How Big Data and AI can support the challenges faced with COVID-19
The emergence of COVID-19 has created an unprecedented public health crisis. In China, where the virus first appeared, the nation quickly utilises its existing big data systems to support in the battle of containing the virus as much as possible. Big data and artificial intelligence professionals can collaborate with public health members to measure and monitor new cases, support with the projecting the spread of the virus and the development of new isolation measures.
Pandemic refers to a disease that will commonly spread exponentially, with an infection level that exceeds the rate of recovery. Health members can use data and computer modelling systems from clinical data to forecast patterns and the trajectory of the pandemic. The significant challenge comes in measuring the spread across communities. Big data tools may provide considerable support in supporting the science of monitoring community spread. For example, calculating the Ro (the rate of a disease spreading in a given population) is complex in an ongoing pandemic as generating an accurate figure requires accounting all untested individuals. Artificial intelligence and big data information surrounding people and their lifestyle can support the development of a range of models and potential scenarios.
As the pandemic progresses, clinical data will be vital in determining what treatment methods are the most effective. There are multiple variables that need to be considered but AI can help calculate which variables are impacting patient outcomes and what techniques are working for the average individual. AI can be implemented to track and assess effective treatment methods for medical professionals treating individuals with heart disease or diabetes, preexisting conditions that make the prognosis for COVID-19 poor. Big data insights may reveal patient outcomes influenced certain variables such as location, income or other socioeconomic factors. This information could be vital to health professionals in improving treatment methods.
The importance of analytics
In the current crisis, proactive analytics can be used to understand what areas and what facilities need more equipment. The existing situation involves a high demand for tests and AI could support us in understanding which locations need tests more urgently than others, by using a specific set of measures. A proactive analytics system could enable an efficient identification plan, distributing tests to areas that are suspects of having a higher impact level.
Proactive analytics can support health professionals in determining high-risk patients that require additional support or testing to maintain safety.
The path of COVID-19 is near impossible to predict completely as official decisions will have a significant influence on shaping its path. These decisions, however, can be influenced by applying big data testing procedures in coordination with public health professionals. The technology industry, big data and the implementation of AI can all support our response to health challenges.