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June 2, 2020

The Rise Of ‘Pandemic Analytics’: Using Data To Fight COVID-19

"In recent months, organisations have brought pandemic data gathering in-house to develop their own proprietary intelligence"

By CBR Staff Writer

We’re all operating in unprecedented times due to the effects of COVID-19 on society and our workplaces, writes David Sogn, Associate VP, HCL Technologies.

As society grapples with the public health and economic challenges the virus is causing, businesses forced to realign themselves to this new reality are looking to technology for help. Data analytics in particular is proving to be an ally for epidemiologists, as they join forces with data scientists to address the scale of the crisis.

The spread of COVID-19 and the public’s desire for information has sparked the creation of open-source data sets and visualisations. This in turn has paved the way for a discipline we’ll introduce as ‘pandemic analytics’: the examination of data from multiple sources to derive insights to fight the global outbreak.

Here are three ways pandemic analytics is helping to combat the COVID-19 crisis.

Recommending the Right Response

Decades of cumulative intelligence has proven that early interventions slow down the spread of disease. However, analysis, decisioning and the subsequent intervention can only be effective when we first take into consideration all accessible and meaningful data points.

At Sheba Medical Center in Israel, healthcare administrators are using data-driven forecasting to optimise the allocation of personnel and resources before local COVID-19 outbreaks can even strike. These solutions are powered by machine learning (ML) algorithms which analyse all accessible data about the spread of the disease – such as confirmed cases, deaths, test results, contact tracing and availability of medical resources – and offer predictive insights accordingly.

Although a huge concern, the more a virus spreads, the more data is collected, which we can learn from and act upon. With the right analytics capabilities, healthcare professionals can answer questions such as where the next cluster is most likely to arise, which demographic is most susceptible, and how the virus may mutate over time.

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Offering Crucial Business Insights

From the dynamic world map created by Johns Hopkins’ Center for Systems Science and Engineering, to the simple yet enlightening animations from the Washington Post, the democratisation of data and analytics tools has been used in incredible ways to educate the public.

In recent months, organisations have brought pandemic data gathering in-house to develop their own proprietary intelligence. Some have even set up internal ‘Track and Respond’ Command Centres to guide their employees, customers and broader partner ecosystem through the current crisis. Techniques such as statistical data analysis, control theory, simulation modeling and natural language processing (NLP) can be used to help leadership teams respond quickly to ongoing developments.

Such techniques can help businesses track the scale of potential impacts, performing topic modeling across thousands of publications from international health agencies to news outlets. This can automatically send alerts about key trends and actionable information that the organisation needs to know about.

Data analytics can also help predict when regions critical to the business and its customers will reach peak infection or, conversely, when the situation will improve. Once this information has been gathered, organisations can take the appropriate measures in response to ensure their operations – and those of their customers – can run smoothly.

Developing Vital Healthcare Solutions

Creating new treatments requires data analysis at scale, and this is where artificial intelligence (AI) can play a crucial role. Even before the WHO alerted the wider public about the emergence of coronavirus, an AI system operated by Toronto-based startup, BlueDot detected a similarity between what was then considered a mysterious pneumonia strain in Wuhan, and the 2003 SARS outbreak.

Since then, AI has been used to help diagnose COVID-19 through imaging analysis, decreasing the diagnosis time from CT scan results from about 5 minutes to 20 seconds – in turn freeing up clinicians’ valuable time to focus on treating patients.

AI and ML can also be used to speed up the pharmaceutical development process. Although only one AI-developed COVID-19 drug has reached human clinical trials so far, that’s extremely impressive considering AI has expedited a process that typically takes years. With the world still in urgent need of a COVID-19 vaccine months after the first reported death, automated solutions in the pharmaceutical industry will become a necessity.

The Path That Lies Ahead

As the world continues to feel the impacts of the COVID-19 outbreak, society is looking to technology to provide the tools we need to navigate this unchartered territory. Although we do not know what lies in store in the coming weeks and months, our greatest strength will be in how we share, analyse and derive insights from the knowledge the world has accumulated so far.

As the world’s leading minds work with data scientists to combat the spread of the virus, ‘pandemic analytics’ will pave the way for the leading solutions needed to fight COVID-19.

See Also: AWS Facial Recognition Tool Incorrectly Matches Over 100 Politicians With Criminals

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