Since the outbreak of the COVID-19 pandemic, efforts to quantitatively measure the global health situation and/or governments’ reaction vis-à-vis the pandemic have flourished. In spite of the significance of data in the fight against the pandemic, however, such global knowledge is largely questionable, insofar as it exposes itself to the many hazards and fallacies associated with global attempts to frame the social world in numbers. This is why the paper attempts to identify the hazards and fallacies most commonly associated with global measurements of social phenomena and to verify whether and to what extent these hazards and fallacies affect numerical representations of the pandemic and its effects. To this end, the paper analyses ten English-language global numerical initiatives that were launched between January and May 2020, and reviews them in light of existing critical literature on global numbers. The aim is to provide a deeper understanding of global measurements of health and related law-and-policy measures, and to suggest caution about their use as a basis for knowledge and action in the context of the pandemic.

The COVID-19 pandemic has given rise to the massive development and use of health indicators. Drawing on the history of international public health and of the management of infectious disease, this paper attempts to show that the normative power acquired by metrics during the pandemic can be understood in light of two rationales: epidemiological surveillance and performance assessment. On the one hand, indicators are established to evaluate and rank countries’ responses to the outbreak; on the other, the evolution of indicators has a direct influence on the content of public health policies. Although quantitative data are an absolute necessity for coping with such disasters, it is critical to bear in mind the inherent partiality and precarity of the information provided by health indicators. Given the growing importance of normative quantitative devices during the pandemic, and assuming that their influence is unlikely to decrease in the future, they call for close scrutiny.

The 2019 Global Health Security Index (GHS Index) assessed the US and the UK as the two countries best prepared to address a catastrophic pandemic. The preparedness rankings of this index have had little correlation with the actual experiences of COVID-19 in various countries. In explaining this disrepancy, the paper argues that better indicators and more data would not have fixed the problem. Rather, the prevailing paradigm of global health security that informs instruments such as the GHS Index needs to be interrogated. This dominant paradigm narrowly conceptualises global health security in terms of the availability of a technical infrastructure to detect emerging infectious diseases and prevent their contagion, but profoundly undertheorises the broader social and political determinants of public health. The neglect of social and political features is amplified in instruments such as the GHS Index that privilege universalised templates presumed to apply across countries but that prove to be inadequate in assessing how individual societies draw on their unique histories to craft public health responses.

Global social indicators, as a form of governance and soft regulation, exert pressure for change and compliance through the way they compare and rank the relative performance of states or other units. Is it reasonable then to expect the comparisons they make in the process of carrying out such strategic exercises to be accurate and fair? In particular, how far can they, or should they, be required to be faithful to the requirement to ‘compare like with like’. Using as an example the role of indicators in documenting and responding to the current coronavirus epidemic, I investigate the way their hybrid combination of both comparison and commensuration may help to account for the difficulty they have had so far in establishing stable rankings of best practice.

The COVID-19 crisis has been accompanied by an extensive use of indicators, such as those related to COVID infections and deaths, but also a good number of COVID policy indicators. This paper discusses these indicators from the perspective of a legal scholar with an interest (and some expertise) in comparative law and empirical legal studies. This means that this paper does not engage in the details concerning epidemiological and medical issues of COVID infections and deaths. Rather, it focuses on two main issues: first, it develops and maps a general causal scheme of indicators and their underlying real-world phenomena in the COVID crisis; second, it shows how such a causal scheme has been, and can be, applied in comparative empirical legal research. Yet, it also notes the difficulties of proving causal relationships and some attempts to overcome them.

The spread of COVID-19 has seen a contest over health governance and sovereignty in Global South states, with a focus on two radically distinct modes: (1) indicators and metrics and (2) securitisation. Indicators have been a vehicle for the government of states through the external imposition and internal self-application of standards and benchmarks. Securitisation refers to the calling-into-being of emergencies in the face of existential threats to the nation. This paper contextualises both historically with reference to the trajectory of Global South states in the decades after decolonisation, which saw the rise and decline of Third-World solidarity and its replacement by neoliberalism and global governance mechanisms in health, as in other sectors. The interaction between these modes and their relative prominence during COVID-19 is studied through a brief case-study of developments in Kenya during the early months of the pandemic. The paper closes with suggestions for further research and a reflection on parallel trends within Global North states.

This paper investigates the data life-cycle of contact-tracing apps (CTAs) in the context of the COVID-19 pandemic. It highlights the socio-legal implications resulting from the design and technology choices that software developers inevitably make. These choices are often neglected by policy-makers due to the inherent technical complexity of algorithmic decision systems and to certain naive belief in technological solutionism. In particular, this paper shows, first, that technology-harvested data do not reflect an objective representation of reality, and therefore require a context within which to be understood and interpreted for policy and legal purposes; and, second, that the use of data analytics to extract insights from these data enables the production of computational indicators. By looking at how CTAs are used to implement pandemic-mitigation restrictions such as lockdowns, quarantines, social distancing and testing, the paper ultimately brings forth the ways in which technologies – and thus their bias and ways of framing social reality – become embedded in the law.