In the wake of Covid-19, countries with strong health systems and heavy investments in the health sector were believed to have an upper hand against the disease. But as it ravaged the globe, the narrative changed.

Some of the world’s biggest economies were the worst hit while emerging economies fared remarkably well. In fact, scientists are still struggling to explain Africa’s low infection rate.

A new report backed by Novartis Foundation and Microsoft has found that lower-income countries are robustly leveraging artificial intelligence (AI) to step up their health systems during and post the pandemic.

AI is the science of making machines do things that would require intelligence if done by people. With AI, machines can learn from experience and perform human-like tasks such as making decisions.

The report, titled "Reimagining Global Health through Artificial Intelligence: The Roadmap to AI Maturity”, suggests that lower-income countries, African countries in particular, could soon leapfrog richer countries with AI-enabled health technologies.

The report was crafted by the Broadband Commission Working Group on Digital and AI in Health established by the International Telecommunication Union (ITU) and UNESCO. It is based on a landscape review of more than 300 existing use cases of AI in health.

In terms of technology uptake, Sub-Saharan Africa has led the world before. Kenya, for instance, has been a world leader in adoption of mobile banking, which has been picked up across Africa.

According to the report, Rwanda is now arguably the most digitally connected health system in Africa. Over 2million people or a third of the adult population are already using Babyl, a digital health consulting service and its AI-enabled chatbot.

Through partnership with the government, Babylon Health also plans to introduce an AI-powered triage and symptom checker platform.

AI-powered robots are used in Covid-19 treatment centres to limit the risk of healthcare workers from contracting the virus by reducing contact with patients. The robots conduct mass temperature screenings, deliver food and medication to patients and detect and warn people who are not wearing facemasks.

Meanwhile, an AI-based diagnosis tool used in the emergency department at King Faisal Hospital. There as well is Insightiv, an AI-powered radiology system that allows medical imaging and CT scans now known to provide a 98 percent Covid-19 test accuracy.

Adoption of health technologies is likely to follow the same trend, with digital transformation accelerated by the COVID-19 pandemic, the report says. It argues that reduced contact between patients and health providers due to social distancing has led to major growth in technologies such as AI-enabled diagnostics.

"There is no reason why this [uptake] should not happen with health tech as well,” said Racey Muchilwa, Head of Novartis Sub-Saharan Africa.

The report illustrates numerous examples of how AI is being used to fight against Covid-19, including diagnostic testing, predictive modeling and vaccine research.

In India, for instance, hospitals are using AI to accurately predict a patient’s risk of a heart attack seven years before it might happen.

In Malaysia, Brazil, and the Philippines, AI is being used to tackle multiple mosquito-borne diseases. The program continuously pulls multidimensional data from over 90 public databases and adjusts for 276 variables that influence the spread of disease to predict when outbreaks are likely.

UNICEF has developed an AI program to reduce the social and economic burden of outbreaks through targeted population health measures. Its Magic Box program both predicts when outbreaks are likely, and allows health systems to reorganize their resources, alert health workers and launch public health campaigns, so they can respond better and faster to emergencies.

The report argues that leveraging supportive AI tools which can help nurses and community health workers diagnose and treat illnesses traditionally seen by doctors would fill the gap of healthcare workers which is predicted to reach 18 million by 2030.

Governments should identify and test innovative ways to finance AI in health solutions, the report says. To ensure financial accessibility in the long run for everyone, national reimbursement of digital and AI-enabled health services is key. Secure and privacy-preserving data governance needs to be part of ensuring a sustainable infrastructure.