COVID-19 Death Rates and Data Analysis in England and the UK Case Study

COVID-19 Death Rates and Data Analysis in England and the UK

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1.0 Introduction: Analyzing UK COVID Vaccination Progress and Hospitalization Rates Over Time

In England as well as in United Kingdom, their speed and they took into account the rising second vaccinations that time and they had almost fifty percent of their adult population with 1 vaccination within some weeks and every adult in the country with vaccination offered until a mid-end month. Covid 19 has exposed the hypocrisy of the governance of England, but they are vaccinated almost one percent of the population on a daily basis and the number of infections has declined. But the hysteria dissipated as people got back to their lives as normal and social media reported the tedious political leadership election as if it were global addicts swapping views about reality. They are in some phase of exponential reduction of virus infections, admission in the hospitals, and in various stages on the respective curves. England has been the county with the most first vaccination getting so close to almost one percent of the overall population getting their first shot on a daily basis on the seven days average.

Set the scene

The local authorities are planning for their money spent over the recent financial year, the England government's public health management of Covid-19 only applies in England. The governments of England have their own public health regulations for Covid-19. England has regional keys with different rules and the rules and restrictions depend on which of the four countries of England an individual lives in. It all depends on the infection rate and how these slightly changed lockdown rules affect the infection rate (Bach-Mortensen and Degli Esposti, 2021). At the moment, everything depends on Covid-19 and how people can follow certain rules. In 2021, when the delta variant was prevalent in the UK with twenty thousand to thirty thousand new infections per day out of a population of 65 million, it is still more serious than many think because the vaccine only limits the level of infection while still being very useful. 

Figure 1: Plot of the research

Effect in reducing mortality and many people are quite sick, but far fewer end up in the hospital. Even among the twice-vaccinated and even younger people, there is now concern that long-term debilitating effects may seriously affect a small minority (Shahar et al. 2021). Many people are satisfied also because they assume that hygiene and maintaining distance is no longer so important from the point of view of public health. Vaccinations have reached a plateau and many other European countries have overtaken us in the race for potential groups of immunity. 

2.0 Data acquisition

Generally, there are some methods of acquiring data files, firstly, the file has been extracted from the CSV file then it is used for build-in functions and extracted that data for using the data then read the CSV then create a name, header=T, sep= “,”, like file name of the file with a path details that have used to extract the information (Bell et al. 2020). If the file’s name of the columns then header = T or otherwise this header = F, the file contains the column's name and then Sep means separated though the CSV file has separated by the comma when this runs the command and all the details have been saved into the variable data. 

This is the method of digital data from the globe around England so that it could be displayed, analyzed, and stored on the desktop. The file has been checked in the checkbox to the next package name to load the overall package and improve access to the database then click on the package name and R-studio has been opened for the help described file the datasets in the package, then put the main path to the file that want to read in within quotation sign.

2.1 IVs & DV:

Independent Variable: Total deaths

Dependent Variable:

1. Couple deaths
2. Deaths of employers
3. Singles death
4. Ethnic group deaths
5. Students death 

3.0 Data Exploration

Figure 2: Q-Q plot coding For Total Deaths

This is the main code of the data exploration of the statistics of the covid death. In R Studio there are the codes of implementing the database in the covid rates in the UK as in the 4 countries in the United Kingdom (Feng et al. 2021). Here the file is attached in the R studio as the database which is given in the file. Here the library is the basic functions of R studio which are in the main function of the R studio. So in that case there will be the normalized function in the R Studio on the codes of the attached file. In the adobe figure there are the codes of the total death rates of UK as the ubited kingdom in the attack of Coid 19. 

Figure 3: Q-Q plot in the general dataset of Total deaths in Covid

In the above figure there is the normalized graph of peoples in the covid death rates in the United Kingdom. In this figure the black line is the graph and the red line is the normalized graph of that figure (Hatton et al. 2020). Actually this normalized function is the saturation points of the graph. In this blackline there are the scattered points of the death cases in the United Kingdom, but this redline is the assumption of the straight line of the black line in the graph. To specify, this is the main covid graph in the United Kingdom.

