PLoS computational biology, 2021-09, Vol.17 (9), p.e1009301-e1009301
2021
Details
- Autor(en) / Beteiligte
- Titel
- PopART-IBM, a highly efficient stochastic individual-based simulation model of generalised HIV epidemics developed in the context of the HPTN 071 (PopART) trial
- Ist Teil von
- PLoS computational biology, 2021-09, Vol.17 (9), p.e1009301-e1009301
- Ort / Verlag
- United States: Public Library of Science
- Erscheinungsjahr
- 2021
- Link zum Volltext
- Quelle
- MEDLINE
- Beschreibungen/Notizen
- Mathematical models are powerful tools in HIV epidemiology, producing quantitative projections of key indicators such as HIV incidence and prevalence. In order to improve the accuracy of predictions, such models need to incorporate a number of behavioural and biological heterogeneities, especially those related to the sexual network within which HIV transmission occurs. An individual-based model, which explicitly models sexual partnerships, is thus often the most natural type of model to choose. In this paper we present PopART-IBM, a computationally efficient individual-based model capable of simulating 50 years of an HIV epidemic in a large, high-prevalence community in under a minute. We show how the model calibrates within a Bayesian inference framework to detailed age- and sex-stratified data from multiple sources on HIV prevalence, awareness of HIV status, ART status, and viral suppression for an HPTN 071 (PopART) study community in Zambia, and present future projections of HIV prevalence and incidence for this community in the absence of trial intervention.
- Sprache
- Englisch
- Identifikatoren
- ISSN: 1553-7358, 1553-734XeISSN: 1553-7358DOI: 10.1371/journal.pcbi.1009301Titel-ID: cdi_plos_journals_2582586669
- Format
- –
- Schlagworte
- Adolescent, Adult, Age, Aged, Agent based models, Algorithms, Antiretroviral drugs, Antiretroviral therapy, Antiretroviral Therapy, Highly Active, Bayesian analysis, Biology and Life Sciences, Calibration, Computer Simulation, Control, Demographics, Design, Disease Progression, Disease transmission, Epidemics, Epidemiologic methods, Epidemiology, Female, HIV, HIV infection, HIV Infections - drug therapy, HIV Infections - epidemiology, HIV Infections - transmission, Human immunodeficiency virus, Humans, Incidence, Intervention, Male, Mathematical analysis, Mathematical models, Medicine and health sciences, Middle Aged, Models, Statistical, People and Places, Population, Prevalence, Programming languages, Reproducibility of Results, Research and Analysis Methods, Risk factors, Sexually transmitted diseases, Simulation, Statistical inference, STD, Stochastic Processes, Stochasticity, Technology application, Young Adult, Zambia, Zambia - epidemiology