Bio:My name is Hammad Nadeem and I am 17 years old.I am currently doing my A levels at a college in Karachi.Due to my interest in Data Science,I have completed many online courses on Data Analysis.By using what I learned from those courses I analysed the data that we currently have for COVID-19 to find out an unusual positive correlation between the indicators of living standards and the maximum infection rate of the Virus.
Who is more vulnerable? Developed vs Developing Countries
Whenever there is a discovery of a new disease or analysis of of a previously existing one, it is believed that countries with a poor standard of living will suffer the most from it due to insufficient and deficient health systems and lack of awareness.Be it Cancer, Hepatitis,Tuberculosis or Diabetes, the number of patients and the number of deaths due to these diseases is higher in Developing Countries when compared to Developed Countries.
This, however, does not remain the same for the latest Pandemic in the world ,the novel ‘COVID-19’ also known as Coronavirus.
Data Analysis of the number of cases per day and the indicators which determine how developed a country is and also how happy its citizens are confirms this odd phenomena.
The labels for the X axis below are indicators of the extent of a countries development.The higher the value for a country in the X axis directly means that the country is more developed.
The label for the Y axis below is the maximum infection rate, and as can be seen there is a positive correlation between the x and y axis I.e the more developed a country is, the higher the infection rate is.
The Data Analysis provides us with confusing results.It is expected that if a country is more developed, they must have a better health system, a higher educated population and hence a higher awareness of diseases, its symptoms as well as the precautions.Which increases the country’s ability to cope up with the disease.In this pandemic it seems as if the tables have turned,the reasons for which are not completely clear but if we were to speculate, we could give three reasons for such results:
1) Age Structure : Developed countries have a lower younger
population due to higher awareness of family planning, which is why they have a higher old aged population (ages 65+ according to WHO).The older
population is more vulnerable to the disease due to pre-existing illnesses and a weakening immune system.
2) Women at work:Most Developing Countries, especially countries in the South East Asia Region have a very high proportion of women who are housewives (In Pakistan 79.4% of women are housewives according to (Healthbridge) and hence have limited exposure to other people outside their homes, which significantly decreases the chances of them passing on the Virus.
3) Testing:It is a known fact that as the number of tests go up, the number of cases reported coincidentally go up too.One could argue that the reason for more cases in the Developed countries is due to more tests per million than other Developing Nations, but when we consider deaths per million we are presented with the real picture, hundreds of thousands of cases may go unreported but it’s not possible for that many deaths to not be recorded.The UK, at the time of writing, has 610.98 deaths with a population of 66.65 million whereas Pakistan only has 28.44 deaths per million with a population of 212.2 million people.
As the Virus is still only a few months old, there is a lot that we do not know about it, hopefully we will be able to derive scientifically backed reasoning for the Virus’s unusual patterns soon.
1) Data for the number of cases is from https://coronavirus.jhu.edu/map.html (Johns Hopkins University)
2) Data for World Happiness Rating is from https://worldhappiness.report/ed/2020/#read (United Nations World Happiness Report 2020)
3) Age Pyramids are from https://www.populationpyramid.net/united-states-of-america/2020/ and https://www.populationpyramid.net/pakistan/2019/ (PopulationPyramid.net)
4)Data about deaths per million is from https://ourworldindata.org/grapher/total-covid-deaths-per-million (Our world in data)