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Abstract
Objectives The effectiveness of HIV index testing (IT) in Eastern Europe has not been described. This study reports the performance of a scaled IT programme in Ukraine.
Design This observational study included clients enrolled in IT services in 2020, and used routinely collected data from programme registers and the national electronic health record system.
Setting The study covered 39 public-sector health facilities where IT services were integrated into medical visits for persons living with HIV (PLHIV) already enrolled in HIV care.
Participants Participants included PLHIV with both recent (<6 months) and previously established (≥6 months) HIV diagnoses.
Intervention Ukraine’s physician-led IT model involves a cascade of steps including voluntary informed consent, partner elicitation, selection of partner notification method and follow-up with clients to ensure partners are notified, tested for HIV and linked to HIV prevention and treatment services, as needed.
Primary and secondary outcome measures Outcomes included contact index, testing, index and HIV case-finding index disaggregated by index client (IC) subgroups, including people with current or past injection drug use (PWID) and men who have sex with men (MSM).
Results Of 14 525 ICs offered index testing, 51.9% accepted, of whom 98.3% named at least one sexual, injection or biological child partner. In total, 14.9% of ICs were PWID and 3.5% were MSM. Clients named 8448 unique partners (contact index=1.14). HIV case finding averaged 0.14 cases per client, and was highest among clients with recent HIV diagnosis (0.29) and among PWID (0.23), and lower among clients with established HIV diagnosis (0.07). More than 90% of all partners with new HIV diagnoses were linked to care.
Conclusions There was a high case-finding index among ICs with recent HIV and high linkage to care for all partners, demonstrating the effectiveness of this integrated, physician-led model implemented in 39 health facilities in Ukraine.
- public health
- HIV & AIDS
- quality in health care
- epidemiology
Data availability statement
Data are available upon reasonable request. The data that support the findings of this study are available from the Public Health Center of the Ministry of Health of Ukraine (PHC), but restrictions apply to the availability of these data, which were used under agreement with PHC for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of PHC.
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STRENGTHS AND LIMITATIONS OF THIS STUDY
The study reports on HIV testing outcomes for populations vulnerable to HIV infection, including men who have sex with men (MSM) and people with current or past injection drug use (PWID), both understudied groups in the Eastern European context.
Ukraine’s Socially Important Diseases Management Information System electronic data system enabled detailed tracking of partner testing and linkage to care outcomes for the national HIV index testing (IT) programme, making it possible to distinguish partners with prior HIV diagnosis who had already enrolled in HIV care, partners with prior HIV diagnosis who had never enrolled in HIV care and partners with new HIV diagnosis.
The study lacked client-level information on reach and acceptance of HIV IT services, as well as information about referrals to HIV pre-exposure prophylaxis for partners with new HIV-negative test results.
The study was able to disaggregate IT cascade results for PWID and MSM but was unable to report on results for commercial sex workers or other subgroups based on available data.
The study found wide variability in IT cascade results across the 39 facilities, but we lacked data on provider-level and facility-level factors to explain these differences.
