NYC Data Science Academy| Blog
Bootcamps
Lifetime Job Support Available Financing Available
Bootcamps
Data Science with Machine Learning Flagship ๐Ÿ† Data Analytics Bootcamp Artificial Intelligence Bootcamp New Release ๐ŸŽ‰
Free Lesson
Intro to Data Science New Release ๐ŸŽ‰
Find Inspiration
Find Alumni with Similar Background
Job Outlook
Occupational Outlook Graduate Outcomes Must See ๐Ÿ”ฅ
Alumni
Success Stories Testimonials Alumni Directory Alumni Exclusive Study Program
Courses
View Bundled Courses
Financing Available
Bootcamp Prep Popular ๐Ÿ”ฅ Data Science Mastery Data Science Launchpad with Python View AI Courses Generative AI for Everyone New ๐ŸŽ‰ Generative AI for Finance New ๐ŸŽ‰ Generative AI for Marketing New ๐ŸŽ‰
Bundle Up
Learn More and Save More
Combination of data science courses.
View Data Science Courses
Beginner
Introductory Python
Intermediate
Data Science Python: Data Analysis and Visualization Popular ๐Ÿ”ฅ Data Science R: Data Analysis and Visualization
Advanced
Data Science Python: Machine Learning Popular ๐Ÿ”ฅ Data Science R: Machine Learning Designing and Implementing Production MLOps New ๐ŸŽ‰ Natural Language Processing for Production (NLP) New ๐ŸŽ‰
Find Inspiration
Get Course Recommendation Must Try ๐Ÿ’Ž An Ultimate Guide to Become a Data Scientist
For Companies
For Companies
Corporate Offerings Hiring Partners Candidate Portfolio Hire Our Graduates
Students Work
Students Work
All Posts Capstone Data Visualization Machine Learning Python Projects R Projects
Tutorials
About
About
About Us Accreditation Contact Us Join Us FAQ Webinars Subscription An Ultimate Guide to
Become a Data Scientist
    Login
NYC Data Science Acedemy
Bootcamps
Courses
Students Work
About
Bootcamps
Bootcamps
Data Science with Machine Learning Flagship
Data Analytics Bootcamp
Artificial Intelligence Bootcamp New Release ๐ŸŽ‰
Free Lessons
Intro to Data Science New Release ๐ŸŽ‰
Find Inspiration
Find Alumni with Similar Background
Job Outlook
Occupational Outlook
Graduate Outcomes Must See ๐Ÿ”ฅ
Alumni
Success Stories
Testimonials
Alumni Directory
Alumni Exclusive Study Program
Courses
Bundles
financing available
View All Bundles
Bootcamp Prep
Data Science Mastery
Data Science Launchpad with Python NEW!
View AI Courses
Generative AI for Everyone
Generative AI for Finance
Generative AI for Marketing
View Data Science Courses
View All Professional Development Courses
Beginner
Introductory Python
Intermediate
Python: Data Analysis and Visualization
R: Data Analysis and Visualization
Advanced
Python: Machine Learning
R: Machine Learning
Designing and Implementing Production MLOps
Natural Language Processing for Production (NLP)
For Companies
Corporate Offerings
Hiring Partners
Candidate Portfolio
Hire Our Graduates
Students Work
All Posts
Capstone
Data Visualization
Machine Learning
Python Projects
R Projects
About
Accreditation
About Us
Contact Us
Join Us
FAQ
Webinars
Subscription
An Ultimate Guide to Become a Data Scientist
Tutorials
Data Analytics
  • Learn Pandas
  • Learn NumPy
  • Learn SciPy
  • Learn Matplotlib
Machine Learning
  • Boosting
  • Random Forest
  • Linear Regression
  • Decision Tree
  • PCA
Interview by Companies
  • JPMC
  • Google
  • Facebook
Artificial Intelligence
  • Learn Generative AI
  • Learn ChatGPT-3.5
  • Learn ChatGPT-4
  • Learn Google Bard
Coding
  • Learn Python
  • Learn SQL
  • Learn MySQL
  • Learn NoSQL
  • Learn PySpark
  • Learn PyTorch
Interview Questions
  • Python Hard
  • R Easy
  • R Hard
  • SQL Easy
  • SQL Hard
  • Python Easy
Data Science Blog > Meetup > COVID-19 Cases, Hospitalisations and Deaths over time in the UK

COVID-19 Cases, Hospitalisations and Deaths over time in the UK

Vallari Shah
Posted on Sep 18, 2022

Overview

The Covid-19 pandemic has changed the world as we know it. For over two years, biologists, data scientists, politicians, and many others have been working to contain the virus and stop or reduce the spread through prescriptive strategies. These strategies included restrictions like  lockdowns, business and school closures, as well as mandates requiring masks and vaccines. While these strategies were considered to be necessary at the time, it is important to recognise the negative societal and business impacts of these measures. Analysis of data to assess timing of lifting the various measures that have been implemented is important to return society to normal.

