Big Data Analytics VS coronavirus – Artificial Intelligence in the fight against the spread of infectious diseases

Not everyone knows that, when the first cases of death caused by the SARS virus (acronym for Severe Acute Respiratory Syndrome) appeared in the Guangdong province (Canton), China in 2002, the spread of the disease was aggravated by the delay with which prophylaxis measures were implemented to protect the population.

Despite the danger of the virus, in fact, the Chinese authorities did not implement any serious procedure, aimed at containing the infection, until February 2003, when they warned the World Health Organization of the epidemic. The SARS virus, also due to the slowness and poor efficiency with which it was countered, saw some 740 victims worldwide.

This sad page in our history teaches us how important it is, in such cases, to be able to provide a timely response in order to stem the spread of potentially lethal viruses and prevent the risk of pandemics

The lesson learned 17 years ago returns to be of great relevance today, in light of the new health emergency that we face due to the coronavirus infection that is rapidly spreading from Whuan, the capital of Hubei province, in Central China. The number of victims currently registered amounts to 106, while there is talk of almost four thousand infected throughout China. The US Centers for Disease Control and Prevention is currently monitoring 63 confirmed cases of contagion in 22 American states.

Unlike what happened during the SARS epidemic, this time the Chinese authorities were noted to have mobilized more quickly to counter the proliferation of the virus, adopting greater transparency and limiting the movement of their population, made aware of the situation and invited not to leave the country. But above all, what makes the difference today in the containment of the epidemic is the possibility of exploiting the tools that technology makes available to us, also in terms of information and prevention.

In this sense, it is enough to mention what has been achieved by the Canadian start-up BlueDot, specialized in the monitoring of infectious diseases, which managed to raise the epidemic alarm to its customers on December 31, or even before the CDC and the World Health Organization disclosed a public warning notice (issued on the 6th and 9th of January respectively).

Kamran Khan, doctor and CEO of BlueDot, claims to have created his start-up having understood, following his first-hand experience in the fight against SARS in 2002, that the speed with which one reacts to contain the spread of aggressive viruses, like the coronavirus, can make a real difference in terms of lives saved.

The early warning mechanism developed by this start-up, founded in 2014, is based on the use of Artificial Intelligence.

Through Big Data Analytics, the company was able to track and predict in which geographic areas the coronavirus would spread.

Using Natural Language Processing and Machine Learning techniques, airline data were analyzed, as well as reports (written in 65 different languages) of hospital admissions and those relating to diseases of plants and animals, in order to know and anticipate the behaviour of the virus. Using this data, BlueDot, whose team is made up of programmers and specialized doctors, was able to predict, before anyone else, that the infection would spread from Whuan, China, to Bangkok, Seoul, Taipei and Tokyo.

The creation of early warning systems, such as the one described, thanks to the use of AI techniques, bodes well for the near future in an increasingly effective ability to control and combat these malicious pathologies.

Author: Claudia Paniconi | DMBI Marketing Manager Photo by Unsplash

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