Over the past five years, immunization coverage in Sub-Saharan Africa has stagnated at 72%. Immunization supply chains are expensive and complicated, and creating a model that helps optimize these supply chains is of great importance not only for people’s health but also for the efficient use of limited budget in developing nations. Most existing supply chain optimization models aim at minimizing costs or maximizing profit, which do not always fit in the context of humanitarian logistics. Also, they regard the demand as exogenous, but the proximity to health centers may affect people’s demand. Therefore, the objective of this project is to build an optimization model for vaccine network design that aims to maximize the access to immunization and incorporates the endogenous demand function. We take a two-step approach to build the model, and each step has a process of model formulation and validation. The first step is to formulate the toy model, a simplified version of the model using an example dataset, to understand the basic behavior of the model. With the toy model validated, we formulate the final model, which incorporates more complexities based on the real dataset. Following that, a case study of The Gambia was conducted to validate the effectiveness of our model and to provide useful insights in a real-world context regarding the applicability of our solution procedure. The results of the case study show the ability of the model to increase access to immunization. Through the opening of new outreach sites and the optimization of outreach allocation and scheduling, it would be possible to increase the immunization access from 91% to 97.1%. Furthermore, our analysis contributes by showing that the better determination of the shape of a demand coverage function is a promising area of future research.