We were given a chart that shows August 2021 data for Israeli hospitalization (“Severe Cases”) rates for people both under and over 50, for both un-vaccinated and fully vaccinated populations.
In order to answer them I needed more information about:vaccination <- read.csv("https://raw.githubusercontent.com/moiyajosephs/Data-607-Homework-5/main/israeli_vaccination_data.csv?token=GHSAT0AAAAAABSDV7RHT2335YTAM3KSBPLGYREB4PA")names(vaccination)<-(c("age","population_novax","population_vax",
"severe_novax","severe_vax","efficacy_vs_severe"))
vaccination<-vaccination[-1,]No we do not have enough information to calculate the total population. According to multiple sources, the actual population of Israel is 9,000,000. The table shows far less than that. This population represents only the people who were eligible to be vaccinated.
# split the table in three, one for the population one for the percentages and the other for severe cases
population <- vaccination %>% slice(seq(1,4,2)) %>% select(2:3)
rownames(population) <- c("<50",">50")
head(population) %>% kbl() %>% kable_styling(bootstrap_options = c("striped", "hover"))| population_novax | population_vax | |
|---|---|---|
| <50 | 1,116,834 | 3,501,118 |
| >50 | 186,078 | 2,133,516 |
severe <- vaccination %>% slice(seq(1,4,2)) %>% select(4:5)
rownames(severe) <- c("<50",">50")
head(severe) %>% kbl() %>% kable_styling(bootstrap_options = c("striped", "hover"))| severe_novax | severe_vax | |
|---|---|---|
| <50 | 43 | 11 |
| >50 | 171 | 290 |
percentage <- vaccination %>% slice(seq(2,4,2)) %>% select(2:3)
rownames(percentage)<- c("<50",">50")
head(percentage) %>% kbl() %>% kable_styling(bootstrap_options = c("striped", "hover"))| population_novax | population_vax | |
|---|---|---|
| <50 | 23.3% | 73.0% |
| >50 | 7.9% | 90.4% |
This table shows more people are vaccinated than unvaccinated.
library(reshape2)##
## Attaching package: 'reshape2'## The following object is masked from 'package:tidyr':
##
## smiths#clean the population, remove the , in the chr
population$population_novax = gsub(",", "", population$population_novax)
population$population_vax = gsub(",", "", population$population_vax)
#Change the chr column into a numeric column
population$population_novax <- as.numeric(population$population_novax)
population$population_vax <- as.numeric(population$population_vax)
# find the total for ages <50 and > 50
population <- population%>%
mutate(sum = rowSums(across(where(is.numeric))))
head(population) %>% kbl() %>% kable_styling(bootstrap_options = c("striped", "hover"))| population_novax | population_vax | sum | |
|---|---|---|---|
| <50 | 1116834 | 3501118 | 4617952 |
| >50 | 186078 | 2133516 | 2319594 |
The population documented in this table does not total to the amount Israel reports. This is because the data only included the population of the eligible people for COVID vaccination.
# convert the chr field into numeric
severe$severe_novax <- as.numeric(severe$severe_novax)
severe$severe_vax <- as.numeric(severe$severe_vax)
# find the total <50 and > 50
severe <- severe%>%
mutate(sum = rowSums(across(where(is.numeric))))
head(severe) %>% kbl() %>% kable_styling(bootstrap_options = c("striped", "hover"))| severe_novax | severe_vax | sum | |
|---|---|---|---|
| <50 | 43 | 11 | 54 |
| >50 | 171 | 290 | 461 |
This table shows the total amount of sever cases is larger in the over 50 population than the under 50.
Efficacy refers to how well a vaccine performs under ideal conditions as reflected in a careful clinical trial. For our purposes efficacy is defined in the function below.
\[
Efficacy\ vs.\ severe\ disease = 1- \% fully\ vaxed\ severe\ cases\ per\ 100K/\% not\ vaxed\ severe\ cases\ per\ 100K)
\]
# calculate the sum of fully vaxed
# calculate the sum of the not vaxed
# find the percentage
severe <- severe%>%
mutate(efficacy = 1 - (severe_vax/severe_novax))
head(severe) %>% kbl() %>% kable_styling(bootstrap_options = c("striped", "hover"))| severe_novax | severe_vax | sum | efficacy | |
|---|---|---|---|---|
| <50 | 43 | 11 | 54 | 0.7441860 |
| >50 | 171 | 290 | 461 | -0.6959064 |
For the ages under 50 the vaccine performed with a 0.744186 efficacy. The amount of people who were not vaccinated was greater than the amount of people who were vaccinated. An efficacy with a value of 0.744186 shows that the vaccinated group experienced 0.744186 fewer cases than if they were not vaccinated.
While for people over 50, the efficacy was -0.6959064 meaning this group’s vaccinated population did not perform ideally. Unlike the under 50 group, the amount of people who were vaccinated and ended up with a severe case was greater than if they were not vaccinated. Meaning that the vaccinated group in the over 50 population experienced an inverse effect compared to those under the age of 50, and were more likely to end up with a severe case.
We cannot compare everyone who was not vaccinated since the data only considers those who were eligible. However it does give us data of people who were at least 12 and vaccinated. According to the data the vaccine is “ineffective”.
This data seems to have damning evidence against the vaccine, at least if you are of a certain age. The data does has inconsistencies throughout. It does not include the entire Israeli population. Not everyone is eligible for the vaccine, for example, children under the age of 12. According to many sources, over 50 group were one of the first groups of people to get vaccinated. This data does not explain if the people who were counted as vaccinated or not received one or more doses. In order to make a more concrete conclusion, we would also need the survival rates of the severe cases. More data would be needed to make a concrete conclusion on whether or not the vaccine in Israel is effective or not.