Collins C Iwuji

PhD Joanna Orne-Gliemann

PhD, N Okesola MBA Joseph Larmarange

PhD Eric Balestre

Rodolphe Thiébaut

Frank Tanser

Nonhlanhla Okesola

R Thiebaut

PhD T Makowa

J Dreyer

Prof. N K Herbst

N Mcgrath

T Bärnighausen

S Boyer

T De Oliveira

C Rekacewicz

B Bazin

M-L Newell

D Pillay
email: d.pillay@ucl.ac.uk

François Dabis
email: francois.dabis@u-bordeaux.fr

Iwuji Mrcp

Prof F Tanser

Prof. T Mcgrath Scd

Prof Barnighausen T Scd

PhD De Oliveira

Prof R Thiebaut

Prof. F Dabis

Universal test and treat and the HIV epidemic in rural South Africa: a phase 4, open-label, community cluster randomised trial

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Research in context Evidence before this study

The HPTN 052 trial demonstrated that antiretroviral therapy (ART) significantly reduces HIV transmission from the HIV-infected to the HIV-negative individual within stable partnerships. However, the applicability of these findings when applied at a population level within high prevalence settings remains unclear, particularly where many HIV-infected individuals are either unaware of their diagnosis or fail to disclose their status to their sexual partners. We searched PubMed for studies in the African setting reporting on HIV transmission at the population level from 1 Jan 2004 to 30 July 2017 using the following search terms ((HIV) AND (Antiretroviral) OR Anti-retroviral) OR ART) OR ARV) OR HAART) AND (Incidence) OR Transmission) OR diagno*) AND (population) OR community) AND Africa)). We identified two prospective cohort studies reporting an association between ART coverage and population HIV incidence from 2 378 abstracts. Tanser et al followed up a total of 16 667 adults who were HIV negative at baseline from 2004 to 2011 in the same sub-district as the ANRS 12249 TasP trial. This study showed that an HIV-uninfected individual living in a community with ART coverage of 30 to 40% was 38% less likely to acquire HIV than an individual living in a community where ART coverage was <10%. The other study by Kong et al in Rakai, Uganda from 1999 to 2013 showed that increased ART coverage in females was associated with lower community HIV incidence in males but no association between ART coverage in males and HIV incidence in females, attributable to lower ART coverage in males during this period. Four cluster-randomised trials (including ours) are implemented in South Africa, Zambia, Botswana, Kenya and Uganda to investigate the impact of population ART on HIV incidence.

Added Value of this study

The ANRS 12249 trial is the first of the four trials to report its findings. We demonstrated no reduction in HIV incidence following the implementation of the universal test and treat strategy at community level within a very high HIV prevalence setting. Despite a higher proportion of HIV-positive individuals becoming aware of their HIV status as a result of the trial, very few of them linked to HIV care. A high proportion of those that sought care and were on ART achieved virological suppression.

Implications of all the available evidence

It is possible to achieve high levels of HIV status awareness but policy change to universal ART without significant improvements in linkage to care is unlikely to reduce HIV incidence.

Introduction

HIV incidence in South Africa remains high, with an estimated 380,000 adults and children newly infected in 2015 1 . Since HIV-1 plasma viral load (VL) is strongly associated with sexual transmission risk 2 , expanded use of antiretroviral treatment (ART) allowing to reach undetectable VL has been suggested key to HIV prevention while providing individual health benefits [START_REF] Danel | A Trial of Early Antiretrovirals and Isoniazid Preventive Therapy in Africa[END_REF][START_REF] Lundgren | Initiation of Antiretroviral Therapy in Early Asymptomatic HIV Infection[END_REF] . Ecological [START_REF] Montaner | Association of highly active antiretroviral therapy coverage, population viral load, and yearly new HIV diagnoses in British Columbia, Canada: a population-based study[END_REF] and cohort studies [START_REF] Tanser | High coverage of ART associated with decline in risk of HIV acquisition in rural KwaZulu-Natal, South Africa[END_REF] and a randomized trial conducted among heterosexual serodiscordant couples [START_REF] Cohen | Antiretroviral Therapy for the Prevention of HIV-1 Transmission[END_REF] have demonstrated substantial reduction in new HIV infections with increased ART coverage. Mathematical models suggest important reductions in HIV transmission are achievable with high uptake of regular HIV testing and universal ART initiation when diagnosed HIV-positive [START_REF] Granich | Universal voluntary HIV testing with immediate antiretroviral therapy as a strategy for elimination of HIV transmission: a mathematical model[END_REF] . However, the hypothesis that universal test and treat (UTT) will reduce HIV incidence has not been demonstrated in a trial at population level. The aim of the ANRS 12249 Treatment as Prevention (TasP) cluster-randomised trial was to investigate whether universal ART initiation offered to all HIV-positive individuals (vs. ART initiation according to national guidelines), identified through home-based HIV testing, reduces HIV incidence in a rural and hyper-endemic region of South Africa.

Methods

Study design and study population

The study design was a phased two-arm cluster-randomised trial. Trial protocol and procedures have previously been reported (https://www.ahri.org/tasp-study-protocol/) [START_REF] Iwuji | Evaluation of the impact of immediate versus WHO recommendations-guided antiretroviral therapy initiation on HIV incidence: the ANRS 12249 TasP (Treatment as Prevention) trial in Hlabisa sub-district, KwaZulu-Natal, South Africa: study protocol for a cluster randomised controlled trial[END_REF][START_REF] Orne-Gliemann | Addressing social issues in a universal HIV test and treat intervention trial (ANRS 12249 TasP) in South Africa: methods for appraisal[END_REF] . We implemented the trial from 9 March 2012 to 30 June 2016 in Hlabisa sub-district, northeast KwaZulu-Natal (KZN) (Figures S1, p8 and S2, p9), where estimated HIV prevalence is 30% [START_REF] Iwuji | Uptake of Home-Based HIV Testing, Linkage to Care, and Community Attitudes about ART in Rural KwaZulu-Natal, South Africa: Descriptive Results from the First Phase of the ANRS 12249 TasP Cluster-Randomised Trial[END_REF] . Inclusion criteria were community residence (defined as spending ≥ 4 nights a week in the study area) and age ≥16 years. We note mobility of individuals in and out of the study area, with some community members only visiting their families at the weekend. The Biomedical Research Ethics Committee, University of KwaZulu-Natal, South Africa (BFC 104/11) and the Medicines Control Council of South Africa approved the trial. The trial was also registered on ClinicalTrials.gov: NCT01509508 and South African National Clinical Trials Register: DOH-27-0512-3974.

Sample size

We used the CEPAC mathematical model [START_REF] Walensky | Scaling up the 2010 World Health Organization HIV Treatment Guidelines in resource-limited settings: a model-based analysis[END_REF] to simulate an intervention of bi-annual HIV screening of the adult population, comparing the impact of universal ART initiation irrespective of CD4 count (intervention) with national eligibility guidelines -CD4 cell counts of ≤350 cells/μL (control). Preliminary sample size calculations based on this model concluded that 34 clusters (2x17) of 1,000 eligible residents each followed-up for two years could detect a 30% reduction in cumulative HIV incidence [START_REF] Iwuji | Evaluation of the impact of immediate versus WHO recommendations-guided antiretroviral therapy initiation on HIV incidence: the ANRS 12249 TasP (Treatment as Prevention) trial in Hlabisa sub-district, KwaZulu-Natal, South Africa: study protocol for a cluster randomised controlled trial[END_REF] . We subsequently amended the trial design to account for a phased introduction of clusters over a three-year time period; sample size calculations explicitly accounting for this phased cluster follow-up demonstrated that 22 clusters (2x11, with an estimated 800 HIV uninfected individuals per cluster), followed for a total of 58 cluster-years, would yield 80% power to detect an overall 34% reduction in cumulative HIV incidence, with an incidence of 2•25% per year in the control clusters over the trial period. The effect size was informed by a detailed STDSIM [START_REF] Hontelez | The impact of the new WHO antiretroviral treatment guidelines on HIV epidemic dynamics and cost in South Africa[END_REF] modelling approach using the following parameters: 90% of HIV test offer to those registered, 80% test uptake amongst those offered, 70% linkage-to-care upon diagnosis among those accepting the test, baseline HIV prevalence of 24% and a cross-arm contamination of 10%. The sample size calculation allowed for 20% loss to follow-up and assumed a coefficient of variation of 0•25 to account for variation between clusters [START_REF] Iwuji | Uptake of Home-Based HIV Testing, Linkage to Care, and Community Attitudes about ART in Rural KwaZulu-Natal, South Africa: Descriptive Results from the First Phase of the ANRS 12249 TasP Cluster-Randomised Trial[END_REF] . Following this approach, the trial began in the first ten clusters between 2012 and 2013; from 2014 the trial was expanded to the full 22 clusters (Figure S2,p9). Taking into account the different lengths of follow-up time in the clusters, loss-to-follow-up and frequency of testing patterns, we estimated the total person-years of follow-up among those HIV-negative at baseline to be 15040 per arm. At an annual incidence of 2•25% per year, we estimated 338 seroconversions in the 11 control clusters by the end of the study period. The corresponding figure for the 11 intervention clusters, with an incidence of 1•485% per year, was estimated to be 223 seroconversions.

Randomization

The clusters were composed of aggregated local areas (neighbourhoods). To minimise the degree of between-cluster variation, we stratified the clusters on predicted antenatal HIV prevalence (six strata), extrapolated from HIV surveillance data from the neighbouring Africa Health Research Institute's HIV surveillance site [START_REF] Iwuji | Uptake of Home-Based HIV Testing, Linkage to Care, and Community Attitudes about ART in Rural KwaZulu-Natal, South Africa: Descriptive Results from the First Phase of the ANRS 12249 TasP Cluster-Randomised Trial[END_REF] . The study statistician carried out randomisation within each stratum to derive an equal number of control and intervention communities per HIV prevalence stratum. We used MapInfo version 11.0 to generate the random numbers and perform the randomisation procedure. The nature of the trial meant it was not possible to blind participants and investigators to the intervention.

