@inproceedings{fdi:010087009,
  title = {{I}mproving our understanding of how structural determinants impact {HIV} epidemics : a scoping review of dynamic models to guide future research [poster]},
  author = {{S}tannah, {J}. and {A}nato, {J}.{L}.{F}. and {M}itchell, {K}.{M}. and {L}armarange, {J}oseph and {M}aheu-{G}iroux, {M}. and {B}oily, {M}.{C}.},
  editor = {},
  language = {{ENG}},
  abstract = {{B}ackground : {D}ynamic models of {HIV} transmission have proven valuable tools for informing {HIV} prevention strategies. {I}ncluding structural determinants in models is crucial to estimate their population-level impacts on {HIV} transmission and inform efforts towards {HIV} elimination. {H}owever, this is challenging due to a lack of coherent conceptual frameworks, limited understanding of their specific causal pathways, and few empirical estimates of their impacts on downstream mediators. {M}ethods :  {W}ith the overarching aim to improve models, we conducted a scoping review of studies that used dynamic {HIV} transmission models to evaluate the impact of structural determinants. {F}rom included studies, we extracted information on the types of structural determinants and methods used to model their impacts on {HIV} transmission. {W}e appraised studies on how they conceptualized structural exposures and represented their causal relationships over time within models. {R}esults : {W}e identified 9 dynamic transmission modelling studies that incorporated structural determinants of {HIV}, including violence ({N}=3), incarceration ({N}=2), stigma ({N}=2), housing instability ({N}=2), migration ({N}=1), and education ({N}=1). {O}nly one study modelled multiple determinants simultaneously. {I}n most models, structural determinants were conceptualized using current, recent, non-recent and/or lifetime exposure categories. {M}odelled structural determinants largely impacted {HIV} transmission through mediated effects on one or more proximate risk factors, including sharing injection equipment, condom use, number of partners, and access to treatment. {H}owever, causal pathways were simplistic, with few mediators and/or lack of clear empirical justification. {T}o measure impact, most studies simply assumed the elimination of structural determinants in counterfactual comparison scenarios. {F}ew models included long-term and/or delayed effects of past, recurrent, or acute exposure, potentially overestimating impacts of determinants. {C}onclusions : {D}espite the importance of structural determinants for {HIV} prevention, methods for including them in dynamic {HIV} transmission models remain insufficient. {F}ew studies have attempted to incorporate structural determinants in {HIV} models, and methods vary considerably. {T}o improve inferences, models should adopt precise exposure definitions, deconstruct and estimate their complex causal pathways, and translate them into their mechanistic components. {T}he need for development of coherent frameworks to conceptualize the synergistic interplay between strengthened empirical data analysis and the inclusion of structural determinants in dynamic models is pressing.},
  keywords = {{MONDE}},
  numero = {},
  pages = {1  multigr.},
  booktitle = {},
  year = {2022},
  URL = {https://www.documentation.ird.fr/hor/fdi:010087009},
}