Figure 4: Q-Q plot coding For Ethnic Group white

In Europe there are the maximum number of white skinned people as well as in the United Kingdom. So this is the programming of the ethnic group of the white skinned death rate in the United Kingdom. This program is also the same with respect to the previous program in R studio. But here the name after $ is changed to the Ethnic Group White (Cook and Roberts, 2021). So this is the important topic to make the graph on the basis of the white skinned peoples in the United Kingdom. This graph is effective to measure the white skinned people in the United Kingdom.

Figure 5: Q-Q plot in the general dataset of Ethnic Group white in Covid

This is the main graph of the Ethnic group white in the United Kingdom. So this black line is the same as the previous graph in the figure. The red line is from the previous figure of the death of the total persons in the United Kingdom in the Covid period (Rasul et al. 2020). So that is the main line of the saturation point of Covid 19 in the world in the covid pandemic situation. Due to the main operation of the graph is the tidal death in the United Kingdom, so black line can’t be changed in the graph. This blue line is the main saturation point in the ethnic group of the white skinned people in the United Kingdom. So this graph is effective in the drawing of the United Kingdom’s covid cases of racism. 

This code of the adobe figure is the code for a mixed group of ethnic people in the United Kingdom. All the codes are the same but the group name is changed by the given datasheet. This code is effective to measure the data sheet in the mixed group in the United Kingdom (Scott et al. 2020). This mixed group means the mulatto, white and black group in the United Kingdom. Here the change is from the $ in the code.

This is the graph of the QQ in the death rate of mixed groups in the covid pandemic. Actually this mixed group is the total United Kingdom death reports on the Covid 19 pandemics. In the graph the green line is the saturated line of date rate of the multi-skinned persons in the United Kingdom (Iacobucci, 2021). So this will be the accurate measurement of covid death in the United Kingdom by the color of people. This green line is the effective lines of the graphs in the saturation points in the death rates in the United Kingdom from Wales, Northern Ireland, England, and Scotland.

This above figure is the main code of the group black in the United Kingdom Covid death. In the United Kingdom as well as the 4 sections of countries have the black skinned peoples somewhere, so there has to be a measurement of the black skinned people in the four segments in the black skinned people. In the above code there will be the change of the group name as the ethnic group black in the given datasheet. So this is the partial measurement of the covid cases in the black people in the 4 components in the United Kingdom.

This is the graph of the ethnic group black in the United Kingdom. This black denotes the black people death database in the United Kingdom by the covid attack in the United Kingdom. These black people are 30 to 40 percent in the 4 components in the United Kingdom. So this graph is effective to make the capture of the data in the United Kingdom’s covid deaths. .

According to the given figure, plotting for the Q-Q norm is done by extracting the final data set according to the given format. Later head “given data” will import the coding section to evaluate its scatter plots. 

The figure is about theoretical quantities along with sample quantities that have been mentioned that major deaths are found in England. 

From that data exploration there should be the hypothesis of the death rate in equal distribution in the factors in United Kingdoms in the covid situation. So from that test this will be an ensurement of the distribution of the death rates in equal distribution in England.

4.0 Factor analysis

There is mainly some factor analysis that is confirmatory and exploratory. In the R studio software factor analysis is implemented through the fictional function of the stats package and it has performed a maximum factor analysis on the covariance data and the various number of factors have to be specified through the argument factors.

Here the factors are the effective parts in the UK as well as the 4 components in the United Kingdoms. In the factors there are the effective sequences to deaths in Corona Virus in the pandemics situation from 2020 march. So there is a need to do the factors in the analysis portion in the case of the United Kingdom death rate. The factors are very much effective to analyze the death rate in England as well as the UK. 