Study procedures

We used global positioning system coordinates to identify households in the trial area and assigned a unique identification number to each of them. At each six-monthly home-based survey round, HIV counsellors obtained verbal consent to proceed from the head of the household and enumerated all eligible adult members. These adult members constitute the population cohort. Eligible individuals providing written informed consent in isiZulu responded to a socio-demographic and sexual behaviour questionnaire and gave a finger prick sample collected as a dried blood spot (DBS) which we used to estimate population HIV prevalence and incidence through 3 rd generation ELISA. HIV counsellors offered individuals point-of-care rapid HIV counselling and testing using local Department of Health (DoH) approved test kits [START_REF] Iwuji | Evaluation of the impact of immediate versus WHO recommendations-guided antiretroviral therapy initiation on HIV incidence: the ANRS 12249 TasP (Treatment as Prevention) trial in Hlabisa sub-district, KwaZulu-Natal, South Africa: study protocol for a cluster randomised controlled trial[END_REF][START_REF] Iwuji | Uptake of Home-Based HIV Testing, Linkage to Care, and Community Attitudes about ART in Rural KwaZulu-Natal, South Africa: Descriptive Results from the First Phase of the ANRS 12249 TasP Cluster-Randomised Trial[END_REF] . We also introduced mobile HIV testing in all clusters in the final survey round only. HIV counsellors offered rapid HIV testing again in subsequent survey rounds to participants who tested HIV-negative or refused testing in a previous round. We referred participants who tested HIV-positive to their cluster trial clinic. We informed those in the intervention arm that they would be offered ART immediately, regardless of their CD4 count to prevent transmission to their sexual partners and that it was possible that the individual health of those with high CD4 count could also be improved, while those in the control arm were informed that ART would be provided according to national guidelines. Self-identified HIV-positive participants already on ART could opt to continue with their current DoH provider or transfer to a trial clinic. From May 2013 following a protocol amendment to improve linkage to care, study investigators set up a linkage-to-care team to recontact HIV-positive participants in both trial arms who were not in care having failed to attend the trial clinic within three months of referral. They were re-contacted by either phone, home visit or both. Trial nurses clinically evaluated consenting HIV-positive patients at their cluster trial clinic, including the performance of a point-of-care CD4 measurement (Alere Pima CD4 test, Alere, Waltham, MA, USA). The only trial-specific randomised intervention was ART eligibility: in intervention clusters HIV-positive participants were offered ART regardless of CD4 count, whereas in control clusters, ART was provided according to national guidelines (initially CD4 count ≤350/µL, then <500/µL from January 2015) [START_REF]adults: Department of Health, Republic of South Africa[END_REF] . ART was to be initiated within 2 weeks of baseline visit, or sooner if severely immunocompromised. First-line ART was fixed-dose combination tenofovir/emtricitabine/efavirenz (Atripla®) as per national guidelines, other than where clinically contra-indicated. Genotypic resistance testing informed switch to second-line ART. Trial nurses saw patients receiving ART monthly for ART prescription but took blood samples for toxicity monitoring (full blood count, liver function tests, urea, electrolytes and creatinine) and HIV VL measurements at the first visit, three and six months post-ART initiation, and six-monthly thereafter. We allowed unscheduled clinic visits for patients with clinical complaints arising before their protocol visit. In control clusters, nurses invited patients not yet eligible for ART to return within 4-6 months for pre-ART care, repeat clinical assessment, and CD4 count measurement [START_REF] Iwuji | Evaluation of the impact of immediate versus WHO recommendations-guided antiretroviral therapy initiation on HIV incidence: the ANRS 12249 TasP (Treatment as Prevention) trial in Hlabisa sub-district, KwaZulu-Natal, South Africa: study protocol for a cluster randomised controlled trial[END_REF][START_REF] Iwuji | Uptake of Home-Based HIV Testing, Linkage to Care, and Community Attitudes about ART in Rural KwaZulu-Natal, South Africa: Descriptive Results from the First Phase of the ANRS 12249 TasP Cluster-Randomised Trial[END_REF] . Investigators defined loss-to-follow up as being >3 months late for next clinic appointment. Trial clinics also provided care for common co-existing chronic medical conditions, including diabetes and hypertension.

Study outcomes

The primary outcome was HIV incidence, defined by seroconversion between repeat (6monthly) DBS samples collected within the population cohort. All secondary outcomes and plan for dissemination are listed in tables S1a and S1b, p5-6. We report some of them in this manuscript including: HIV status ascertainment (HIV rapid test or HIV-positive self-report), linkage-to-care and sexual behaviours documented within the full trial population cohort; ART initiation among those presenting as ART-naïve, retention in care, virological suppression estimated among the people ascertained as HIV-positive. Investigators estimated population ART coverage (proportion being on ART among all HIV-infected) and the 90-90-90 HIV care cascade for all HIV-positive participants at the population level (Table S2, p6 for detailed definitions).

Statistical analysis

We summarised continuous variables with median and interquartile range (IQR) and categorical variables with frequencies and percentages. We calculated HIV incidence among participants with an initially HIV-negative sample and at least one further sample, and stratified by arm. To estimate person-years of follow-up, we right-censored participants who did not seroconvert to HIV at the date of the last HIVnegative sample. For those who seroconverted, the date of seroconversion was a random-point date between the last negative and the first positive sample. We calculated HIV incidence by dividing the number of seroconversions by the total person-years of follow-up, stratified by arm. We used an intention-to-treat Poisson generalized estimating equation (GEE) taking cluster effect into account with an exchangeable working correlation matrix to estimate the marginal effect of the intervention on HIV incidence [START_REF] Stephens | Augmented generalized estimating equations for improving efficiency and validity of estimation in cluster randomized trials by leveraging cluster-level and individual-level covariates[END_REF] . To improve efficiency of the estimated effect of the intervention, we supplemented this main analysis with an augmented GEE. To do so, we performed an outcome model including as cluster-level covariates: age at inclusion (proportion of participants <30 and ≥60 years), sex (proportion of females), estimated population ART coverage at the beginning of the trial, estimated HIV prevalence at the beginning of the trial and modification of WHO guidelines (time-varying). For the estimation of mortality rate amongst HIV-positive patients in trial clinics, patients contributed person-years of follow-up in the analysis if they had at least one follow-up visit following the baseline clinic visit date and we censored patients who known to be alive at the date of their last clinic visit date. We calculated mortality rate by dividing the number of deaths by the person-years of follow-up, stratified by arm. All analyses were performed with SAS® version 9•4 (SAS Institute, Cary, NC, USA), R package CRTgeeDR® (The R Foundation, 1020 Vienna, Austria) was used to perform the augmented GEE.

Role of the funding source

Representatives of the sponsor were part of the study team and were involved in the design of the study, data interpretation and writing of the manuscript. Pharmaceutical companies providing study drugs had no role in study design, data collection, data analysis, data interpretation, or writing of the manuscript. No listed author received any payments to write this article from a pharmaceutical company or any other agency. The corresponding authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Results

Trial registration and enrolment of participants 28 419 individuals (13 381 intervention, 15 038 control) were eligible for inclusion in the trial (Figure 1); cluster size ranged between 324 and 2872 residents aged 16 years and above. Median age was 30•2 years (IQR 21•4-49•4), 63% were women (Table 1). Overall, 26 518 (93%) of eligible individuals were contacted at least once, of whom 23 476 participants (89%) had their HIV status ever ascertained (i.e. had a HIV rapid test or self-reported being HIVpositive) by a trial fieldworker (Figure S3, p10). Contacted individuals were more likely to be female and older compared to non-contacted individuals, and similar between arms (Table S3, p11). 8 960 of the 26 518 individuals contacted out-migrated from the study area at some point during the trial. Those who out-migrated were more likely to be men, younger, of better educational attainment, never married and actively seeking employment (Table S4, p11).

Population HIV incidence

We excluded a total of 8 710 (33%) of those contacted from the incidence calculation either because their first DBS sample was positive (7 775) or because no valid result was obtained from available sample (935). Of the 17 808 (67•2%) individuals with a first sample being negative, who were thus eligible for inclusion for the incidence cohort, (Figure 1) 79•8% (n=14223: 6756 intervention, 7467 control) had a second sample test and contributed data for the incidence analysis. Those available for the incidence analysis were significantly older (median 29•9 years vs. 23•5 years) and less likely to be male (35•6% vs. 52•6%) than the remaining 20•1% of HIV-negative individuals with only one sample, with no difference between trial arms (Table S5a, p12). They also differed from those HIV-positive at baseline (Table S6, p13). 503 new HIV infections were identified after 22891 person-years, for an overall HIV incidence rate of 2•20 (95% CI 2•01-2•39) per 100 person-years (Table 2). Overall, the incidence of 2•27 per 100 person-years in the control arm (Table 2) was remarkably similar to the rate of 2•25 per 100-years assumed in our sample size calculations. The crude hazard ratio (intervention vs. control) was 0•95 (95% CI 0•75-1•20; p=0•68) and adjusted hazard ratio was 1•01 (95% CI 0•87-1•17; p=0•89) allowing for temporal changes in national ART guidelines and cluster-level measure of sex, age, estimated HIV prevalence and estimated population ART coverage at the beginning of the trial (Tables S7a, p13 and S8, p14).

Identification of HIV-positive individuals and linkage to care

The proportion of registered individuals contacted per round was slightly lower in the intervention arm than in the control arm (72•7% vs. 73•9%, p<0•0001). Amongst those contacted, HIV status ascertainment was also slightly lower in the intervention arm than in the control arm (79•5% vs. 81•1%, p<0•0001) (Table 3). One female participant who tested HIVpositive suffered an acute adjustment reaction with suicidal attempt. Cumulatively in all survey rounds, 7615 adults were ever ascertained HIV-positive and referred to trial clinics in their cluster; 1 972/3 247 (60•7%) of those already in follow-up in DoH clinics switched their care to the trial clinics, while 1 047/4 368 (24•0%) who were never previously in care linked to the trial clinics 1 072 of the 7 615 HIV positive were newly diagnosed during the trial (Figure S3,p10). We estimated entry into care within six months among individuals not previously in care to be 29•7%, similar between arms (p=0•49) and much lower than expected in our model assumptions (Table 3). Amongst those linked to trial clinics, median time between referral and first trial clinic visit was 2•7 weeks (IQR 0•9-21•7) (Table S9, p15).

ART uptake and clinical outcomes in trial clinics

HIV counsellors referred all 7 615 HIV-positive individuals identified to the trial clinics. Of the 3019 who ever linked to trial clinics, 1 492 (49•4%) were ART naïve at the first visit. 635/704 (90•2%) in intervention and 525/788 (66•6%) in control arms initiated ART. At ART initiation, median CD4 was 401 cells per µL (IQR 265-572) and median VL 4.4 log copies per mL (IQR 3•8-5•1) in intervention arm and 320 cells per µL (IQR 212-442) and 4•5 log copies per mL (3•7-5•1) in control arm (Table S9, p15). Of the 698 participants who had been on ART for 12 months, 628 had documented viral load, of whom 611 (97•3%) achieved viral suppression (VL <400 copies per mL), similar between arms. 1 478 ART-experienced participants had been on ART for a median of 3•80 years (IQR 1•75-5•99) at their first visit (639 in intervention and 839 in control), with no difference between arms. The ART status of the remaining 49 individuals was unknown at the first clinic visit (Table S9, p15). Retention in care 12 months after the first trial clinic visit was 81•6% (1 004/1 230) in intervention arm and 75•4% (1 027/1 495) in the control arm. Among all HIV-positive individuals seen in trial clinics, crude mortality rates were 1•28 per 100 PY (95% CI 0•84-1•72) in intervention arm (N=33) and 1•86 per 100 PY (95% CI 1•38-2•34) in control arm (N=58), adjusted hazard ratio intervention vs. control of 0•69 (95% CI: 0 S10, p16). 128 patients experienced 189 life-threatening or Grade 4 clinical events; 69/1 652 (4•2%) in control and 59/1367 (4•3%) in intervention arm (p=0•83) (Table S11, p16).