Introduction
HIV index testing (IT) programmes offer contact tracing to persons living with HIV (PLHIV) in order to confidentially notify contacts of their exposure, and promote HIV testing, prevention and care.1 2 Randomised trials from sub-Saharan Africa have shown that IT increases HIV case finding3–5 and is cost-effective.6 7 With endorsement from the WHO as an effective strategy to meet the Joint United Nations Programme on HIV and AIDS target of 95% of all PLHIV knowing their HIV status by 2030, HIV IT services are now offered in more than 120 countries.8
To date, multiple studies have evaluated IT in the USA, Western Europe and sub-Saharan Africa, but few studies have done so in Eastern Europe.3 5 9–14 Ukraine has the second largest population of PLHIV, approximately 240 000 people, in Eastern Europe and Central Asia, a region leading the world in HIV epidemic growth in recent years.15–17 Among PLHIV in Ukraine, approximately 75% knew their status in 2021, lower than levels globally (85%) and in Western and Central Europe and North America (91%).17 People with current or past inject drug use (PWID), men who have sex with men (MSM) and sex workers (SW), all vulnerable groups facing social stigma, have high HIV burden and unmet needs for HIV testing in Ukraine. In 2020–2021, HIV prevalence among PWID was 20.9% and only 51% knew their status,17 while HIV prevalence among MSM was 3.9% and only 72% knew their status.17 SW had an estimated HIV prevalence of 3.1% but estimates were not available for their knowledge of status.17 Coverage of HIV antiretroviral treatment (ART) among children and adults living with HIV in Ukraine was estimated at 62% in 2021 (approximately 150 000 PLHIV), with 93.3% of those on ART having achieved viral suppression (approximately 140 000 PLHIV).17 ART coverage was estimated at 86.2% among PWID, 55.4% among MSM and 78.0% among SW.17
Ukraine’s IT programme uses a staffing model different from those employed in previously described studies and programme evaluations. In general, IT programmes in the USA, the UK, Scandinavia, sub-Saharan Africa and other regions rely heavily on trained staff including community health workers, disease intervention specialists and health advisors to interview clients, elicit names of their partners, assess for risk of intimate partner violence (IPV) or other harms with HIV disclosure, and ensure that partners test and link to medical care.3 5 9 11 13 14 18 The Ukrainian IT model integrates the programme fully into clinical care provided in public-sector outpatient HIV clinics and is primarily staffed by medical doctors and nurses, without separate, dedicated IT staff. During clinic visits, infectious disease doctors act as IT focal points, across the steps of the IT process. A module within the country’s point-of-service electronic health record, the Socially Important Diseases Medical Information System (SID MIS), reinforces the integrated IT services workflow by prompting doctors to offer IT services and capturing data on named partners. Ukraine’s programme seeks to provide IT to index clients (ICs) with both recent (those who accepted IT services within 6 months of diagnosis) and established HIV diagnosis (those who accepted IT services more than 6 months after diagnosis).
Recent observational studies of scaled IT programmes describe variable success in HIV case-finding across low-income, middle-income and high-income settings.9 10 13 14 Reported case finding indices, representing the number of newly diagnosed partners identified per participating IC, have varied from 5.4 newly diagnosed partners per hundred participating ICs (0.054) in the USA in 2019 to 14 newly diagnosed partners per hundred participating ICs (0.14) in Botswana in 2018–2020.9 14 This variability reflects differing efficiency of case finding efforts, depending on the undiagnosed fraction of PLHIV in the population and key subgroups, the model and intensity of case finding services, HIV stigma, accessibility of HIV testing services and other factors. There have been few reports on IT outcomes in Eastern Europe, and data on the success of IT among ICs with established (vs recent) HIV diagnoses is likewise limited. We evaluated the case-finding effectiveness of Ukrainian’s integrated IT model, including outcomes among key subgroups (ICs with recent vs established HIV diagnosis, PWID and MSM), as implemented in 39 health facilities in 11 regions that covered approximately 60% of all PLHIV on ART in those regions.
Materials and methods
Setting and programme overview
The International Training and Education Center for Health (I-TECH) at the University of Washington was funded by the Health Resources and Services Administration through the US President’s Emergency Plan for AIDS Relief (PEPFAR) to assist the Ukraine Ministry of Health (MOH) in IT programme implementation through the dissemination of standard operating procedures, health worker training, programme monitoring, quality improvement and evaluation. While Ukraine had a long-time legislative basis for contact tracing for sexually transmitted infections,8 HIV index testing was not emphasised until 2019, when PEPFAR funding and technical support enabled activation of this service on a routine basis. The US Centers for Disease Control and Prevention (CDC) worked with I-TECH and the MOH to establish the technical direction of Ukraine’s IT programme. I-TECH provided technical and financial support to 39 Ukrainian public health facilities to implement the IT programme. These facilities were not necessarily representative of all health facilities in the country, but they constituted the universe of facilities actively involved in Ukraine’s IT programme during the timeframe of the present study. In addition, community-based non-governmental organisations provided HIV self-testing services outside of HIV clinics, and collaborated with health facility personnel to facilitate partner testing and linkage to care.
