@inproceedings{fdi:010087006,
  title = {{E}stimating the impact of {HIV} self-testing on {HIV} testing services, diagnoses, and treatment initiation at the population-level with routine data : the example of the {ATLAS} program in {C}{\^o}te d'{I}voire [poster]},
  author = {{S}imo {F}otso, {A}. and {J}ohnson, {C}. and {V}autier, {A}. and {K}ouam{\'e}, {K}.{B}. and {D}iop, {P}.{M}. and {S}ilhol, {R}. and {M}aheu-{G}iroux, {M}. and {B}oily, {M}.{C}. and {R}ouveau, {N}icolas and {D}oumenc-{A}{\¨ie}dara, {C}. and {B}aggaley, {R}. and {E}hui, {E}. and {L}armarange, {J}oseph and {A}tlas {T}eam},
  editor = {},
  language = {{ENG}},
  abstract = {{B}ackground : {HIV} self-testing ({HIVST}) is a critical testing approach particularly for reaching those at {HIV} risk who are hesitant or unable to access existing services. {W}hile the discreet and flexible nature of {HIVST} is appealing to users, these features can limit the ability for programmes to monitor and estimate the population-level impacts of {HIVST} implementation. {T}his study triangulates publicly available routine programme data from {C}{\^o}te d'{I}voire in order estimate the effects of {HIVST} distribution on access to testing, conventional testing (self-testing excluded), {HIV} diagnoses, and antiretroviral treatment ({ART}) initiations. {M}ethods : {W}e used quarterly programmatic data ({Q}3-2019 to {Q}1-2021) from {ATLAS}, a project that aims to promote and implement network-based {HIVST} distribution in {W}est {A}frica, in addition to routine {HIV} testing services program data obtained from the {PEPFAR} dashboard. {W}e performed ecological time series regression using linear mixed-models. {R}esults : {B}etween {Q}3-2019 and {Q}1-2021, 99,353 {HIVST} kits were distributed by {ATLAS} in 78 health districts included in the analysis. {T}he results ({T}able 1) show a negative but non-significant effect of the number of {ATLAS} {HIVST} on the volume of conventional tests (-190), suggesting the possibility of a slight substitution effect. {D}espite this, the the beneficial effect on access to testing is significant: for each 1000 {HIVST} distributed via {ATLAS}, 390 to 590 additional {HIV} tests were performed if 60% to 80% of {HIVST} are used . {T}he effect of {HIVST} on {HIV} diagnosis was significant and positive, with 8 additional diagnoses per 1,000 {HIVST} distributed. {N}o effect of {HIVST} was observed on {ART} initiations. {C}onclusions : {O}ur study provides a standard methodology for estimating the population-level impact of {HIVST} that can be used across countries. {I}t shows that {HIVST} distribution was associated with increased access to {HIV} testing and diagnosis in {C}{\^o}te d'{I}voire. {W}ide-scale adoption of this method will improve {HIVST} data quality and inform evidence-based programming.},
  keywords = {{COTE} {D}'{IVOIRE}},
  numero = {},
  pages = {1  multigr.},
  booktitle = {},
  year = {2022},
  URL = {https://www.documentation.ird.fr/hor/fdi:010087006},
}