Chew formular calculation becomes very simple. The Proof of Peter Chew Formular must also be shown.


1.Background:
The World Health Organization (WHO) said the situation in India was a "devastating reminder" of what the coronavirus could do. India shifts from mass vaccine exporter to importer, worrying the world. Every country needs to vaccinate its citizens faster, vaccination can reduce viral load.
This results in vaccination that can reduce transmission, preventing serious illness and death'. Therefore, Countries with higher levels of vaccination can prevent them from becoming "Second India".
Preprint study, Vaccination Education App (1). [Peter Chew, 2021] shows that most people do not take the covid-19 vaccine because they question the safety and effectiveness of the vaccine. Therefore, it is important to create a simple formula for calculate the efficiency of the covid-19 vaccine. The purpose of creating this calculation formula is to allow the public to calculate the efficiency of the covid-19 vaccine by themselves, so that they can understand the effectiveness of the vaccine and decide to take the vaccine. This helps to get a high response to COVID vaccination From Wikipedia, Vaccine efficacy is the percentage reduction of disease in a vaccinated group of people compared to an unvaccinated group, using the most favourable conditions. Vaccine efficacy was designed and calculated by Greenwood and Yule in 1915 for the cholera and typhoid vaccines. It is best measured using double-blind, randomized, clinical controlled trials, such that it is studied under "best case scenarios." Vaccine effectiveness differs from vaccine efficacy in that vaccine effectiveness shows how well a vaccine works when they are always used and in a bigger population whereas vaccine efficacy shows how well a vaccine works in certain, often controlled, conditions. Vaccine efficacy studies are used to measure several possible outcomes such as disease attack rates, hospitalizations, medical visits, and costs.

Formula
The outcome data (vaccine efficacy) generally are expressed as a proportionate reduction in disease attack rate (AR) between the unvaccinated (ARU) and vaccinated (ARV), or can be calculated from the relative risk (RR) of disease among the vaccinated group.The basic formula [6]  The ideal vaccine efficacy study is a clinical trial starting with persons susceptible to disease. In a double blind randomized placebo controlled fashion,** half of the children receive vaccine and half receive placebo. To calculate vaccine efficacy both groups are followed prospectively to determine attack rates for disease in vaccinees and non vaccinees. This type of study is generally not possible after a vaccine has been licensed because the vaccine is of proven benefit and use of a placebo is unethical. In most countries today, measles vaccine has been used in a proportion of the population. These vaccinees are a self-selected rather than a randomly selected group and their susceptibility prior to vaccination is generally unknown. Nonetheless, vaccine efficacy studies are still possible if biases are reduced to a minimum in order to recreate as closely as possible the "ideal" conditions of the prospective clinical trial.
Calculation of vaccine efficacy -General principles Vaccine efficacy is measured by calculating the incidence rates (attack rates) of disease among vaccinated and unvaccinated persons and determining the percent reduction in the incidence rate of disease among vaccinated persons relative to unvaccinated persons. The basic formula is written as: The relative risk (RR) is the ratio of the probability of an outcome in an exposed group to the probability of an outcome in an unexposed group [ = (exposed group) (unexposed group) ].
For example, in a study examining the effect of the drug apixaban on the occurrence of thromboembolism, 8.8% of placebo-treated patients experienced the disease, whereas only 1.7% of patients treated with the drug experienced the disease, therefore the risk ratio is calculated as 1.7/8.8, which is 0.19. This can be interpreted as those receiving apixaban had 19% the risk of recurrent thromboembolism than did patients receiving the placebo. In this case, apixaban is considered to be a protective factor rather than a risk factor because it is associated with causing a reduced risk of disease.
Assuming the causal effect between the exposure and the outcome, values of RR can be interpreted as follows: RR = 1 means that exposure does not affect the outcome, RR < 1 means that the risk of the outcome is decreased by the exposure, which can be called a "protective factor" RR > 1 means that the risk of the outcome is increased by the exposure The study , published by NCBI ,The National Center for Biotechnology Information advances science and health , Relative Risk [Steven Tenny et all, 2020]. Relative risk is a ratio of the probability of an event occurring in the exposed group versus the probability of the event occurring in the non-exposed group. [ = Relation between Vaccine efficiency (VE) and Relative Risk (RR=  = 95.0599% = 95.0599 % = 95.0617 % Note: If the total vaccination ≈ the total placebo , we can let k% = 100%, then the final answer of VE is almost the same, 95.06%. Therefore, the advantage of Peter Chew formulator is that we can assume a high target population of vaccination with k = 100, such as the medical worker group. When k = 100, the calculation becomes very simple. Let we modify the Data 1. Let process of vaccination just 90% the total target group. So for vaccinated data, all are 90% form original data. is not much different from the original answer of 95.06%. Therefore, the advantage of Peter Chew formulator is that we can assume a high target population of vaccination with k = 100, such as the medical worker group. When k = 100, the calculation becomes very simple. Chew's formula also shows that before the vaccination, about 12 medical staff were infected every day, but after the full vaccination, only about one medical worker was infected every two days. The calculation of relative risk can also make it easier for the public to know that people who are not vaccinated with Pfizer BioNTech's COVID-19 vaccine are 22 times more likely to be infected than people who are fully vaccinated. The above results can convince those who easily question the effectiveness of vaccination.
4. Conclusions: Peter Chew Formular easy to calculate, and the data required for the Peter Chew Formular calculation easy to obtain from public news. This is to ensure that the public can calculate the efficacy of the vaccine by themselves. The information on the calculation can let public compare the average target group get infected every day before and after fully vaccination is also an advantage to let public know the effectiveness of vaccination. One of the advantage of Peter Chew formulator is that we can assume a high target population of vaccination with k = 100, such as the medical worker group. When k = 100, the Peter Chew formular calculation becomes very simple.
According to article from Proofs and Mathematical Reasoning [Agata Stefanowicz et all, 2014]. Mathematical proof is absolute, which means that once a theorem is proved, it is proved for ever. Until proven though, the statement is never accepted as a true one. Therefore, the Proof of Peter Chew Formular must also be shown.

Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Information
Corresponding author: peterchew999@hotmail.my

Notes
Declaration of conflicting interests. The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Ethical approval: This article does not contain any studies with human participants or animals performed by any of the authors.