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Due to COVID in July 2020, WHO (World Health Organization) and UNICEF estimated ~80,000,000 children are either un or under-vaccinated. 

By April 2021, ~228,000,000 people, mostly children, are un or under vaccinated due to COVID.  

228,000,000 people, mostly children, are un or under vaccinated due to COVID.
Analytics for Living Foundation's artificial intelligence geographic subnational syndicated tools will help vaccinate 200 million children.

The reasons are multi-faceted due to COVID.  As of April 2021, mass immunization campaigns have been disrupted in ~50 countries.  Half of the 50 affected countries are in Africa highlighting the inequalities of access to critical immunization services.  

Data exists to understand where the un and under-vaccinated children populations are located at the national and subnational level.  Applying machine learning and artificial intelligence algorithms the children who have not been vaccinated can be understood as well as the varying reasons within each geography.  Learning over time and implementing vaccination programs which would measured via analytics tools these ~80,000,000 could be back to rates as estimated in 2017.  Its assumed the number is increasing over time given COVID restrictions is one of the key causes as well as continued children being born.  In 2017, typically only ~20,000,000 children are under-vaccinated; data suggests 62% of these children are within 10 countries.  The impact of such an ML/AI program would be to decrease the un or under-vaccinated rate by 4x.  Assuming it has been ~12-months since WHO/UNICEF published and COVID waves are continuing its assumed ~200,000,000 children today are impacted.  The children's lives impacted and lives saved by such a program would be impacted 180,000,000 children and families world wide.  

Analytics for Living is positioned and prepared to support such a world wide problem by applying its advanced analytics framework.