Ukraine’s IT services were rolled out as a standard part of Ukraine’s HIV service package at the targeted governmental health facilities, carried out by existing physicians, nurses, medical psychologists and social workers. These personnel typically offered IT to ICs at the time of HIV diagnosis or during their regular HIV clinic visits. After receiving patient consent to participate, they conducted partner elicitation interviews with each IC. ICs selected among four different modes of partner notification: (1) client notification (ICs notify partners); (2) provider notification (health workers notify partners directly without disclosing IC identity); (3) joint notification (IC and health worker together notify partners); or (4) contract notification (ICs commit to notify partners within a certain timeframe and agree to provider notification after that timeframe if needed). For each named partner, health workers assessed for risk of IPV based on the history of physical, emotional, or sexual violence, or concern about IPV with disclosure of HIV status. If IPV concerns were present, health workers discussed joint or provider notification, and continued only if the safety of the IC was not at risk.
At each facility, one to two IT staff members were designated as focal persons for IT case management and follow-up. Health workers could print standard referral letters which explained that the partner may have been exposed to HIV and where and when they could access free HIV testing services. These letters could be delivered by either the IC or by a health worker, depending on the notification mode selected. When health workers carried out partner notification, they typically contacted partners by phone, although some health facilities had access to a cadre of lay health educators who made physical visits. When ICs returned for their regular clinic visits, physicians inquired about additional exposed contacts and encouraged that exposed partners complete HIV testing.
Ukraine’s HIV diagnostic protocol used HIV rapid tests for screening (based on a single test with at least 99% sensitivity) as well as for confirmatory testing (based on two tests with at least 99% specificity), allowing same-day HIV diagnosis for most clients.19 The protocol included a third rapid test for HIV case identification prior to initiation of ART, as recommended by WHO HIV testing guidelines.1
Study design and facility sample
This observational study took place in 39 health facilities located in 11 out of the 12 PEPFAR-prioritised oblasts (regions), high-burden regions where approximately 66% of PLHIV and 54% of the population of Ukraine resided. The 39 health facilities were prioritised by the PEPFAR programme based on epidemiological analysis of HIV disease burden in Ukraine, and served 49 693 HIV clients for care and treatment services within the 11 oblasts (representing 58.8% of approximately 84 497 PLHIV on ART in the 11 regions and 40.9% of approximately 121 569 PLHIV on ART in all government-controlled regions of Ukraine as of December 2020).20 The study cohort included all clients who accepted IT services and named partners during January–December 2020 in the 39 health facilities.
Data sources and methods
The study used routinely collected surveillance and programmatic data from two data sources: (1) the information system for socially significant diseases (IS SSD), an electronic health record system used by all health facilities providing HIV services; and (2) IT service programme registers. The IS SSD is a comprehensive system designed for public-sector HIV testing, care and treatment services under PEPFAR and Global Fund support. The IT service programme register is an electronic spreadsheet-based tool capturing data required for routine programme monitoring. The IT register was typically filled out by the IT focal point, either in real-time or retrospectively, using documentation from paper-based client case files. Both tools collected information on IC age and sex, partner type(s), IT partner notification mode, and partner age group, sex and HIV testing status. Data were extracted in March 2021, meaning that all partners had at least 60 days of follow-up time to observe their HIV testing and linkage to care outcomes.
Measures
Key IT cascade indicators of interest included: (1) IT acceptance (# ICs accepted/# ICs offered); (2) IT reach (# ICs accepted/# ICs eligible); (3) contact index (# partners named/# ICs accepted); (4) testing index (# partners newly tested/# ICs accepted); (5) HIV case finding index (# partners with new HIV diagnosis/# ICs accepted); (6) testing yield (# partners with new HIV diagnosis/# partners newly tested); and (7) linkage to care (# partners newly linked to HIV antiretroviral therapy (ART) services/# partners diagnosed with HIV). ICs diagnosed within 6 months of participating in IT serves were categorised as those with ‘recent diagnosis’ while ICs diagnosed more than 6 months before participating in IT services were categorised as those with ‘existing diagnosis’. Partners were categorised as either sexual partners, needle-sharing partners or biological children of mothers living with HIV, in accordance with PEPFAR Monitoring, Evaluation and Reporting guidance.21 PWID and MSM groups were characterised based on risk factors recorded at the time of HIV diagnosis, or the types of partners they listed. IT reach was estimated based on the count of active HIV patients at the 39 health facilities, and only aggregate data on IT acceptance and reach was available, not data by the IC subgroups of interest.
