  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.