•42-1•15, p=0•15) (Table

ART coverage and HIV care cascade at population level

At the beginning of the trial, population ART coverage among all HIV-positive adults living in the study area was estimated at 29•6% in intervention arm and 33•7% in control arm, below the initial ART coverage of 40% assumed in STDSIM modelling (Table 3).

ART coverage rose to 53•4 (+23•8) in the intervention arm and 52•8% (+19•1) in the control arm by 1 January 2016, with the difference between arms not statistically significant (p=0•69) (Table 4). As of 1 January 2016, we estimated population 90-90-90 cascade for both arms combined as follows; 91•5% of HIV-positive participants knew their HIV status, of whom 58•0% were on ART, with 85•3% of these virally suppressed, amounting to 49•4% of all HIV-positive participants virally suppressed; similar in intervention and control arms (Table S12, p16).

Sexual risk activity

In the last survey round, among 6 968 participants who reported a sexual partner in the previous six months, condom use at last sexual intercourse was 44•2%, similar between arms. The frequencies of reporting having a sexual partner outside the TasP trial area during the previous six months were 41•6% and 37•1% in the intervention and control arms, respectively (p <0•001) (Table S13, p16).

Discussion

This is the first of four cluster-randomised trials investigating the impact of ART on HIV incidence [START_REF] Hayes | HPTN 071 (PopART): rationale and design of a cluster-randomised trial of the population impact of an HIV combination prevention intervention including universal testing and treatment -a study protocol for a cluster randomised trial[END_REF][START_REF]Sustainable East Africa Research in Community Health[END_REF][START_REF]Clinton Health Access Initiative. MaxART Newletter 6. From Evidence to Action -Evaluating Early Access to ART for All: CHAI[END_REF][START_REF]Botswana Combination Prevention Project[END_REF] . In our trial, HIV incidence was high and we found no significant populationlevel impact of universal ART (vs. national ART initiation guidelines) on HIV incidence. HIV testing uptake was high and repeat testing acceptable [START_REF] Iwuji | Uptake of Home-Based HIV Testing, Linkage to Care, and Community Attitudes about ART in Rural KwaZulu-Natal, South Africa: Descriptive Results from the First Phase of the ANRS 12249 TasP Cluster-Randomised Trial[END_REF] . However, linkage-to-HIV care was both slow and poor, leading to a lower than anticipated increase of population ART coverage (from 31•7% to 53•2%), with no significant difference in ART coverage between arms at trial completion. In this way, the conditions required for a policy of test and treat to translate into a reduction in HIV incidence were not met. Viral suppression among participants on ART was high (>90%) with few serious adverse events. The overall HIV care cascade did not differ by trial arm and fell considerably short of the UNAIDS 90-90-90 targets for 2020 [START_REF]An ambitious treatment target to help end the AIDS epidemic[END_REF] , contrary to what has been recently reported in Eastern Africa [START_REF] Petersen | Association of Implementation of a Universal Testing and Treatment Intervention With HIV Diagnosis, Receipt of Antiretroviral Therapy, and Viral Suppression in East Africa[END_REF] . Those in the intervention arm showed a trend towards a mortality advantage even after a relatively short period of follow-up of one year on average. The most obvious explanation for a lack of difference in HIV incidence between the two trial arms relates to the low linkage-to-care, particularly disappointingly so in the intervention arm. The rate of linkage-to-care was similar in both arms, with only 30% of individuals registering at the trial clinic within six months of home HIV diagnosis, considerably lower than the expected 70%. This was despite HIV-positive individuals in the intervention arm being informed they would be offered ART regardless of their CD4 count and those in the control arm being informed ART will be offered only if eligible according to national guidelines. The consequence of this poor linkage was that even though ART coverage increased during the trial, the increase was not as high as expected, with no significant difference in population ART coverage between the study arms. The inability to create experimental separation between the two arms of the trial would have contributed to the null finding seen with HIV incidence

The poor linkage-to-HIV care despite the introduction of UTT is comparable to South African national estimates [START_REF] Takuva | The continuum of HIV care in South Africa: implications for achieving the second and third UNAIDS 90-90-90 targets[END_REF] , but lower than reported in another trial in Uganda and South Africa [START_REF] Barnabas | Uptake of antiretroviral therapy and male circumcision after community-based HIV testing and strategies for linkage to care versus standard clinic referral: a multisite, open-label, randomised controlled trial in South Africa and Uganda[END_REF] , although definitions of linkage-to-care differed. Delayed linkage-to-care could have resulted in continued HIV transmission from viraemic individuals. Factors we have previously described associated with poor linkage include being young, more educated, newly diagnosed, not knowing anyone HIV-positive and increasing distance between home and the trial clinic [START_REF] Plazy | Access to HIV care in the context of universal test and treat: challenges within the ANRS 12249 TasP cluster-randomized trial in rural South Africa[END_REF] . Trial clinics only catered for HIV-positive people, who may thus have had increased concerns relating to stigma and unintended HIV status disclosure [START_REF] Moshabela | It is better to die": experiences of traditional health practitioners within the HIV treatment as prevention trial communities in rural South Africa (ANRS 12249 TasP trial)[END_REF] , although we had hypothesized that mobile clinics close to participants homes would encourage attendance. Home-based ART initiation could mitigate against some of these challenges. Indeed, it was shown to triple linkage to care in Malawi, although follow-up was too short to evaluate long-term ART adherence and retention on treatment [START_REF] Macpherson | Effect of optional home initiation of HIV care following HIV self-testing on antiretroviral therapy initiation among adults in Malawi: a randomized clinical trial[END_REF] . More studies on the effectiveness and safety of home ART initiation are urgently required.

Other factors may have also contributed to the null finding in secondary ways, especially population mobility, which is high in our setting [START_REF] Dobra | Space-time migration patterns and risk of HIV acquisition in rural South Africa[END_REF] , and could have contributed to low linkageto-care and fuelled a contamination effect. We previously showed [START_REF] Larmarange | Measuring the Impact of Test & Treat on the HIV Cascade: The Challenge of Mobility[END_REF] that mobility dilutes the HIV care cascade at population level due to differences between in-and out-migrations. The impact of a UTT approach could be improved if implemented over a larger geographical area and/or access to care was more actively facilitated and recorded. Mobility was also associated with sexual mixing patterns. We assumed when designing the trial [START_REF] Tanser | Effect of concurrent sexual partnerships on rate of new HIV infections in a high-prevalence, rural South African population: a cohort study[END_REF] that those in the trial area would preferentially have sexual contacts with people in the same locality. We have indeed reported previously that HIV prevalence in the local community is the strongest determinant of HIV acquisition [START_REF] Tanser | High coverage of ART associated with decline in risk of HIV acquisition in rural KwaZulu-Natal, South Africa[END_REF] . However, in this trial, some 40% of participants reported having a sexual partner outside of the trial area, some as far as major cities outside of KwaZulu-Natal. We expect that frequency of sexual contacts would be low for much of this group, given the large distances between partners. Nevertheless, this phenomenon could also have played a role in diluting the effect size between study arms. Phylogenetic work is ongoing to determine whether external sexual partnerships could have also led to a significant contamination effect.

Finally, we implemented the intervention uniformly across the 22 clusters in the six HIV prevalence strata used in the randomisation. However, as anticipated from our previous work in the neighbouring community [START_REF] Tanser | Localized spatial clustering of HIV infections in a widely disseminated rural South African epidemic[END_REF] , there was extraordinary variation in HIV prevalence, which ranged from 17% in deep rural areas to 39% in communities close to the national highway (Table S6). A more focused approach of interventions targeted to areas of high transmission and people most at-risk may have a greater impact; such an approach is supported by modelling, using the Kenyan epidemic as a case study [START_REF] Anderson | Maximising the effect of combination HIV prevention through prioritisation of the people and places in greatest need: a modelling study[END_REF] .

Apart from the lack of impact on transmission, the TasP trial provides further evidence regarding the individual benefits of universal ART. Following the 2015 WHO ART guidelines recommending ART initiation regardless of CD4 count [START_REF]Guideline on when to start antiretroviral therapy and on pre-exposure prophylaxis for HIV[END_REF] for individual benefits [START_REF] Danel | A Trial of Early Antiretrovirals and Isoniazid Preventive Therapy in Africa[END_REF][START_REF] Lundgren | Initiation of Antiretroviral Therapy in Early Asymptomatic HIV Infection[END_REF] and transmission reduction in serodiscordant couples [START_REF] Cohen | Antiretroviral Therapy for the Prevention of HIV-1 Transmission[END_REF] , concerns were expressed regarding ART adherence in asymptomatic individuals. We observed high viral suppression at 12 months, also reported in the SEARCH trial conducted in Uganda and Kenya [START_REF] Petersen | Association of Implementation of a Universal Testing and Treatment Intervention With HIV Diagnosis, Receipt of Antiretroviral Therapy, and Viral Suppression in East Africa[END_REF] and a weak evidence of a 30% reduction in mortality amongst trial clinic attendees over a relatively short period of time. We also found a higher retention rate in the intervention than control arm, with participants on ART more likely to be retained in care than those pre-ART [START_REF] Lessells | Retention in HIV Care for Individuals Not Yet Eligible for Antiretroviral Therapy: Rural KwaZulu-Natal, South Africa[END_REF] . These are strong arguments to roll out UTT without any restriction.

The TasP trial has a number of limitations. Our home-based HIV testing strategy failed to reach 10•8% of eligible men and 4•2% of eligible women. Non-resident household members were not included, although some visited the trial area regularly and were sexual partners of resident members. ART coverage at trial start was by chance higher in the control arm than in the intervention arm. Linkage-to-care counsellors were not present from trial start, and we only intervened after a three-month delay in linkage to care. The South African ART

Table 4 .

