GY7702 Project: Comprehensive Covid-19 Data Analysis of Leicester, UK

This project provides a detailed analysis of COVID-19 data in Leicester, UK, from December 2020 to October 2021. It examines new cases as a percentage of the local population, changes in new cases compared to previous weeks, and the average daily number of first vaccine doses administered per week. The analysis identifies trends in infection rates and vaccination progress, highlighting key periods of high and low activity. The project employs Excel for data manipulation and analysis, utilizing formulas and pivot tables to extract meaningful insights. The findings reveal fluctuations in new cases and vaccination rates, providing a comprehensive overview of the pandemic's impact on Leicester.

GY7702 Project on Covid-19

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................2
PART 1............................................................................................................................................2
1.1 Necessary code for each LAD...............................................................................................2
1.2 Merge the information (code of each LAD) with population................................................2
PART 2............................................................................................................................................2
2.1 Presenting new cases as a percentage of the local population in Leicester...........................2
2.2 Changes in the new case as percentage compared to new case...........................................16
2.3 Average daily new first dose in per week............................................................................17
PART 3..........................................................................................................................................18
Discussing the results................................................................................................................18
PART 4..........................................................................................................................................19
Discussion about the approach taken.........................................................................................19
CONCLUSION..............................................................................................................................19
REFERENCES..............................................................................................................................21

INTRODUCTION
From 2020, the pandemic affected the entire world in negative manner and majority of
the countries recorded the highest deaths within this tenure. The present study is based upon the
data extracted from official sites where table details with number of new and cumulative covid-
19 cases as well as people who were vaccinated with their first and second dose from 6th
December, 2020 to 2nd October 2021. The assigned LAD is Leicester and it will first assign the
necessary codes to each region or area in order to extract the data through codes. Further,
determine the percentage of population who suffered from new case within assigned LAD.
Along with this, through formulas it will shows the new cases as a percentage compared to
number of new cases 7 days earlier in the month of July, 2021. Also, the average number of first
dose are administrated per week with the highest number of first vaccination in a month.
PART 1
1.1 Necessary code for each LAD
Enclosed in Excel name with 1.1
1.2 Merge the information (code of each LAD) with population
Enclosed in Excel name with 1.2
PART 2
2.1 Presenting new cases as a percentage of the local population in Leicester
Date reported value
New
case
(perc.
Of
pop.)
12/6/2020 125 0.04%
12/7/2020 142 0.04%
12/8/2020 106 0.03%
12/9/2020 155 0.04%

12/10/2020 143 0.04%
12/11/2020 122 0.03%
12/12/2020 102 0.03%
12/13/2020 103 0.03%
12/14/2020 209 0.06%
12/15/2020 175 0.05%
12/16/2020 170 0.05%
12/17/2020 160 0.05%
12/18/2020 132 0.04%
12/19/2020 142 0.04%
12/20/2020 137 0.04%
12/21/2020 230 0.06%
12/22/2020 143 0.04%
12/23/2020 188 0.05%
12/24/2020 125 0.04%
12/25/2020 89 0.03%
12/26/2020 155 0.04%
12/27/2020 212 0.06%
12/28/2020 203 0.06%
12/29/2020 337 0.10%
12/30/2020 282 0.08%

12/31/2020 251 0.07%
1/1/2021 154 0.04%
1/2/2021 299 0.08%
1/3/2021 299 0.08%
1/4/2021 351 0.10%
1/5/2021 316 0.09%
1/6/2021 334 0.09%
1/7/2021 273 0.08%
1/8/2021 258 0.07%
1/9/2021 210 0.06%
1/10/2021 186 0.05%
1/11/2021 314 0.09%
1/12/2021 379 0.11%
1/13/2021 264 0.07%
1/14/2021 288 0.08%
1/15/2021 284 0.08%
1/16/2021 217 0.06%
1/17/2021 266 0.08%
1/18/2021 319 0.09%
1/19/2021 362 0.10%
1/20/2021 294 0.08%
1/21/2021 263 0.07%

1/22/2021 246 0.07%
1/23/2021 167 0.05%
1/24/2021 104 0.03%
1/25/2021 172 0.05%
1/26/2021 234 0.07%
1/27/2021 232 0.07%
1/28/2021 205 0.06%
1/29/2021 186 0.05%
1/30/2021 142 0.04%
1/31/2021 142 0.04%
2/1/2021 190 0.05%
2/2/2021 180 0.05%
2/3/2021 175 0.05%
2/4/2021 157 0.04%
2/5/2021 130 0.04%
2/6/2021 94 0.03%
2/7/2021 114 0.03%
2/8/2021 147 0.04%
2/9/2021 141 0.04%
2/10/2021 127 0.04%
2/11/2021 145 0.04%
2/12/2021 125 0.04%

