The Escalation of COVID-19

As COVID-19 Coronavirus cases began to escalate in late December of 2019, data analyst companies began to analyze headlines and aggregate data to help monitor working conditions for their employees. When companies such as Tableau began to examine the effects of the virus on their own operations, they stumbled upon a trove of data published by Johns Hopkins University. The university had collected and made public information from various government bodies and agencies such as the Center for Disease Control and Prevention (CDC) and the World Health Organization (WHO).

Inevitable Errors in Data Collection

Unfortunately, even though JHU’s data was made publicly available it was presented in multiple formats which made it messy and difficult to read. Because they were collecting day-to-day reports from nearly 200 countries and agencies, there were some inevitable issues such as double counting, language and translation issues, and nomenclature differences when assembling them into a single data set. An example being the classification of the Vatican and Holy See as two distinct locations when in reality they are one and the same.

Cleaning Things Up

Tableau, which builds data visualization software, was well on their way to tackling these issues. By late February Tableau used their Prep software to clean and compile the data while presenting it in concise and easy to understand visuals. This allows users to easily search and sort confirmed COVID-19 cases and deaths based on a wide variety of countries and other related metrics. There is even the option to download the entire data set so individuals or organizations may perform their own analyses. Breaking down such a vast amount of data and presenting it in easily understood ways also saves users from painstakingly sifting through JHU’s GitHub and downloading data sets individually. 

Breaking Things Down

Taking things a step further, Tableau also introduced a COVID-19 Data Hub that provides an even more extensive range of data revolving around the effectiveness of social distancing, the effects of the pandemic on restaurant and hospitality industries, detailed state and country maps, and much more via a data visualization gallery. There are also links to other credible data sets from various sources that are intended to provide further reading and context to their own data. The data is even available for download in a wide variety of file types, allowing compatibility with various third-party data analysis tools.

The Importance of Data

The question remains, how is this data important and what exactly is it used for? Real-world examples include a healthcare company using Johns Hopkins University’s data to better predict and manage its supply chains, or other companies using it to stay on top of human resource issues with fresh data updated daily. Other companies involved in providing personal protective equipment or testing kits for the virus are using the data to make better informed decisions on where to send supplies at any given time. “By using this data, organizations can contextualize it and make decisions for their own environments," says Steve Schwartz, Tableau’s director of public affairs. This allows a more efficient system for distributing the critically important protective gear and testing kits while helping to avoid caches of supplies sitting unused in areas where they are not needed.

While there may be some privacy concerns, data tracking from things like mobile phones can also be an effective way of monitoring whether high-risk communities are practicing social distancing or not. With this kind of data, there is even the potential to instate some kind of COVID-19 public registry that uses smartphone location data to send real-time notifications and alerts of infections in your vicinity. There would inevitably be quite a few hurdles to instate these kinds of policies but in times of extraordinary circumstances (such as a global pandemic) they could prove useful.

Preparing for the Future

With such an unprecedented amount of data being recorded and aggregated, the COVID-19 outbreak just may be the most visualized ever. Never before has such a vast and detailed amount of data involving a pandemic been collected for easy analysis. This means that current data sets will likely become invaluable in modeling and predicting any possible future pandemic outbreaks. Through tools like predictive analysis and machine learning, governments and organizations can learn how to fine-tune their response across the board and save many lives.

Easing Uncertainty

Another benefit of making this data publicly available is the reduction of uncertainty when making important business decisions. According to Schwartz, "This is a very uncertain situation. We've all never been through anything like this before, and data can help with public understanding. Right now every business decision-maker is facing an unprecedented situation. So, we are taking the view of providing what is useful to help get our country back to functioning."

Advanced Software Tools in the Fight Against COVID-19

With the data from Johns Hopkins University now showing over 2.2 million confirmed COVID-19 cases worldwide and nearly 700,000 in the United States alone, the coronavirus pandemic has proved to be a global public health emergency. However, unlike previous pandemics scientists now have better access to tools that help combat the virus’ spread such as predictive analysis algorithms, machine learning, and improved gene sequencing instruments. When combined with extensive data analysis from companies like Tableau which help organizations make better informed decisions, several new avenues are opened for containing and treating the virus.