COVID-19 pandemic and artificial intelligence possibilities: A healthcare perspective

Abstract

What are the skills and competencies we will need in the post-COVID era? The world economic forum ranks innovation, active learning, and complex problem solving as the top 3 skills which will be useful by 2025. The post-COVID era shall continue to tickle our minds in seeking new solutions to newer problems. A random observation by BlueDot, an artificial intelligence (AI) platform, was the first alert to the world of an outbreak when it registered clustering of an unusual respiratory pneumonia-like disease in December 2019 and January 2020 in China.1, 2, 3 It had spotted the beginnings of what would be known as the Coronavirus Disease 2019 (COVID-19) caused by a novel coronavirus. This was nine days before the World Health Organization (WHO) released its official statement alerting the world to a new threat, the severe acute respiratory syndrome virus (SARS-CoV-2). Its role in spotting the beginnings of the SARS-CoV-2 pandemic is an example of the possibilities of AI in health care and the possibility of pandemic proofing the world in the future. How can we be prepared for similar eventualities in the future? Developing disease surveillance AI-based platforms which can actively monitor and track rising number of cases of a disease would be needed for predicting pandemics.4 Such platforms would perform real-time surveillance of population demographics. They would be required to screen data including an individual’s medical history, professional details and socioeconomic parameters across regions and ethnicities in large subsets of population. This would provide the link between the disease and its possible origins. This will enable us to find the first site where patients are in contact with a positive case. This would require transparency and open data-sharing policies globally. AI is intelligent thought and action using computers. It performs tasks requiring thinking, learning, problem-solving, and decision-making. Machine learning (ML) gives computers the capability to learn without being explicitly programmed. Based on using the data, it lets the computer or the machine to adapt and learn. The computer uses the data set to generate a model or logic, and this output is ML. Predicting trends of diseases locally and globally by AI-based solutions could give a lead time to pandemic proof and prepare. Throughout history, outbreaks of infectious diseases have resulted in pandemics that have ravaged across continents, giving rise to lasting economic, political, and social changes. It has been during these times that new ways of prevention, immunization, and treatment have been evolved. Today as we face the pandemic by the novel Coronavirus, there is again a need for developing innovative solutions. Contextual thinking and historical lessons from the Spanish flu helped us adopt measures such as social distancing and using face masks. The need of the hour is mathematical models that can track the spread of novel pathogens and automation of these tracking tools for online real-time decision-making. By developing, compiling, and analysing data of the infected people, including patient details, their community movement, and public health data, we would be able to predict disease behavior.5 Integrating these data with AI, ML forecasts can be carried out of where and when the disease is likely to spread. Prior notification to these regions may be given in time to make necessary arrangements. Today AI is capable of imitating human intelligence, performing tasks that require thinking and learning, solving problems, and decision-making. In today's era of personalized and precision medicine, data referred to as recreational data are becoming more and more relevant in health care. Multiple sources of data in the form of online communications, social media, and web-based articles may be extremely useful in analysing the growth of infection within a community. Internet of things includes a network of all devices and gadgets being used in our daily life which can monitor and collect vital information. Smartphone applications and wearable devices generate continuous data that can be useful for COVID-19. Contact tracing using smartphone data can help identify people who may have come in contact with a COVID-positive case. Identifying these individuals may limit the spread of COVID-19 by breaking the chain of transmission. But automated contact tracing also carries serious privacy risks which need to be safeguarded.