Abstract
The novel coronavirus has become a worldwide threat, causing severe acute respiratory syndrome in humans. Epidemiological data studies including their trends and patterns of ongoing cases are needed for a better holistic plan to mitigate the impacts of the COVID-19 pandemic. This exploratory study presents an effort to develop various animated plots of the spread of worldwide COVID-19 disease in sequential time frames from different geographical areas, based on open datasets from Johns Hopkins University using R programming. The animated plot presents different cases obtained from worldwide data and has significant risks in its locality for taking appropriate control actions to adapt to new control measures. The COVID-19 cases data at country and provincial levels in spreadsheets are not sufficiently presented for epidemic situations to take appropriate control measures unless they are visualized in plots using animated plots with daily, monthly, and annual analysis. A large number of static COVID cases present global general information rather than dynamic trends and patterns of COVID cases in the locality. Therefore, dynamic animated plots with lines, bars, and bubble plots are very useful to authorities for the prevention of COVID-19 cases at a global level.
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