 4 Estimated population ART coverage in the ANRS 12249 TasP trial (2012-2016) (calculated from TasP and DoH data)

		01/07/2012*	01/01/2013 †	01/07/2013	01/01/2014	01/07/2014 ‡	01/01/2015	01/07/2015	01/01/2016
	4 clusters opened in 2012
	Intervention	31•7%	43•1%	43•7%	45•5%	47•5%	48•4%	54•2%	57•3%
	arm	(126/397) §	(176/408)	(185/423)	(192/422)	(205/432)	(209/432)	(202/373)	(220/384)
	Control arm	30•7%	43•4%	46•5%	48•1%	45•6%	47•0%	55•4%	57•6%
		(99/323) §	(122/281)	(139/299)	(148/308)	(150/329)	(154/328)	(160/289)	(147/255)
	Difference	+1•1% (p=0•8162)	-0•3%	-2•8%	-2•6%	+1•9%	+1•4%	-1•2%	-0•4%
	intervention		(p=1•00)	(p=0•51)	(p=0•54)	(p=0•66)	(p=0•75)	(p=0•82)	(p=0•99)
	vs. control
	6 clusters opened in 2013
	Intervention		29•8%	40•5%	46•9%	47•1%	49•9%	57•0%	59•3%
	arm		(230/772) §	(346/854)	(477/1 016)	(505/1 073)	(553/1 108)	(576/1 011)	(589/993)
	Control arm		34•7%	37•4%	41•3%	42•9%	44•1%	51•0%	54•3%
			(429/1 237) §	(400/1 070)	(620/1 500)	(655/1 527)	(703/1 593)	(761/1 492)	(763/1 406)
	Difference		-4•9%	+3•1%	+5•6%	+4•2%	+5•8%	+6•0%	+5•0%
	intervention		(p=0•03)	(p=0•18)	(p<0.01)	(p=0•04)	(p<0.001)	(p<0.01)	(p=0•02)
	vs. control
	12 clusters opened in 2014
	Intervention					28•9%	37•1%	44•7%	48•4%
	arm					(439/1 517) §	(589/1 588)	(691/1 547)	(732/1 511)
	Control arm					33•5%	38•2%	45•5%	50•9%
						(528/1 576) §	(633/1 659)	(783/1 722)	(853/1 677)
	Difference					-4•6%	-1•1%	-0•8%	-2•4%
	intervention					(p<0.01)	(p=0•56)	(p=0•67)	(p=0•18)
	vs. control
	All clusters combined
	Intervention
	arm

Acknowledgments

We thank the study volunteers for allowing us into their homes and participating in this trial, the KwaZulu-Natal Provincial and the National Department of Health of South Africa for their support of this study. We thank staff of the Africa Health Research Institute (previously Africa Centre for Population Health) for the trial implementation and analysis of data, including those who conducted the fieldwork, provided clinical care, developed and maintained the database, entered the data and verified data quality. We acknowledge the advice and support of the Scientific Advisory Board: Bernard Hirschel (Chair), Xavier Anglaret, Hoosen Coovadia, Eric Djimeu, Eric Fleutelot, Eric Goemaere, Alice Jacob, Jean-Michel Molina, Lynn Morris, Golriz Pahlavan-Grumel, Calice Talom, Francois Venter, Sibongile Zungu. We acknowledge the advice and support of the DSMB: Patrick Yeni (Chair), Nathan Ford, Hakima Himmich, Catherine Hankins, Helen Weiss, Sinead Delany-Moretlwe. We thank Alpha Diallo and Severine Gibowski at the ANRS for pharmacovigilance support.

guidelines evolved during the study from a 350 CD4 threshold to 500 cells/µL [START_REF]adults: Department of Health, Republic of South Africa[END_REF] , which could have diluted the anticipated effect size, thus reducing the statistical power to observe a difference between arms. Older females were more likely to have contributed to the incidence analysis, with no difference between arms. Because incidence is lower in older individuals, this may have contributed to a lower overall incidence, but would not have biased the estimate of the difference in incidence between arms. We further assessed sensitivity to violation of missing data assumptions and robustness of the estimates by re-analysing the data under two assumptions; all missing second DBS were considered as positive or negative. We observed that neither the point estimate nor the significance changed. We conclude that although missing completely at random is a strong assumption, it is not invalidated by the sensitivity analysis, and the primary analysis can be trusted. Finally, our estimates of population ART coverage and of the HIV care cascade are lower bounds because the status of participants receiving care outside of trial clinics or government clinics is unknown; such individuals could have been wrongly classified as not being on ART or in care. The size of this specific group is also unknown.

In this pivotal cluster-randomised trial, universal testing was implemented in both arms and we tested the hypothesis that provision of universal treatment reduces HIV transmission at population level. The implementation of universal HIV testing and enhanced linkage to care improved population ART coverage in both arms but not differentially by arm, despite provision of universal ART in the intervention trial clinics. Subsequently, we found no difference in HIV incidence at the conclusion of the study. An important finding, however, was the reduction by 30% in the mortality rate among all HIV-positive participants in the intervention communities receiving care in trial facilities. Whilst our study demonstrated overall good viral suppression rates and retention in those entering care, poor linkage to care, possibly associated with HIV-related stigma remains an important obstacle in our setting. Comprehensive intervention packages that increase ART uptake and retention in care are urgently required in order to achieve the 90-90-90 targets so as to maximise the individual and societal benefits of ART.

Authors and contributions

CI, FT, J O-G, M-L N, DP and FD designed and implemented the study. TM, NO, JD, KH, implemented the study. CI and J O-G searched the literature and co-wrote the first draft of the manuscript. EB, JL, FT and RT did the statistical analysis. FT and RT did the sample size calculations. All authors contributed to the interpretation and presentation of the findings. All authors approved the final version of the manuscript for submission. Parameter settings and characteristics of HIV epidemic as modelled by the STDSIM model. Model was quantified to represent the HIV epidemic in rural KwaZulu-Natal, South Africa, using demographic, behavioural, and epidemiological data from the Africa Centre. Model and quantification described elsewhere.

TasP trial (ANRS 12249 group)

Proportion of individuals contacted and whose HIV status was ascertained was computed per homebased survey round, i.e., an individual eligible in three survey rounds, fully contacted in two rounds, but accepting a HIV rapid test only in one round will contribute three episodes in the denominator and two episodes in the numerator for estimation of contact, and two episodes in the denominator and one in the numerator for HIV ascertainment

Reasons for exclusion from analysis:

No DBS result N=478 First sample test positive N=3,584

Reasons for exclusion from analysis:

No sample result N=457 First sample test positive N=4,1 91

First sample negative test Individuals analysed N=8,462

Average cluster size: 769 Range of cluster size: 382-1 ,1 32


Arlette Simo Fotso
email: arlette.simofotso@ird.fr

Cheryl Johnson
email: johnsonc@who.int

Anthony Vautier

Konan Blaise Kouamé

Moussa Papa

Diop

Romain Silhol
email: r.silhol@imperial.ac.uk

Mathieu Maheu-Giroux

Marie-Claude Boily
email: mc.boily@ic.ac.uk

Nicolas Rouveau
email: nicolas.rouveau@ceped.org

Clémence Doumenc-Aïdara

Rachel Baggaley
email: baggaleyr@who.int

Eboi Ehui
email: ehui.eboi@pnls-ci.com

Joseph Larmarange
email: joseph.larmarange@ird.fr

Arlette Simo Fotso
email: simofotsoarlette@yahoo.fr

Elvis Amani

Georges

Badiane Kéba Solthis

Bekelynck Anne

Boye Sokhna

Diop Papa

Moussa Solthis

Sénégal Doumenc-Aïdara

Clémence Solthis

Ehui Eboi

PNLS Directeur Coordonnateur

Jean Kévin

Kouadio Brou

Maheu-Giroux Mathieu

Medley Graham

Simo Fotso

Traore Métogara

Mohamed Solthis

Ivoire Côte D'

Dakar, Sénégal Solthis

Sanata Diallo

Gueye Papa

Alioune Solthis

Geoffroy Olivier Solthis

Armand Abokon

Ariel Fondation

Glaser

Camille Espace Anoma

Confiance

Côte D'ivoire

Using routine programmatic data to estimate the population-level impacts of HIV selftesting: The example of the ATLAS program in Cote d'Ivoire

Background

HIV self-testing (HIVST) is recommended by the World Health Organization as an additional HIV testing approach. Since 2019, it has been implemented in Côte d'Ivoire through the ATLAS project, including primary and secondary distribution channels. While the discreet and flexible nature of HIVST makes it appealing for users, it also makes the monitoring and estimation of the population-level programmatic impact of HIVST programs challenging. We used routinely collected data to estimate the effects of ATLAS' HIVST distribution on access to testing, conventional testing (self-testing excluded), diagnoses, and antiretroviral treatment (ART) initiations in Côte d'Ivoire.

Methods

We used the ATLAS project's programmatic data between the third quarter (Q) of 2019 (Q3 2019) and Q1 2021, in addition to routine HIV testing services program data obtained from the President's Emergency Plan for AIDS Relief dashboard. We performed ecological time series regression using linear mixed models.

.

Implications of all the available evidence

Our results showed that HIVST increased the overall HIV testing uptake and diagnoses in Côte d'Ivoire without significantly reducing conventional HIV testing uptake. We demonstrated that routinely collected programmatic data could be used to estimate the effects of HIVST kit distribution outside a trial environment. The methodology used in this paper could be replicated and implemented in different settings and enable more countries to routinely evaluate HIVST programming at the population level.

Findings

The results are presented for 1000 HIVST kits distributed through ATLAS. They show a negative but nonsignificant effect of the number of ATLAS HIVST on conventional testing uptake (-190 conventional tests [95% CI: -427 to 37, p=0 •10]). We estimated that for 1000 additional HIVST distributed through ATLAS, +590 [95% CI: 357 to 821, p<0•001] additional individuals have accessed HIV testing, assuming an 80% HIVST utilization rate (UR) and +390

[95% CI: 161 to 625, p<0•001] assuming a 60% UR. The statistical relationship between the number of HIVST and HIV diagnoses was significant and positive (+8 diagnosis [95% CI: 0 to 15, p=0•044]). No effect was observed on ART initiation (-2 ART initiations [95% CI: -8 to 5, p=0•66]).

Interpretations

Social network-based HIVST distribution had a positive impact on access to HIV testing and diagnoses in Cote d'Ivoire. This approach offers a promising way for countries to assess the impact of HIVST programs.

Funding

Unitaid 2018-23-ATLAS Keywords: HIV; HIV self-testing; access to HIV testing; conventional testing; diagnoses; antiretroviral treatment; Key populations; vulnerable populations; ATLAS project; programmatic data; triangulation of data; time series regression; West Africa; Côte d'Ivoire

Research in context Evidence before this study

We searched PubMed between November 9 and 12, 2021, for studies assessing the impact of HIVST on HIV testing, 'conventional' testing, HIV diagnoses and ART initiation. We searched published data using the terms "HIV self-testing" and "HIV testing"; "HIV self-testing" and "traditional HIV testing" or "conventional testing"; "HIV self-testing" and "diagnosis" or "positive results"; and "HIV self-testing" and "ART initiation" or "Antiretroviral treatment".

Articles with abstracts were reviewed. No time or language restriction was applied. Most studies were individual-based randomized controlled trials involving data collection and some form of HIVST tracking; no studies were conducted at the population level, none were . conducted in western Africa and most focused on subgroups of the population or key populations. While most studies found a positive effect of HIVST on HIV testing, evidence was mixed regarding the effect on conventional testing, diagnoses, and ART initiation.

Added value of this study

HIVST can empower individuals by allowing them to choose when, where and whether to test and with whom to share their results and can reach hidden populations who are not accessing existing services. Inherent to HIVST is that there is no automatic tracking of test results and linkages at the individual level. Without systematic and direct feedback to program implementers regarding the use and results of HIVST, it is difficult to estimate the impact of HIVST distribution at the population level. Such estimates are crucial for national AIDS programs. This paper proposed a way to overcome this challenge and used routinely collected programmatic data to indirectly estimate and assess the impacts of HIVST distribution in Côte d'Ivoire.