Data analysis
We first identified unique ICs and partners. Named partners were coded with a sequential identifier at the time of contact elicitation. After participating in HIV testing services, partners received a unique IS SSD identifier linked to their full name, sociodemographic details and a civil registration identifier. We removed duplicate records for the same partner named by different ICs using their unique IS SSD identifiers. There were 23 unique partners associated with more than one IC, and we randomly selected one IC for purposes of associating partner and IC characteristics. We used the earliest HIV positive test result or the most recent HIV negative test result as the definitive HIV status outcome for each partner.
We described IT cascade indicators overall and by IC subgroup. We used descriptive statistics to summarise characteristics of ICs and partners, assessing frequencies for categorical variables and medians and interquartile ranges (IQRs) for continuous age variables. We compared characteristics across IC subgroups, using χ2 test of equality of proportions for categorical variables and the Wilcoxon rank-sum test for age variables, and compared IT cascade indicators across IC subgroups using Student’s t-test. We performed statistical analyses using R Statistical Software22 and Stata 15.0.23
Patient and public involvement
Patients were not involved in the research process.
Results
Reach and acceptance of IT services and characteristics of ICs
At the 39 facilities, health workers offered IT services to 14 525 of the 49 693 HIV positive patients served during the time frame, and approximately half accepted (n=7533, 51.9% of those offered, for reach of 15.2%). The IQR for the acceptance rate by facility was 47%–77% (results not shown). Most named at least one partner (n=7408, 98.3% of those who accepted); only 125 ICs accepted IT services but did not name any partners.
ICs who accepted IT services were predominantly those with established HIV diagnosis (ie, those diagnosed >6 months before participating in IT services; n=5105, 67.8%), were evenly divided by sex and had a median age of 39 years (IQR: 33–45) (table 1). About 15% of ICs had current or past injection drug use (PWID, 14.9%), 3.5% of male ICs were MSM. Other HIV risk factors included being pregnant (20.9% of female ICs) or having a known HIV+ partner (12.1%) at the time of their own HIV diagnosis (table 1). Most ICs with recent HIV (63.7%) had not yet started ART at the time they accepted IT services, while the largest share of ICs with established HIV diagnosis were on ART with HIV viral load (VL) ≤1000 copies/mL (48.1%) or were on ART but with no recent VL results (39.4%) (table 1).
Characteristics of index clients (ICs) (n=7533)
Most ICs named a single partner of any type (87.5%), and 2.2% named three or more partners (table 1). Most ICs named sexual partners (n=6931, 92.0%), while 306 (4.1%) named needle sharing partners, and 433 (5.7%) named biological children. Compared with ICs with established HIV diagnosis, ICs with recent HIV were more likely to be male, to be younger, to be PWID or MSM, and less likely to list any partner with a known HIV diagnosis (table 1, all p<0.01). IPV concerns were low overall and no different among ICs with recent versus established HIV diagnosis (p=0.13). Online supplemental table 1 presents IC characteristics by their ART and viral suppression status.
Supplemental material
Contact elicitation and characteristics of named partners
ICs named 8471 contacts, of whom 8448 were unique individuals (figure 1, table 2). The contact index was 1.14, with an IQR of 1.05–1.16 across the 39 health facilities (table 3). Fifty-two per cent of contacts were male, and median partner age was 38 (IQR: 31–45) (table 2). The most common mode of notification selected by the IC was client notification (72.2%), followed by joint notification (19.0%), provider notification (7.8%) and contract notification (1.0%) (table 2). Compared with partners of ICs with establish HIV, partners of ICs with recent HIV were more likely to be female, younger, a needle-sharing partner or biological child, and were less likely to be selected for client notification (table 2, all p<0.001).
Partner and partnership characteristics, by index client (IC) subgroup (n=8448)
Comparison of key IT cascade indicators among index client (IC) subgroups
IT programme participation and results in 39 health facilities, January–December 2020. ART, antiretroviral treatment; IT, index testing; PLHIV, persons living with HIV.
Partner testing and HIV case finding
Out of the 8448 partners, 1327 (15.7%) were already known to the ICs as PLHIV who were enrolled in HIV care, and 162 (1.9%) were identified on tracing as known PLHIV who were unlinked to ART (figure 1). Of the remaining 6959 (82.4%) partners of unknown HIV status, 5021 (72.2%) completed testing within 60 days and 1938 (27.8%) did not complete testing within this time window (figure 1). We used the 60-day follow-up window because it likely reflected testing attributable to IT services; among those who ever completed testing, 93.6% did so within 60 days. The testing index was 0.72, with an IQR of 0.65–0.94 across health facilities (table 3). Completion of testing among partners with unknown HIV status was similar among partners of ICs with recent versus established HIV (71.1% vs 70.6%) (figure 2A,B).
