Catching the flu: Syndromic surveillance, algorithmic governmentality and global health security

Abstract

How do algorithms shape the imaginary and practice of security? Does their proliferation point to a shift in the political rationality of security? If so, what is the nature and extent of that shift? This article argues that efforts to strengthen global health security are major drivers in the development and proliferation of new algorithmic security technologies. In response to a seeming epidemic of potentially lethal infectious disease outbreaks – including HIV/AIDS, Severe Acute Respiratory Syndrome (SARS), pandemic flu, Middle East Respiratory Syndrome (MERS), Ebola and Zika – governments and international organizations are now using several next-generation syndromic surveillance systems to rapidly detect new outbreaks globally. This article analyses the origins, design and function of three such internet-based surveillance systems: (1) the Program for Monitoring Emerging Diseases, (2) the Global Public Health Intelligence Network and (3) HealthMap. The article shows how each newly introduced system became progressively more reliant upon algorithms to mine an ever-growing volume of indirect data sources for the earliest signs of a possible new outbreak – gradually propelling algorithms into the heart of global outbreak detection. That turn to the algorithm marks a significant shift in the underlying problem, nature and role of knowledge in contemporary security policy.