9 July 2021
Over the past year, several new categories of people have been defined as we have responded to the unprecedented pandemic; the clinically extremely vulnerable, the long-hauler, the vaccine hesitant. Categories can appear to be neutral, even scientific, descriptors of emergent groupings but, once created, they have an impact on the people classified, and those people then affect the categories. Ian Hacking has described this process as looping: “sometimes, our sciences create kinds of people that in a certain sense did not exist before. I call this ‘making up people’”.(1)
People like us #longcovid. Photo from “Message in a bottle: Long COVID SOS”, a video made by members of the LongCovidSOS Group in July 2020
In our research on personalisation we have explored the fluid ways in which people are rendered ‘like’ each other through tracking and analysing data from a range of everyday activities. Previous blogs have addressed some of the ways in which categories are constructed and applied to individuals with more or less face-validity and apparent relevance.
Categories based on similarity or affinity group people into those who are alike, and their application creates the corollary of people who are different. We use the phrase ‘People like you’ in our project title in reference to the well-known address of targeted, personalised marketing: ‘people like you like/buy things like this’. The phrasing can be more or less inclusive: a personal address to ‘people like you’ with similar preferences; a call for identification with ‘people like me’ to establish solidarity around a shared experience; a way of excluding ‘people like them’ who are not you or me.
These forms of address resonate with my experiences working as an epidemiologist on the COVID-19 pandemic, in which we attempt to understand its unequal impact. Defining and analysing categories is the bread and butter of epidemiology, often with little attention to their context and impact. I consider this issue here.
My first example, described in an earlier blog, is the category of the ‘clinically extremely vulnerable’. The process of creating and then labelling this group started with experts agreeing what kinds of people were most likely to have severe COVID-19, followed by the development of an algorithm which was applied to routine health data to generate a list. Once labelled, people received recommendations to shield, because ‘people like you’ are clinically extremely vulnerable. The algorithmic process of segregation has been changing and also contested, but the social impact of the categorisation and its boundaries is profound and ableist. Some people are locked into a vulnerable-shielder dyad which was rationalised as a way of allowing greater freedoms for everyone else, (2). Shielding advice has also been framed as solidarity and protection in which the vulnerable are protected through the altruistic actions of others, “‘I exist because of we’: shielding as a communal ethic of maintaining social bonds during the COVID-19 response in Ethiopia”. (3)
In contrast to the application of this category of shielding, people with Long Covid form a group that claims its own existence. Callard and Perego argue, “Long Covid has a strong claim to be considered the first illness to be collectively made by patients finding one another through Twitter and other social media.” (4) They report how patient voices consolidated around the hashtag #longcovid after experiencing and reporting unexpected ongoing and relapsing symptoms, including with initially mild disease. The hashtag was first used in May 2020 (5) and has been a powerful tool. People affected were frustrated by lack of recognition in the medical press and from individual clinicians. The category of #longcovid was not generated from routine health data, and people associated with #long covid claim that it remains almost entirely invisible in such platforms,(6). To the contrary, the category was a product of linking through social media. The sharing of experiences enabled the identification of ‘people like me’ who collectively defined and refined this category. Once people started using the term #longcovid, it developed a momentum as a patient movement which advocates in favour of resources, research, and recognition
In medical research, including a project of mine, we are trying to understand long covid better through large scale surveys, detailed phenotyping and genotyping, and data linkage, working with patients to help define outcomes and understand their experiences. I have already felt a tension between the tendency in biological sciences to stratify and subdivide conditions into every more precise categories, (7,8) and the desire of those identifying with #long covid to retain this general, overall term rather than be redistributed into finer grained sub-categories. (5) From the perspective of personalised medicine, precise strata and deep understanding of biological mechanisms is a goal through which more appropriate treatments can be designed; from the perspective of the people living with long covid, shared challenges, including destructive stigma, can be addressed more effectively as a unified group. (9)
The final emergent category I want to mention is the so-called “vaccine hesitant”. People who do not automatically respond with enthusiasm to the offer of a COVID vaccine appear to be spoiling the future for everyone. Earlier this year, a press release from another group in my own department carried the headline, “COVID-19 vaccine hesitancy could lead to thousands of extra deaths”. Our own research shows that people who are unsure about whether to be vaccinated have concerns about safety and evidence, whether they need it (if they have had prior infection for example), or general mistrust of a system.(10) Conversations with local members of the public and community organisations indicate that people are “hesitant” when they are not heard, and that individual discussions, as well as acknowledging their concerns, may allow them to make informed choices. Labelling people ‘deviant’ or ‘normal’ shifts blame to the former category and further marginalises them. This category of vaccine-hesitant thus further excludes and stigmatises by making up ‘people like them’ who are different.
- Hacking I. Making Up People. London Review of Books [Internet]. 2006 Aug 17 [cited 2021 Jul 7];28(16). Available from: https://www.lrb.co.uk/the-paper/v28/n16/ian-hacking/making-up-people
- Ganguli-Mitra A, Young I, Engelmann L, Harper I, McCormack D, Marsland R, et al. Segmenting communities as public health strategy: a view from the social sciences and humanities. Wellcome Open Res [Internet]. 2020 May 26 [cited 2021 Mar 28];5. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309410/
- Seifu Estifanos A, Alemu G, Negussie S, Ero D, Mengistu Y, Addissie A, et al. ‘I exist because of we’: shielding as a communal ethic of maintaining social bonds during the COVID-19 response in Ethiopia. BMJ Glob Health. 2020 Jul;5(7):e003204.
- Callard F, Perego E. How and why patients made Long Covid. Soc Sci Med. 2021 Jan 1;268:113426.
- Perego E, Callard F, Stras L, Melville-Jóhannesson B, Pope R, Alwan N. Why we need to keep using the patient made term “Long Covid” [Internet]. The BMJ. 2020 [cited 2021 Mar 29]. Available from: https://blogs.bmj.com/bmj/2020/10/01/why-we-need-to-keep-using-the-patient-made-term-long-covid/
- Wise J. Long covid: doctors call for research and surveillance to capture disease. BMJ. 2020 Sep 15;370:m3586.
- NIHR. Living with Covid19 [Internet]. NIHR Evidence. 2020 [cited 2021 Mar 29]. Available from: https://evidence.nihr.ac.uk/themedreview/living-with-covid19/
- Mahase E. Long covid could be four different syndromes, review suggests. BMJ. 2020 Oct 14;371:m3981.
- Pantelic M, Alwan N. Marija Pantelic and Nisreen Alwan: The stigma is real for people living with long covid [Internet]. The BMJ. 2021 [cited 2021 Mar 29]. Available from: https://blogs.bmj.com/bmj/2021/03/25/marija-pantelic-and-nisreen-alwan-the-stigma-is-real-for-people-living-with-long-covid/
- Ward H, Cooke G, Whitaker M, Redd R, Eales O, Brown JC, et al. REACT-2 Round 5: increasing prevalence of SARS-CoV-2 antibodies demonstrate impact of the second wave and of vaccine roll-out in England. medRxiv. 2021 Jan 1;2021.02.26.21252512.