The year, 2020, could only be defined by COVID-19 that forced the world to shut its doors and face a lockdown. Most of the countries witnessed a large number of cases resulting in nearly two million people dying worldwide.
The pandemic compelled governments to stop major economic activities that led to markets running at an all-time low. Citizens of the world resorted to using technology to curb the spread of the deadly virus and keep track of its changes.
One of the most popular technologies that many countries deployed and even made compulsory involved contract-tracing applications. These were used to monitor people who had tested positive for the virus and track their movement, along with informing those who had come in contact with them and providing necessary medical help.
Apart from such apps, health officials in various countries generated large amounts of data related to COVID-19, which were used to understand how it was spreading and learn how to control it. Artificial intelligence (AI), machine learning (ML) and blockchain technology have played a major role in this.
How data analysis can help
Data analysis related to diseases and pandemics has been in existence since 1850 when John Snow used urban design to examine how cholera was spreading. Studying current data trends can help in understanding how the spread of future diseases can be reduced and even prevented.
Today, with evolved technology and increased population, data has transformed into big data, which are, essentially, large amounts of data that are difficult to sift through and analysed manually. Instead, AI can be used to examine this data, find patterns in them and make recommendations accordingly. Data collected from medical records, health professionals, search engines and social media can be used to learn the trends of a pandemic and provide effective solutions. If used during the initial stages, AI and ML can help keep the virus contained in a particular area.
There were reports that said that an AI company from Toronto called BlueDot, which uses ML to examine outbreak of diseases, had alerted various countries and governments about an increase in pneumonia cases in Wuhan, China, on 30 December 2019. After nine days, the World Health Organization officially declared the existence of COVID-19.
Technology in health
These technologies are already in use to make predictions and recommendations for various products and services like OTT platforms, social media and search engines. By using vast amounts of medical data, these can make predictions about any disease and help in avoiding a pandemic.
Using Natural Language Processing algorithms, these technologies can screen various news reports, healthcare reports and terms used in search engines in several languages. This can help authorities understand how different countries are dealing with such diseases. It can also help them predict whether trade, travel and socialising could worsen a disease’s effects. ML models can also be used to predict how certain diseases can affect a person by analysing their medical records. AI can also be used to find appropriate treatments for diseases.
Predictions by such models are also highly accurate. For example, Metabiota, a company specialising in infectious disease management, had predicted that by 3 March, 2020, there would be a total of 1,27,000 COVID-19 cases in the world. The actual number was just 30,000 less than that.
If there is a concern for privacy for patient data and identities, anonymised data can be fed into these technologies. Or blockchain technology can be used for data handling with automatic data collection. Here data can be stored most securely, which can be made available at any time to the authorities concerned. Blockchain can also develop a decentralised surveillance system, so that there is no single authority controlling the data.
Private firms, governments and health officials need to work together to fight deadly diseases like COVID-19. The technologies mentioned in this article have many applications in various sectors like business, entertainment and education; they can also help in the prevention and prediction of any future disease when used appropriately.