Introduction

In 2019, up to 19% of people living with HIV (PLHIV) worldwide were not aware of their HIV status. [START_REF] Rouveau | Describing, analysing and understanding the effects of the introduction of HIV self-testing in West Africa through the ATLAS programme in Côte d'Ivoire, Mali and Senegal[END_REF] In Western Africa, this proportion of undiagnosed PLHIV reached 33% in 2020. [START_REF] Giguère | Trends in knowledge of HIV status and efficiency of HIV testing services in Sub-Saharan Africa (2000-2020): a modelling study of survey and HIV testing program data[END_REF] This is quite far from the Joint United Nations Programme on HIV/AIDS (UNAIDS) target to achieve less than 5% of PLHIV being undiagnosed by 2025. HIV testing is a crucial element of responses to HIV, as it is the first step to linkage to care and treatment. It is also key for prevention, as PLHIV who are on antiretroviral treatment (ART) and virally suppressed will not transmit HIV to their sexual partners. [START_REF] Li | Vital Signs: HIV Transmission Along the Continuum of Care -United States, 2016[END_REF] West African countries, including Côte d'Ivoire, are characterized by mixed epidemics: national HIV prevalence levels in the adult population are lower than those in East and Southern . Africa (2•4% in Côte d'Ivoire in 2019 vs. 6•7% in East and Southern Africa), but HIV remains widespread, and higher prevalence levels are observed in key populations (KPs), such as female sex workers (FSW), men who have sex with men (MSM), and people who use drugs (PWUD) (between 3•4% and 12•3% in 2019). [START_REF]UNAIDS data 2020[END_REF][START_REF] Avert | HIV and AIDS in East and Southern Africa regional overview[END_REF] According to the UNAIDS, in West and Central Africa, 42% of new HIV infections (15-49 years old) in 2019 occurred among KPs and 27% among clients of sex workers and other sexual partners of this KP. [START_REF]UNAIDS data 2020[END_REF] A mathematical modeling study estimated that 44% of new infections in Côte d'Ivoire between 2005 and 2015 were due to partnerships between clients of FSW and their non-FSW female partners. [START_REF] Maheu-Giroux | Changing Dynamics of HIV Transmission in Côte d'Ivoire: Modeling Who Acquired and Transmitted Infections and Estimating the Impact of Past HIV Interventions (1976-2015)[END_REF] The World Health Organization (WHO) recommends HIV self-testing (HIVST), which allows individuals to test and learn their results themselves when and how they want. [START_REF]Guidelines on HIV self-testing and partner notification: supplement to Consolidated guidelines on HIV testing services[END_REF] It is an innovative tool that has been demonstrated to be safe, accurate, empowering, and acceptable and to also consistently increase the uptake and frequency of HIV testing across settings and populations. [START_REF] Chanda | HIV self-testing among female sex workers in Zambia: A cluster randomized controlled trial[END_REF][START_REF] Figueroa | Reliability of HIV rapid diagnostic tests for selftesting compared with testing by health-care workers: a systematic review and meta-analysis[END_REF][START_REF] Johnson | Realizing the potential for HIV self-testing[END_REF][START_REF] Knight | I think it is right": a qualitative exploration of the acceptability and desired future use of oral swab and finger-prick HIV self-tests by lay users in KwaZulu-Natal, South Africa[END_REF][START_REF] Kurth | Accuracy and Acceptability of Oral Fluid HIV Self-Testing in a General Adult Population in Kenya[END_REF][START_REF] Njau | A systematic review of qualitative evidence on factors enabling and deterring uptake of HIV self-testing in Africa[END_REF][START_REF] Oldenburg | Intimate Partner Violence and Antiretroviral Therapy Initiation Among Female Sex Workers Newly Diagnosed With HIV in Zambia: A Prospective Study[END_REF][START_REF] Thirumurthy | Promoting male partner HIV testing and safer sexual decision making through secondary distribution of self-tests by HIV-negative female sex workers and women receiving antenatal and post-partum care in Kenya: a cohort study[END_REF] It is recommended that a reactive HIVST must be followed by a conventional test to confirm or disprove the results.

In Southern and East Africa, HIVST has been scaled up quickly, catalyzed by the Unitaidfunded Self-test Africa (STAR) initiative, which was started in 2015. [START_REF] Ingold | The Self-Testing AfRica (STAR) Initiative: accelerating global access and scale-up of HIV self-testing[END_REF] However, before 2019, HIVST was offered only in West Africa through small-case pilot projects. [START_REF] Lyons | Use and Acceptability of HIV Self-Testing Among First-Time Testers at Risk for HIV in Senegal[END_REF] [START_REF] Rouveau | Describing, analysing and understanding the effects of the introduction of HIV self-testing in West Africa through the ATLAS programme in Côte d'Ivoire, Mali and Senegal[END_REF] From 2019-2022, together with national programs, ATLAS planned to deliver 400 000 HIVST kits (214 000 in Côte d'Ivoire). The ATLAS program had set a target for 90% of HIVST implementation to reach KPs and their sexual partners, peers and clients. The remaining target of the HIVST implementation was to reach people with sexually transmitted infections (STIs), their partners and partners of people living with HIV. ATLAS activities rely on both primary and secondary distribution channels. With primary distribution, HIVST kits are distributed by peer educators and frontline health care workers to primary contacts-MSM, PLHIV, STI patients, FSW, and PWUD-for their personal use. For secondary distribution, primary contacts are invited to redistribute HIVST kits to their peers, partners, clients and relatives (see Figure 1a). These secondary contacts are often members of key and vulnerable populations who often do not have easy access to the health system, including sexual partners of PLHIV or individuals in KPs. This specificity of HIVST kit . distribution implies that HIVST beneficiaries (end users) are not limited to primary contacts.

First, ATLAS's program results have shown that HIVST can reduce stigma; preserve anonymity and confidentiality; reach KPs that do not access testing via other testing approaches; save opportunity costs for users and providers; empower users with autonomy and responsibility; and is noninvasive and easy to use. [START_REF] Ky-Zerbo | Enthusiasm for Introducing and Integrating HIV Self-Testing but Doubts About Users: A Baseline Qualitative Analysis of Key Stakeholders' Attitudes and Perceptions in Côte d'Ivoire, Mali and Senegal[END_REF] Several programs have developed methods to assess the use of HIVST and test results, such as supervision by health workers, the return of used kits, messages or phone call reminders to return used samples, the electronic transmission of photographs of test results, or the use of Bluetooth sensors. [START_REF] Tahlil | Verification of HIV Self-Testing Use and Results: A Global Systematic Review[END_REF] However, such tracking can be costly and counterproductive by limiting the use and distribution of HIVST and is not in line with the philosophy of HIVST, where users can anonymously decide when and where they are tested and if and to whom they want to report their results. The systematic tracking of HIVST though secondary distribution is logistically challenging and can also hinder the secondary distribution of HIVST, as primary contacts can be reluctant to redistribute an HIVST kit if they need to collect contact information. It could also be challenging for tracking HIVST at a large scale due to the logistics it might involve. To preserve the anonymity and confidentiality of those using HIVST and not impede the use of HIVST, ATLAS decided not to systematically track distributed HIVST kits. Nevertheless, HIVST users can still, if they wish, obtain additional support by calling a peer educator or a national HIV hotline.

Without systematic and direct feedback regarding the use and results of HIVST and linkage to confirmatory testing and ART, it is challenging to estimate the population-level impacts of HIVST distribution. [START_REF] Choko | Measuring linkage to HIV treatment services following HIV self-testing in low-income settings[END_REF] In this paper, we aimed to circumvent this problem by using routinely collected programmatic data to estimate the effects of ATLAS's HIVST distribution on access to HIV testing, conventional HIV testing (i.e., self-testing excluded), HIV diagnoses, and ART initiations in Côte d'Ivoire.

Methods

Data sources

In 2020, Côte d'Ivoire was divided into 33 health regions and 113 health districts. the number of HIVST kits distributed through PEPFAR-funded activities; (ii) conventional testing, i.e., the number of "individuals tested for HIV who received results"; (iii) HIV diagnoses, i.e., the number of "individuals who newly tested positive for HIV"; and (iv) ART initiations, i.e., the number of "people newly enrolled to receive ART".

ATLAS HIVST distribution in

For this study, we used quarterly data aggregated at the health district level-harmonized according to the 2020 subdivision-from Q3 2019 to Q1 2021. Over this period, the PEPFAR data were only available for 78/113 (69%) Ivorian health districts. Only these districts were included in the analysis.

Modeling strategy

The exact proportion of distributed HIVST kits that people actually use is unknown. We assumed, both for PEPFAR and ATLAS HIVST kits, a utilization rate (UR) of 80% based on the literature. [START_REF] Choko | Uptake, Accuracy, Safety, and Linkage into Care over Two Years of Promoting Annual Self-Testing for HIV in Blantyre, Malawi: A Community-Based Prospective Study[END_REF] We constructed a composite indicator reflecting access to HIV testing-all types-by summing the number of conventional tests and the number of HIVST kits that were actually used (UR 80%). We also considered a more conservative assumption with an HIVST UR of 60%.

Our analysis considered five outcomes: access to HIV testing (UR 80%), access to HIV testing (UR 60%), conventional testing, HIV diagnoses and ART initiations. The last three outcomes were obtained directly from the PEPFAR datasets.

We used ecological time series regression to model the linear effect of the number of HIVST kits distributed through ATLAS for each outcome. [START_REF] Bhaskaran | Short term effects of temperature on risk of myocardial infarction in England and Wales: time series regression analysis of the Myocardial Ischaemia National Audit Project (MINAP) registry[END_REF] We first used linear mixed models with district-level random effects, as presented in Equation (1):

𝑦 𝑖,𝑡 = 𝛽 1 • 𝐻𝐼𝑉𝑆𝑇 𝑖,𝑡 + 𝛽 2 • 𝑡 + 𝑑 𝑖 (1)
where 𝑦 𝑖,𝑡 is the outcome of district i at time t. 𝐻𝐼𝑉𝑆𝑇 is the number of HIVST kits distributed through ATLAS. 𝛽 1 represents the effect of the latter variable on the outcomes. 𝑡 is time, which . captures conjectural effects. Conjectural effects (time) were modeled as a categorical variable of the quarter of the year to account for any nonlinear or nonpolynomial trend. [START_REF] Bhaskaran | Time series regression studies in environmental epidemiology[END_REF] 𝑑 𝑖 is the district-specific random effect. District-level random effects were used to account for autocorrelation due to multiple observations and to produce standard errors adjusted for clustering.

Then, contextual effects were also taken into account by introducing the categorical variable of health regions (𝑅 𝑖 ) in the second model defined by Equation ( 2):

𝑦 𝑖,𝑡 = 𝛽 1 • 𝐻𝐼𝑉𝑆𝑇 𝑖,𝑡 + 𝛽 2 • 𝑡 + 𝛽 3 • 𝑅 𝑖 + 𝑑 𝑖 (2)
For each outcome, both Models (1) and (2) were run.

