Medtech can build our resilience in crises
Winston Churchill once said “never let a good crisis go to waste”, referring to the importance of taking advantage of lessons learnt from times of crisis to inform how we evolve, adapt and build resilient systems. The coronavirus outbreak has wreaked havoc in the global economy, threatening the lives of more than 100,000 people and counting, with the older population particularly vulnerable to falling seriously ill.
A lack of resilience in health systems threatens social and economic development in any country and can result in longlasting economic slumps. According to the Journal of Infectious Disease, the 2014 Ebola outbreak cost the economies of Sierra Leone, Guinea and Liberia about $53bn. The 2015 Zika virus was estimated to have cost the US more than $20bn; the severe acute respiratory syndrome outbreak cost about $40bn.
But the largest cost of these outbreaks was the human cost. Ebola reportedly took more than 11,000 lives over a threeyear period, the Zika virus resulted in newborn babies being born with microcephaly and genetic abnormalities, brain injury and malnutrition, among others. The human cost of these outbreaks is immeasurable.
As is often said, necessity is the mother of invention; new health tech players are emerging in the bid to make health care accessible for marginalised populations, to detect and monitor outbreaks, and to diagnose and treat at the lowest cost. Weak epidemiological data has catalysed large investment in the health technology space. A recent CBInsight report showed US investors allocated more than $11bn to digital health-care start-ups, a 16% increase from the previous year.
Google’s Verily Study Watch, Buoy Health and Google Trends are early-stage health surveillance and detection innovations that have started moving the sector in the right direction. The study watch is an electrocardiogram and can record heart rate, electrodermal activity and inertial movements. When fully commercialised this would enable early detection of infection and exposure to disease. Bouy Health similarly developed an artificial intelligence (AI) health assistant that provides real-time information on symptoms and triages them to the necessary care facility. Google Trends uses algorithms to study the search trends in communities to detect the propensity of a disease outbreak as early as possible.
What is still missing in this part of the industry is a solution that studies environmental factors, population density, geographical variables and socioeconomic variables that would more accurately detect outbreaks as well as proactively provide insights on changes and developments that increase the risk of health outbreaks.
AIME, a US-headquartered start-up founded out of the Singularity University, has made immense strides in closing this gap. It uses AI to study more than 270 variables every 23 seconds that can increase the likelihood of a dengue fever outbreak, including weather, geographical and socioeconomic variables.
Dengue is a mosquito-borne viral infection that is mostly found in tropical and subtropical climates across the world. The World Health Organisation estimates there are 390-million dengue virus infections per year and 3.9-billion people are at risk of contracting the virus. AIME’s platform can reliably predict a dengue outbreak in up to a 400m radius three months in advance, with an accuracy rate of 88.7%.
Resilience of health systems requires that there are adequate health stocks and resource capacity to ensure the sustainability of people and the economies in which they reside. Resilient health systems are sufficiently capacitated to absorb acute external shocks and respond appropriately with as little effect on health outcomes and the economy as possible. We now have an opportunity to learn from the coronavirus what it truly means to build resilient health systems.