The UK government published daily rates of COVID-19 confirmed cases, deaths within 28 days of testing positive for COVID-19, hospitalisation and vaccination rates in every region of the country. As a country, it provided some of the most comprehensive testing per capita in the world. I performed an analysis of COVID-19 case rates, death and hospitalisations over time  exploratory data analysis (EDA) techniques in R and using Shiny to display my findings and create an interactive app in which the user can explore this data over time for themselves.

To begin, I obtained UK Covid-19 time series data on cases, deaths and hospitalisation over time. Data collection began on March 1, 2020 and has continued every since. When I obtained the files, they contained data up through September 2021, resulting in 1.5 years of Covid-19 data to analyze. Next I found UK local authority geomapping data from the UK government geoportal website to map the case rates with deaths.

Data analysis

The R-shiny interactive page for this data analysis can be found here.

Cases over time

March 2020

As you can see, if you toggle the dates on the R-shiny page, at the beginning of the pandemic, the deaths initially reported within the database  were limited to the southeast of England, largely in high-population density areas like London, Birmingham and Manchester. As the availability of testing for COVID-19 had not been established as yet, the case data is limited at this time. Due to the exponential rise in cases and the preceding events in Italy a few weeks earlier, the UK went into its first and most restrictive lockdown on the 11th of March 2021.

 

April 2020

By April 2020, deaths had spread across the whole country and were mainly concentrated along areas of high population density. Case counts were not being reported within the application at this time.

June 2020

By June 2020, case counts were being reported more accurately as the availability of testing increased across the country. Death counts had fallen, as had case counts within the UK across all regions, despite easing of lockdowns.

January 2021

However, by winter 2021, both case counts and deaths in all regions had risen. In December 2020, the UK approved its first COVID-19 vaccine and prioritised these for the most vulnerable and elderly in society. Vaccination was performed in a stepwise fashion to ensure availability of vaccines for the most vulnerable. The UK went into a second short lockdown in November 2020 and then into a third lockdown in January 2021 as cases, hospitalisations and deaths all continued to rise.

August 2021

As vaccinations continued to cover the population with a relatively good uptake across the population, a clear break can be seen. Case counts continued to rise by August 2021, but deaths remained relatively low. As a result, further lockdowns were not instigated within the UK, though some mitigation measures continued. Although further data is not shown, the omicron variant and further sub-variants have shown a similar disconnect between case counts and rates of death within the UK and the world. This is thought to be due to the fact that, while these variants are more infectious, they are  less deadly than the previous variants.

Hospitalisation over time

As you would expect, hospitalisation and deaths followed a clear correlation over time in the UK. As COVID-19 primarily causes respiratory issues, the severity of COVID-19 illness can also be seen through the numbers of mechanically vs non-mechanically ventilated patients due to COVID-19 in UK hospitals over time through the interactive map on R-shiny. We show that, of the patients who needed hospitalisation for COVID-19, a higher ratio of patients needed mechanical ventilation in the first peak of COVID-19 in the UK compared to the second peak. It is, however, possible that this ratio is also skewed during the first peak due to medical advice from China where the first cases were seen, advising that mechanical ventilation is better for management of COVID-19 than positive airway pressure. However, by the second peak, this advice had been shown to be inaccurate, and patients were managed with a variety of measures including positive airway pressure and mechanical ventilation if needed. This demonstrates that although you can look at the data in isolation, domain specific knowledge can also help interpret the data that is being generated.

 

Conclusions

  • In the UK, compared to the early part of the pandemic, the case counts and deaths from COVID 19 now appear lower than what had originally been reported.
  • This is likely to be due to significant proportion of the population who have been vaccinated or previously contracted the infection.
  • This is also seen in the data comparing case counts and hospitalised patients.
  • Although data is not shown after September 2021, new variants such as Omicron and its sub-variants have demonstrated an even higher disconnect between case counts, mortality, and hospitalisation.
  • The data supports the re-opening of both businesses, public spaces and schools as mortality and morbidity from COVID-19 approaches that of other respiratory illnesses such as Influenza.