We performed the first sensitivity analysis by using cubic splines instead of a categorical variable for modeling time and compared the AIC (Akaike information criterion) of the models. ATLAS activities were implemented in 9 of the 78 districts covered by the PEPFAR dataset.

We also performed a second sensitivity analysis by restricting the sample to these 9 health districts.

All analyses were performed in R (version 4.0.3) using the lme4 package for statistical models.

Role of the funding source

The funder had no role in the research design, data collection, analysis, interpretation, or writing of the manuscript.

Results

Descriptive statistics

In the 78 health districts monitored by PEPFAR, between Q3 2019 and Q1 2021, 30 781 HIVTS kits were distributed through PEPFAR, and 99 353 HIVST kits were distributed through ATLAS, compared with 2 167 828 conventional tests performed over the same period (Table 1). High disparities in terms of volume were observed between districts, with a minimum of 1 832 conventional tests and a maximum of 139 214 (median of 13 348). The 9 districts-out of 78-where ATLAS activities were implemented accounted for one quarter (532 287/2 167 828) of conventional tests. Important variations were also observed in terms of access to HIV testing, HIV diagnoses, and ART initiations across districts.

In the 78 districts included in the analysis, conventional testing decreased between Q3 2019 and Q1 2021, from 379 554 individuals tested for HIV who received their results in Q3 2019 . to 268 807 in Q1 2021 (Figure 1a). In the 69 districts that were not covered by ATLAS (Figure 1c), HIVST kits distributed through PEPFAR remained limited and largely insufficient to compensate for the reduction in conventional testing; only 13% of the tests in these districts were HIVST kits. In the 9 ATLAS districts, HIVST kit distribution-mainly through ATLAS, but also partially through PEPFAR-has increased continuously since Q3 2019 (Figure 1b), with a slow-down in Q2 2020, when governmental COVID-19 measures were introduced.

Overall, HIVST in these districts mitigated the decreased access to HIV testing in these districts

(Figure 2a & 2b).
HIV diagnoses and ART initiations remained relatively stable over time (Figures 2c &2d), with a catch-up effect observed in Q1 2020 after a slowdown in Q4 2019. Trends were fairly similar in the ATLAS districts and the districts not covered by ATLAS.

Regression results

When adjusting for time and region, the model estimated a significant positive statistical relationship between ATLAS's HIVST and access to HIV testing: for every 1000 additional 2).

The sensitivity analyses modeling time with cubic splines instead of categorical variables showed very similar results (Table A1) overall, except that the effect on HIV diagnoses was no longer significant at 5% (p=0•055). A comparison of the AIC values of the models indicated that the models with categorical variables fit the time series better (Table A2).

When restricting the analyses to the 9 ATLAS districts, the estimated magnitudes of association were larger. Only access to testing was statistically significantly associated with the number of HIVST kits distributed through ATLAS (Table A3).

.

Discussion

Using routinely collected programmatic data aggregated quarterly at the health district level, our analysis showed a significant positive effect of HIVST kits distributed through ATLAS on access to HIV testing and HIV diagnoses, a negative but not significant effect on conventional testing and no observable effect on ART initiations.

HIVST could lead to some substitution effects if HIVST kits are used by individuals who would have undergone a conventional HIV test in its absence, as observed in other studies. [START_REF] Chanda | HIV self-testing among female sex workers in Zambia: A cluster randomized controlled trial[END_REF][START_REF] Ortblad | Direct provision versus facility collection of HIV self-tests among female sex workers in Uganda: A cluster-randomized controlled health systems trial[END_REF] Such effects may be concerning for policy-makers, as gains in HIV testing coverage due to HIVST distribution may result in a reduction in the number of conventional HIV tests. Our results did show a negative but nonsignificant effect of HIVST kit distribution on conventional testing (-195 conventional tests for every 1000 distributed HIVST), suggesting a possible but limited substitution effect. However, the overall net effect on HIV testing remained significantly positive, with +390 to +590 persons who would have not been tested otherwise, per 1000 distributed HIVST (depending on the assumption of the HIVST UR).

Moreover, the descriptive data showed that a decrease in conventional testing occurred in all districts, including those not covered by ATLAS activities, this is linked to the fact that PEPFAR's testing strategies are revised annually and favoring more targeted approaches. [START_REF] Bekelynck | ANRS 12323 DOD-CI Study Group. Pepfar 3.0's HIV testing policy in Côte d'Ivoire (2014 to 2018): fragmentation, acceleration and disconnection[END_REF] Our results suggest that ATLAS HIVST distribution allowed to maintain access to HIV testing in its implementation districts despite the slowdown observed in Q2 2020 when governmental COVID-19 measures were introduced. In fact, the first results of the ATLAS project have shown that HIVST distribution activities among KPs could be easily adapted, including in the context of the COVID-19 pandemic. [START_REF] Kra | Introducing and Implementing HIV Self-Testing in Côte d'Ivoire, Mali, and Senegal: What Can We Learn From ATLAS Project Activity Reports in the Context of the COVID-19 Crisis?[END_REF] Due to its confidential nature, HIVST could overcome several structural barriers for HIV diagnoses-such as stigma and opportunity costs-and create new approaches to reach firsttime testers and boost HIV retesting for KPs, therefore improving access to HIV testing overall.

These results are in line with previous studies among KPs in East and South Africa. [START_REF] Chanda | HIV self-testing among female sex workers in Zambia: A cluster randomized controlled trial[END_REF][START_REF] Ortblad | Direct provision versus facility collection of HIV self-tests among female sex workers in Uganda: A cluster-randomized controlled health systems trial[END_REF][START_REF] Kelvin | A Randomized Controlled Trial to Increase HIV Testing Demand Among Female Sex Workers in Kenya Through Announcing the Availability of HIV Self-testing Via Text Message[END_REF] If HIVST is appropriately used as a triage test and individuals with reactive self-tests are linked for confirmatory testing, HIVST distribution activities should lead to a higher number of positive tests in conventional testing. Several actors have expressed concern that HIVST could have a negative impact on new diagnoses. [START_REF] Ky-Zerbo | you also need to know the results": lay providers' concerns on HIV self-testing provision to peers[END_REF] Our results did not show any deleterious effect on HIV diagnoses but rather showed a significant positive effect. This is in line with some other studies, such as that by MacGowan et al., who found that the number of HIV infections detected . in their HIVST arm was higher compared to the control arm in a randomized trial conducted among MSM. [START_REF] Macgowan | Effect of Internet-Distributed HIV Self-tests on HIV Diagnosis and Behavioral Outcomes in Men Who Have Sex With Men: A Randomized Clinical Trial[END_REF] Our model did not observe any significant effect of ATLAS HIVST kit distribution on ART initiations. The estimated effect was negative when all 78 districts were included and positive when the analysis was limited to the 9 ATLAS districts. The analysis with 9 districts could suffer from a lack of power. A time effect could also be encountered if many newly diagnosed patients delayed ART initiation by several months; in such cases, the treatment initiation would not be registered and reported during the same quarter of the year.

The PEPFAR datasets are not exhaustive for Côte d'Ivoire and cover only 78 out of the 113 health districts at the national level and 9 of the 12 ATLAS districts.

Using aggregated data rather than individual data implies a lower number of observation points and therefore lower statistical power, although these data allow us to make population-level estimates. Aggregated data is subject to ecological bias and statistical relationships must be interpreted with caution. In addition, it is not possible to completely rule out any 'contamination' effect, as individuals living on district borders could perform conventional testing in the neighboring district. However, we could assume that population movement at boundaries could happen in both directions, thus compensating for each other, or expect the observed effect to have been even stronger without a 'contamination' effect. The collected data did not allow us to distinguish between confirmatory tests following HIVST and classic conventional tests, but as the HIV prevalence is relatively low in the country, the former number might not be important. Finally, HIVST kits distributed through UNICEF or the Global Fund to fight AIDS, tuberculosis and malaria were not taken into account when computing access to HIV testing, although the volumes of tests distributed by these programs were very low, 6 879 and 1 373 kits, respectively, by 2020, representing less than 7% of all HIVST kits distributed in the country.

A strength of this study is that it specifically used only indicators that had already been routinely collected by countries, which means that the method could be easily replicated in other contexts and used by other countries to monitor the impact of their HIVST activities without any additional cost. Our analysis did not rely on any systematic tracking system or data collection process, which can be expensive and complex and are counter to the rationale for HIVST.

The core component of the ATLAS HIVST strategy in West Africa is the secondary distribution of HIVST kits, primarily distributed through activities targeting individuals in KPs, in particular . FSW and MSM. It is therefore expected that many HIVST users would not self-identify as being in a KP and that those with a reactive test would not link to partner community facilities serving KPs for confirmatory testing but rather to more general public or private facilities, making it difficult to link specific records with the distribution of HIVST kits. In addition, records of prior HIVST kit use at health facilities are expected to be underestimated, as recognizing such use would mean the individual was a member of and/or in a network of a KP. By using data aggregated at the district level and covering all testing facilities, confirmatory tests prompted by reactive HIVST results are considered, regardless of where they occurred.

By allowing programs to shift from systematic tracking for evaluation, such indirect evaluation would help to focus on and increase access to HIV testing for hard-to-reach populations and first-time testers and allow large-scale secondary distribution implementation.

To the best of our knowledge, this represents the first study estimating the impact of HIVST kit distribution at the population level in West Africa. Such evaluation is pragmatic and could be performed with routinely collected programmatic indicators. The WHO recommends reporting on the number of HIVST kits distributed and estimating HIVST access and use through population-based surveys. Countries are burdened with multiple HIV reporting systems and numerous indicators. It could therefore be of considerable benefit to monitor the impact of selftesting through current data systems without introducing new indicators and further data collection. This method of triangulating available data provides further information on the population-level impacts of HIV self-testing to guide program use.

Our results highlight that a social network-based distribution strategy of HIVST, targeting key population members as primary contacts but aiming to reach their partners and social contacts, does have a positive impact on access to HIV testing and diagnoses that is observable at the population level.

.

Table and Figures

) 0•798 0•160 to 1•436 0•015 0•710 0•068 to 1•353 0•031 Conventional testing 0•199 -0•435 to 0•833 0•53 0•112 -0•527 to 0•750 0•73 HIV diagnoses 0•018 -0•008 to 0•043 0•17 0•014 -0•010 to 0•038 0•25 ART initiations 0•004 -0•016 to 0•024 0•70 0•005 -0•014 to 0•025 0•57

  A medium-scale HIVST program was implemented in Côte d'Ivoire, Mali, and Senegal in 2018, with an effective distribution of kits through the ATLAS project funded by Unitaid and implemented by a consortium led by Solidarité thérapeutique et initiatives pour la santé (Solthis) and the French Research Institute for Sustainable Development (IRD) since 2019.

