Timeline

How AI supported the fight against COVID-19

As we emerge from the pandemic and adjust to the ‘new normal’, AI Magazine reflects on how AI-enabled technology supported the fight against coronavirus

DEC 2019

Early detection BlueDot used AI and its ability to continuously review data sets, such as news, airline ticket sales, demographics, climate data and animal populations. On 31 December 2019, BlueDot detected what was then considered an outbreak of pneumonia in Wuhan, China and identified the cities most likely to experience this outbreak.

FEB 2020

High hopes for AI Just before the World Health Organisation (WHO) declared the coronavirus outbreak a global pandemic, the press and the scientific community echoed the high hopes that data science and AI could be used to confront coronavirus and "fill in the blanks" still left by science.

MAR 2020

Supporting efforts in China Known for its advances in the AI field, China were well equipped to utilise AI as it helped fight the pandemic. AI was used to speed up genome sequencing, make faster diagnoses, carry out scanner analyses or, more occasionally, handle maintenance and delivery robots.

MAR 2020

Enterprises supporting the efforts with AI DeepMind – a subsidiary of Google's parent company, Alphabet – shared its predictions of coronavirus protein structures with its AlphaFold AI system. IBM, Amazon, Google and Microsoft also provided the computing power of their servers to the US authorities to process very large datasets in epidemiology, bioinformatics and molecular modelling.

JAN 2021

Using AI to distribute the vaccine Just shy of a year after COVID-19 was declared a pandemic, countries began to roll out their vaccine programmes. AI proved helpful, as it could be applied to improve understanding on which populations to target to curve the pandemic sooner and adjust both supply chain and distribution logistics to ensure the most people get vaccinated in the least amount of time.

FEB 2021

Creating COVID vaccines candidates with AI A team at the Viterbi School of Engineering at the University of Southern California created an AI framework that significantly speeds-up the analysis of COVID vaccine candidates and also finds the best preventative medical therapies. This came at a time when more and more COVID mutations were emerging, bringing existing vaccines’ efficacy into question.