In the United States, clinical HIV data reported to surveillance systems operated by jurisdictional departments of public health are re-used for epidemiology and prevention. In 2018, all jurisdictions began using HIV genetic sequence data from clinical drug resistance tests to identify people living with HIV in "clusters" of others with genetically similar strains. This is called "molecular HIV surveillance" (MHS). In 2019, "cluster detection and response" (CDR) programs that re-use MHS data became the "fourth pillar" of the national HIV strategy. Public health re-uses of HIV data are done without consent and are a source of concern among stakeholders. This article presents three cases that illuminate bioethical challenges associated with re-uses of clinical HIV data for public health. We focus on evidence-base, risk-benefit ratio, determining directionality of HIV transmission, consent, and ethical re-use. The conclusion offers strategies for "HIV data justice." The essay contributes to a "bioethics of the oppressed."

Reassessing the Ethics of Molecular HIV Surveillance in the Era of Cluster Detection and Response: Toward HIV Data Justice

The effects of the coronavirus disease 2019 (COVID-19) pandemic globally are striking as it impacts greatly the social, political, economic, and healthcare aspects of many countries. The toll of this pandemic quantified with human lives and suffering (1), the psychosocial impact (2), and the economic slowdown (3) constitute strong reasons to translate experiences into actionable lessons, not simply to prevent similar future crises, but rather to improve the whole spectrum of population health and healthcare delivery. This is the third coronavirus (CoV) outbreak of international concern in 20 years, after the severe acute respiratory syndrome (SARS-CoV) and the Middle-East respiratory syndrome (MERS-CoV), in addition to other viral outbreaks such as Zika virus and Ebola virus over the last decade. It becomes clear that infectious diseases should be considered among the most important health hazards that we will need to continue facing in the foreseeable future (4). Thus, the transformation of various aspects at the individual as well as the societal and governmental levels seems inevitable. The COVID-19 pandemic has become a reality check for many aspects of healthcare systems, especially regarding their overall readiness. Public health surveillance programs and available infrastructures were shown as not consistently optimal (5–7). Additionally, healthcare systems appeared unable to absorb and manage sudden and persistent pressures on their workload especially in the settings of acute care. Even though contingency plans were often in place, healthcare systems seemed unable to cope with the sudden, intense surge in demand (8, 9). From a policy perspective, potential delay(s) in committing tomajor decisions, such as lockdownmeasures, in an “epidemiologically timely fashion” could significantly impact downstream healthcare outcomes (10, 11). The latter is of particular importance, as healthcare challenges in one country should be considered both an internal and a potentially global challenge, at least for infectious diseases (12, 13). Finally, the speed at which a global public health issue translated into a financial downturn, affecting many different industries, was underestimated (3, 14). The COVID-19 pandemic acts as a transformation catalyst, accelerating the implementation and adoption of changes in public health interventions. Thus, a new model of healthcare delivery emerges with more emphasis on preventive measures, remote care, and substantial technological dependence. However, these are juxtaposed against ongoing technical challenges to meet the surge capacity in laboratory testing, the fast-tracked implementation of new technologies, the mental health concerns, the ethical concerns on the potential rationing of insufficient resources, and the protection of privacy and personal data during times of crises. Taking the former into account, the following aspects seem likely to emerge as most affected in the post-COVID-19 era.

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Healthcare Transformation in the Post-Coronavirus Pandemic Era

Viral genetic sequencing can be used to monitor the spread of HIV drug resistance, identify appropriate antiretroviral regimes, and characterize transmission dynamics. Despite decreasing costs, next-generation sequencing (NGS) is still prohibitively costly for routine use in generalized HIV epidemics in low- and middle-income countries. Here, we present veSEQ-HIV, a high-throughput, cost-effective NGS sequencing method and computational pipeline tailored specifically to HIV, which can be performed using leftover blood drawn for routine CD4 cell count testing. This method overcomes several major technical challenges that have prevented HIV sequencing from being used routinely in public health efforts; it is fast, robust, and cost-efficient, and generates full genomic sequences of diverse strains of HIV without bias. The complete veSEQ-HIV pipeline provides viral load estimates and quantitative summaries of drug resistance mutations; it also exploits information on within-host viral diversity to construct directed transmission networks. We evaluated the method's performance using 1,620 plasma samples collected from individuals attending 10 large urban clinics in Zambia as part of the HPTN 071-2 study (PopART Phylogenetics). Whole HIV genomes were recovered from 91% of samples with a viral load of >1,000 copies/ml. The cost of the assay (30 GBP per sample) compares favorably with existing VL and HIV genotyping tests, proving an affordable option for combining HIV clinical monitoring with molecular epidemiology and drug resistance surveillance in low-income settings.

A comprehensive genomics solution for HIV surveillance and clinical monitoring in low income settings.

Purpose of review
The HIV epidemic in sub-Saharan Africa is far from being under control and the ambitious UNAIDS targets are unlikely to be met by 2020 as declines in per-capita incidence being largely offset by demographic trends. There is an increasing number of proven and specific HIV prevention tools, but little consensus on how best to deploy them.
Recent findings
Traditionally, phylogenetics has been used in HIV research to reconstruct the history of the epidemic and date zoonotic infections, whereas more recent publications focus on HIV diversity and drug resistance. However, it is also the most powerful method of source attribution available for the study of HIV transmission. The PANGEA (Phylogenetics And Networks for Generalized Epidemics in Africa) consortium has generated over 18 000 NGS HIV sequences from five countries in sub-Saharan Africa. Using phylogenetic methods, we will identify characteristics of individuals or groups, which are most likely to be at risk of infection or at risk of infecting others.
Summary
Combining phylogenetics, phylodynamics and epidemiology will allow PANGEA to highlight where prevention efforts should be focussed to reduce the HIV epidemic most effectively. To maximise the public health benefit of the data, PANGEA offers accreditation to external researchers, allowing them to access the data and join the consortium. We also welcome submissions of other HIV sequences from sub-Saharan Africa to the database.

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Cordelia C. Coltart

Papers

Ethical considerations in global HIV phylogenetic research.