@conference {1638805, title = {ADVISER: AI-Driven Vaccination Intervention Optimiser for Increasing Vaccine Uptake in Nigeria}, booktitle = {International Joint Conference on AI (IJCAI) 2022}, year = {2022}, abstract = {More than 5 million children under five years die from largely preventable or treatable medical conditions every year, with an overwhelmingly large proportion of deaths occurring in under-developed countries with low vaccination uptake. One of the United Nations{\textquoteright} sustainable development goals (SDG 3) aims to end preventable deaths of new-borns and children under five years of age. We focus on Nigeria, where the rate of infant mortal-ity is appalling. We collaborate with HelpMum, a large non-profit organization in Nigeria to design and optimize the allocation of heterogeneous health interventions under uncertainty to increase vaccination uptake, the first such collaboration in Nigeria. Our framework, ADVISER: AI-Driven Vaccination Intervention Optimiser, is based on an integer linear program that seeks to maximize the cumulative probability of successful vaccination. Our optimization formulation is intractable in practice. We present a heuristic approach that enables us to solve the problem for real-world use-cases. We also present theoretical bounds for the heuristic method. Finally, we show that the proposed approach out-performs baseline methods in terms of vaccination uptake through experimental evaluation. HelpMum is currently planning a pilot program based on our approach to be deployed in the largest city of Nigeria, which would be the first deployment of an AI-driven vaccination uptake program in the country and hopefully, pave the way for other data-driven programs to improve health outcomes in Nigeria.}, author = {Vineet Nair and Kritika Prakash and Michael Wilbur and Aparna Taneja and Corrine Namblard and Oyindamola Adeyemo and Abhishek Dubey and Abiodun Adereni and Tambe, Milind and Mukhopadhyay, Ayan} }