Essay #6 in the Data and Pandemic Politics series on data justice and COVID-19

When the Government of India announced a lockdown in March 2020 in an attempt to manage the COVID-19 outbreak, it precipitated a large-scale exodus of workers from cities to villages. With the closure of factories, construction sites, restaurants, hotels and other workplaces, millions of migrant workers who had moved to cities in search of work had to make their way to their villages because of the loss of work, income, food, and shelter. With no transportation to get back home due to the cancellation of buses and trains, one of the most distressing images of the lockdown was of millions of workers walking home for thousands of kilometres. Many vowed not to return to the cities after being abandoned by their employers and offered no security.

In September 2020, the Government of India said that over 10 million migrant workers had been displaced and had travelled to their villages between March and June 2020 during the lockdown. However, in response to a question raised in the Parliament about whether compensation or economic assistance was provided to workers who had died during the lockdown, the government stated that the question of compensation did not arise, because no data had been maintained of migrant deaths, and further that there was no data on job losses either. The casualness of this response not only points to the incompetency and unwillingness to understand the impacts of the lockdown on citizens, but also an abdication of responsibility in responding to the impact on life and livelihood that such a lockdown had.

Reporting by civil society and academia

The apathy towards collecting and making available data by the government seemed to have almost been anticipated by non-government actors who in contrast undertook several data collection exercises. A group of researchers and students put together a list of deaths that had taken place during the lockdown based on newspaper and online reports in English, Hindi, and other regional languages and came up with a list of at least 971 deaths of migrant workers that took place until July 2020. The database not only provided information about the deaths caused due to the pandemic, but also offered insights into the kinds of hardships that people faced. It categorised deaths on the basis of starvation and financial distress, lack of medical care, exhaustion, suicides, police brutality, accidents during migration, and also retained some deaths as unclassified in cases where the reports were not clear. Over 216 people died due to starvation and financial distress, 47 from exhaustion from walking or standing in line, 133 from suicides — a grim reading of the devastation that was caused to migrant workers across the country.

A voluntary group called the Stranded Workers Action Network (SWAN) also documented the experiences of workers who had been displaced during the pandemic and organised relief for them. They came up with an extensive response to the questions raised in the Parliament comparing the government’s response of a lack of data with a consolidated response of publicly available studies including on matters related to compensation announced for workers who had died, information regarding how migrant workers had returned home, information on food insecurity, and the extent of job losses across the country. Another report by Azim Premji University with data collected through a phone survey of 5000 respondents between 13 April and 20 May 2020, found that over 80% of migrant workers lost their jobs during lockdown, 74% of households of migrant workers had to reduce their food intake, 5 in 10 households did not have money for a week’s worth of essentials, and 6 in 10 did not receive cash transfers.

These databases are among several other initiatives that arose as a part of the need to document and monitor the impacts that COVID-19 had on the livelihood of migrant workers. While these studies point to the robust and critical role that civil society groups, volunteers, and academic institutions played to provide empirical information about migrant distress, they also highlight that in their absence, the Government had the capacity to determine the narrative on how the migrant crisis unfolded, deny any responsibility on the basis of the data available to them, and limit the capacity of the citizenry to hold them accountable for their policies and actions. This method of silencing experiences and facts of hardship for whatever reasons, from incompetency to political expediency, demonstrates the role that data justice plays in addressing broader challenges of justice and equality.

The effects of not collecting data

The collection of essays in the book Data Justice and COVID-19: Global Perspectives and the subsequent online series show how deeply entrenched data technologies have been in governmental responses to COVID-19. These have included the development of surveillance technologies through public-private partnerships, the function creep of certain technologies through their repurposing for tracking and tracing public health responses, and the tech solutionism that dominated the response to the pandemic through the proliferation of apps and other tools often at the expense of understanding the utility of the technology intervention. The Government of India similarly adopted a data-driven approach with at least 64 technology tools being supported across different state and district administrators in areas such as testing and screening, telemedicine to quarantine management, and virus mapping according to research conducted on tracking tech tools in response to COVID-19. In this regard, contrasting the neglect to collect data on migrant deaths becomes even more jarring, because it cannot be an outcome of a lack of state capacity, given the several other initiatives available and supported by the government, but a lack of political will.

A serious concern from the lack of data on migrant deaths is that it appears that only whatever is measured has value and is responded to. It raises questions about the priorities of what data is valuable enough to be collected, what data is considered okay to share, and what data can be ignored or made invisible. For instance, in the response to the question of compensation for migrant deaths, the government stated that since it did not have data, the question of compensation did not arise. Besides the coldness of the response, it shows that there are ways in which narratives can be determined, distorted or ignored through methods of counting, collecting, and sharing information.

Let’s examine how this process of ‘data silences’ takes place. What is clear from the case is that only that data, which is documented, is managed, and if it is not documented, a response is not warranted. The process of documentation therefore becomes a precondition to be able to prove the gravity of the crisis and the necessity of a response. It also shows that through the refusal to collect or give information other narratives can be provided through distortions, distractions or media management where in this case outlets discussed the migrant crisis as a tragedy but not as a result of state policies.

By not collecting data, not only is information not provided about the number of deaths, but also about the types of deaths, which in turn prevents a nuanced understanding about the kinds of situations people were in, from battling exhaustion at having to walk great distances, to starvation and suicide from the impacts that the lockdown had. The documentation of such information provides a way to know in more granular detail about the layers of the crisis, what kind of assistance was needed on an urgent basis, and who was most affected. The studies mentioned above offer a glimpse of the kind of inequalities that emerged but also demonstrated the kind of failures of policy and relief responses that resulted in many people lacking access to very basic facilities like food and shelter. Documentation thus not only denied one an understanding of the gravity of the situation, it also denied one the ability to assess the different aspects of the crisis.

Further by not collecting data, the capacity to act by non governmental actors and the victims’ families was also severely hampered, whether in the case of applying for compensation in case of deaths, in ensuring access to government welfare schemes but also in the capacity to demand transparency and fix accountability from government for the failure of policy and relief measures.


Several months later, after much criticism, the government announced in early December that it would develop a new database for migrant workers and other workers in the informal economy. This is a long overdue step that has been called for by activists working in the field.

What this case has shown is how injustice can be perpetuated through strategies of omitting documentation, denying knowledge, and avoiding responsibility through facilitating ‘data silences’. Such deliberate silences can then be used as a powerful tool by the government to change narratives around the crisis and use its infrastructure to make information that is uncomfortable for it unavailable to the public discourse thereby limiting scrutiny of its actions.

In this case, ‘data silences’ were countered by non-governmental actors who took on the role of counting by using independent data sources. These silences could also be responded to by mapping the impacts caused by these informational deficits. Doing so, will demonstrate the lifecycle of active ‘data silences’ and will demonstrate how these have tangible impacts both in terms of their impacts on the production of knowledge, but also in terms of government accountability and on the monitoring by the general public.

Siddharth Peter de Souza is a postdoctoral researcher at the Global Data Justice project and is interested in the role data plays at the intersection of law and development. Prior to joining TILT he was a PhD researcher at Humboldt University Berlin, and has studied law at the University of Cambridge and at the University of Delhi.

Suggested citation: de Souza, S. P. (2020, December 18). Data Silences— Invisibilising Migrant Distress in Times of COVID-19. Data and Pandemic Politics, 6.