Introduction

Intelligent systems are innovative and technologically advanced machines that can perceive and respond to the world around them. 

The COVID-19 pandemic is the first global public health crisis of the 21st century. And today, various AI-powered projects based on data science, big data, or Machine Learning (ML), are being used through a broad range of fields to forecast, describe and handle the various scenarios caused by the health crisis.

Medicine, Public Policies, and Health Management

With regards to the pandemic, AI is being implemented and providing results in the following three fields: 

• virus research and the creation of vaccines and drugs
• management of resources and services at healthcare centers
• examination of data to support public policy decisions intended to manage the crisis, such as confinement measures.

The applications of intelligent systems, which include AI techniques related to the present pandemic, such as forecasting the extinction time, probable risk groups, and place of the next outbreak, may lead to a paradigm shift within the healthcare sector. There have also been important studies conducted on the use of intelligent systems in detection of the older versions of coronavirus, such as SARS-CoV.

There are various uncertainties and questions associated with the virus: however, scientific teams continue with their work and researchers find something new each day. DeepMind, a Google-owned AI firm, has scientists working to study the protein structures of the novel coronavirus. This study is essential to understand better how the virus evolves and how to control it. The understanding of the protein structure is also critical to develop a vaccine in combination with the findings of other research projects.

The decisions of lockdowns in the year 2020 were enforced based on data evidence. Data scientist Nuria Oliver is currently working on a pilot project to analyze mobility during the pandemic based on the anonymized and aggregated datasets shared by the Spanish Statistical Institute and telecommunications service providers. “We’ve created a human mobility model to quantify and measure the impact of mobility during a lockdown situation and to understand what type of mobility has been reduced and to make decisions taking into account the data at our disposal,” explains Oliver. In the second stage, both the mobility models and their findings will be evaluated with the SIR epidemiological models, which are used to understand how a pandemic evolves, taking into account the number of individuals susceptible to the disease, the number of individuals infected and capable of spreading the disease, and the number of individuals who have recovered. The third stage of the project comprises the conduction of a survey to understand the situation of citizens, their social behavior, and the economic impact of public decisions. This project clearly demonstrates how societies and public administrations can benefit from AI.

Big data and data science and are proving highly valuable for improving hospital management as well. ML and AI algorithms enable us to diagnose and customize medical care and follow-up plans to receive better results.

Future Leanings from COVID-19 

The main questions surrounding COVID-19 are if and when will things get back to being normal and if we should prepare for fresh waves of the infection. Though no there are no final answers, using data analysis, we have learned a lot about the pandemic and now have access to actionable knowledge for any such crisis in the future. South Korea is a great example of a country that had prepared itself for a third pandemic after the MERS and SARs outbreaks. The country relied on technology to successfully contain the virus as it had all the infrastructures in place using data analysis from the previous outbreaks.