FPsim: An agent-based model of family planning

Abstract

The biological and behavioral underpinnings of family planning (FP) unfold on an individual level, across a full reproductive life course, and within a complex system of social and structural constraints. Yet, much of the existing FP modeling landscape has focused solely on macro- or population-level dynamics of family planning. There is a need for an individual-based approach to provide a deeper understanding of how family planning is intertwined with individuals' lives and health at the micro-level, which can contribute to more effective, person-centered design of both contraceptive technologies and programmatic interventions. This article introduces the Family Planning Simulator (FPsim), a data-driven, agent-based model of family planning, which explicitly models individual heterogeneity in biology and behavior over the life course. Agents in FPsim can experience a wide range of life-course events, such as increases in fecundability (and primary infertility), sexual debut, contraceptive choice, postpartum family planning, abortion, miscarriage, stillbirth, infant mortality, and maternal mortality. The core components of the model - fecundability and contraceptive choice, are represented individually and probabilistically, following age-specific patterns observed in demographic data and prospective cohort studies. Once calibrated to a setting leveraging multiple sources of data, FPsim can be used to build hypothetical scenarios and interrogate counterfactual research questions about the use, non-use, and/or efficacy of family planning programs and contraceptive methods. To our knowledge, FPsim is the first open-source, individual-level, woman-centered model of family planning.

HPVsim: An agent-based model of HPV transmission and cervical disease

“…HPVsim is a modeling tool built upon the architecture and design of the Starsim modeling platform, a flexible Python-based framework for epidemiological modeling which thus far includes Covasim for modeling COVID-19 (64)(65)(66), FPsim for family planning (67,68), and Synthpops for population modeling (69). All Starsim models share several core design principles in terms of their distribution, philosophy, architecture, and structure.…”

“…In this paper, we introduce software for creating, calibrating, and analyzing agent-based models of HPV and cervical disease, called the Human papillomavirus simulator (HPVsim). HPVsim is built upon the architecture and design of the Starsim modeling platform, a flexible Python-based framework for epidemiological modeling which thus far includes Covasim for modeling COVID-19 (19), FPsim for family planning (20), and Synthpops for population modeling (21). Because this core software architecture has been described in detail elsewhere, in this paper we mainly focus on the two key innovations of HPVsim: (1) on the science side, HPVsim is designed to complement the existing suite of HPV models by offering a novel methodological approach to modeling HPV's natural history; and (2) on the software side, we introduce a multi-scale modeling technique that substantially decreases the variability of agent-based simulations.…”

HPVsim: An agent-based model of HPV transmission and cervical disease

“…In this paper, we introduce software for creating, calibrating, and analysing agent-based models of HPV and cervical disease, called the Human papillomavirus simulator (HPVsim). HPVsim is built upon the architecture and design of the Starsim modelling platform, a flexible Python-based framework for epidemiological modelling which thus far includes Covasim for modelling COVID-19 [ 19 ], FPsim for family planning [ 20 ], and Synthpops for population modelling [ 21 ]. Because this core software architecture has been described in detail elsewhere, in this paper we mainly focus on the two key innovations of HPVsim: (1) on the science side, HPVsim is designed to complement the existing suite of HPV models by offering a novel methodological approach to modelling HPV’s natural history; and (2) on the software side, we introduce a multiscale modelling technique that substantially decreases the variability of agent-based simulations.…”