Visualizing pandemics with calendar heatmaps : a case study of COVID-19 in Malaysia

The COVID-19 pandemic has had a significant impact on Malaysia, with over 4 million cases and 30,000 deaths reported as of January 2023. This has led to a need for new approaches to visualize and analyze COVID-19 data in order to support decision-making and public health interventions. The chapter proposes a calendar heatmap visualization approach for COVID-19 data in Malaysia where it allows users to easily compare different metrics, such as daily cases and deaths across different time periods. This can be helpful for identifying trends and patterns in the spread of the virus, as well as for understanding the impact of different interventions. The proposed approach is implemented as a webbased system using the D3.js algorithm. The results showed that the calendar heatmap visualization approach was effective in helping users to understand COVID-19 trends and patterns. It could be used to support a variety of decision-making processes, such as planning vaccination campaigns, allocating resources, and implementing public health interventions. The approach could be extended to include additional metrics, such as the number of tests and recoveries, to support predictive analytics using machine learning models. It is a promising new tool for analyzing pandemic data as it is effective in identifying trends and patterns, and has the potential to be expanded to support a variety of decision-making processes in other types of pandemics such as HIV-Aids and influenza. It can be accessed by a wide range of stakeholders, including government officials, healthcare workers, and the general public.

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