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Smart Immunization Targeting by Combining Artificial Intelligence and Mobile Tools

Rumi Chunara of New York University in the U.S. will collect data from mobile phones of healthcare workers to develop algorithms that will help prioritize healthcare resources to increase vaccine coverage in Punjab, Pakistan. Immunization is one of the most cost-effective and successful public health strategies and is estimated to prevent up to three million deaths each year. Still, many rural areas of low- and middle-income countries have an under-vaccinated population due to a lack of formal education and awareness of the importance of vaccinations. They will collect data on disease incidence and vaccine resources and coverage from the mobile phones of 3,800 rural healthcare workers. These data will be used to train an artificial intelligence model to identify the ideal times and locations to target vaccine efforts. The model will also address accessibility and awareness issues by incorporating distance to healthcare centers and frequency of visits. Their approach will be evaluated by analyzing coverage before and after implementation. Once proven, it can be scaled to other areas in Pakistan.

More information about Innovations Driving Programmatic Performance in Immunization: Service Experience and Data Use + Measurement (Round 22)

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