For millions of migrant workers left jobless after the suddenly declared lockdown in India – who largely worked in big cities with no job security or labor laws – returning to their “home villages” was the only way to stave off death and starvation. As the government turned a blind eye to these stranded workers and their families, a few NGOs, activist organizations and civil society initiatives stepped in to mitigate this humanitarian-political crisis by supplying food, access to transportation and tickets. Some even moved the courts to effect some change at the state/policy level. Vipin Kaushik gathered his globally dispersed family on zoom to jumpstart lockdownmovement.in. Everyone chipped in to set up software, collect data, promote, design or lay out content. lockdownmovement.in became a digital repository where migrants could update their current conditions, their intended place and route of travel, and accompanying family members. For others chronicling lives on the internet, databases like lockdownmovement.in became ways to document the lives and existences of migrant workers who had fallen off the state’s radar. Perhaps, in lockdown grammar, one could say this was not contact tracing, but tracing the contacts of those without means of communication, travel and food, without smartphones and apps, without paper and document. It became a mode of documenting the undocumented, even if as the Kaushik family admits, the actual migration back to villages remained an unsurmountable task given the absolute apathy of the ruling political class.

Aloha Trace

AlohaTrace is a contact tracing initiative developed for the state of Hawai’i through a collaborative effort by the University of Hawai’i, the National Disaster Preparedness Training Center, the Pacific Urban Resilience Lab, and private funding. The project represents nongovernmental entities attempting to provide public health services which the government has failed to fill; particularly AlohaTrace attempts to compensate for inadequate testing across the state. On the website-based platform, users are asked to answer an anonymous, six question survey on their health and movements. Ideally, users are encouraged to enter data every day. The habitual reporting allows the platform to aggregate a large body of data which, in case of infection, can be used to reverse engineer the path of transmissions and alert those who may have been exposed. AlohaTrace presents a different model of contact tracing from the mobile applications upon which many other solutions are reliant. Rather than gathering location data, whether passively or journalistically, AlohaTrace and its web-based capability is fully reliant on user reporting. Thus, the information collected is fully user-generated. While the AlohaTrace approach attempts to provide more individual control over user data, the data map provides the potential shortcomings of this contact tracing infrastructure. The map only shows five data points, all of which are near metropolitan areas within the state. This could be the result of several factors: unreliable internet or computer access, lack of daily compliance in user reporting, and/or lack of knowledge about AlohaTrace’s existence and functionality. 

Link: https://www.alohatrace.org/

Platforms in the Pandemic

Newscasters rarely shy away from declaring the ongoing pandemic to be a state of war. A war with clear defined enemies – in this case, the novel Coronavirus (SARS COVID 2/ COVID19). The virus is an unknown, unforeseen enemy, wreaking havoc on our anthropocentric territory. Bodies, land, resources, transports, have to be guarded, communities monitored and populations managed against the backdrop of the spread of the virus. Pandemic demands preparedness, isolation, carceral labour, and the maintenance of critical supply chains despite disruptions. Pandemic for policy-makers is a state of war. But perhaps, the most telling thing is that for governments and states the pandemic is not merely a war against the virus, it is often a war against its own people. Viruses, though airborne, travel through human bodies. Human bodies are the primary medium of viral transmission in our civilizational world. Viruses may jump species and therefore scales of travel. Having entered human worlds, viruses become tied to the fate of the human bodies and social scales. Therefore, governing the movement of the virus is more often than not conflated into governing populations at large. To take Marshall McLuhan’s aphorism “Medium is the message” seriously, humans and their status as mediums of virus transmission sets the discourse for the pandemic itself (mywebcowtube 2011) . Needless to say, not all mediums are the same. Racial, sexual, ethnic, and caste-based hierarchies complicate our status as mediums. Some communities have historically been typecast as superspreaders down to the present day through racialization, as active mediums prone to diseases and infections. And some others, by infrastructural and social design, have been rendered prone to higher morbidity rates. If the pandemic is a war, it also exacerbates the existing race and class wars in our society. 

So, if the war is against the virus, it is also equally against humans. Wars demand the close coordination of logistics and constant surveillance of enemies for possible threats. True to the symptoms of paranoia in war, however, threat is often not outside and elsewhere. It spreads infectiously, threatens our close quarters as well. So a surveillance gaze turned to the world outside is always already folded back to the interior space of one’s home turf (Hu 2015; 24-25). In the pandemic, contact tracing apps have become the predominant, ubiquitous “weapon” within everyone’s reach to fight the war against the pandemic. In brief, contact tracings apps try to determine and inform you if you have been in proximity with other infected people. Hailed as the digital ammunition in the war against Covid-19, contact tracing apps have in reality had a rather lukewarm response and drawn the ire of the critics for its gross invasion of privacy, mass extraction of data and potential for future abuse (Sweeney 2020). Across many varied types of data collection practices, which include extraction of phone data, compulsory questionnaires, bluetooth and location mapping/GPS tracking, contact tracing apps seek to document every facet, movement and step of your life (Franch-Pardo et al. 2020). Since war is a state of suspension of rights, privacy concerns have been largely overridden in favour of data extraction practices purportedly in order to manage risks, resources and response of a population at large (Ostherr et al. 2017). But beyond concerns around mere dataveillance, contact tracing apps also govern how you live your life, measure and assess your risks, how you define the time and space of your existence. It not only records all your spatial habitations, but in the case of the Aarogya Setu app (made by Govt of India), it also color codes your spaces (Figure 1). The Green colour indicates that the risk of infection is low for the user. Yellow colour on the screen indicates moderate risk of  infection, orange indicates high risk of infection and red appears once the individual has tested positive for the virus. Which then raises the question, how do we as users make sense of this data? And how do data analysts, policy makers who aggregate this data make sense of it? 