  HIVST kits distributed through ATLAS during a quarter in a district, ~590 [95% confidence interval (CI): 357 to 821, p<0•001] additional individuals accessed HIV testing under the 80% UR hypothesis, and ~390 [95% CI: 161 to 625, p<0•001] accessed testing under the 60% UR hypothesis. ATLAS HIVST kit distribution had a negative but non-statistically significant effect on conventional testing, with ~-190 [95% CI: -427 to 37, p=0•10] conventional tests for every 1000 additional HIVST kits distributed by ATLAS. The association between HIVST kit distribution and HIV diagnoses was statistically significant and positive: +8 diagnoses [95% CI: 0 to 15, p=0•044]. No statistically significant association between HSVST kit distribution and ART initiations was observed: -2 [95% CI: -8 to 5, p=0•66]. Similar results were observed when adjusting only for time regarding the linear effect of the number of HIVST kits distributed through ATLAS on the different outcomes (first columns of Table

Figure 1 :

 1 Figure 1: Number of conventional testing and HIVST kits distributed through PEPFAR and ATLAS from Q3 2019 to Q1 2021 in a) all 78 health districts monitored by PEPFAR in Côte d'Ivoire, b) the 9 ATLAS districts only, and c) the 69 districts not covered by ATLAS.

.

Figure 2 :

 2 Figure 2: Number of testing, HIV diagnoses and ART initiations in the 78 health districts monitored by PEPFAR in Côte d'Ivoire (Q3 2019 to Q1 2021)

  Côte d'Ivoire started during the third quarter of 2019 (Q3 2019) among individuals aged 16 years or older (minimum legal age for HIV testing without parental.consent). All ATLAS implementing partners reported the number of HIVST kits distributed through ATLAS monthly by distribution site, delivery channel, age group and sex of primary contacts. Data were aggregated per health district and quarter of the year.

	Routine programmatic data for adults over 15 years of age were obtained from the President's
	Emergency Plan for AIDS Relief (PEPFAR) open-access public repository
	(https://data.pepfar.gov/). PEPFAR is the principal donor to the national AIDS program in Côte
	d'Ivoire. It collects programmatic data in the health districts where it intervenes, including (i)

Table 1 :

 1 District characteristics and activities between Q3 2019 and Q1 2021 in 78 health districts monitored by PEPFAR in Côte d'Ivoire

	Variable	All districts, N = 78	ATLAS districts, N = 9	Districts not covered by ATLAS, N = 69
	HIV testing (HIVST UR:
	80%)
	Total	2 271 935	619 674	1 652 261
	Median	19 417	71 044	18 351

Table 2 :

 2 Linear effect of the number of HIVST kits distributed through ATLAS on access to HIV testing, conventional tests, diagnoses and ART initiations in the 78 health districts monitored by PEPFAR in Côte d'Ivoire (Q3 2019 to Q1 2021) CI = Confidence Interval. Coef.= coefficient. UR= utilization rate. For the five outcomes, only the regression coefficients of the number of HIVST kits distributed through ATLAS are presented. For the full regression table, see the Supplementary Material (Table A4 through A8).

			Adjusted for time		Adjusted for time and region
	Outcome	Coef.	95% CI 1	p value	Coef.	95% CI 1	p value
	HIV testing (HIVST UR: 80%)	0•649	0•417 to 0•881	<0•001	0•589	0•356 to 0•821	<0•001
	HIV testing (HIVST UR: 60%)	0•453	0•221 to 0•686	<0•001	0•393	0•160 to 0•625	<0•001
	Conventional tests	-0•133	-0•365 to 0•099	0•26	-0•195	-0•427 to 0•038	0•10
	HIV diagnoses	0•009	0•001 to 0•016	0•019	0•008	0•000 to 0•015	0•044
	ART initiations	0•000	-0•007 to 0•006	0•90	-0•002	-0•008 to 0•005	0•66

[START_REF] Rouveau | Describing, analysing and understanding the effects of the introduction of HIV self-testing in West Africa through the ATLAS programme in Côte d'Ivoire, Mali and Senegal[END_REF]

Table A1 : Effect of the number of HIVST kits distributed by ATLAS on HIV testing, conventional testing, diagnoses and ART initiations, time modeled using a cubic spline Adjusted for time Adjusted for time and region

 A1

	Outcome	Coef.	95% CI 1	p value	Coef.	95% CI 1	p value
	HIV testing (HIVST UR: 80%)	0•629	0•394 to 0•863	<0•001	0•567	0•333 to 0•802	<0•001
	HIV testing (HIVST UR: 60%)	0•434	0•200 to 0•669	<0•001	0•373	0•138 to 0•607	0•002
	Conventional testing	-0•149	-0•383 to 0•085	0•21	-0•211	-0•446 to 0•023	0•077
	HIV diagnoses	0•009	0•001 to 0•016	0•024	0•007	0•000 to 0•015	0•055
	ART initiations	0•000	-0•007 to 0•007	0•97	-0•001	-0•008 to 0•006	0•78
	1 CI = Confidence Interval. Coef.= coefficient. UR= utilization rate.

Table A2 : Akaike information criterion comparison of the models according to trend modeling

 A2

			Outcome
	Trend modeling	HIV testing (HIVST UR: 80%)	HIV testing (HIVST UR: 60%)	Conventional testing	HIV diagnoses	ART initiations
	Time (categorical variable) indicator	8 908•4	8 907•5	8 906•9	5 365•0	5 264•5
	Cubic splines	8 949•9	8 948•7	8 947•4	5 393•5	5 293•2

Note: AIC was compared for the models adjusted for time and region. UR= utilization rate.

Table A3 : Effect of the number of HIVST kits distributed by ATLAS on HIV testing, conventional testing, diagnoses and ART initiations, data restricted to the ATLAS districts Adjusted for time Adjusted for time and region

 A3

	Outcome	Coef.	95% CI 1	p value	Coef.	95% CI 1	p value
	HIV testing (HIVST UR: 80%)	0•997	0•357 to 1•637	0•003	0•910	0•265 to 1•554	0•007
	HIV testing (HIVST
	UR: 60%

Table A4 . Linear effect of the number of HIVST kits distributed through ATLAS on access to HIV testing (HIVST UR: 80%) in the 78 health districts monitored by PEPFAR in Côte d'Ivoire (Q3 2019 to Q1 2021) Adjusted for time Adjusted for time and region

 A4 CI = Confidence Interval. Coef.= coefficient. UR= utilization rate. Time is modeled as a categorical variable.

				. Adjusted for time Adjusted for time and region
	Outcome	Coef.	95% CI 1	p value	Coef.	95% CI 1	p value
	Outcome Moronou	Coef.	95% CI 1	p value	Coef. -4 413•957	95% CI 1 -8 221•761 to -606•152	p value 0•024
	Number N'zi	of				-5 155•861	-8 963•666 to -1 348•056	0•009
	HIVST distributed Poro	kits	0•649	0•417 to 0•881	<0•001	0•589 -3 401•490	0•356 to 0•821 -7 209•295 to 406•315	<0•001 0•079
	through ATLAS Tchologo				-5 147•618	-9 593•785 to -701•452	0•024
	Year, quarter Tonkpi				-3 196•842	-7 004•647 to 610•963	0•10
	2019 Q3 Worodougou	-	-		--3 398•676	--7 844•842 to 1 047•490	0•13
	2019 Q4 1 CI = Confidence Interval. Coef.= coefficient. -648•483 -949•095 to -347•872	<0•001	-640•099	-940•512 to -339•686	<0•001
	2020 Q1		-388•826	-689•875 to -87•777	0•011		-680•290 to -78•587	0•014
	2020 Q2		-923•909	-1 224•827 to -622•991	<0•001	-914•811	-1 215•531 to -614•091	<0•001
	2020 Q3		-1 191•344	-1 496•342 to -886•346	<0•001	-1 175•526	-1 480•335 to -870•717	<0•001
	2020 Q4		-1 514•979	-1 821•074 to -1 208•883	<0•001	-1 497•785	-1 803•694 to -1 191•876	<0•001
	2021 Q1		-1 360•697	-1 666•589 to -1 054•804	<0•001	-1 343•749	-1 649•455 to -1 038•044	<0•001
	Health region
	Abidjan 1-Grands Ponts	-	-		-	-
	Abidjan 2					6 277•155	2 830•228 to 9 724•082	<0•001
	Agneby-Tiassa					-2 671•299	-6 479•104 to 1 136•505	0•17
	Bagoue					-4 839•861	-9 286•027 to -393•695	0•033
	Belier					-2 804•795	-6 612•600 to 1 003•010	0•15
	Bere					-4 984•623	-8 792•428 to -1 176•818	0•011
	Cavally					-4 840•133	-9 286•299 to -393•967	0•033
	Gbeke					-2 734•833	-5 772•984 to 303•319	0•077
	Gbokle-
	Nawa-San				1 239•698	-2 210•768 to 4 690•163	0•47
	Pedro
	Goh					-2 497•642	-6 305•447 to 1 310•163	0•19
	Gontougo					-3 941•187	-7 148•081 to -734•293	0•017
	Guemon					-3 694•680	-7 502•485 to 113•124	0•057
	Hambol					-3 723•804	-9 688•319 to 2 240•711	0•22
	Haut-Sassandra					-1 280•947	-4 725•489 to 2 163•595	0•46
	Iffou					-3 694•718	-9 659•233 to 2 269•796	0•22
	Indenie-Djuablin					-2 107•190	-6 553•356 to 2 338•976	0•35
	Loh-Djiboua				317•224	-5 647•290 to 6 281•739	0•92
	Marahoue				-1 896•518	-5 704•323 to 1 911•286	0•32
	Me					-3 430•036	-6 873•947 to 13•875	0•051

1

.

