FPsim+: An Agent Based Model of Contraceptive Use and Empowerment

Abstract

FPsim is an agent-based model designed to simulate individual family planning (FP) behaviors and outcomes, capturing biological and behavioral heterogeneity among women. The model provided detailed calibration to simulate the potential impact of new contraceptive technologies and interventions. However, the first version of FPsim was limited in that it did not include women’s contraceptive intentions, nor the broader social impacts of FP, such as empowerment. Thus, in this study, we aim to dynamically integrate women’s decision-making (across multiple dimensions), economic life, and intentions to use contraceptive methods into FPsim. We integrate these features so that they both impact, and are impacted by, women’s contraceptive use. In this way, these enhancements allow the model to investigate the multidirectional relationship between family planning and women’s empowerment. We enhanced FPsim across three key dimensions: (1) refined the models that determine a woman’s probability of using contraception, her choice of contraceptive method, and the duration she will remain on this method, (2) included women’s intentions to use contraception and become pregnant, and (3) integrated empowerment metrics. Using data from the Kenya Performance Monitoring for Action (PMA) surveys, we implement the model in a Kenya-like setting. We add demographic attributes (education, urban/rural residence, and wealth quintile), contraceptive and fertility intentions, and various empowerment metrics. We call this enhanced model FPsim+. FPsim+ advances a more comprehensive and person-centered approach to modeling FP behaviors. The new model provides significant insight into the dynamics between family planning and women’s empowerment, critical for FP policy and program design. FPsim+ is able to simulate more tailored and effective interventions that align with women’s preferences and contribute to their empowerment, allowing policymakers to understand a wider range of impact of investing in family planning. Further validation in diverse settings is necessary to generalize these findings and maximize the model’s utility.