4.1 Employers:

In England there is a heavy death rate in the employers section in Covid 19 in the year 2020. So this is the effective factor to count the death rate in covid as the economic problems rises in the employer’s death in United Kingdom. Actually the employers are the backbone of the United Kingdom to make the United Kingdom in a strong position in the economy at the global level. So this factor is effective to analyze in the covid death rate (Kulu and Dorey, 2020). In the codes there are the codes of employers in the R studio on the basis of a given database. In there, all the given databases are implemented in the R studio as the saturation line comes in. This saturation line denotes the average death in the United Kingdom's employers in covid situations. 

4.2 Unemployed Section:

In every country there are unemployed persons who are on their way to find jobs. So in the United Kingdom there are also the death rates in the covid 19 virus attack in pandemic situations. There are the 50 to 60 percent who are von the unemployed sections in the United Kingdom as Wales, Northern Ireland, England and Scotland (Kuo et al. 2020). So there will be a very effective section in the country's population. So their death rate in covid 19 is very effective in the United Kingdom. So in this case the death rate of unemployed persons is taken as a factor of the death rate counting in England and other 3 regions. Also this will show effect in the counting the covid section deaths in the United Kingdom. This database is verified by the United Kingdom's government as the rate of deaths. 

4.3 Couples:

In a country there will be a lot of couples. In that case all the countries are growing in their population by the couples. Couples are producing the manpower to make the country stronger in the case of the labor force and the armed forces. So the death of couples is the effective factor to control the population in a low populated country. So these are the essential factors in the country to control the population (Ledford, 2020). In the year of covid the United Kingdom became the graveyard of the dead bodies of corona victims in the pandemic situation. So this is taken as the factor of the counting death rate in the United Kingdom. In that case this factor contributes to the effective counting of the death rate of covid in the United Kingdom. In this R studio programming there are the couples factors to make the stat of the population as well as the vaccines in the United Kingdom. 

4.4 Ethnic group White:

In the United Kingdom the maximum persons are on the white skinned. So to count the persons in the death rate of United Kingdom’s there is a need to make the count of the white skinned person’s death in the corona region. So this factor is taken as the code in R studio in the counting of the death rate in the covid pandemic situation (Lawlor et al. 2020). This graph shows the average rates of the covid attacks as the death lists of the humans in the United Kingdoms. So this is the effective part in counting the graphs of death rates in the United Kingdom. So this is the effective portion of the death rate calculation in Europe only.

4.5 Ethnic Group Mixed:

This is the mixed factors of the United Kingdom as the black, mulatto and the white persons in the United Kingdom. In these countries there are the Nigros, Gorkhas and the western people who are on the black skinned, mulattos and the white skinned persons in these four countries. England is the only country in the United Kingdom who contains the Ghorka in their population as well as the armed forces (Maben and Bridges, 2020). So there are sources of mulatto in England as in the United Kingdom. This ethnic group mixed is very efficient to make the count of all total people in England. So in that graph there is the count of the average death in the ethnic mixed as the all people in the death rates. Actually this group is essential to make the count of the deaths in Corona in the pandemic situation. 

If anyone wants to take the project of this counting death rates in the covid pandemic situation in England, it would be very good to approach the vaccination making and population counting in the pandemic situation in Covid 19 situation (Mahase, 2020). In this situation the ex-prime minister Sir Boris Johnson was the victim of Coronavirus in the last stages in pandemic situations. So from there the United Kingdom government has taken the initiative to count the covid death in the pandemic situations. So this research is very much useful to make the covid vaccine and the track record of the population of any country in the pandemic situation.

