Dive Into the Future of Health With Predictive Analytics
Predictive analytics, a promising tool to combat ‘black swan’ events in the future – The COVID-19 pandemic has generated enormous data that can be harnessed to develop resilient and sustainable healthcare systems to cope with the future global health issues including epidemics.
When the human genome was completely sequenced back in 2000, there was so much hope and excitement to develop personalized medicine based on an individual’s genomic data. Now it has become clear that in the fast-paced and dynamic field of global health, scientists should not just focus on a string of nucleotides while making decisions about healthcare, but must also incorporate a growing set of clinical data to analyse trends, monitor patient populations, manage unforeseen disease outbreaks, and begin to rectify longstanding issues in the healthcare industry. The predictive modelling gathers knowledge from millions of data points about several diseases and syndromes from around the world, it then classifies this data into a taxonomy and applies machine learning to identify relevant cases to accurately detect the potential danger. Thus, predictive analytics will accelerate the understanding of the interplay between external factors and human biology, ultimately resulting in better remodeling of clinical pathways to provide best personalized care.
The major threats to health will come from environmental, socio-political forces and from individual’s social and psychological behaviors. Pressures of over-population will exacerbate the epidemic activity in future resulting in long-term health effects including severe depression in all segments of the population. On the other hand, emerging technologies have enabled characterization of infectious agents more rapidly to produce effective vaccines and potential therapy for associated illness as evident from the current COVID-19 pandemic situation. The COVID-19 pandemic could be a good reference for clinicians, biomedical scientists, data scientists, pharmaceutical industry and policymakers to create a framework cooperatively using predictive analytics for forecasting diseases, formulating action plans, designing diagnostic and therapeutic strategies for prevention and control of public health issues.
Payel Bhattacharjee, Lindau Alumnus 2014
Senior Research Associate at Department of Biophysics, Bose Institute, Kolkata, India