(Figure 1 – Aarogya Setu infographic on its color code spatial segregation. Source – Govt. of India Twitter Page) 

Digital platform cultures thrive not just by collecting and extracting data, but by discovering an operability, a pattern, a future value for that data in times to come (Cheney Lippold 2017). Its promise of future value is also its impulse for totalizing the art of data capture itself. Every data is potentially valuable data and has to be collected for its promised futurity. Contact tracing apps thrive on this premise, not of the present utility/value, but of the future. As digital platforms, they seek to capture or rather mitigate the unknowability of our futures. The future, like the pandemic, operates within the realm of the unknowable, marked by constant threats of harmful exposures against which immunity has to be secured in time. This rhetoric of securitization is embodied in the recording of contacts, movements, networks and trails, all the information that might safeguard you from future infection. Contact tracing apps thus fold upon the present an ever evolving set of future possibilities, inscribing our daily habits, movements, social spaces, our very forms and contours of habitation into loops of pre-emptive prediction. GPS and Bluetooth map out infection rates, track infections spatially through network spreads, routes of travel and so on. Tethered to the digital logics of storing data for future use, they exhume our futures from our spatialized presents. In the ideal world of the app, the future we encounter is free from the risk of incalculability, from contingency.

What futures are we seeing then, precipitated by the war against the virus and humans? A future where color-coded spatial demarcations shape the inequities of urban design. Contact tracing apps demarcate or segregate spaces by their present and future potentiality for threat. Given the ability of algorithmic platforms to store and operationalize data, one has to ask speculative but all too real questions about our futures. That is, what if future market and land prices came to be demarcated by whether the plot was in a long term red, orange, yellow or green zone? Could access to credit, school, law and police be determined by where we stay, and how we stay, the resilience of our health and medical infrastructure? In America’s racialized and India’s caste segregated pasts, this in a sense has always been the case. A history of urban civilization is the history of segregation based on racial, ethnic, caste, or labour lines. Contact tracing apps add a computational modality to these racialized histories – reinforcing segregation by constantly computing parameters, limits and extensions based on our health, existing quality of life and wellness. Existing social disparities (themselves produced by technologies and infrastructures of governance) are deepened by COVID-era algorithmic governance, as red-lined contagion zones digitally reinscribe violence and deprivation upon red-lined communities and their lifeworlds yet again. Our quality of life has always been shaped by our relations and positions within racialized capital. Are we by using contact tracing apps then – to speak in the grammar of both racial segregation and epidemiology – participating in a renewed redlining of our cities? Platform cultures, especially as they operate within existing capital systems, always tend to segregate by their own design. We are recommended content by content we already like, given credit by measure of people who already earn similar incomes, or even given health advice based on symptoms ‘people like us’ already share. Platforms capitalise by selling the more of the same; they promote, extend and update homophily (the love for the same) (Chun 2018). Homophily is segregatory in its very nature, perceiving difference as a disturbance or a threat that must be repelled. If data collected through contact tracing apps follow segregatory practices, or are overlaid with existing segregatory practices, data sets and so on, what futures of health do we stare at? The question that contact tracing apps bring to the forefront (or, rather, hide in their public welfare discourse) is the key point of segregation that controlling the pandemic necessitates: can we safeguard lives through quarantining without down on existing histories of ethnic, communitarian and social violence? That is the fraught question that must be asked for any post-corona world. 


Cheney-Lippold, John. 2017. We Are Data: Algorithms and the Making of our Digital Selves. New York: New York University Press. 

Chun, Wendy Hui Kyong. 2018. “Queerying Homophily.” In Pattern Discrimination, 59-98. Lunenberg, Minneapolis and London: Meson Press and University of Minnesota Press.

Hu, Tung-Hui. 2015. Pre-History of the Cloud. Cambridge, Massachusetts: MIT Press.

Franch-Pardo,Ivan, Brian M. Napoletano, Fernando Rosete-Verges, Lawal Billa. 2020. “Spatial analysis and GIS in the study of COVID-19: A review.” Science of The Total Environment,

Volume 739, https://doi.org/10.1016/j.scitotenv.2020.140033.

mywebcowtube. 2011. “Marshall Mcluhan Full lecture: The medium is the message – 1977 part 1 v 3.” YouTube video, 14:22. Aug 9, 2011. https://www.youtube.com/watch?v=ImaH51F4HBw  

Ostherr, Kirsten, Svetlana Borodina, Rachel Conrad Bracken, Charles Lotterman, Eliot Storer, and Brandon Williams. 2017. “Trust and Privacy in the Context of User-Generated Health Data.” Big Data & Society, June 2017. https://doi.org/10.1177/2053951717704673.

Sweeney, Y. 2020. “Tracking the debate on COVID-19 surveillance tools.” Nature Machine Intelligence, 2, 301–304. https://doi.org/10.1038/s42256-020-0194-1.