Data Visualization and Analyzation of COVID-19

Journal of Scientific Research &

Reports
26(3): 42-52, 2020; Article
no.JSRR.56278
ISSN: 2320-0227

Data Visualization and

Analyzation of
COVID-19
Fahima Khanam
1
, Itisha Nowrin
1
and M. Rubaiyat Hossain
Mondal
1*
1
Institute of Information and
Communication Technology, Bangladesh
University of Engineering and
Technology, Dhaka-1205, Bangladesh.
Authors’ contributions
This work was carried out in
collaboration among all authors. Author
FK collected and managed the
data. Authors FK and IN designed the
study and performed the statistical
analysis. Authors FK, IN
and MRHM wrote the original and the
revised version of the manuscript. All
authors read and
approved the final manuscript.
Article Information
DOI: 10.9734/JSRR/2020/v26i330234
Editor(s):
(1) Dr. Karl Kingsley, University of Nevada, USA.
Reviewers:
(1)
Antipas T. S. Massawe, University of Dar Es
Salaam, Tanzania.
(2)
Lívia Garcia Bertolacci-Rocha, Universidade
Federal de Goiás, Brasil.
(3)
Lamiaa A. Madkour, Cairo University, Egypt
Complete Peer review History:
http://www.sdiarticle4.com/review-history/56278

Received 03 April 2020

Accepted 19 April 2020
Published 20 April 2020
ABSTRACT
Since December 2019 the world is
experiencing a deadly disease caused by
a novel coronavirus
termed as severe acute respiratory
syndrome coronavirus 2 (SARS-CoV-
2). The disease
associated with this virus is known as
COVID-19. This paper focuses on
COVID-19 based on freely
available datasets including the ones in
Kaggle repository. Data analytics is
provided on a number
of aspects of COVID-19 including the
symptoms of this disease, the
difference of COVID-19 with
other diseases caused by severe acute
respiratory syndrome (SARS), Middle
East respiratory
syndrome (MERS), and swine flu. The
impact of temperature on the spread of
COVID-19 is also
discussed based on the datasets.
Moreover, data visualization is
provided on the comparison of
infections in males/females which shows
that males are more prone to this
disease and the older
people are more at risk. Based on the
data, the pattern in the increase of
confirmed cases is found
to be an exponential curve in nature.
Finally, the relative number of
confirmed, recovered and
death cases in different countries are
shown with data visualization.
Since December 2019 the world is experiencing a deadly disease caused by a novel coronavirus
termed as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease associated
with this virus is known as COVID-19. This paper focuses on COVID-19 based on freely available
datasets including the ones in Kaggle repository. Data analytics is provided on a number of aspects
of COVID-19 including the symptoms of this disease, the difference of COVID-19 with other
diseases caused by severe acute respiratory syndrome (SARS), Middle East respiratory syndrome
(MERS), and swine flu. The impact of temperature on the spread of COVID-19 is also discussed
based on the datasets. Moreover, data visualization is provided on the comparison of infections in
males/females which shows that males are more prone to this disease and the older people are
more at risk. Based on the data, the pattern in the increase of confirmed cases is found to be an
exponential curve in nature. Finally, the relative number of confirmed, recovered and death cases in
different countries are shown with data visualization.

