Study population and setting
The study deployed an existing pandemic influenza planning model in Great Britain to explore the potential impact of five non-pharmaceutical interventions (NPIs) implemented in Great Britain and the United States. This model used Census data such as the population density and age distribution, household structure, workplace and school size, and commuting data, to create a synthetic, yet realistic, population similar to that of Great Britain. Authors modeled disease-causing contact patterns by relying on previously-collected surveys of social mixing. The model evaluated the following NPIs: case isolation in the home, voluntary home quarantine, social distancing of the elderly, social distancing of the entire population, and school and university closure.
Summary of Main Findings
Population-wide social distancing would have the largest impact; in combination with other interventions – notably home isolation of cases and school and university closure. NPI strategies enduring for three months, which the authors termed “mitigation strategies,” were unlikely to enable the US and UK healthcare systems to remain below emergency surge capacity limits. Population-wide social distancing, when applied for extended periods of time (e.g. five months), suppressed disease transmission to a level where R (the reproductive number) fell below 1 (on average, a single case infects less than one other individual).
Incorporates information from China, as well as new (at the time) data from Italy and the UK. Study applies these data to specific population and geographical information, allowing the trajectory of the epidemic to be modeled for both the UK and US.
These models provide useful insights on the relative impact of NPIs, but due to large uncertainties in disease features like the efficiency of virus transmission and the proportion of asymptomatic infection and behavioral compliance of NPIs over extended periods of time, it is difficult to evaluate the accuracy of the absolute magnitude of health impact from these models. Ethical and economic implications of these strategies were not considered, which further breeds uncertainty in behaviors that may affect disease transmission. Results may not be applicable to low- and middle-income countries.
This is one of the first studies to estimate the impact of NPIs on the course of the epidemic in high-income countries. Compares strategies that aim to suppress disease transmission to those that aim to slow disease spread, thus mitigating the impact on surge capacity. Considers feasibility and the health impact when triggering NPIs with epidemic outcomes (e.g., using weekly ICU cases to turn an NPI on or off in the model) for multiple NPI measures.