Incorporating non-expert evidence into surveillance and early detection of public health emergencies

‘Big data’ has promised significant improvements for the global surveillance of infectious disease. This SSHAP Case Study highlights how, over the past two decades, new disease surveillance practices built on amassing and processing large data sets – analysed computationally to reveal patterns, trends, and associations, relating to human behaviour and interactions – have been successful in the advanced forecasting of deadly disease outbreaks including severe acute respiratory syndrome (SARS), Middle East respiratory syndrome coronavirus (MERS-CoV), human influenza, the Ebola virus and novel coronavirus (COVID-19). The increasing incorporation of non-expert evidence – that is, data that is collected and analysed from sources outside of traditional clinical/healthcare sectors into infectious disease and public health surveillance practices – must be continually monitored and verified as technological capacities and innovation towards the rapid identification of public health threats advance

Security, surveillance and shambles: the UK's contact-tracing app

The delayed and problematic UK contact-tracing app has become a parable of the government’s failure to deal with the pandemic effectively, says Stephen L Roberts (LSE)

Covid-19: the controversial role of big tech in digital surveillance

Big tech can trace the movement of not only viruses, but also people, whether in an emergency or not, writes Stephen L Robert

Tracking Covid-19 using big data and big tech: a digital Pandora’s Box

Stephen L Roberts explains why, despite the supplemental value of some digital surveillance practices in the tracking of disease outbreaks, the concerns which arise from their use are multi-faceted and complex

Global health security and islands as seen through COVID-19 and vaccination

Since the declaration of COVID-19 as a pandemic in March 2020, significant research and attention has focused on countries’ abilities and interests in enacting response measures to the spread of the coronavirus including lockdowns, travel restrictions, and vaccination programmes to contain infections, hospitalisations, and deaths. As the pandemic has continued, much discussion has also centred on the ability of islands to control borders, enact public health measures, and keep the virus out or controlled, owing in part to presumed islandness characteristics of isolation and remoteness. Drawing from ongoing empirical examples of island experiences in the context of COVID-19, this article examines to what extent islandness impacts health concerns and health responses within aspects of global health security and health systems. In considering how islands around the world have been implementing health security measures regarding COVID-19, linkages or suggested linkages among islands, global health security, and pandemics indicate the lack of exceptionality of islands and archipelagos. That is, how islandness or lack thereof is managed ends up being far more important for global health security outcomes than islandness itself

Molecular basis for resistance of acanthamoeba tubulins to all major classes of antitubulin compounds

Tubulin is essential to eukaryotic cells and is targeted by several antineoplastics, herbicides, and antimicrobials. We demonstrate that Acanthamoeba spp. are resistant to five antimicrotubule compounds, unlike any other eukaryote studied so far. Resistance correlates with critical amino acid differences within the inhibitor binding sites of the tubulin heterodimers

Digital epidemiology and global health security; an interdisciplinary conversation

Contemporary infectious disease surveillance systems aim to employ the speed and scope of big data in an attempt to provide global health security. Both shifts - the perception of health problems through the framework of global health security and the corresponding technological approaches – imply epistemological changes, methodological ambivalences as well as manifold societal effects. Bringing current findings from social sciences and public health praxis into a dialogue, this conversation style contribution points out several broader implications of changing disease surveillance. The conversation covers epidemiological issues such as the shift from expert knowledge to algorithmic knowledge, the securitization of global health, and the construction of new kinds of threats. Those developments are detailed and discussed in their impacts for health provision in a broader sense