INTRODUCTION

Enveloped, single stranded positive-sense ribonucleic acid (RNA) viruses named coronaviruses contain
one of the largest viral genomes which are around 32 kbp in length. They can infect humans as well as a
wide range of animals. The 2019 novel coronavirus termed as SARS-CoV-2 caused pneumonia outbreak
in Wuhan, China resulting in the 2019- 2020 coronavirus pandemic declared by World Health
Organization (WHO). It belongs to the Ortho corona virinae subfamily. It is distinct from Middle East
respiratory syndrome (MERS) and severe acute respiratory syndrome corona virus (SARS-CoV). Wuhan’s
Huanan Seafood Wholesale Market trades a variety of live animal species which includes fish, poultry,
marmots, snakes and bats which linked the outbreak. Researchers identified the highly identical genome
similarity between SARS-CoV-2 and bat coronavirus and pointed to bat as the natural host. The infected
patients showed clinical manifestations of dry cough, fever, confusion, sore throat, rhinorrhea, chest
pain, dyspnea, bilateral lung infiltrates on imaging, nausea, vomiting and diarrhea. The disease caused
by SARS-CoV-2 known as COVID-19 can be deadly. This happens when the severity of the disease onset
results in massive alveolar damage with progressive respiratory failure with a 2% case fatality rate.
According to the WHO, an infected patient can spread the virus during close contact and via respiratory
droplets while coughing, talking or sneezing. People can inadvertently transfer the pathogen to a
mucous membrane by touching contaminated surface. Though the virus can be transmitted by the
asymptomatic carrier, it is the most contagious when people are symptomatic. A recent study reports
that for the case of SARS-CoV-2, aerosol transmission may be possible in closed places when there is
longer exposure to the virus. Generally symptoms may arise in patients between two to fourteen days,
with an average of five days. According to the Centers for Disease Control and Prevention, the standard
diagnosis method for the identification of the virus in the patient is by reverse transcription polymerase
chain reaction (rRTPCR) from nasopharyngeal swab. A combination of symptoms, risk factors and a CT
scan showing features of pneumonia can diagnose the infection.

In order to prevent the spread of this infection, the WHO recommends frequent hand washing, keeping
unwashed hands away from the face, social distancing, and covering coughs and sneezes with a tissue or
inner elbow. Some national health authorities recommend masks for the suspects and their caregivers.
So far no vaccine or antiviral treatment is available for COVID-19. In order to stop this pandemic, the
route of transmission of the virus to humans via animals, identification of the reservoirs, the incubation
period of the virus, the characteristics of the susceptible population and their survival rates need to be
identified. The analysis of the clinical information regarding age, gender, source of the virus, incubation
period, transmission route, treatment response will help researchers to develop vaccines against
COVID19. As of 13 April 2020, COVID-19 has affected more than 1,858,800 patients in 210 countries and
territories around the world and has become a major global health concern. This paper analyzes COVID-
19 based on the currently available data. Analytics is provided on a number of aspects of COVID-19
including the symptoms, the difference with other viruses, and the impact of temperature. Moreover,
data visualization is provided on the comparison of infections on male/females, and the pattern in the
increase of confirmed cases and the relative number of confirmed /recovered/death cases in different
countries. The rest of the paper is organized as follows. Section 2 describes the different aspects of
COVID-19 using tabular data. It provides visualization of how the infection has spread across the world
using pie charts and bar charts.

2. FEATURES OF COVID-19

2.1 Symptoms of COVID-19

The common symptoms of COVID-19 are fever, cough, shortness of breath, muscle ache, headache, sore
throat, rhinorrhoea (runny nose), chest pain, diarrhea, nausea and vomiting. The patients will not have
all the symptoms; rather, they will carry different combination of symptoms. In order to find the most
influential symptoms, informatics is provided here using the dataset available in Kaggle repository. Table
1 depicts different combination of symptoms. Note that only the complete data from are used after
removing the null values as a part of preprocessing. It can be seen from Table 1 that majority of the
patients carry only the symptoms of fever which is 33%. Then there are 30.7%

Table 1. Percentage of patients having different combination of symptoms

Symptoms Cases Percentage%

Fever 90 33%
Fever, Cough 47 17%
Fever, Cough, Shortness of 13 4.8%
Breath
Fever, Runny Nose 4 1.48%
Throat Pain, Fever 9 3.33%
Vomiting, Diarrhea, 10 3.70%
Fever,Headache, Cough
Fever, Headache 6 2.22%
Fever, Pneumonia 2 0.74%
Fever, Cough, Sputum 6 2.22%
More than one sign or symptoms 83 30.7%

patients who have more than one sign and symptoms. Among all the symptoms, fever and cough are
found to be the most common, indicating that the combination of fever and cough is one of the major
indicators of carrying this virus.
Using the dataset in we estimated how long it takes for the symptoms to build from the start of
exposure. Table 2 shows the days of incubation period and the associated number of cases. In the
dataset, many records do not have either the exposure start date or the symptoms start date. Probably
many patients could not remember exactly when they were exposed to the virus or when their
symptoms began. Hence, either or both of these dates for those patients were recorded as null.
Considering only the records that have the exposure start date and the symptoms start date, we got 73
cases. Table 2 shows that incubation period of COVID-19 is between 1 to 14 days. Table 2 also shows
that among a total of 73 cases, the highest number of cases is 11 which corresponds to 4 to 5 days. This
is consistent with another study where the authors estimated that in most cases, the coronavirus
incubation period is about 5 days. However, a larger data sample must be studied to confirm the actual
incubation period of COVID-19.

