| Literature DB >> 29171178 |
Sheree R Schwartz1, Matthew M Kavanagh2,3, Jeremy Sugarman4, Sunil S Solomon5, Illiassou M Njindam1, Kevin Rebe6, Thomas C Quinn5,7, Coumba Toure-Kane8, Chris Beyrer1, Stefan Baral1.
Abstract
INTRODUCTION: Key populations bear a disproportionate HIV burden and have substantial unmet treatment needs. Routine viral load monitoring represents the gold standard for assessing treatment response at the individual and programme levels; at the population-level, community viral load is a metric of HIV programme effectiveness and can identify "hotspots" of HIV transmission. Nevertheless, there are specific implementation and ethical challenges to effectively operationalize and meaningfully interpret viral load data at the community level among these often marginalized populations. DISCUSSION: Viral load monitoring enhances HIV treatment, and programme evaluation, and offers a better understanding of HIV surveillance and epidemic trends. Programmatically, viral load monitoring can provide data related to HIV service delivery coverage and quality, as well as inequities in treatment access and uptake. From a population perspective, community viral load data provides information on HIV transmission risk. Furthermore, viral load data can be used as an advocacy tool to demonstrate differences in service delivery and to promote allocation of resources to disproportionately affected key populations and communities with suboptimal health outcomes. However, in order to perform viral load monitoring for individual and programme benefit, health surveillance and advocacy purposes, careful consideration must be given to how such key population programmes are designed and implemented. For example, HIV risk factors, such as particular sex practices, sex work and drug use, are stigmatized or even criminalized in many contexts. Consequently, efforts must be taken so that routine viral load monitoring among marginalized populations does not cause inadvertent harm. Furthermore, given the challenges of reaching representative samples of key populations, significant attention to meaningful recruitment, decentralization of care and interpretation of results is needed. Finally, improving the interoperability of health systems through judicious use of biometrics or identifiers when confidentiality can be maintained is important to generate more valuable data to inform monitoring programmes.Entities:
Keywords: zzm321990HIVzzm321990; Asia; epidemiology; implementation; key populations; sub-Saharan Africa; surveillance; viral load
Mesh:
Year: 2017 PMID: 29171178 PMCID: PMC5978693 DOI: 10.1002/jia2.25003
Source DB: PubMed Journal: J Int AIDS Soc ISSN: 1758-2652 Impact factor: 5.396
Case studies of key populations viral load monitoring opportunities and challenges
| Population | Country | Methods & illustration of viral load utility | Advancements | Challenges | Source |
|---|---|---|---|---|---|
| PWID, MSM | India |
Serial cross‐sectional respondent driven sampling Population‐level surveillance |
Prevalence of viraemia is the closest correlate of HIV incidence in the community Community viral load as a marker of epidemic trends |
Viral suppression data is from research studies, which suggest that treatment and viral load monitoring must be provided alongside other CBO services due to gaps in linkages to referral centres |
Solomon Mehta McFall |
| FSW | South Africa |
Programmatic data and cross‐sectional respondent driven sampling Demonstration of programme effectiveness Indication of selection biases from use of programme data |
Programmatic data from the urban centre of Hillbrow demonstrate higher rates of viral suppression among FSW participating in the programme than corresponding clinic data from the broader population |
Programme data may mask population‐level disparities in treatment initiation and viral suppression among FSW not engaged in care Data collected through respondent driven sampling in Johannesburg suggested much lower viral suppression; 81% of FSW were not on ART and uncontrolled viral load would thus be even higher |
Program data Wits Reproductive Health Institute University of California in San Francisco, Anova Health Institute, and WRHI |
| MSM, FSW | Cameroon |
Implementation science and programmatic data Community‐based specimen collection |
Viral load monitoring can be performed through integrated, community‐based programmes which collect specimens within the community |
Lack of point‐of‐care diagnostics are a challenge; blood work for viral load monitoring is sent to reference laboratory, where results often take 45–60 days to be returned Results are directly communicated with patients for confidentiality purposes; however, this makes tailored counselling by case managers and peer educators difficult as they do not receive the results directly |
CHAMP program data |
| Transgender FSW | South Africa |
Programmatic data Impact of community‐based programmes on viral load |
Clinician has taken HIV treatment and viral load monitoring services to a local NGO space in Cape Town Laboratory results are provided individually before support meetings No patients were previously linked to HIV treatment, many now virally suppressed |
Absence of point‐of‐care diagnostics due to small scale of services Data sent to reference laboratory which requires patient names and sex which may not match patients’ identity |
Anova Health Institute's Health4Men program data |
| MSM | Nigeria |
Cohort study Advocacy |
Viral load can be an objective marker of the impact of stigma and discriminatory policies |
Loss to follow‐up higher among men not engaged in care, potentially leading to overestimation of viral suppression |
Schwartz Chauraut |
PWID, people who inject drugs; MSM, men who have sex with men; CBO, community‐based organisation; FSW, female sex worker; ART, antiretroviral therapy; LTFU, loss to follow‐up. Case studies present work from authors or collaborators.
Methods for sampling key populations (KP) for viral load monitoring
| Sampling methods | Advantages | Disadvantages |
|---|---|---|
| Key population programme service delivery |
KP‐identifiable and viral loads returnable using programmatic resources Blood draws can be collected in the community where KP are more easily reached |
Sample includes those engaged in services and underrepresents those not engaged in care Data may include duplicates if biometrics are not utilized |
| Clinic data and national registries |
Data longitudinal, assuming individuals are retained in care |
Difficult and often impossible to identify KP through clinic data or national registries Sample includes those engaged in services and under‐represents those not engaged in care |
| Social network‐based recruiting, such as respondent driven sampling or snowball sampling |
Methods can reach those not engaged in care Results may be generalizable to underlying population of interest If serial cross‐sectional studies are conducted, can ascertain insight into changes over time in terms of KP viral suppression |
Difficult to verify that individuals truly belong to KP Need to account for recruitment methods, which may not be possible for subanalyses such as viral suppression due to breaks in chains since not all individuals enrolled will be living with HIV |
| Venue based sampling |
Efficient recruitment method Community‐based viral load monitoring may reach those not engaged in care |
May be difficult at certain venues to verify that individuals truly belong to KP Individuals who do not attend venues are not represented and may be substantively different from those that do In the absence of point‐of‐care diagnostics, returning results to individuals may be challenging Individuals may be recruited at multiple sites, potentiating duplicate enrolments if biometrics are not utilized |