4.6 Classification

There are so many groups that have been chosen and this is a system of grouping things according to hierarchy and order. Unlike the data used for the classification strategies, it enables the prediction of probability of unknown classes at the various levels and burdens the incomplete databases. To make the classification in the detailed way there have to choose some groups in the covid victim in the United Kingdom in the pandemic situations. In this covid situation there is the hierarchical selection in the covid rates in the United Kingdom as the interesting part in that work. This RStudio is the new part to make the graph of the covid 19 deaths in the United Kingdom. Normally these graphs are plotted in the excel and in the tableau. But here the graphs are made in the R studio (Moorthy, A. and Sankar, T.K., 2020. That is the new and innovative thing in that research. Not only are that, the data collection from the medical reports from the hospitals very much interesting for serving mankind. In this work the normalized graph is the spectacular version in the R studio to make the achievement of the average deaths of the persons in the United Kingdoms.

To measure the classification all the groups are very important to make the graph. But from that group the employers and couples are the4 effective groups in the measurement of graphs. These 2 groups are the crucial parts to make the report on the covid deaths in the pandemic situations. Actually these two groups are taking initiative in the way of economic power and the manpower in the 4 sectors in the United Kingdom (Pagano et al. 2020). Calcification is very much needed to make the report complete and in the accurate way to clarify the groups. If anyone wants to say to distinguish between the groups then there will be a way to distinguish. In the first group there will be the employees who are providing the jobs to the civilians in the United Kingdoms. This is the main pillar in the economic growth in the United Kingdom. 

On the other hand, couples are contributing to the birth of a newborn baby which is the main seed of the manpower in the labor force as well as the armed forces. So this is also an important group in the death rate counting in United Kingdoms. 

These two groups are the main allocation in the graphs which are contributing the main allocation of the death rate in R studio on behalf of their death rate in United Kingdoms. So these two groups are very much important to choose in the given database. 

5.0 Hypothesis testing

In the hypothesis testing is the effective parts in a project. So in this project there is hypothesis testing in the project. To evaluate the hypothesis there is the null hypothesis to make the evolution of data. There the null hypothesis is the death rate of the total death rate is very high and equally divided in monthly death rate and the other factors. But when the experiment is done, then there are seen that the death rate of the parts or the factors are more or less in the high death rate of the monthly tracking of death (Sá, 2020). In the first stages of covid, the high death rate of the people in the first month is very much high as the thrust of the covid virus was unbeatable. So in those months people died at a high rate in a natural way. In this graph there is the total death rate of the United Kingdom in the pandemic situation. This above figure is the monthly database of the deaths in the United Kingdom as the killings of coronavirus is very high. 

This given database is the source of normal distribution of the points which are posted in the codes as “qqnorm” in the codes in the R studio. Actually this is the normalization factor in the death rates of the civilians in the United Kingdoms. So this graph is normally distributed on the basis of the given points of the database of the death rate in United Kingdoms. These points are the paraired in the graph of the given database. This is paired because there are the header variables and the dependent variables in these projects. To accomplish the projects there is a need for the headers data as the total death and the dependent data as the monthly deaths and the partial deaths in the database (Silberstein, M., 2020). These death rates are very scary to analyze the corona attack symptoms in the world. So this hypothesis is partially true in the making database. In this null hypothesis there was a talk about the equal distribution of the death rates in the United Kingdom. But by seeing the result of the graph in R studio there is a small or high deflection in the total death points in the graph. This minimal deflection implements the high deflection in the real cases of covid in United Kingdoms. This kind of graph is the evidence of rejecting the null hypothesis in actual cases. This small defection will vary in the graphs in high ratting. So this can be said that the null hypothesis is on the way to a heavy rejection case. In there the 5 percent is the chance to match the hypothesis from the reality and in the graph. 

6.0 Regression

This above figure is the main coding as the program in the R studio as the script in the regression is counted in the normal factors of the employers group and in the covid 19 deaths in pandemic situations (Viner et al. 2020). In the first there will be the employer’s death curve in the R studio code. After that there will be the two plots which are based on the couples with respect to singles and managers with respect to the employers. In the above there are taken 3 graphs in the same code. But in the given scenario R² is needed. So in the regression model there are taken only the two graphs as the R*R as the R² in the given scenario. 

