Visual Data Analysis and Simulation Prediction for COVID-19

  title={Visual Data Analysis and Simulation Prediction for COVID-19},
  author={Baoquan Chen and Mingyi Shi and Xingyu Ni and Liangwang Ruan and Hongda Jiang and Heyuan Yao and Mengdi Wang and Zhenhua Song and Qiang Zhou and Tong Ge},
  journal={International Journal of Educational Excellence},
The COVID-19 (formerly, 2019-nCoV) epidemic has become a global health emergency, as such, WHO declared PHEIC. China has taken the most hit since the outbreak of the virus, which could be dated as far back as late November by some experts. It was not until January 23rd that the Wuhan government finally recognized the severity of the epidemic and took a drastic measure to curtain the virus spread by closing down all transportation connecting the outside world. In this study, we seek to answer a… 

Figures from this paper

Visual Data Analysis and Simulation Prediction for COVID-19 in Saudi Arabia Using SEIR Prediction Model

  • Shakira Khan
  • Medicine
    International Journal of Online and Biomedical Engineering (iJOE)
  • 2021
The SEIR model was applied to predict the epidemic situation in Saudi Arabia and evaluate the effectiveness of some epidemic control measures, and finally, providing some advice on preventive measures.

Understanding the COVID19 Outbreak: A Comparative Data Analytics and Study

This paper provides a comprehensive analytical study about the Coronavirus, providing descriptive and predictive models that give insights into COVID-19 impact through the analysis of extensive data updated daily for the outbreak in all countries.

An intelligent forecast for COVID‐19 based on single and multiple features

This paper visually analyze the real‐time data of COVID‐19, to monitor the trend of CO VID‐19 in the form of charts and establishes a logistic growth model to predict the development of the epidemic by using the same data source in the visualization.

Forecasting confirmed cases of the COVID-19 pandemic with a migration-based epidemiological model

The unprecedented coronavirus disease 2019 (COVID-19) pandemic is still a worldwide threat to human life since its invasion into the daily lives of the public in the first several months of 2020.

Forecasting the long-term trend of COVID-19 epidemic using a dynamic model

A new model named Dynamic-Susceptible-Exposed-Infective-Quarantined (D-SEIQ) is proposed, by making appropriate modifications of the Susceptibles model and integrating machine learning based parameter optimization under epidemiological rational constraints, that could accurately forecast the long-term trend of the COVID-19 outbreak.

Covid-19 spread: Reproduction of data and prediction using a SIR model on Euclidean network.

It is reported here that the SIR model on the Eucledean network can reproduce with a high accuracy the data for China for given parameter values, and can also predict when the epidemic, at least locally, can be expected to be over.

Neural network based country wise risk prediction of COVID-19

A shallow long short-term memory (LSTM) based neural network to predict the risk category of a country and shows that the proposed pipeline outperforms state-of-the-art methods for data of 180 countries and can be a useful tool for such risk categorization.


A literature review is conducted to highlight the contributions of several studies within the domain of COVID‐19‐based big data analysis, and presents as taxonomy of several applications accustomed manage and control the pandemic.

COVID-19 spread forecast using recurrent auto-encoders

  • Radu BecheR. BailaA. Marginean
  • Computer Science
    2020 IEEE 16th International Conference on Intelligent Computer Communication and Processing (ICCP)
  • 2020
The results are promising, showing that the proposed method is capable of making reliable predictions for a 30-days period, and the concept of nearest neighbour countries is introduced to estimate the cumulative number of confirmed cases for any country.

Applications of Big Data Analytics to Control COVID-19 Pandemic

A literature review is conducted to highlight the contributions of several studies in the domain of COVID-19-based big data analysis, and presents as a taxonomy several applications used to manage and control the pandemic.

Data Visualization Analysis and Simulation Prediction for COVID-19

This study uses a mathematical model of infectious disease spreading to calculate some key indicators of the epidemic control, evaluate the effectiveness of some epidemic prevention and control measures, and advise on public policies and living behaviors of the general public, in the mist of this historic event.

A compartmental model for the analysis of SARS transmission patterns and outbreak control measures in China

Clinical Characteristics of Coronavirus Disease 2019 in China

During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness, and patients often presented without fever, and many did not have abnormal radiologic findings.

Scientists are racing to model the next moves of a coronavirus that's still hard to predict

Beyond China itself, Thailand is the country that most likely will have people who arrive at one of its airports with an infection by the novel coronavirus (2019-nCoV) that has sickened more than

Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19)

  • 2020

Report of the WHO-China Joint Mission on Coronavirus Disease

  • 2019

Data Visualization Analysis and Simulation

  • 2020

Un artículo reciente de expertos en salud de primera línea en China informó de una tasa de mortalidad del 1,4

  • (Guan, et al.,
  • 2020