For companies mapping their ESG strategies to the UN SDG´s (2) Zero Hunger and (3) Good Health and Well-being, they may be interested in the publication from Scientific American reporting a recent AI advancement which can predict potential nutrient deficiencies from space. A team at Harvard University used publicly available satellite data and artificial intelligence to “reliably pinpoint geographical areas where populations are at high risk of micronutrient deficiencies”. This level of insight significantly enhances local data capture. While the Harvard team believes the application could allow public health officials to interact with the AI insights to help inform interventions, many countries that could benefit from these insights still face incredible challenges on how they could proactively respond to the improved findings. For example, is the response solely based on nutrition through improved food sources or can the gap in micronutrient deficiencies also be reduced with the support of health services? All too often health services that fit well within the biomedical agenda of global intervention priorities are inappropriate at local levels and are, therefore, under-utilised, ineffective and unsustainable. Additionally, many local health services are fee-based and are a cost that vulnerable populations cannot afford. As a team focused on addressing protection gaps, we are extremely supportive of AI's potential to advance public health. The data provided by the Harvard team and supported by additional new data points provides the finance and (re)insurance industries with a unique opportunity to support vulnerable populations via the creation of new sustainable finance and (re)insurance products, while embracing a simplified underwriting process and engaging with local partners to create more effective distribution channels. The new sustainable products would significantly meet Zero Hunger and Good Health and Well-being SDG objectives and close the protection gap. I encourage the finance and (re)insurance industries to explore the use of the Harvard data further to support the building of new sustainable products.
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