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Over the course ofjust two weeks in mid-March 2020, most of the world went into a state of general lockdown in response to the novel coronavirus disease 2019 (COVID-19). This rapid shift in public-health policy implemented a suite of countermeasures referred to as nonpharmaceutical interventions (NPIs), including wide-scale nonessential business closures, event cancellations, school closures, numerical restrictions on gathering sizes, suspensions of international travel, and shelter-in-place orders-all intended to reduce or mitigate the transmission of the virus. Although initially presented as short-term emergency measures to flatten the curve of demand for hospital capacity, many of these responses quickly morphed into persistent policies for the duration of the pandemic.
No single event precipitated the widespread adoption of NPIs. However, the political movement behind them reached something of a tipping point on March 16, 2020. This was the day that a team of experts at Imperial College London (ICL) released an epidemiological model of the pandemic, predicting catastrophic death tolls of 2.2 million in the United States and more than 500,000 in the United Kingdom, barring the immediate adoption of lockdown-style NPIs (Ferguson, Laydon, et al. 2020). The ICL reports death-toll forecasts directly induced the governments of both countries to alter their pandemic-response strategies in favor of wide-scale lockdowns, which saw implementation across the majority of both countries over the following two weeks (Fink 2020). Most governments around the world shortly thereafter adopted similar policies in conjunction with this model (Oxford Stringency index n.d.).
This unprecedented succession of events is distinctive for its direct reliance on the prescriptive forecasts of an epidemiological computer simulation-arguably the first time in history and certainly the first instance of this scale. As the lead author of an influential paper in 2006 on the use of NPIs during an influenza pandemic (Ferguson, Cummings, et al. 2006), Neil Ferguson, the primary modeler of the ICL report, played a central role in this shift toward modeling. (Ferguson directly adapted the same influenza model to forecast the coronavirus outbreak in the ICL report.) In addition to the study published on March 16 (Ferguson, Laydon, et al. 2020), Ferguson personally advised the U.K. government's decisions as a member of its SAGE (Scientific Advisory Group for Emergencies) committee on COVID-19 and directly influenced a similar course taken...