library(tidyverse)## Warning: package 'tidyverse' was built under R version 4.1.1## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --## v ggplot2 3.3.5 v purrr 0.3.4
## v tibble 3.1.4 v dplyr 1.0.7
## v tidyr 1.1.3 v stringr 1.4.0
## v readr 2.0.1 v forcats 0.5.1## Warning: package 'tibble' was built under R version 4.1.1## Warning: package 'readr' was built under R version 4.1.1## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(stringr)url <- "https://raw.githubusercontent.com/omocharly/DATA607_Assignment4/main/israeli_vaccination_data_analysis_start.csv"
rawdata <- read.csv(url, header = TRUE)
rawdata## Age Population.. X Severe.Cases X.1
## 1 Not Vax\n% Fully Vax\n% Not Vax\nper 100K\n\n\np Fully Vax\nper 100K
## 2 <50 1,116,834 3,501,118 43 11
## 3 23.30% 73.00%
## 4 >50 186,078 2,133,516 171 290
## 5 7.90% 90.40%
## Efficacy
## 1 vs. severe disease
## 2
## 3
## 4
## 5vac_data = rawdata %>% rename(
AgeGroup = Age,
NotVax = Population..,
Vax = X,
Sev.NotVaxPr100k = Severe.Cases,
Sev.VaxPr100k = X.1,
Efficacy.Sev=Efficacy)vac_data=slice(vac_data,2:5)
PcNotVax=vac_data[[2]][c(2,4)]
PcNotVax=as.numeric(str_remove_all(PcNotVax,"%"))
PcVax=vac_data[[3]][c(2,4)]
PcVax=as.numeric(str_remove_all(PcVax,"%"))
vac_data=slice(vac_data,c(1,3))
vac_data$PcNotVax=PcNotVax
vac_data$PcVax=PcVax
vac_data$Sev.NotVaxPr100k=as.numeric(vac_data$Sev.NotVaxPr100k)
vac_data$Sev.VaxPr100k=as.numeric(vac_data$Sev.VaxPr100k)
vac_data=vac_data[,c(1,2,7,3,8,4,5,6)]
vac_data$NotVax=str_remove_all(vac_data$NotVax,",")
vac_data$NotVax=as.integer(vac_data$NotVax)
vac_data$Vax=str_remove_all(vac_data$Vax,",")
vac_data$Vax=as.integer(vac_data$Vax)
vac_data## AgeGroup NotVax PcNotVax Vax PcVax Sev.NotVaxPr100k Sev.VaxPr100k
## 1 <50 1116834 23.3 3501118 73.0 43 11
## 2 >50 186078 7.9 2133516 90.4 171 290
## Efficacy.Sev
## 1
## 2Israel’s total population is about 9216900 according to WorldBank data.
Eligible to receive vaccine in Israel: From february 2021, only those who are 16 years and older could get covid vaccinated in Israel, but by August 2021, the covid vaccines have been made available to those age 12 and older.
To be fully vaccinated in Israel means that 14 days have elapsed after completing the series (2 doses) of either the Pfizer or Moderna vaccines as those are the only covid-19 vaccines currently approved in Israel.
Do you have enough information to calculate the total population? What does this total population represent?
There is enough information to calculate the total Population.
From the table, it can be clearly seen that the 96.3% of Agegroup less than 50 are the addition of Non-vaccinated(1116834) and the vaccinated(3501118); while 98.3% of the greater than 50 population is also the addition of the non-vaccinatied and the vaccinated in that categories.
96.3% Agegroup(<50) = 1116834 + 3501118 = 4,617,952
98.3% Agegroup(<50) = 186078 + 2133516 = 2,319,594
Total population for Agegroup(<50)
4,617,952/96.3 * 100 = 4,795,381
Total Population for Agegroup(>50)
2,319,594/98.3 * 100 = 2,359,709
Total Population = 4,795,381 + 2,359,709 = 7,155,090.
vac_data = vac_data %>% mutate(total.pop = (NotVax+Vax) / ((PcNotVax+PcVax)/100))
vac_data %>% summarize(total = sum(total.pop))## total
## 1 7155090This total population represent the population eligible for vaccine in Israel. This population include the Vaccinated, Unvaccinated and the partially vaccinated that is not captured in the data. Since, the population of Israel is about 9.21 million, there are over 2 million people that are outside this data which i believe are minors that are not eligible for vaccines.
Calculate the Efficacy vs. Disease; Explain your results.
EfficacyVSev = (1- V/N),
V = rate of infection per 100k for fully vaccinated.
N = rate of infection per 100k for unvaccinated.
rate Per 100k for 43 = 3.9; rate per 100k for 11 = 0.3
rate Per 100k for 171 = 91.9; rate per 100k for 290 = 13.6
(<50 Agegroup Efficacy) = 1 - 0.3/3.9 = 91.9%
(>50 Agegroup EfficacyvSev) = 1 - 13.6/91.9 = 85.2%
Explanation
The Efficacy vs severe result shows that the vaccine is more effective in the less than 50 Age-group. The unvaccinated in this agegroup are more likely to have severe cases if infected. On the contrary, for the Age-group greater than 50, the vaccine is less effective
From your calculation of efficacy vs. disease, are you able to compare the rate of severe cases in unvaccinated individuals to that in vaccinated individuals?
I can compare the rate of severe cases in unvaccinated individuals to vaccinated individuals. The Efficacy vs. Severe basically represents the percent reduction in the severity of infection in the vaccinated group relative to the unvaccinated. From the severe rate, we can see that the unvaccinated are more likely to be hospitalized if infected.