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

Abstract

AbstractIn 2020, the WHO launched its first Global Strategy to Accelerate the Elimination of Cervical Cancer, outlining an ambitious set of targets for countries to achieve over the next decade. At the same time, new tools, technologies, and strategies are in the pipeline that may improve screening performance, expand the reach of prophylactic vaccines, and prevent the acquisition, persistence and progression of oncogenic HPV. Detailed mechanistic modeling can help identify the combinations of current and future strategies to combat cervical cancer. Open-source modeling tools are needed to shift the capacity for such evaluations in-country. Here, we introduce the Human papillomavirus simulator (HPVsim), a new, flexible agent-based model that can be parameterized with country-specific vital dynamics, structured sexual networks, co-transmitting HPV genotypes, B- and T-cell mediated immunity, and high-resolution disease natural history. HPVsim is designed with a user-first lens: it is implemented in Python, has built-in tools for simulating commonly-used interventions, includes a comprehensive set of tests and documentation, and runs quickly (seconds to minutes) on a laptop. Useful complexity was not sacrificed: the platform is flexible, allowing bespoke scenario modeling.Author summaryMathematical models have been integral in setting ambitious goals for cervical cancer elimination, along with determining intermediate targets for vaccination, screening, and treatment. However, given that elimination strategies encompass decade-long timelines, these targets will inevitably need updating over time as the landscape of available technologies for combating cervical cancer evolves. In this work, we introduce a new model, HPVsim, which can rapidly evaluate pathways toward elimination under complex combinations of new and existing interventions. HPVsim is a flexible agent-based model with country-specific vital dynamics, structured sexual networks, co-transmitting HPV genotypes, B- and T-cell mediated immunity, and high-resolution disease natural history. Written in Python, with easy installation and full testing and documentation, the model is designed so that analysis pipelines can be created with very little effort. By improving access to cervical cancer modeling tools, we aim to enable real-time updates and nimble adaptation of cervical cancer elimination targets in response to changing technologies providing realistic targets on the path to cervical cancer elimination.