Count of clients served along IT cascade, stratified by index clients (ICs) with recent HIV diagnosis (<6 months) (A) and established HIV diagnosis (≥6 months) (B). IT, index testing; PLHIV, persons living with HIV.
There were 976 partners with new HIV diagnoses (11.6% of all partners named), for an overall testing yield of 19.3% (table 3). Six had previously tested negative through the IT programme (results not shown). The HIV case finding index was 0.14, with an IQR of 0.08–0.20 across facilities, and the average HIV testing yield had an IQR of 11.6%–23.8% across facilities (table 3). ICs reported no cases of IPV due to IT programme participation (results not shown).
IT cascade indicators by IC subgroup
The contact index was higher among ICs with recent versus established HIV (1.23 vs 1.10, p<0.001) (table 3). The testing index was 1.2 times higher (0.82 vs 0.67, p<0.001) and the HIV case finding index was 4.1 times higher (0.29 vs 0.07, p<0.001) for ICs with recent versus established HIV. The HIV case finding index was 0.23 among PWID but only 0.12 among heterosexual non-PWID clients (p<0.001). Since PWID ICs were more likely to have recent HIV diagnosis, we compared case finding in analyses stratified by recent versus established HIV diagnosis. In both strata, the HIV case finding index was higher for PWID versus heterosexual non-PWID (0.39 vs 0.26 for ICs with recent HIV, and 0.12 vs 0.06 for ICs with established HIV diagnosis, p<0.001 in both strata). The HIV case finding index was slightly higher among MSM ICs versus heterosexual non-PWID ICs, but the difference was not significant (0.17 vs 0.12 overall, p=0.12) (results not shown).
Linkage to care among partners newly diagnosed with HIV was high across all subgroups examined, reaching above 95% for partners of ICs with recent HIV, PWID and MSM, and above 90% for partners of ICs with established diagnoses (table 3).
Discussion
Our evaluation of the IT programme as scaled in 39 health facilities in 11 PEPFAR-supported regions of Ukraine, provides evidence of the intervention’s success in HIV case finding and linkage to care in the context of a mixed HIV epidemic. The programme outcomes were particularly impressive given the country’s rolling lockdowns to prevent COVID-19 transmission starting in March 2020. The programme helped to newly diagnose HIV infection in 976 partners in 2020. Among ICs with recent HIV, the case finding index was 0.29, higher than that observed in the USA in 2019 (0.054),14 the UK in 2018 (0.066),10 Botswana in 2018–2020 (0.14)9 or Namibia in 2019–2021 (0.14).24 The Ukraine programme was also successful in linking >90% of unlinked partners to HIV care and treatment, including 147 partners with known HIV infections who were not in care. HIV case finding in Ukraine was fourfold higher among ICs with recent versus established HIV diagnosis. Still, ICs with established HIV diagnosis were responsible for nearly one-third of all new partner infections identified through IT services and the testing yield was above 10% in this group, demonstrating an important contribution to HIV case finding despite lesser relative efficiency.
The scaled IT programme in Ukraine faced a key challenge with coverage of IT services, while other programmes globally have faced challenges along subsequent steps of the IT cascade. Due to resource limitations in Ukraine, I-TECH was only able to include 1–2 providers per site in trainings and IT quality improvement forums, so providers’ motivation and skills in providing IT services were likely not uniform across all providers at the 39 sites. Time limitations may also have prevented providers from consistently offering IT services. In other countries, documented barriers to HIV case finding include challenges in training and retaining the workforce providing IT services,25 the need to engage field-based partner tracing as a time-intensive method of partner notification,14 the need to focus on subpopulations facing high access barriers,14 and weak record keeping and data systems (leading to a concentration of services on PLHIV who already knew their status, but for whom routine records were not up to date).9
With Ukraine’s integrated, physician-led IT services model, it was operationally streamlined and productive to target ICs with both recent and established HIV diagnosis, to arrive at a high number of new cases of HIV identified. In the future, if it becomes difficult to offer IT services to all PLHIV enrolled in care (because resource constraints require realigning staff time, for example), it could be prudent to target the programme toward ICs with recent HIV diagnosis, where the relative likelihood of HIV case finding among partners is the greatest, or to task shift more aspects of IT services to non-physician staff, as is done in many other countries. Further measurement of the denominator for acceptance and reach indicators and prioritisation of eligible clients, based on who most needs the intervention, is warranted.
