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Big Data Pandemic Help   Featured

Big Data Pandemic Help    Austin Kehmeier

As the world continues battling the COVID-19 pandemic, getting the right data needed to fight this disease is a matter of life and death. Governments and responsible agencies are running against time to find the source of information that will help them trace the potentially infected persons and their contacts. However, with a large amount of information from different sources every day, it is hard to determine which is correct from what is not. This is where big data come into place. Big data gives governments insights that allow them to take preventive action against the pandemic. Here is how big data is helping governments and other agencies in the fight against COVID-19.

  1. Large database integration in tracking down possible infections

Countries that have successfully curtailed the spread of the COVID-19 outbreak have taken advantage of big data analytics. According to Taiwanese officials, they were able to map out the person-to-person transfer and stop possible transmission of the virus in the early stages of the outbreak. With the integration of Taiwan’s national health database with the country’s customs and immigration database, tracking the possible infections was made possible through contact tracing. The information at the government's disposal helped track the 14-day travel histories and potential COVID-19 symptoms among the citizens. This information was given to the pharmacies and hospitals across the country to monitor the possible infections. With big data analytics as to the main approach towards the fight, the country avoided total nationwide lockdown. 

  1. Monitoring movement

Big data has been used in different countries to monitor population mobility across the world. Dalberg Data Insights, an organization in Belgium, is an example of how governments have used aggregated and anonymized telecom data in efforts against the coronavirus. Dalberg used data from three leading telecom operators in the country to analyze the human mobility trends. This data was also used to identify the risk of infections in specific regions within the country. The data obtained indicated that the overall human mobility declined by over 50 percent, with some areas registering more during the lockdown. The entire operation has given response teams datasets that they can use to enforce specific measures to limit infections and curb the risk of an outbreak. 

  1. Identifying vulnerable groups

We can only win the fight against coronavirus if the most vulnerable groups are identified in time. Identifying the vulnerable groups allows effective preventive measures to be implemented, infrastructure to be improved, and emergency funding sought in underdeveloped areas. The underprivileged are mostly individuals in high-density areas without adequate running water to wash their hands and low daily wages. With analytics tools, governments can identify these areas within communities and the population in the category. Governments can use primary data collection, satellite imaging, and statistics from national bureaus in such instances. 

  1. Improving clinical trials

With the urgency in developing vaccines for the coronavirus, efficiency in clinical trials is needed now more than ever. With big data, clinical trials operations create faster recruitment and correctly target the right people. Parexal, for example, explores ways of creating large-scale COVID-19 studies that collect data from past observations on the patients under treatment. Such data allows healthcare professionals to make quick and informed decisions that save many lives. Big data is also useful in identifying the patient histories at the testing point and track their progress. 

The coronavirus pandemic has devastated economies driving many people to poverty across the world. Businesses have shut due to the restrictions, and many others are facing bankruptcy. However, with all these challenges, there is still hope that technologies such as big data analytics can offer a solution in tracking the people affected and making the right decisions. 

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Scott Koegler

Scott Koegler is Executive Editor for Big Data & Analytics Tech Brief

scottkoegler.me/

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