Abstract
Background Strategies for containing an emerging infectious disease outbreak must be non-pharmaceutical when drugs or vaccines for the pathogens do not yet exist or are unavailable. However, little work exists to guide decisions between competing non-pharmaceutical strategies, as exemplified by the confusion about whether to employ quarantine or symptom monitoring during the recent Ebola epidemic in West Africa.
Methods We compared the effectiveness of quarantine and symptom monitoring in controlling epidemics using an agent-based branching model that accommodates non-pharmaceutical interventions. We used Sequential Monte Carlo particle filtering methods to parameterize disease dynamics of symptoms and infectiousness for seven case study diseases with diverse natural histories including Ebola, Influenza A, and Severe Acute Respiratory Syndrome (SARS). We quantify the key characteristics of an emerging disease that are most influential for determining the optimal intervention, given varying feasibility of its implementation.
Findings The comparative effectiveness of symptom monitoring and quarantine depends critically on the natural history of the infectious disease, its inherent transmissibility, and the intervention feasibility in the particular healthcare setting. The benefit of quarantine over symptom monitoring is generally maximized for fast-course diseases, or when there is a long delay between symptom onset and isolation. We find that symptom monitoring could effectively control an outbreak of a new Ebola-like disease, even when infectiousness precedes symptoms and interventions are not perfectly implemented.
Interpretation We establish a quantitative framework for guiding policy-makers in their decisions about how best to use non-pharmacological interventions to contain emerging outbreaks. Our method also provides guidelines for prioritizing research during an outbreak of a novel pathogen, by highlighting which aspects of the disease determine the epidemic potential of emerging pathogens.
Funding NIH-MIDAS, Smith Family Foundation.
