COVID-19 and Data Analytics

As the world grapples with the onset of COVID-19 pandemic, there are various health and economic challenges that we as a society have to face. Organizations and businesses are being realigned to sustain and survive based on the new norms, and we can only look technology for help to adjust to this new reality. Data analytics in particular is a field that is proving to be both efficient and user friendly for epidemiologists as they help data scientists understand and respond to the pandemic crisis.

Artificial Intelligence (AI) and Machine Learning (ML) can be used to speed up the pharmaceutical creation process. As of now, only one AI-developed drug for COVID-19 has reached the human clinical trials. This is quite impressive as technology has been able to speed up a process that generally takes years.

As the pandemic rages, the public is looking for valuable information, which has led to the setting up of visualizations and open-source data sets. This in turn has introduced a discipline termed as pandemic analytics. Analytics is the inspection and accumulation of data from various sources to gain an understanding of a situation, and pandemic analytics is a modern means to fight the spread of disease.

How does COVID-19 Analysis use Data Analytics help?

Following are the three ways as to how pandemic analytics is helping us combat COVID-19 crisis:

• To Plan the Right Response: During the 1850s, London was attacked by an extensive rise in the number of cholera cases. John Snow (founder of modern epidemiology), observed that there were cluster patterns of cholera cases around water pumps. With this discovery, scientists were enabled to leverage the power of data to fight pandemics for the first time, and they focused their efforts towards measuring the risk, recognizing the attack, and developing a suitable response plan. However, one must remember that the examination, decision making, and then intervention can be effective only if all available/suitable data points are taken into consideration. With the spread of the virus, a huge amount of new data is being generated, and this data enables us to learn from and act upon it. With appropriate analytics abilities, healthcare workers have the answers to questions such as where is the next cluster most likely to emerge, which demographics are the most vulnerable, and how the virus can mutate with time.
• To View Hidden Facts: Widely accessible data have led to the sharing of messages and visualizations in a bid to educate the public. The public can quickly learn about how the virus spreads and what can be done to prevent the spread. The combination of data and analytics tools, along with the ability to share information through the internet, has enabled data to be used for the public good. From developing their own proprietary intelligence to set up internal Track and Respond to Command Centers for their employees and customers, organizations are doing it all.
• To Diagnose, Treat, and Cure: Creating healthcare solutions is a challenge that emerges out of analyzing data at scale, and this is where AI plays a vital role. Using automation, AI can not only help manage the virus-related workload, but also free up resources to focus on treating patients.

Conclusion

It is important to remember that technology can provide us with the tools required to help us sustain and prevent ourselves. We have to face what lies ahead, and we can only overcome this challenge if we share, analyze, and derive insights from our shared knowledge. Once the technology is efficiently applied in the direction towards the analysis of this pandemic, we can minimize the impact of this Covid-19.