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Stuart RM, Cohen JA, Kerr CC, Mathur P, Abeysuriya RG, Zimmermann M, Rao DW, Boudreau MC, Lee S, Yang L, Klein DJ. HPVsim: An agent-based model of HPV transmission and cervical disease. PLoS Comput Biol 2024; 20:e1012181. [PMID: 38968288 PMCID: PMC11253923 DOI: 10.1371/journal.pcbi.1012181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 07/17/2024] [Accepted: 05/20/2024] [Indexed: 07/07/2024] Open
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).
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Affiliation(s)
- Robyn M. Stuart
- Gender Equality Division, Bill & Melinda Gates Foundation, Seattle, Washington, United States of America
| | - Jamie A. Cohen
- Institute for Disease Modeling, Global Health Division, Bill & Melinda Gates Foundation, Seattle, Washington, United States of America
| | - Cliff C. Kerr
- Institute for Disease Modeling, Global Health Division, Bill & Melinda Gates Foundation, Seattle, Washington, United States of America
| | - Prashant Mathur
- National Centre for Disease Informatics and Research, Indian Council of Medical Research, Bangalore, India
| | | | - Romesh G. Abeysuriya
- Institute for Disease Modeling, Global Health Division, Bill & Melinda Gates Foundation, Seattle, Washington, United States of America
- Burnet Institute, Melbourne, Victoria, Australia
| | - Marita Zimmermann
- Institute for Disease Modeling, Global Health Division, Bill & Melinda Gates Foundation, Seattle, Washington, United States of America
| | - Darcy W. Rao
- Gender Equality Division, Bill & Melinda Gates Foundation, Seattle, Washington, United States of America
| | - Mariah C. Boudreau
- Institute for Disease Modeling, Global Health Division, Bill & Melinda Gates Foundation, Seattle, Washington, United States of America
- Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America
| | - Serin Lee
- Institute for Disease Modeling, Global Health Division, Bill & Melinda Gates Foundation, Seattle, Washington, United States of America
- Department of Industrial & Systems Engineering, University of Washington, Seattle, Washington, United States of America
| | - Luojun Yang
- Institute for Disease Modeling, Global Health Division, Bill & Melinda Gates Foundation, Seattle, Washington, United States of America
| | - Daniel J. Klein
- Institute for Disease Modeling, Global Health Division, Bill & Melinda Gates Foundation, Seattle, Washington, United States of America
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Kamuyu G, Coelho da Silva F, Tenet V, Schussler J, Godi A, Herrero R, Porras C, Mirabello L, Schiller JT, Sierra MS, Kreimer AR, Clifford GM, Beddows S. Global evaluation of lineage-specific human papillomavirus capsid antigenicity using antibodies elicited by natural infection. Nat Commun 2024; 15:1608. [PMID: 38383518 PMCID: PMC10881982 DOI: 10.1038/s41467-024-45807-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 02/05/2024] [Indexed: 02/23/2024] Open
Abstract
Human Papillomavirus (HPV) type variants have been classified into lineages and sublineages based upon their whole genome sequence. Here we have examined the specificity of antibodies generated following natural infection with lineage variants of oncogenic types (HPV16, 18, 31, 33, 45, 52 and 58) by testing serum samples assembled from existing archives from women residing in Africa, The Americas, Asia or Europe against representative lineage-specific pseudoviruses for each genotype. We have subjected the resulting neutralizing antibody data to antigenic clustering methods and created relational antigenic profiles for each genotype to inform the delineation of lineage-specific serotypes. For most genotypes, there was evidence of differential recognition of lineage-specific antigens and in some cases of a sufficient magnitude to suggest that some lineages should be considered antigenically distinct within their respective genotypes. These data provide compelling evidence for a degree of lineage specificity within the humoral immune response following natural infection with oncogenic HPV.
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Affiliation(s)
- Gathoni Kamuyu
- Virus Reference Department, Public Health Microbiology Division, UK Health Security Agency, London, UK
| | - Filomeno Coelho da Silva
- Virus Reference Department, Public Health Microbiology Division, UK Health Security Agency, London, UK
| | - Vanessa Tenet
- International Agency for Research on Cancer (IARC/WHO) Early Detection, Prevention and Infections Branch, Lyon, France
| | - John Schussler
- Information Management Services Inc, Silver Spring, MD, USA
| | - Anna Godi
- Virus Reference Department, Public Health Microbiology Division, UK Health Security Agency, London, UK
| | - Rolando Herrero
- Agencia Costarricense de Investigaciones Biomédicas (ACIB) formerly Proyecto Epidemiológico Guanacaste, Fundación INCIENSA (FUNIN), San José, Costa Rica
| | - Carolina Porras
- Agencia Costarricense de Investigaciones Biomédicas (ACIB) formerly Proyecto Epidemiológico Guanacaste, Fundación INCIENSA (FUNIN), San José, Costa Rica
| | - Lisa Mirabello
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - John T Schiller
- Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Mónica S Sierra
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Aimée R Kreimer
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Gary M Clifford
- International Agency for Research on Cancer (IARC/WHO) Early Detection, Prevention and Infections Branch, Lyon, France
| | - Simon Beddows
- Virus Reference Department, Public Health Microbiology Division, UK Health Security Agency, London, UK.
- Blood Safety, Hepatitis, Sexually Transmitted Infections and HIV Division, UK Health Security Agency, London, UK.
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