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New Series on the Social Dynamics of Biomedical Prevention on Transcriptions

This article is part of the following series:

In the context of a growing emphasis on biomedical approaches to HIV prevention, we are seeking contributions to a new series that aims to examine the increasing biomedicalisation of HIV prevention. We are particularly interested to include contributions on the role of social research in relation to the impacts and effectiveness of implementation of biomedical technologies. As Treatment as Prevention (TasP) and other biomedical prevention approaches (most notably, pre-exposure prophylaxis or PrEP) are proposed for communities identified as at risk of increasing HIV infections, important questions are brought to the fore. Neither TasP nor any other single biomedical approach will function as a magic bullet or ‘biological fix,’ as if unaffected by the conditions of social life. Because these interventions are likely to affect and be affected by the long-standing inequalities and vulnerabilities that have shaped the course of the epidemic, it will be necessary to build interdisciplinary collaborations between social scientists and HIV affected communities, public health researchers, clinicians, activists, and other stakeholders. The need for interdisciplinary collaborations is now, as ever, critically important and we are keen to support a new conversation on biomedical prevention that is cognisant of the ways in which biological, social, and technological processes are deeply intertwined and locally contingent.

To encourage this dialogue and open up a space for critical conversation, we are seeking contributions to what we hope will become a lively online conversation about the social dynamics of biomedical prevention of HIV and the role of social research.

Questions to be addressed include the following:

  • At which point is evidence (specifically for TasP and/or PrEP) considered sufficient to roll out? What is the status of such evidence when considering translation into safe and effective prevention?  What are the ethical implications of this question?
  • Is it reasonable to consider that the use of ART could reduce incidence of HIV to zero, and hence end the epidemic? In what ways do mathematical models estimating of the effectiveness of TasP engage with complex social phenomena? Can we rely on their predictive value? Do models differ and, if so, what might be the implications of such in shaping the future of the epidemic?
  • What factors are driving the push for biomedical prevention? How do we trace the shift to biomedical prevention over time? What are the particular histories of rollout of HIV treatment programs and possibly other sorts of treatment and prevention programs that we might learn from?  Are there lessons from other treatment and prevention programs that might inform the design of biomedical prevention randomised controlled trials and implementation studies (including demonstration studies)?
  • How should we think about treatment as prevention in the context of other biomedical prevention approaches?
  • How should we understand the relations and distinctions between prevention and treatment in the context of biomedical prevention? What role can social research take in responding to to the clinical and prevention implications of treatment gaps?
  • For whom is ‘treatment as prevention’ relevant? Can it be implemented in ways that reduce transmission at a population level while also addressing individuals’ HIV-related risk practices? What happens to discussions of sexual and drug using practice in the context of biomedical prevention?
  • What sort of subjects of HIV prevention does biomedical prevention presume and enact?  How do biomedical prevention programs engage, or seek to engage affected communities? What are the implications for HIV-positive individuals?
  • How do we think of behavior change in the context of biomedical prevention? What are the key behavioral and social dynamics underlying the potential success of treatment as prevention and other forms of biomedical prevention?
  • How will these models be implemented in divergent settings, and what considerations need to be taken into account in resource-poor settings? What will be the health systems-wide effects?


Submission deadline: August 15

Word count limit: 2000 words


For more information, or to submit a contribution, please contact us at


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