The ‘front end’ of the IT cascade represents an area for IT service performance improvement in Ukraine. The acceptance (approximately 50%) and reach (approximately 15%) of the programme appeared to be low, though many of the unreached may have been established ICs without any recent partners of unknown HIV status, a premise we could not assess given available data.
The contact index in our study was only 1.14 overall and 1.23 among ICs with recent HIV− short of the programme’s improvement target of 1.5—although health worker training emphasised the need to consistently elicit >1 partner per IC. Contact indices in other routine IT programmes have consistently reported levels comparable to or lower than those found in Ukraine (0.68 in USA,14 0.67 in UK,10 1.37 in Mozambique26). Given that success of IT services depends on a cascade starting with robust partner elicitation, having a low contact index is one barrier to improving programme performance.
A second area for programme improvement was the low number of PWID and MSM participating in IT: only 14.9% of ICs were classified as PWID and 3.5% were classified as MSM, based on self-reported risk factors or partnership types. Prior studies have documented persistent and notable under-reporting of these risk factors in routine data systems, due to widespread social stigma.27 The 2020 Stigma Index in Ukraine estimated that 19% of MSM and 20% of PWID experienced discrimination in healthcare, including refusal of care, verbal abuse or avoidance of physical contact.28 29 Under-reporting of PWID and MSM status is estimated at up to 45% and 27%, respectively,27 30 and this provides context for the low numbers of PWID and MSM served. Whether the low numbers reflect unwillingness to disclose sensitive information during contact elicitation, preferential refusal by vulnerable groups to participate in IT, or failure of the clinics to serve these populations altogether is uncertain. However, we noted a 10-point gap in the percentage of ICs classified as PWID versus those naming any needle-sharing partners, pointing to a particular need to improve elicitation of needle-sharing partners.
Strengths and limitations
Ukraine’s IS SSD, a centralised electronic system used in all public health facilities providing HIV care since 2016, enabled detailed tracking of partner testing and linkage to care. The system made it possible to distinguish partners with prior HIV diagnosis who had already enrolled in HIV care, partners with prior HIV diagnosis who had never enrolled in HIV care, and partners with new HIV diagnosis. The data system also definitively tracked linkage to care across health facilities. It is likely that settings with weaker data systems might misclassify many partners with prior HIV diagnosis as having a new diagnosis. Ukraine’s experience shows the valuable role IT programmes can play in newly linking partners with prior HIV diagnoses, in addition to HIV case finding.
A limitation of the routine data sources used for the study was the inability to identify clients involved in sex work, due to systematic under-reporting of this risk factor (since sex work is illegal), and the possibility of misclassification of PWID and MSM risk groups due to stigma.27 The lack of client-level information on reach and acceptance was also a limitation. We also lacked information about referrals to HIV pre-exposure prophylaxis for partners with new HIV-negative test results. Our study found wide variability in IT cascade results across the 39 facilities, but we lacked data on provider-level and facility-level factors to explain these differences.
Future research
Research is needed to identify implementation strategies to optimise IT quality (eg, high acceptance of services, high contact index), efficiency (eg, cost of IT programme per new HIV case identified) and effectiveness (eg, number of new HIV cases identified and linked to care as a result of the IT programme, number of partners with negative HIV test results linked to prevention services). In Ukraine’s IT programme, clients chose provider-assisted methods of partner notification for <10% of partners. An IT programme meta-analysis found that assisted partner services resulted in a 1.5 increase in completed HIV testing over passive referral by clients.31 Finding ways to increase the uptake of assisted notification could be useful in Ukraine. A staff training intervention in Malawi’s mature IT programme improved contact elicitation 1.9-fold and partner testing 1.6-fold, and this strategy could be useful to adapt and test.32 Extending IT services to social networks for PWID and MSM might accelerate HIV case finding in these vulnerable groups, based on promising findings of a social network testing intervention for PWID in the Odesa region of Ukraine.33 Designing and testing culturally and contextually relevant strategies to integrate community-based and clinic-based IT services could be fruitful in reaching vulnerable PWID and MSM populations.34 35 Future research could also examine whether the effectiveness of IT services differs by type of provider (eg, doctor, nurse, social worker) or by characteristics of health facilities and their specific IT service delivery models.
