Nonpharmaceutical interventions (NPIs) intended to reduce infectious contacts between persons form an integral part of plans to mitigate the impact of the next influenza pandemic. Although the potential benefits of NPIs are supported by mathematical models, the historical evidence for the impact of such interventions in past pandemics has not been systematically examined. We obtained data on the timing of 19 classes of NPI in 17 U.S. cities during the 1918 pandemic and tested the hypothesis that early implementation of multiple interventions was associated with reduced disease transmission. Consistent with this hypothesis, cities in which multiple interventions were implemented at an early phase of the epidemic had peak death rates ≈50% lower than those that did not and had less-steep epidemic curves. Cities in which multiple interventions were implemented at an early phase of the epidemic also showed a trend toward lower cumulative excess mortality, but the difference was smaller (≈20%) and less statistically significant than that for peak death rates. This finding was not unexpected, given that few cities maintained NPIs longer than 6 weeks in 1918. Early implementation of certain interventions, including closure of schools, churches, and theaters, was associated with lower peak death rates, but no single intervention showed an association with improved aggregate outcomes for the 1918 phase of the pandemic. These findings support the hypothesis that rapid implementation of multiple NPIs can significantly reduce influenza transmission, but that viral spread will be renewed upon relaxation of such measures.

This paper describes a multimembership Bayesian index of severity calculated by MEDAS (the Medical Emergency Decision Assistance System). This severity index measures the likelihood that the patient will die without immediate intervention. The MEDAS inference engine operates on binary features representing signs, symptoms, and laboratory results. As a basis for calculation of the severity index, severity weights, ranging from 0 to 9 were assigned to each feature by an expert physician in order to form a severity pattern. To evaluate the MEDAS severity index, two physician experts in critical care medicine independently provided severity assessments for a series of patients hospitalized for congestive heart failure (N=19) or diabetes mellitus (N=22). These disorders were selected because they are common in the patient load at our VA hospital and lead to a wide range of outcomes. Agreement between the MEDAS severity index and the expert assessments was at or was close to the theoretical maximum.