According to the given figure, plotting for regression between singles and couples is done by extracting the final data set according to the given format.

In this above figure, there is the linear regression in the scattered plot of singles and couples. This is liner because the maximum points are in the linear case. If the reader sees properly in the graph there will be a great shadow in the linear movement in the graphs (Torr et al. 2020). So in that case this linearity is counted in the normalized version or in the assumption version in the graph. This graph is not logistics carve due to the heavy points are on the “S” points or near to the “S” print of the curve in the R studio platform. 

Here, it gives an import coding section to evaluate its scatter plots within managers and employees which shows 10000 to 20000 according to 0 to 8000 employers’ collection. 

On the other hand this is also the linear curve in the case of managers and employers in the covid attack. These two are the regression model of the curves as the R² model. This is linear because the heavy impact is on the linear impact on the curve in the R studio. From the given database the impacts are on the linear because the covid attack to the civilians in the United Kingdom is on the Geometric progression (Torjesen, I., 2020). Due to the R² testing in the data regression so two graphs are taken for the R² as the R*R regression. In this case the S curve is not possible in the pandemic death rates. In maximum cases there are the linear regression in the Pandemic situation in any kind of covid death rates. 

7.0 Source Code:

attach(u2174218_ds7006_cw2_data851)

library(fBasics)

install.packages("fBasics")

#QQ Plot Source Code

# For employers

head(u2174218_ds7006_cw2_data851)

qqnorm(u2174218_ds7006_cw2_data851$Employers)

#couples

head(u2174218_ds7006_cw2_data851)

qqnorm(u2174218_ds7006_cw2_data851$Couples)

qqline(u2174218_ds7006_cw2_data851$Couples,col = "orange")

#Employers

head(u2174218_ds7006_cw2_data851)

qqnorm(u2174218_ds7006_cw2_data851$Employers)

qqline(u2174218_ds7006_cw2_data851$Employers,col = "Yellow")

#EthnicGroup: Black

head(u2174218_ds7006_cw2_data851)

qqnorm(u2174218_ds7006_cw2_data851$`EthnicGroup: Black`)

qqline(u2174218_ds7006_cw2_data851$`EthnicGroup: Black`,col = "Black")

#EthnicGroup: Mixed

head(u2174218_ds7006_cw2_data851)

qqnorm(u2174218_ds7006_cw2_data851$`EthnicGroup: Mixed`)

qqline(u2174218_ds7006_cw2_data851$`EthnicGroup: Mixed`,col = "Green")

#EthnicGroup: White

head(u2174218_ds7006_cw2_data851)

qqnorm(u2174218_ds7006_cw2_data851$`EthnicGroup: White`)

qqline(u2174218_ds7006_cw2_data851$`EthnicGroup: White`,col = "Blue")

#Total Deaths

head(u2174218_ds7006_cw2_data851)

qqnorm(u2174218_ds7006_cw2_data851$`Total Deaths`)

qqline(u2174218_ds7006_cw2_data851$`Total Deaths`,col = "Red")

#regressions

head(u2174218_ds7006_cw2_data851)

plot(Couples, Single)

#SCATTER DIAGRAM IN BETWEEN managers and employees

#head(u2174218_ds7006_cw2_data851)

plot(Managers, Employers)

#SCATTER DIAGRAM IN BETWEEN managers and employees

plot(Unemployed, Students)

8.0 Conclusions

The England leaders would be hailed as geniuses. But it turns out that wasn't the best way to fight this virus and they had to turn around. This meant that more effective gear adjustments were made too late. Unfortunately, many people in the UK live close to each other in large cities. Ideal for air sickness. It is important to get the Covid-19 vaccine. People who got the first two shots should get a third boost. Vaccinated people can sometimes become infected with Covid 19, in which case the disease is usually mild and the probability of death is low. 

Reference list

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