2/13/2021 107 0.03%
2/14/2021 103 0.03%
2/15/2021 168 0.05%
2/16/2021 139 0.04%
2/17/2021 126 0.04%
2/18/2021 134 0.04%
2/19/2021 131 0.04%
2/20/2021 93 0.03%
2/21/2021 89 0.03%
2/22/2021 139 0.04%
2/23/2021 118 0.03%
2/24/2021 110 0.03%
2/25/2021 94 0.03%
2/26/2021 96 0.03%
2/27/2021 56 0.02%
2/28/2021 55 0.02%
3/1/2021 87 0.02%
3/2/2021 93 0.03%
3/3/2021 67 0.02%
3/4/2021 59 0.02%
3/5/2021 75 0.02%
3/6/2021 43 0.01%

3/7/2021 54 0.02%
3/8/2021 59 0.02%
3/9/2021 62 0.02%
3/10/2021 70 0.02%
3/11/2021 68 0.02%
3/12/2021 48 0.01%
3/13/2021 42 0.01%
3/14/2021 50 0.01%
3/15/2021 58 0.02%
3/16/2021 63 0.02%
3/17/2021 50 0.01%
3/18/2021 63 0.02%
3/19/2021 54 0.02%
3/20/2021 55 0.02%
3/21/2021 43 0.01%
3/22/2021 52 0.01%
3/23/2021 59 0.02%
3/24/2021 81 0.02%
3/25/2021 58 0.02%
3/26/2021 54 0.02%
3/27/2021 41 0.01%
3/28/2021 40 0.01%

3/29/2021 40 0.01%
3/30/2021 54 0.02%
3/31/2021 46 0.01%
4/1/2021 45 0.01%
4/2/2021 42 0.01%
4/3/2021 44 0.01%
4/4/2021 39 0.01%
4/5/2021 33 0.01%
4/6/2021 58 0.02%
4/7/2021 34 0.01%
4/8/2021 35 0.01%
4/9/2021 51 0.01%
4/10/2021 23 0.01%
4/11/2021 39 0.01%
4/12/2021 46 0.01%
4/13/2021 33 0.01%
4/14/2021 34 0.01%
4/15/2021 37 0.01%
4/16/2021 32 0.01%
4/17/2021 21 0.01%
4/18/2021 24 0.01%
4/19/2021 30 0.01%

4/20/2021 33 0.01%
4/21/2021 28 0.01%
4/22/2021 37 0.01%
4/23/2021 20 0.01%
4/24/2021 21 0.01%
4/25/2021 19 0.01%
4/26/2021 27 0.01%
4/27/2021 23 0.01%
4/28/2021 19 0.01%
4/29/2021 19 0.01%
4/30/2021 11 0.00%
5/1/2021 16 0.00%
5/2/2021 8 0.00%
5/3/2021 20 0.01%
5/4/2021 23 0.01%
5/5/2021 26 0.01%
5/6/2021 24 0.01%
5/7/2021 17 0.00%
5/8/2021 18 0.01%
5/9/2021 21 0.01%
5/10/2021 38 0.01%
5/11/2021 30 0.01%

5/12/2021 12 0.00%
5/13/2021 26 0.01%
5/14/2021 29 0.01%
5/15/2021 21 0.01%
5/16/2021 24 0.01%
5/17/2021 34 0.01%
5/18/2021 22 0.01%
5/19/2021 43 0.01%
5/20/2021 35 0.01%
5/21/2021 31 0.01%
5/22/2021 37 0.01%
5/23/2021 23 0.01%
5/24/2021 40 0.01%
5/25/2021 41 0.01%
5/26/2021 62 0.02%
5/27/2021 54 0.02%
5/28/2021 47 0.01%
5/29/2021 28 0.01%
5/30/2021 34 0.01%
5/31/2021 42 0.01%
6/1/2021 61 0.02%
6/2/2021 51 0.01%

6/3/2021 68 0.02%
6/4/2021 65 0.02%
6/5/2021 40 0.01%
6/6/2021 50 0.01%
6/7/2021 95 0.03%
6/8/2021 74 0.02%
6/9/2021 72 0.02%
6/10/2021 53 0.01%
6/11/2021 66 0.02%
6/12/2021 47 0.01%
6/13/2021 44 0.01%
6/14/2021 69 0.02%
6/15/2021 76 0.02%
6/16/2021 60 0.02%
6/17/2021 56 0.02%
6/18/2021 68 0.02%
6/19/2021 61 0.02%
6/20/2021 47 0.01%
6/21/2021 63 0.02%
6/22/2021 89 0.03%
6/23/2021 81 0.02%
6/24/2021 75 0.02%