Table A5 . Linear effect of the number of HIVST kits distributed through ATLAS on access to HIV testing (HIVST UR: 60%) in the 78 health districts monitored by PEPFAR in Côte d'Ivoire (Q3 2019 to Q1 2021) Adjusted for time Adjusted for time and region

 A5

				. Adjusted for time Adjusted for time and region
	Outcome	Coef.	95% CI 1	p value	Coef.	95% CI 1	p value
	Gontougo					-3 921•359	-7 115•518 to -727•199	0•017
	Guemon					-3 682•555	-7 475•236 to 110•126	0•057
	Hambol					-3 704•422	-9 645•239 to 2 236•396	0•22
	Haut-Sassandra					-1 270•208	-4 701•070 to 2 160•655	0•46
	Iffou					-3 673•822	-9 614•639 to 2 266•996	0•22
	Indenie-Djuablin					-2 092•336	-6 520•840 to 2 336•168	0•35
	Loh-Djiboua				327•207	-5 613•611 to 6 268•024	0•91
	Marahoue				-1 892•708	-5 685•389 to 1 899•974	0•32
	Me					-3 419•005	-6 849•235 to 11•226	0•051
	Outcome Moronou	Coef.	95% CI 1	p value	Coef. -4 394•060	95% CI 1 -8 186•741 to -601•379	p value 0•024
	Number	of
	HIVST distributed N'zi	kits	0•453	0•221 to 0•686	<0•001	0•393 -5 134•441	0•160 to 0•625 -8 927•122 to -1 341•760	<0•001 0•009
	through ATLAS Poro				-3 382•650	-7 175•332 to 410•031	0•079
	Year, quarter Tchologo				-5 126•408	-9 554•912 to -697•903	0•024
	2019 Q3 Tonkpi		-	-		--3 186•260	--6 978•941 to 606•421	0•10
	2019 Q4 Worodougou	-642•300	-942•751 to -341•850	<0•001	-633•892 -3 376•808	-934•143 to -333•641 -7 805•312 to 1 051•697	<0•001 0•13
	2020 Q1		-385•996	-686•884 to -85•109	0•012	-376•582	-677•271 to -75•893	0•014
	2020 Q2		-938•792	-1 239•549 to -638•036	<0•001	-929•668	-1 230•226 to -629•110	<0•001
	2020 Q3		-1 196•979	-1 501•813 to -892•146	<0•001	-1 181•116	-1 485•760 to -876•472	<0•001
	2020 Q4		-1 515•986	-1 821•916 to -1 210•057	<0•001	-1 498•744	-1 804•486 to -1 193•001	<0•001
	2021 Q1		-1 366•110	-1 671•837 to -1 060•383	<0•001	-1 349•114	-1 654•654 to -1 043•575	<0•001
	Health region
	Abidjan 1-Grands Ponts	-	-		-	-
	Abidjan 2					6 251•295	2 818•041 to 9 684•549	<0•001
	Agneby-Tiassa					-2 655•936	-6 448•617 to 1 136•745	0•17
	Bagoue					-4 818•322	-9 246•826 to -389•817	0•034
	Belier					-2 790•117	-6 582•798 to 1 002•564	0•15
	Bere					-4 963•298	-8 755•979 to -1 170•617	0•011
	Cavally					-4 823•365	-9 251•869 to -394•860	0•033
	Gbeke					-2 722•646	-5 748•734 to 303•443	0•077
	Gbokle-
	Nawa-San				1 222•206	-2 214•597 to 4 659•008	0•48
	Pedro
	Goh					-2 486•384	-6 279•065 to 1 306•297	0•19

1 CI = Confidence Interval. Coef.= coefficient.

Table A6 . Linear effect of the number of HIVST kits distributed through ATLAS on HIV conventional testing in the 78 health districts monitored by PEPFAR in Côte d'Ivoire (Q3 2019 to Q1 2021) Adjusted for time Adjusted for time and region Outcome Coef. 95% CI 1 p value Coef. 95% CI 1 p value

 A6

			. Adjusted for time Adjusted for time and region
	Outcome	Coef.	95% CI 1	p value	Coef.	95% CI 1	p value
	Moronou			-162•228	-282•552 to -41•904	0•009
	N'zi				-180•895	-301•219 to -60•570	0•004
	Poro				-116•799	-237•124 to 3•525	0•057
	Tchologo			-169•276	-309•771 to -28•780	0•019
	Tonkpi					-81•466	-201•790 to 38•858	0•18
	Worodougou			-149•776	-290•271 to -9•280	0•037
			1 CI = Confidence Interval. Coef.= coefficient.
	Number	of
	HIVST kits
	distributed	-0•133	-0•365 to 0•099		0•26	-0•195	-0•427 to 0•038	0•10
	through
	ATLAS
	Year, quarter
	2019 Q3	-	-			-	-
	2019 Q4	-623•816	-924•473 to -323•159		<0•001	-615•297	-915•751 to -314•843	<0•001
	2020 Q1	-377•580	-678•674 to -76•486		0•014	-368•042	-668•934 to -67•150	0•017
	2020 Q2	-983•512	-1 284•475 to -682•549	<0•001	-974•267	-1 275•028 to -673•507	<0•001
	2020 Q3	-1 214•009	-1 519•048 to -908•970	<0•001	-1 197•936	-1 502•782 to -893•090	<0•001
	2020 Q4	-1 519•143	-1 825•278 to -1 213•008	<0•001	-1 501•672	-1 807•617 to -1 195•727	<0•001
	2021 Q1	-1 382•481	-1 688•414 to -1 076•549	<0•001	-1 365•261	-1 671•003 to -1 059•519	<0•001
	Health region

Table A8 . Linear effect of the number of HIVST kits distributed through ATLAS on ART initiations in the 78 health districts monitored by PEPFAR in Côte d'Ivoire (Q3 2019 to Q1 2021) Adjusted for time Adjusted for time and region

 A8

	. Adjusted for time Adjusted for time and region 95% CI 1 p value Coef. 95% CI 1 . Kouame Blaise Outcome Coef. Service Dépistage, PNLS Arcad-Sida, Mali . Yattassaye Camara Adam .	p value
	Goh Kouakou Venance Implementation in Senegal		-83•170 Heartland Alliance, Côte d'Ivoire	-191•166 to 24•825	0•13
	Gontougo					-109•970	-200•924 to -19•017	0•019
	Koffi Odette Bâ Idrissa			Aprosam, Côte d'Ivoire CEPIAD, Sénégal
	Guemon					-131•361	-239•357 to -23•365	0•018
	Hambol Kpolo Alain-Michel Diallo Papa Amadou Niang		-120•885 Ruban Rouge, Côte d'Ivoire CNLS, Sénégal	-290•047 to 48•278	0•16
	Haut-Sassandra Tety Josiane Fall Fatou			-64•028 DLSI, Ministère de la Santé et de l'action sociale, Sénégal -161•721 to 33•666 Blety, Côte d'Ivoire	0•19
	Iffou					-129•885	-299•047 to 39•278	0•13
	Traore Yacouba Guèye NDèye Fatou NGom		ORASUR, Côte d'Ivoire CTA, Sénégal
	Indenie-Djuablin Implementation in Mali Ndiaye Sidy Mokhtar			Enda Santé, Sénégal	-40•028	-166•128 to 86•073	0•53
	Loh-Djiboua					-38•170	-207•333 to 130•992	0•65
	Marahoue Bagendabanga Jules Niang Alassane Moussa		-86•647 DLSI, Ministère de la Santé et de l'action sociale, Sénégal -194•642 to 21•349 FHI 360, Mali	0•11
	Me Berthé Djelika Samba Oumar			PSI, Mali CEPIAD, Sénégal	-142•715	-240•389 to -45•040	0•005
	Outcome Moronou	Coef.	95% CI 1		p value	Coef. -144•789	95% CI 1 -252•785 to -36•794	p value 0•010
	Number HIVST N'zi Diakite Daouda Thiam Safiatou distributed through ATLAS of kits Poro Diakité Mahamadou Turpin Nguissali M.E.	0•000	-163•361 Secrétariat Exécutif du Haut Conseil National de Lutte contre le Sida, Mali -271•357 to -55•365 CNLS, Sénégal 0•004 -0•007 to 0•006 0•90 -0•002 -0•008 to 0•005 0•66 -105•789 -213•785 to 2•206 0•055 Danayaso, Mali Enda Santé, Sénégal
	Tchologo Year, quarter Diallo Youssouf Partners			CSLS/MSHP	-149•742	-275•842 to -23•642	0•021
	2019 Q3 Tonkpi	-	-			--83•123	--191•118 to 24•873	0•13
	2019 Q4 Worodougou Daouda Minta Bouaré Seydou	-5•220	-13•918 to 3•477 Comité scientifique VIH 0•24 -5•073 -127•242 Assistant de recherche, Mali	-13•766 to 3•620 -253•342 to -1•142	0•25 0•048
	2020 Q1 Hessou Septime Camara Cheick Sidi	6•031	-2•679 to 14•741 Plan Mali Assistant de recherche, Mali 0•17 6•196	-2•510 to 14•902	0•16
	2020 Q2	-17•946	-26•652 to -9•240	<0•001	-17•786	-26•488 to -9•084	<0•001
	Kanambaye Saidou Eponon Ehua Agnes			PSI, Mali Assistante de recherche, Sénégal
	2020 Q3	-12•307	-21•131 to -3•482	0•006	-12•028	-20•849 to -3•208	0•008
	2020 Q4 Kanoute Abdul Karim Kouvahe Amélé	-6•181	-15•037 to 2•675 Plan Mali Stagiaire IRD 0•17	-5•879	-14•731 to 2•973	0•19
	2021 Q1	-6•632	-15•482 to 2•219	0•14	-6•334	-15•180 to 2•513	0•16
	Keita Dembele Bintou Montaufray Marie-Anne		Arcad-Sida, Mali Stagiaire IRD
	Health region
	Abidjan Koné Dramane Mosso Rosine Grands Ponts 1-	-	-	Secrétariat Exécutif du Haut Conseil National de Lutte contre le Sida, Mali ENSEA Ecole Nationale de Statistiques et d'Economie Appliquée, Abidjan, Côte --d'Ivoire
	Abidjan 2 Koné Mariam Ndeye Pauline Dama			179•593 Chargée de l'enquête coupons, Sénégal 81•829 to 277•356 AKS, Mali	<0•001
	Agneby-Maiga Almoustapha Tiassa Sarrassat Sophie			-111•742 Comité scientifique VIH Centre for Maternal, Adolescent, Reproductive and Child Health, London School of -219•738 to -3•746 0•043
	Bagoue Nouhoum Telly			-143•313 Hygiene and Tropical Medicine, London, UK -269•414 to -17•213 CSLS/MSHP	0•027
	Belier Sow Souleymane			-105•599 Assistant de recherche, Sénégal	-213•595 to 2•397	0•055
	Sanogo Abdoulaye			Amprode Sahel, Mali
	Bere					-151•789	-259•785 to -43•794	0•007
	Cavally Saran Keita Aminata			Soutoura, Mali	-147•956	-274•056 to -21•856	0•022
	Gbeke					-99•242	-185•410 to -13•074	0•025
	Sidibé Fadiala			Soutoura, Mali
	Gbokle-
	Nawa-San					-71•021	-168•889 to 26•846	0•15
	Pedro Tall Madani			FHI 360, Mali

1 CI = Confidence Interval. Coef.= coefficient.

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Composition of the ATLAS Team

Acknowledgments

The ATLAS Project was funded by Unitaid, Grant number 2018-23-ATLAS.

Data sharing statements

Upon request to the first or last author

Ethics statement

This study does not raise any ethical concern, as the data used are aggregated and thus completely anonymized.

A secondary analysis of the ATLAS programmatic data is included in the associated research protocol available at https://atlas.solthis.org/en/research/. This protocol (version 2.

Authors' contribution

ASF and JL conceptualized the paper. ASF and PMD curated the data. ASF performed the formal analysis, wrote the initial computer programs and wrote the first draft of the paper, while JL supervised, validated and ensured the reproducibility of the results and was in charge of the project administration. ASF and JL defined the methodology and visualization adopted for the paper. ASF, PMD and AV provided the resources used for the research. JL, AV and CD secured funding for the project. ASF, KBK, EE, AV and PMD were involved in the investigation. All authors wrote, reviewed and edited the paper.

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Supplementary Material

Table of contents