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

Authors :
Stuart RM
Cohen JA
Kerr CC
Mathur P
Abeysuriya RG
Zimmermann M
Rao DW
Boudreau MC
Lee S
Yang L
Klein DJ
Source :
PLoS computational biology [PLoS Comput Biol] 2024 Jul 05; Vol. 20 (7), pp. e1012181. Date of Electronic Publication: 2024 Jul 05 (Print Publication: 2024).
Publication Year :
2024

Abstract

In 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 modelling can help identify the combinations of current and future strategies to combat cervical cancer. Open-source modelling tools are needed to shift the capacity for such evaluations in-country. Here, we introduce the Human papillomavirus simulator (HPVsim), a new open-source software package for creating flexible agent-based models parameterised with country-specific vital dynamics, structured sexual networks, and co-transmitting HPV genotypes. HPVsim includes a novel methodology for modelling cervical disease progression, designed to be readily adaptable to new forms of screening. The software itself 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. Performance is greatly enhanced by HPVsim's multiscale modelling functionality. HPVsim is open source under the MIT License and available via both the Python Package Index (via pip install) and GitHub (hpvsim.org).<br />Competing Interests: The authors have declared that no competing interests exist.<br /> (Copyright: © 2024 Stuart et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Details

Language :
English
ISSN :
1553-7358
Volume :
20
Issue :
7
Database :
MEDLINE
Journal :
PLoS computational biology
Publication Type :
Academic Journal
Accession number :
38968288
Full Text :
https://doi.org/10.1371/journal.pcbi.1012181