As COVID-19 has been widely spread, governments across the globe are working in collaboration with local authorities and health-care providers to track, respond to and prevent the spread of disease caused by the coronavirus, health experts are turning to advanced analytics and artificial intelligence to augment current efforts to prevent further infection.
Data and analytics have proved to be useful in combating the spread of disease, Machine learning’s ability to consider large amounts of data and offer insights can lead to deeper knowledge about diseases and enable health and government officials to make better decisions throughout the entire evolution of an outbreak.
Government health agencies can leverage AI technology in four ways to limit the spread of COVID-19 and others pandemics:
As the global human population grows and continues to interact with animals, other opportunities for viruses that originate in animals (like COVID-19) could make the jump from to humans and spread.
AI and ML can integrate data about known viruses, animal populations, human demographics and cultural/social practices around the world to predict outbreaks.
When previously unknown viruses make the jump to humans, time becomes a precious resource. The quicker a disease outbreak is detected, the sooner action can be taken to stop the spread and effectively treat the infected population. AI can help here as well.
AI provided not only better detection of an abnormal disease event, but was able to do it faster — weeks before traditional disease reporting would indicate a spike in disease.
After a disease event is identified, making informed decisions in a timely manner is critical to limiting the impact. AI can integrate travel, population and disease data to predict where and how quickly disease might spread.
AI to predict disease spread, it can improve the application of current treatment and accelerate the time it takes to develop new treatments. Radiologists are also using AI deep learning — machine learning systems that learn from experience with large data sets — to make better treatment decisions.
Once an outbreak is contained or has ended, governments and global health organizations must make decisions about how to prevent or limit outbreaks in the future. ML can be used here too by simulating different outcomes to test and validate policies, public health initiatives and response plans.
In short, AI permits policy-makers and health leaders to conduct a host of “what if” analyses that will enable them to make data-driven decisions that have an increased likelihood of being effective.
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