Future Work

  • For further analysis, data should be broken down into different age groups.
  • Hospitalisations for each area should also be compared to vaccination rates and previous infection rates for each area to evaluate the effect of vaccination.
  • Previous rates of infections should be evaluated in each area compared to current rates to see if previous infection is proving to be more protective than vaccination for the new variants of COVID-19 by area.
  • Multivariate analysis of all measures employed during COVID-19 should be utilised using different data-sets available in the UK

Data sources

  • https://coronavirus.data.gov.uk/
  • https://www.geoportal.statistics.gov.uk/

 

About Author

Vallari Shah

View all posts by Vallari Shah >

Related Articles

Capstone
Catching Fraud in the Healthcare System
Data Analysis
Car Sales Report R Shiny App
Data Analysis
Injury Analysis of Soccer Players with Python
Capstone
Acquisition Due Dilligence Automation for Smaller Firms
R Shiny
Forecasting NY State Tax Credits: R Shiny App for Businesses

Leave a Comment

No comments found.

View Posts by Categories

All Posts 2399 posts
AI 7 posts
AI Agent 2 posts
AI-based hotel recommendation 1 posts
AIForGood 1 posts
Alumni 60 posts
Animated Maps 1 posts
APIs 41 posts
Artificial Intelligence 2 posts
Artificial Intelligence 2 posts
AWS 13 posts
Banking 1 posts
Big Data 50 posts
Branch Analysis 1 posts
Capstone 206 posts
Career Education 7 posts
CLIP 1 posts
Community 72 posts
Congestion Zone 1 posts
Content Recommendation 1 posts
Cosine SImilarity 1 posts
Data Analysis 5 posts
Data Engineering 1 posts
Data Engineering 3 posts
Data Science 7 posts
Data Science News and Sharing 73 posts
Data Visualization 324 posts
Events 5 posts
Featured 37 posts
Function calling 1 posts
FutureTech 1 posts
Generative AI 5 posts
Hadoop 13 posts
Image Classification 1 posts
Innovation 2 posts
Kmeans Cluster 1 posts
LLM 6 posts
Machine Learning 364 posts
Marketing 1 posts
Meetup 144 posts
MLOPs 1 posts
Model Deployment 1 posts
Nagamas69 1 posts
NLP 1 posts
OpenAI 5 posts
OpenNYC Data 1 posts
pySpark 1 posts
Python 16 posts
Python 458 posts
Python data analysis 4 posts
Python Shiny 2 posts
R 404 posts
R Data Analysis 1 posts
R Shiny 560 posts
R Visualization 445 posts
RAG 1 posts
RoBERTa 1 posts
semantic rearch 2 posts
Spark 17 posts
SQL 1 posts
Streamlit 2 posts
Student Works 1687 posts
Tableau 12 posts
TensorFlow 3 posts
Traffic 1 posts
User Preference Modeling 1 posts
Vector database 2 posts
Web Scraping 483 posts
wukong138 1 posts

Our Recent Popular Posts

AI 4 AI: ChatGPT Unifies My Blog Posts
by Vinod Chugani
Dec 18, 2022
Meet Your Machine Learning Mentors: Kyle Gallatin
by Vivian Zhang
Nov 4, 2020
NICU Admissions and CCHD: Predicting Based on Data Analysis
by Paul Lee, Aron Berke, Bee Kim, Bettina Meier and Ira Villar
Jan 7, 2020

View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day ChatGPT citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay football gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income industry Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI

NYC Data Science Academy

NYC Data Science Academy teaches data science, trains companies and their employees to better profit from data, excels at big data project consulting, and connects trained Data Scientists to our industry.

NYC Data Science Academy is licensed by New York State Education Department.

Get detailed curriculum information about our
amazing bootcamp!

Please enter a valid email address
Sign up completed. Thank you!

Offerings

  • HOME
  • DATA SCIENCE BOOTCAMP
  • ONLINE DATA SCIENCE BOOTCAMP
  • Professional Development Courses
  • CORPORATE OFFERINGS
  • HIRING PARTNERS
  • About

  • About Us
  • Alumni
  • Blog
  • FAQ
  • Contact Us
  • Refund Policy
  • Join Us
  • SOCIAL MEDIA

    ยฉ 2025 NYC Data Science Academy
    All rights reserved. | Site Map
    Privacy Policy | Terms of Service
    Bootcamp Application