Conclusion
Ukraine’s physician-led IT model that integrates partner elicitation and notification into routine medical visits was scalable and effective in identifying persons with undiagnosed HIV infection and linking them to treatment. The programme yielded the highest HIV case finding among ICs with recent HIV, though ICs with established HIV contributed one-third of HIV case finding. Programme strengths included a high case finding index and success in linkage to care. Areas for improvement encompass reach and acceptance of IT services, use of assisted partner notification, overall partner elicitation, and coverage and partner elicitation among PWID and MSM (who may have hesitated to disclose partners due to stigma). Further research is needed on implementation strategies which can improve IT programme effectiveness.
Data availability statement
Data are available upon reasonable request. The data that support the findings of this study are available from the Public Health Center of the Ministry of Health of Ukraine (PHC), but restrictions apply to the availability of these data, which were used under agreement with PHC for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of PHC.
Ethics statements
Patient consent for publication
Ethics approval
The University of Washington Human Subjects Division (#STUDY00013565) and the US Centers for Disease Control and Prevention (CDC) Science Integrity Branch (#CGH-HIVPKP-4/14/21-f6e6a) reviewed and approved the study protocol as a program evaluation with minimal risk to human subjects. The Institutional Review Board of the Public Health Center of the Ukraine Ministry of Health waived off the need to provide a formal review of the study protocol, based upon it being a program evaluation with minimal risk to human subjects. Both the University of Washington Human Subjects Division and the US Centers for Disease Control and Prevention (CDC) Science Integrity Branch waived off the need for informed consent from study participants, based on the secondary use of routinely collected, deidentified client data. There were no experiments performed as part of the study, and all study procedures were performed in accordance with the Declaration of Helsinki and other relevant guidelines and regulations.
Acknowledgments
The authors would like to acknowledge Jaclyn Perlman, MPH, International Public Health Advisor and Salem Gugsa, PhD, Deputy Director of the Office of Global Health, US Health Resources and Services Administration for their review and comments on the manuscript. On behalf of I-TECH Ukraine team, the authors would like to thank the whole team of US Centers for Disease Control and Prevention (CDC) in Ukraine for long-lasting strategic partnership in country and guidance on this manuscript. In particular, we would like to acknowledge Dr Ezra Barzilay, MD, CPH, Ukraine Country Director, Natalya Podolchak, MD, Deputy Director for Programmes and Roksolana Kulchynska, MSE, MPH, Strategic Information Advisor for the review and input into both—the protocol for this project as well as the manuscript itself.
Supplementary materials
Supplementary Data
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Footnotes
Contributors All authors listed in this paper meet the four criteria for authorship as identified by the International Committee of Medical Journal Editors (ICMJE); all authors have contributed to the conception and design of the study, drafted or have been involved in revising this manuscript, reviewed the final version of this manuscript before submission and agreed to be accountable for all aspects of the work. The specific contributions of each author are as follows: API led the planning, conceptualisation, methodology, data acquisition, investigation and analysis, writing, review and editing. AYS supervised planning and data acquisition, provided project administration, and provided review and editing of the manuscript. APK supported data preparation and analysis, and provided review and editing of the manuscript. IVK and SVR facilitated data acquisition, and reviewed and edited the manuscript. SS and MRM provided project administration, and provided review and editing of the manuscript. MRG supported study planning, methodology and analysis, and provided review and editing of the manuscript. NHP supported study planning and methodology, led validation of analysis, led preparation of figures and tables, and supported writing and editing of the manuscript. API acted as guarantor of the study, having full responsibility for the work and/or the conduct of the study, having full access to the data, and controlling the decision to publish.
Funding This publication was made possible by a grant to the International Training and Education Center for Health (number U91HA06801) from the US Department of Health and Human Services, Health Resources and Services Administration (HRSA), Office of Global Health. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the government.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.