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Breaking the COVID-19 Chain with Data Analytics

Breaking the COVID-19 Chain with Data Analytics

The Coronavirus Infectious Disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is posing a challenge to humanity. It is predicted that global GDP could shrink by 3 percent in 2020 due to this pandemic, instead of growing a projected 3.3 percent (I.M.F.). The overall impact on our global economy could go up to a staggering figure of 9 Trillion USD(I.M.F)

Technology has always been a strategic instrument in providing ways to improve people’s lives and bring optimization and growth for businesses. This pandemic has triggered an unprecedented demand for digital health solutions. The world witnessed China successfully suppressing the spread of COVID-19 using high-tech IT systems such as thermal camera-equipped drones and advanced facial recognition technologies that monitored and controlled masses and other sophisticated technologies. 

So, how could Teradata help communities in Breaking the Chain of COVID-19?


Through many decades, Teradata remained part of a perpetual cycle of advancement. We believe that using technology to fight back is inevitable.

To place an effective defensive line we must first understand the overall life cycle of spread, as well as the contributing and control factors of COVID-19.
Based on the COVID-19 lifecycle spread view, we believe that the following are top challenges that need to be addressed imminently:

  • Delayed Identification of high-risk areas, spreaders and asymptomatic patients. If these risk factors are not identified in early stages of the fight, they could fuel the exponential growth of positive COVID-19 cases.
  • Mobility & Proximity. The primary reason for exponential growth of COVID-19 is that timely and accurate information is not being disseminated to at-risk individuals. This allows them fall, unknowingly, into the proximity of an infectious zone or person. 


The top three measures of Geo Risk Profiling, Individual Risk Profiling and Spread Prediction through Modeling & Simulation (M&S), would address the challenges outlined above and ensure helpful insight. The following figure shows the approach, from left to right, of intended data sources leading to actual outcomes.


The solution is primarily analytics-driven, covering a set of modeling use cases, which form an early warning ecosystem against the spread of COVID-19. These cases could be mapped with the following three top business outcomes:

  • Early identification of COVID-19 cases
  • Informed mobility
  • Effective healthcare outreach and administration
Bringing it All Together
  • Proactively identify and geo fence the high-risk zones through Geo-Profiling. Identify emerging risks and indicators through Text Analytics. Perform causal analysis through Pathing and Classification techniques, etc.
  • Supervise the spreaders. Know the spreaders and break the chain by monitoring and restricting their mobility. Guide and recommend the un-infected individuals through Profiling, Text Analysis, Segmentation, Social Network, A/B Party, Affinity, Home/work location Analysis, and Pathing.
  • Know the math of COVID-19. Understand the behavior of the spread and ensure that any proactive and preventative measures taken are effective and efficient to break the chain and flatten the curve through modelling and simulation.

Teradata’s capability around Data Science-driven analytical spread and control of the ecosystems is what will proactively answer the most critical questions. In leveraging the top eight use cases outlined in the figure above, governments and organizations will create understanding and pave the way for timely and optimized preventive and control measures.

Our world is seeing this level of epidemic outbreak for the first time. Unfortunately, it will not be the last time. So, setting up the right analytical foundation to break the growth now is a good investment and will also save lives and our economy in the future.

Portrait of Bilal Khan

Bilal Khan

Bilal Khan is member of Teradata Analytics leadership team in Teradata Global Delivery Center (GDC) leading the Advance Analytics teams across GDC Centers. Prior to Teradata he has been working in Telecom, Retail and Consulting domain enabling businesses to drive decisions through high end Data and Analytics. His major expertise is developing strategies in domains like improving analytics maturity, services and solutions development, market outreach and GTM. With his core team, he works on designing and architecting analytical solutions on Teradata Vantage, SAS, and Open Source environments and deliver it with excellence ensuring overall business value and best possible ROI. Currently involved in R&D of multiple analytical solutions for controlling the spread of COVID-19 and optimizing the health care and administrative decisions. View all posts by Bilal Khan
Portrait of Kamran Shafi

Kamran Shafi

Kamran is a seasoned data scientist with a PhD in machine learning and AI and more than 15 years of experience working in different industries. He is currently a principal data scientist with Teradata GDC, Pakistan. Prior to that he has worked in several senior data science roles, including as an independent consultant, with the Australian Government and with other academic and research organizations in Australia. Kamran’s expertise includes a range of machine learning, optimization and simulation technologies including deep learning, evolutionary computing, multi-agent systems and reinforcement learning. He is currently leading several data science projects including the one for predicting and containing COVID-19 spread. View all posts by Kamran Shafi

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