COVID-19 Data Analysis and Forecasting: Algeria and the World

07/19/2020
by   Sami Belkacem, et al.
0

The novel coronavirus disease 2019 COVID-19 has been leading the world into a prominent crisis. As of May 19, 2020, the virus had spread to 215 countries with more than 4,622,001 confirmed cases and 311,916 reported deaths worldwide, including Algeria with 7201 cases and 555 deaths. Analyze and forecast COVID-19 cases and deaths growth could be useful in many ways, governments could estimate medical equipment and take appropriate policy responses, and experts could approximate the peak and the end of the disease. In this work, we first train a time series Prophet model to analyze and forecast the number of COVID-19 cases and deaths in Algeria based on the previously reported numbers. Then, to better understand the spread and the properties of the COVID-19, we include external factors that may contribute to accelerate/slow the spread of the virus, construct a dataset from reliable sources, and conduct a large-scale data analysis considering 82 countries worldwide. The evaluation results show that the time series Prophet model accurately predicts the number of cases and deaths in Algeria with low RMSE scores of 218.87 and 4.79 respectively, while the forecast suggests that the total number of cases and deaths are expected to increase in the coming weeks. Moreover, the worldwide data-driven analysis reveals several correlations between the increase/decrease in the number of cases and deaths and external factors that may contribute to accelerate/slow the spread of the virus such as geographic, climatic, health, economic, and demographic factors.

READ FULL TEXT

page 7

page 8

page 9

research
04/16/2020

Coronavirus (COVID-19): ARIMA based time-series analysis to forecast near future

COVID-19, a novel coronavirus, is currently a major worldwide threat. It...
research
12/21/2020

COVID-19 Outbreak Prediction and Analysis using Self Reported Symptoms

The COVID-19 pandemic has challenged scientists and policy-makers intern...
research
06/02/2020

Comparing and Integrating US COVID-19 Daily Data from Multiple Sources: A County-Level Dataset with Local Characteristics

Over the past several months, the outbreak of COVID-19 has been expandin...
research
05/29/2020

Ranking the explanatory power of factors associated with worldwide new Covid-19 cases

Disease spread is a complex phenomenon requiring an interdisciplinary ap...
research
11/16/2020

Critical data analysis of COVID-19 spreading in Indonesia to measure the readiness of new-normal policy

COVID-19 pandemic has become a global issue nowadays. Various efforts ha...
research
07/23/2020

Causal analysis of Covid-19 spread in Germany

In this work, we study the causal relations among German regions in term...
research
04/03/2020

Generating Similarity Map for COVID-19 Transmission Dynamics with Topological Autoencoder

At the beginning of 2020 the world has seen the initial outbreak of COVI...

Please sign up or login with your details

Forgot password? Click here to reset