Analysis of the Global Data on Covid-19 Pandemic mainly focusing on Bangladesh until 01 September 2021: A case study

Abstract

The objective of this whole analysis is to identify the situation created by covid-19 both in Bangladesh and worldwide by asking some questions stated below in the introduction section. Downloading the data from a trusted online source, analysis was done using Structured Query Language and visualized using Excel and Spreadsheet. The questions were answered accordingly and the steps for analysis were minimized. The data are visualized using bar chart, histogram, control chart and frequency plots.

Keywords -

PostgreSQL, Analysis, Coronavirus, Covid-19, Infected, Death, Vaccinated, Structured thinking

Introduction-

The first human cases of COVID-19, the disease caused by the novel coronavirus, subsequently named SARS-CoV-2 were first reported by officials in Wuhan City, China, in December 2019. Now its September, 2021 and the death toll is still rising due to covid-19. In this study, the main analysis will be:

Bangladesh:

Infected vs Death
Infected vs Population
Likelihood of dying if one contracts Covid-19 in Bangladesh
Infected Per Day
Total Population vs Fully Vaccinated
Total Population vs Vaccinated Once

Worldwide:

Countries with Highest Infection Rate compared to Population
Countries with Highest Death Count per Population
Continents with the Highest Death Count per Population
Making a list of the countries whose percentage of at least once vaccinated by total population is 60% and above
Infected Per Day
Overall total cases, deaths and death percentage

Methods

Data Collection -

The live data was from: ourworldindata.org/covid-deaths. PostgreSQL and Valentina studio were used to do the analysis and then exported the data as Excel file to visualize through Microsoft excel and Google Spreadsheets.

Data Analysis and Visualization -

Bangladesh:

Infected Vs Death

Figure 01: Infected Vs Death

Infected vs Population

Figure 02: Infected vs Population

Likelihood of dying if one contracts covid in Bangladesh

Figure 03: Likelihood of dying if you contract covid in Bangladesh

Here, time was measured in the horizontal axis and in (total deaths/total cases) *100 was used in the vertical axis to identify, after each day, the percentage of total death to total infected and a daily analysis was made to find the likelihood of dying if anyone came in contract with covid in Bangladesh.

Infected Per Day

Following is the daily trend of infected patients due to corona virus from March, 2020.

Figure 04: Infected Per Day

Total Population vs Fully Vaccinated vs Vaccinated Once

Figure 05: Total Population vs Fully Vaccinated vs Vaccinated Once

Worldwide:

Countries with Highest Infection Rate compared to Population

Figure 06: Visualization of the top countries whose total infected to population percentage is 10% and above.

Countries with Highest Death Count with respect to Infected

Figure 07: Visualization of the top countries whose total death to infected percentage is 3% and above in a death to case% by location.

Continents with the highest death count per population

Figure 08: Death count with respect to continents

Figure 09: Death count per total population with respect to continent

Infected Per Day

Figure 10: Total cases by date

Overall total cases, total deaths and death percentage with respect to total infected

Here is a list of the countries whose percentage of at least once vaccinated by total population is 60% and above

Results and Discussion

The charts and tables clearly answer all the questions asked in the introduction part.

Here, all the basic SQL quires to analyse the data downloaded from the link. The numbers were in text format in the downloaded excel file which were converted into decimal numbers using cast in SQL.

Two separate excel files from the source file one containing the affected and death numbers and the other containing about the vaccination data. Both the excel file are connected by date and location.

Structured thinking for the whole analysis. The APPASA (Ask, Prepare, Process, Analyse, Share and Act) steps were followed accordingly.

The findings reported showed that:

• Total infected due to Covid-19 is 1,503,680 and total death count is 26,274 up till September 01, 2021 (as shown in figure 01).

• 0.9% of the total population was infected due to Covid-19 (as shown in figure 02)

• By September 01, 2021, the likelihood of dying due to Covid-19 is 1.74%. (Data shown in figure 03)

• There is a spike in the percentage of infection of Covid 19 in Bangladesh at around July, 2020. This trend is followed in the following year with an almost 0.008% increase. (Figure 04)

• 11.17% and 4.745% of the population of Bangladesh have received the first dose and second dose of vaccine respectively. (Figure 05)

• Seychelles has the highest percentage of infection (21%) on basis of population followed by Andorra (19%) and Montenegro (17%). (Figure 06)

• Vanuatu (25%) and Yemen (18%) has the highest percentage of death to case ratio with respect to location. (figure 07)

• North America has the highest number of deaths (642081) followed by South America (581150). (figure: 08)

• South America has the highest death count per population (27%) followed by North America (19%). (figure 09)

• There is a spike of infected cases at the middle of each month that lasts for 2 months since November, 2020 with a 1-month interval after each spike. (From a stable value of 350,000 to a maximum of 800,000) (figure 10).

Conclusion

Covid-19 has impacted the sociological, economical state of the world as we know it, from an individual basis and well as country-wise From the above visualizations and tables, we can conclude that

• There will be a spike in the infection of Covid-19 in Bangladesh by the end of July, 2022 which can range from around 0.016% to 0.020% of the total population.

• The most amount of death by percentage is happening in the Americas.

• There might be a huge spike in Covid-19 Cases at around the end of October.

Implications

These data can be used at an individual level as well as large-scale to prepare for the necessary precautions during the time when Covid-19 is most likely to cause death and infection. It can also show which countries and continent have the higher chance of contracting Covid.

--Also, a special thanks to my friend, Tazwar Azim Baigh for helping me with the content writing.--