title: Understanding the modes of transmission model of new HIV infection and its use in prevention planning.
abstract: The modes of transmission model has been widely used to help decision-makers target measures for preventing human immunodeficiency virus (HIV) infection. The model estimates the number of new HIV infections that will be acquired over the ensuing year by individuals in identified risk groups in a given population using data on the size of the groups, the aggregate risk behaviour in each group, the current prevalence of HIV infection among the sexual or injecting drug partners of individuals in each group, and the probability of HIV transmission associated with different risk behaviours. The strength of the model is its simplicity, which enables data from a variety of sources to be synthesized, resulting in better characterization of HIV epidemics in some settings. However, concerns have been raised about the assumptions underlying the model structure, about limitations in the data available for deriving input parameters and about interpretation and communication of the model results. The aim of this review was to improve the use of the model by reassessing its paradigm, structure and data requirements. We identified key questions to be asked when conducting an analysis and when interpreting the model results and make recommendations for strengthening the model's application in the future.
authors.affiliation: Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, England. k.case@imperial.ac.uk
authors.forename: Kelsey K
authors.initials: KK
authors.lastname: Case
authors.forename: Peter D
authors.initials: PD
authors.lastname: Ghys
authors.forename: Eleanor
authors.initials: E
authors.lastname: Gouws
authors.forename: Jeffrey W
authors.initials: JW
authors.lastname: Eaton
authors.forename: Annick
authors.initials: A
authors.lastname: Borquez
authors.forename: John
authors.initials: J
authors.lastname: Stover
authors.forename: Paloma
authors.initials: P
authors.lastname: Cuchi
authors.forename: Laith J
authors.initials: LJ
authors.lastname: Abu-Raddad
authors.forename: Geoffrey P
authors.initials: GP
authors.lastname: Garnett
authors.forename: Timothy B
authors.initials: TB
authors.lastname: Hallett
mesh_terms: D000328:Adult; D005260:Female; D014943:Global Health / Q000706:statistics & numerical data* / Q000639:trends; D015658:HIV Infections / Q000453:epidemiology / Q000517:prevention & control / Q000635:transmission*; D006801:Humans; D008297:Male; D008954:Models, Biological; D015995:Prevalence; D018570:Risk Assessment / Q000379:methods; D015819:Substance Abuse, Intravenous / Q000150:complications* / Q000453:epidemiology / Q000517:prevention & control; D047568:Unsafe Sex / Q000517:prevention & control / Q000706:statistics & numerical data*