1 Kenney M, Mamo L. Med Humanit 2019;0:1–12. doi:10.1136/medhum-2018-011597 The imaginary of precision public health Martha Kenney, 1 Laura Mamo 2 Original research To cite: Kenney M, Mamo L. Med Humanit Epub ahead of print: [please include Day Month Year]. doi:10.1136/ medhum-2018-011597 1 Women and Gender Studies, San Francisco State University, San Francisco, California, USA 2 Health Equity Institute, San Francisco State University, San Francisco, California, USA Correspondence to Dr Martha Kenney, Women and Gender Studies, San Francisco State University, San Francisco, CA 94132, USA; mkenney@sfsu.edu Accepted 12 February 2019 © Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ. ABSTRACT In recent years, precision medicine has emerged as a charismatic name for a growing movement to revolutionise biomedicine by bringing genomic knowledge and sequencing to clinical care. Increasingly, the precision revolution has also included a new paradigm called precision public health—part genomics, part informatics, part public health and part biomedicine. Advocates of precision public health, such as Sue Desmond-Hellmann, argue that adopting cutting-edge big data approaches will allow public health actors to precisely target populations who experience the highest burden of disease and mortality, creating more equitable health futures. In this article we analyse precision public health as a sociotechnical imaginary, examining how calls for precision shape which public health efforts are seen as necessary and desirable. By comparing the rhetoric of precision public health to precision warfare, we fnd that precision prescribes technical solutions to complex problems and promises data-driven futures free of uncertainty, unnecessary suffering and ineffcient use of resources. We look at how these imagined futures shape the present as they animate public health initiatives in the Global South funded by powerful philanthropic organisations, such as the Bill & Melinda Gates Foundation, as well as local efforts to address cancer disparities in San Francisco. Through our analysis of the imaginary of precision public health, we identify an emerging tension between health equity goals and precision’s technical solutions. Using large datasets to target interventions with greater precision, we argue, fails to address the upstream social determinants of health that give rise to health disparities worldwide. Therefore, we urge caution around investing in precision without a complementary commitment to addressing the social and economic conditions that are the root cause of health inequality. INTRODUCTION Since the completion of the Human Genome Project well over a decade ago, researchers in the biomedical sciences have sought to expand genomic knowledge and sequencing into clinical care. These efforts are driving what the biomedical sciences refer to as a revolution in healthcare, first framed as 'personalised medicine' and now as 'precision medicine'. Precision medicine offers a vision for how genomic and clinical data can be leveraged by doctors to tailor treatment and prevention strate- gies to a patient’s genome, environment and life- style, especially—but not only—through advances in pharmacogenomics. In recent years, calls for a precision revolution have expanded to the realm of public health, with key advocates arguing for the benefits of applying the 'big data' approaches of precision medicine to targeting public health prob- lems in populations. 1 While some public health experts argue that precision medicine constitutes a 'distraction from low cost and effective popula- tion-wide interventions and policies', 2 others advo- cate for a new paradigm of 'precision public health' (PPH). Building on existing data-driven approaches in epidemiology and population health, PPH seeks to mobilise state-of-the-art information technology and data science to assess and improve health at the population level. 3 Whereas precision medicine emphasises the use of genomic data in clinical care, PPH seeks to modernise public health surveillance by integrating multiple datasets in order to respond more efficiently to contain outbreaks, improve health and prevent disease. While epidemiological data (eg, surveillance data, registries, infectious disease rates, surveys and other data collection tools) has long been a crucial aspect of public health research and practice, PPH emphasises collecting and analysing real-time data with increased granularity and harnessing this knowledge in rapid response efforts. As Weeraman- thri and colleagues state: 4 It is the combination of data-related skills and tech- nologies (eg, in epidemiology, data linkage, informat- ics and communications) and the ability to aggregate, analyze, visualize and make available high quality data, larger or linked, in closer to real time, that is at the heart of PPH, much like epidemiology is at the heart of traditional public health. This big data approach to public health goes beyond clinical and genomic data to include social, environmental and behavioural factors that contribute to differential rates of morbidity and mortality in populations. Following recent trends in public health such as 'digital epidemiology', 5 'infodemiology' 6 and 'digital pharmacovigilance', 7 PPH seeks to utilise unconventional datasets such as internet search trends and cell phone GPS data to identify and understand public health risk. This is a far-reaching vision for what increased invest- ment in data and data infrastructure can offer to public health efforts. Kirsten Bibbins-Domingo (Vice Dean for Population Health and Health Equity at the University of California San Fran- cisco (UCSF) School of Medicine) argues that PPH, when fully realised, will 'telescope down' into the genome, microbiome and epigenetic profiles of individuals and then 'telescope back out' to look at family, community and larger social/environmental contexts. 8 For example, in the future, epigenetic data could be brought together with environmental data on air quality and epidemiological data on asthma rates to address environmental justice issues that disproportionately affect people of colour. 9