Digital Public Health Transformation for Noncommunicable Diseases: A Narrative Perspective on the Difficulties and Possibilities.

Abstract

The efficacy and speed of digital public health interventions particularly digital proximity tracing apps that use Bluetooth to track and alert users of possible infection exposures were highlighted by the recent SARS-CoV-2 pandemic. Digital proximity tracings, supported by prominent institutions like the European Union and the World Health Organization, demonstrated the potential of digital public health. Noncommunicable diseases (NCDs), which cause the great majority of health care costs and premature disability-adjusted life years lost, must be addressed as the world shifts away from pandemic responses. Compared to infectious diseases, the story of digital transformation in the field of NCD public health is different. With its diverse approach spanning fields like medicine, epidemiology, and psychology, public health works to promote healthy choices and lifestyles through "Assessment," "Policy Development," "Resource Allocation," "Assurance," and "Access." It is remarkable how powerful artificial intelligence (AI) is in this digital revolution. Health care providers can prioritize human interactions particularly those that cannot be digitalized, like emotional support by using AI to automate repetitive tasks. Additionally, AI gives people the means to manage their health proactively. AI is a companion that helps navigate the health care system, but the human touch is still invaluable. Despite being revolutionary, digital evolution comes with its own set of difficulties. At the forefront are concerns about access and equity. Vulnerable groups risk further marginalization, whether as a result of financial limitations, geographic obstacles, or a lack of digital literacy. This shift necessitates an inclusive approach that aims to eradicate current health disparities rather than exacerbate them. Social consensus is required for population-level digital interventions in NCD prevention. Even though they work, laws like sugar taxes or smoking bans may have an impact on people who aren't directly benefited. Transparent benchmarks and criteria that guarantee maximum benefits without excluding vulnerable or minority groups are essential to the wider success of digital public health. AI's ability to avoid bias is crucial, particularly when making population-centric decisions like allocating resources. As a result, the advancement of AI-integrated digital public health depends critically on the ongoing participation of stakeholders, including patients and minority groups.