Using the dataset in we estimated how long it takes for the symptoms to build from the start of
exposure. Table 2 shows the days of incubation period and the associated number of cases. In the
dataset, many records do not have either the exposure start date or the symptoms start date. Probably
many patients could not remember exactly when they were exposed to the virus or when their
symptoms began. Hence, either or both of these dates for those patients were recorded as null.
Considering only the records that have the exposure start date and the symptoms start date, we got 73
cases.

Table 2 shows that incubation period of COVID-19 is between 1 to 14 days. Table 2 also shows that
among a total of 73 cases, the highest number of cases is 11 which corresponds to 4 to 5 days. This is
consistent with another study where the authors estimated that in most cases, the coronavirus
incubation period is about 5 days. However, a larger data sample must be studied to confirm the actual
incubation period of COVID-19. people were still not fully concerned about COVID-19. However, the
number of hospitalized patients increased rapidly from the end of January and the beginning of
February when people were already aware of the symptoms of this disease. So after seeing the
symptoms they got hospitalized within one day.

Comparison with Other Viruses

The WHO said that the novel coronavirus originated from China to other countries around the world
does not seem to be as “deadly as other coronaviruses including MERS and SARS”. WHO’s director
general, Tedros Adhanom Ghebreyesus called a briefing on 17 February and said that 80% of patients
with COVID-19 have a “mild disease and will recover” and he also added that “it is fatal in 2% of
reported cases”. In comparison, the 2003 outbreak of SARS had a case fatality rate of around 10% (8098
cases and 774 deaths), while MERS killed 34% of people with the illness between 2012 and 2019 (2494
cases and 858 deaths). However, COVID-19 has so far resulted in more deaths (114,698 as of 13 April
2020) than SARS and MERS combined (1632). In particular, the death rate has increased significantly
from mid-February to date. As of 13 April, 2020, the total number of confirmed cases, deaths and
recovered cases for COVID-19 are 1,858,800, 114,698 and 429,020, respectively. Since many of the cases
are not closed, the death rate cannot be calculated properly. Nevertheless, by calculating the death rate
as a ratio of total deaths to total confirmed cases as of 13 April 2020, we obtain a death rate of 6.17%
for COVID-19.
3. CONCLUSION

The deadly novel coronavirus termed as SARS CoV-2 has caused thousands of deaths across the world
since December 2019. This COVID has been declared as a pandemic and the whole world was not in
more danger after World War II. Since no vaccine or antiviral treatment is available, the WHO has
recommended that infection should be avoided by frequent hand washing, social distancing, keeping
unwashed hands away from the face, and covering coughs and sneezes with a tissue or inner elbow.
Since the number of confirmed cases and deaths are increasing every day, and the virus hotspot has
changed several times, it is very difficult to completely describe the nature of COVID current data. Still
this work provides data analytics and data visualization to descr different aspects of the disease using
the currently available datasets. Based on the dataset used and the data analytics of this paper, it can be
seen that the combination of fever and cough is one of the major indicators of carrying this virus. It is
also found that many patients develop the symptoms within 14 days of exposure. Furthermore, the
currently available data shows that males and elderly people are more affected by the disease. It is also
shown that the number of confirmed infections is much more in countries which have low average
temperature compared to countries with high average temperature. It can be seen that although the
disease started in China, currently China has managed to restrict the spread of the disease. On the other
hand, Italy, Spain and the USA now have very high number of confirmed cases and deaths.

REQUIREMENT ANALYSIS

HARDWARE REQUIREMENTS

 Hardware :Processor Intel dual core and above

 Clock speed :3.0 GHz
 RAM size :512 MB
 Hard Disk capacity :400 GB
 Monitor type :15 inch color monitor

SOFTWARE REQUIREMENTS

 Operating System :Windows XP, Windows 7, Windows

8,Windows 10
 Design :HTML, CSS, JS, Bootstrap
 Application :Python
 Browser :Google chrome, Firefox
 Database :MySQL/Sqlite.
 Documentation :MS-Office