“The world needs to prepare for pandemics in the same serious way it prepares for war.”
This is according to Bill Gates in a lecture for the Massachusetts Medical Society. He said that the sense of urgency when it comes to biological threats is quite lacking.
As a commitment, The Bill & Melinda Gates Foundation recently announced that it will give up to US $ 100 million for accelerating the suppression of the recent 2019 novel coronavirus (2019-nCov) outbreak.
Truly enough, pandemics can as easily paralyze and wreak havoc to our society as waging wars. It is indeed quite puzzling why leaders do not feel the urgency to address the potential of disease outbreak not until the world is already facing one.
What can be done in order to prevent pandemics from spreading? Experts propose that Artificial Intelligence (AI) has a central role.
The role of AI
We are in the age of information, and AI is in the perfect position to leverage Big Data.
However, according to Vulcan, AI is no silver bullet for pandemics. Nonetheless, they said that it can serve as a valuable tool for disease outbreak prevention, detection, and response.
By taking advantage of data and advanced analytics, AI can help us better understand the spread of pandemics and how we can control it.
One specific way that AI can accomplish this is by using predictive modeling. A recent initiative known as AI in Medical Epidemiology (AIME) infuses AI algorithm, epidemiological research, and other data in order to pinpoint the potential epicenter of spreading disease within a 400 meter radius. With this knowledge, health officials can better focus on these critical areas in order to prevent outbreaks.
Another AI-related method in combating pandemics is the use of machine learning computer programs. These programs can map animal species such as bats, profiling them based on similar traits in order to pinpoint which ones can be potential hosts of a disease outbreak.
Barriers
Dr. Jabe Wilson said that while AI has a huge potential for battling pandemics, there are several barriers that need to be addressed first:
- Lack of data
- Incorrect data
- Siloed data
- Formatting issues
- Language barriers
- Incompatible tools
In short, the main problem that stands in the way of AI is also what enables its power: data.
There is a need to harmonize the data we have about diseases since the predictions and conclusions that AI models can make will only be as good as the quality of the data which trained it. This is what Dr. Wilson can the principle of “garbage in, garbage out.”
However, to harmonize data is easier said than done. What Dr. Wilson recommends instead is the establishment of life sciences platforms that will intelligently gather and contextualize the data that will be collected in future. This way, we are making data AI-ready.
For this to materialize, there is, of course, a need to invest in this venture. Hopefully, the current disease outbreak is already enough of a lesson for us to realize the urgency of this matter. We cannot be waiting until millions of lives have already been lost before we begin our preparations.
