Infectious Disease Modelling of HIV Prevention Interventions: A Systematic Review and Narrative Synthesis of Compartmental Models.


Journal

PharmacoEconomics
ISSN: 1179-2027
Titre abrégé: Pharmacoeconomics
Pays: New Zealand
ID NLM: 9212404

Informations de publication

Date de publication:
06 2023
Historique:
accepted: 26 02 2023
medline: 8 5 2023
pubmed: 30 3 2023
entrez: 29 3 2023
Statut: ppublish

Résumé

The HIV epidemic remains a major public health problem. Critical to transmission control are HIV prevention strategies with new interventions continuing to be developed. Mathematical models are important for understanding the potential impact of these interventions and supporting policy decisions. This systematic review aims to answer the following question: when a new HIV prevention intervention is being considered or designed, what information regarding it is necessary to include in a compartmental model to provide useful insights to policy makers? The primary objective of this review is therefore to assess suitability of current compartmental HIV prevention models for informing policy development. Articles published in EMBASE, Medline, Econlit, and Global Health were screened. Included studies were identified using permutations of (i) HIV, (ii) pre-exposure prophylaxis (PrEP), circumcision (both voluntary male circumcision [VMMC] and early-infant male circumcision [EIMC]), and vaccination, and (iii) modelling. Data extraction focused on study design, model structure, and intervention incorporation into models. Article quality was assessed using the TRACE (TRAnsparent and Comprehensive Ecological modelling documentation) criteria for mathematical models. Of 837 articles screened, 48 articles were included in the review, with 32 unique mathematical models identified. The substantial majority of studies included PrEP (83%), whilst fewer modelled circumcision (54%), and only a few focussed on vaccination (10%). Data evaluation, implementation verification, and model output corroboration were identified as areas of poorer model quality. Parameters commonly included in the mathematical models were intervention uptake and effectiveness, with additional intervention-specific common parameters identified. We identified key modelling gaps; critically, models insufficiently incorporate multiple interventions acting simultaneously. Additionally, population subgroups were generally poorly represented-with future models requiring improved incorporation of ethnicity and sexual risk group stratification-and many models contained inappropriate data in parameterisation which will affect output accuracy. This review identified gaps in compartmental models to date and suggests areas of improvement for models focusing on new prevention interventions. Resolution of such gaps within future models will ensure greater robustness and transparency, and enable more accurate assessment of the impact that new interventions may have, thereby providing more meaningful guidance to policy makers.

Sections du résumé

BACKGROUND
The HIV epidemic remains a major public health problem. Critical to transmission control are HIV prevention strategies with new interventions continuing to be developed. Mathematical models are important for understanding the potential impact of these interventions and supporting policy decisions. This systematic review aims to answer the following question: when a new HIV prevention intervention is being considered or designed, what information regarding it is necessary to include in a compartmental model to provide useful insights to policy makers? The primary objective of this review is therefore to assess suitability of current compartmental HIV prevention models for informing policy development.
METHODS
Articles published in EMBASE, Medline, Econlit, and Global Health were screened. Included studies were identified using permutations of (i) HIV, (ii) pre-exposure prophylaxis (PrEP), circumcision (both voluntary male circumcision [VMMC] and early-infant male circumcision [EIMC]), and vaccination, and (iii) modelling. Data extraction focused on study design, model structure, and intervention incorporation into models. Article quality was assessed using the TRACE (TRAnsparent and Comprehensive Ecological modelling documentation) criteria for mathematical models.
RESULTS
Of 837 articles screened, 48 articles were included in the review, with 32 unique mathematical models identified. The substantial majority of studies included PrEP (83%), whilst fewer modelled circumcision (54%), and only a few focussed on vaccination (10%). Data evaluation, implementation verification, and model output corroboration were identified as areas of poorer model quality. Parameters commonly included in the mathematical models were intervention uptake and effectiveness, with additional intervention-specific common parameters identified. We identified key modelling gaps; critically, models insufficiently incorporate multiple interventions acting simultaneously. Additionally, population subgroups were generally poorly represented-with future models requiring improved incorporation of ethnicity and sexual risk group stratification-and many models contained inappropriate data in parameterisation which will affect output accuracy.
CONCLUSIONS
This review identified gaps in compartmental models to date and suggests areas of improvement for models focusing on new prevention interventions. Resolution of such gaps within future models will ensure greater robustness and transparency, and enable more accurate assessment of the impact that new interventions may have, thereby providing more meaningful guidance to policy makers.

Identifiants

pubmed: 36988896
doi: 10.1007/s40273-023-01260-z
pii: 10.1007/s40273-023-01260-z
pmc: PMC10163138
doi:

Types de publication

Systematic Review Research Support, Non-U.S. Gov't

Langues

eng

Pagination

693-707

Subventions

Organisme : PEPFAR
Pays : United States

Informations de copyright

© 2023. The Author(s).

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Auteurs

Rebecca Giddings (R)

London School of Hygiene & Tropical Medicine, London, UK.

Pitchaya Indravudh (P)

London School of Hygiene & Tropical Medicine, London, UK.

Graham F Medley (GF)

London School of Hygiene & Tropical Medicine, London, UK.

Fiammetta Bozzani (F)

London School of Hygiene & Tropical Medicine, London, UK.

Mitzy Gafos (M)

London School of Hygiene & Tropical Medicine, London, UK.

Shelly Malhotra (S)

IAVI, New York, USA.

Fern Terris-Prestholt (F)

London School of Hygiene & Tropical Medicine, London, UK. Fern.Terris-Prestholt@lshtm.ac.uk.

Sergio Torres-Rueda (S)

London School of Hygiene & Tropical Medicine, London, UK.

Matthew Quaife (M)

London School of Hygiene & Tropical Medicine, London, UK.

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