Authors :
Weiyi Ma; Dongmei Zhang
Volume/Issue :
Volume 6 - 2021, Issue 11 - November
Google Scholar :
http://bitly.ws/gu88
Scribd :
https://bit.ly/3oxfJJz
Abstract :
The new coronavirus pneumonia (COVID-19)
that broke out at the end of 2019 was designated by the
World Health Organization (WHO) as an "emergency
public health event of international concern." In the
process of epidemic prevention and control, big data and
Internet technology have played an important role in the
collection, analysis, and release of epidemic data. The
purpose of the project is to implement a Python-based data
analysis and visualization program for the COVID-19
epidemic. The thesis displays the epidemic situation and
transmission characteristics of the existing data through a
visualization scheme, establishes a dynamic model of
infectious diseases, evaluates the prevention and control
measures of the epidemic situation, and makes
recommendations and early warnings. In addition, to a
certain extent, it can predict the trend of epidemic diseases
and provide reference for epidemic prevention and control
decisions and public behavior.
Keywords :
Novel coronavirus pneumonia; COVID-19; Python; data analysis; data visualization.
The new coronavirus pneumonia (COVID-19)
that broke out at the end of 2019 was designated by the
World Health Organization (WHO) as an "emergency
public health event of international concern." In the
process of epidemic prevention and control, big data and
Internet technology have played an important role in the
collection, analysis, and release of epidemic data. The
purpose of the project is to implement a Python-based data
analysis and visualization program for the COVID-19
epidemic. The thesis displays the epidemic situation and
transmission characteristics of the existing data through a
visualization scheme, establishes a dynamic model of
infectious diseases, evaluates the prevention and control
measures of the epidemic situation, and makes
recommendations and early warnings. In addition, to a
certain extent, it can predict the trend of epidemic diseases
and provide reference for epidemic prevention and control
decisions and public behavior.
Keywords :
Novel coronavirus pneumonia; COVID-19; Python; data analysis; data visualization.
