Prosperity in public health sector

“Insanity: doing the same thing over and over again and expecting different results.” This famous quote teaches us the importance of focusing on the lesson but not the problem. One of the main lessons that Coronavirus pandemic has taught us is getting ready for the next big public health challenge. The prescription for prosperity in the resource-constrained world is to reduce the disease burden through proven scientific interventions. Digital technologies, machine learning and Artificial Intelligence (AI) are triggering a paradigm shift in the fields of medicine, research and public health due to the rising proliferation of healthcare data and the rapid development in analytics techniques.

Areas of Impact for Artificial Intelligence (AI) in Healthcare

AI-assisted interventions have been applied broadly and viewed as a critical enabler for clinical decision making, medical imaging, chronic care management, self-care, prevention & wellness, triage and diagnosis, diagnostics, clinical decision support, care delivery, drug and vaccine research, patient triage to contract tracing, surveillance systems and predicting COVID-19 cases. AI based solutions can serve as a force multiplier in reducing the disease burden through early and quick identification that aims to shorten recovery times, increase access to services, and accelerate the spread of medical innovation. 

AI assisted interventions can benefit the Public Health Sector

AI based products detect and localize anomalies on X-rays, MRIs, and CT scans using deep learning technology and millions of images. For example, the deep learning algorithms calculate the number of intracranial structures and lesions quickly and accurately. Clinicians and researchers use this capability to monitor the success of patients suffering from hemorrhagic stroke, traumatic brain injury, or hydrocephalus, as well as to create novel quantitative outcome indicators. Clinicians may use these numerical metrics to help determine the magnitude of a stroke, lesion, or underlying condition, as well as to compare various CT scans. 

Leading the race of AI Interventions

According to the Stanford Institute for Human-Centered Artificial Intelligence's 2019 AI Index Survey, global private investment in AI in 2019 totaled more than US$70 billion. The United States, China, and Europe received the greatest share, with Israel, Singapore, and Iceland investing the most per capita. According to the survey, AI-based startups are a big part of the economy, with more than $37 billion in funding received globally in 2019, up from $1.3 billion in 2010.

AI benefit Low-and Mid Income Countries (LMICs) 

The resource-constrained Low-and Mid Income Countries (LMICs) might have a hard time to build AI based healthcare infrastructure solutions, but it could prove transformative for public health in the long run. The Global health community including major donor organizations is advocating for implanting AI based solutions in LMICs. United Nations Secretary General's High-Level Panel on Digital Cooperation recommended that “by 2030, every adult should have affordable access to digital networks, as well as digitally-enabled financial and health services, as a means to make a substantial contribution to achieving the SDGs”. Chronic obstructive pulmonary disease (COPD), Tuberculosis, Cirrhosis of the liver, Diabetes mellitus are among the top causes of death in LMICs as reported by World Health Organization (WHO) Global Health Estimates published in 2020. To fight with these killer diseases, we need to integrate with a needs-based approach; ensure rapid and equitable access to AI based public health solutions, establish a study plan for the rollout of new AI-driven interventions that includes implementation and system-related issues, establish and enforce global regulatory, economic, and ethical norms and guidance that protect LMICs' interests, in alignment with the Sustainable Development Goals (SDGs), universal health coverage, and the response to the coronavirus disease 2019 (COVID-19). 

Now it’s the time for political commitment, policy level effort, and engagement of the diverse stakeholders to incorporate AI based public health solutions as an effort to reduce the disease burden in the long-term approach.

*Author, a Community Health and Social Impact specialist currently residing in the USA.