This paper examines the determinants of social distancing during the COVID-19 epidemic. We classify state and local government actions, and we study multiple proxies for social distancing based on data from smart devices. Mobility fell substantially in all states, even ones that have not adopted major distancing mandates. There is little evidence, for example, that stay-at-home mandates induced distancing. In contrast, early and information-focused actions have had bigger effects. Event studies show that first case announcements, emergency declarations, and school closures reduced mobility by 1-5% after 5 days and 7-45% after 20 days. Between March 1 and April 11, average time spent at home grew from 9.1 hours to 13.9 hours. We find, for example, that without state emergency declarations, event study estimates imply that hours at home would have been 11.3 hours in April, suggesting that 55% of the growth comes from emergency declarations and 45% comes from secular (non-policy) trends. State and local government actions induced changes in mobility on top of a large response across all states to the prevailing knowledge of public health risks. Early state policies conveyed information about the epidemic, suggesting that even the policy response mainly operates through a voluntary channel.
The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. At least one co-author has disclosed a financial relationship of potential relevance for this research. Further information is available online at http://www.nber.org/papers/w27280.ack NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.
IMPORTANCEThe efficacy of endovascular thrombectomy (EVT) for symptomatic large anterior vessel occlusion (sLAVO) sharply decreases with time. Because EVT is restricted to comprehensive stroke centers, prehospital triage of patients with acute stroke codes for sLAVO is crucial, and although several prediction scales are already in use, external validation, head-to-head comparison, and feasibility data are lacking.OBJECTIVE To conduct external validation and head-to-head comparisons of 7 sLAVO prediction scales in the emergency medical service (EMS) setting and to assess scale feasibility by EMS paramedics. DESIGN, SETTING, AND PARTICIPANTSThis prospective cohort study was conducted between July 2018 and October 2019 in a large urban center in the Netherlands with a population of approximately 2 million people and included 2 EMSs, 3 comprehensive stroke centers, and 4 primary stroke centers. Participants were consecutive patients aged 18 years or older for whom an EMS-initiated acute stroke code was activated. Of 2812 acute stroke codes, 805 (28.6%) were excluded, because no application was used or no clinical data were available, leaving 2007 patients included in the analyses.EXPOSURES Applications with clinical observations filled in by EMS paramedics for each acute stroke code enabling reconstruction of the following 7 prediction scales: Los Angeles Motor Scale (LAMS); Rapid Arterial Occlusion Evaluation (RACE); Cincinnati Stroke Triage Assessment Tool; Prehospital Acute Stroke Severity (PASS); gaze-face-arm-speech-time; Field Assessment Stroke Triage for Emergency Destination; and gaze, facial asymmetry, level of consciousness, extinction/inattention. MAIN OUTCOMES AND MEASURES Planned primary and secondary outcomes were sLAVO and feasibility rates (ie, the proportion of acute stroke codes for which the prehospital scale could be reconstructed). Predictive performance measures included accuracy, sensitivity, specificity, the Youden index, and predictive values. RESULTSOf 2007 patients who received acute stroke codes (mean [SD] age, 71.1 [14.9] years; 1021 [50.9%] male), 158 (7.9%) had sLAVO. Accuracy of the scales ranged from 0.79 to 0.89, with LAMS and RACE scales yielding the highest scores. Sensitivity of the scales ranged from 38% to 62%, and specificity from 80% to 93%. Scale feasibility rates ranged from 78% to 88%, with the highest rate for the PASS scale.CONCLUSIONS AND RELEVANCE This study found that all 7 prediction scales had good accuracy, high specificity, and low sensitivity, with LAMS and RACE being the highest scoring scales. Feasibility rates ranged between 78% and 88% and should be taken into account before implementing a scale.
Measures to improve detection and reporting of adverse drug reactions by all health care professionals should be undertaken, to enhance our understanding of the nature and impact of these reactions in children.
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