Evaluating the impact of point-of-care diagnostics on disease outbreaks in low resource settings

Abstract

Rapid disease diagnosis is critical during infectious disease outbreaks to enable early intervention measures and minimize risk of disease transmission. Recent outbreaks in low-resource settings have highlighted challenges with traditional laboratory-based diagnostic approaches including a dependence on supporting infrastructure and highly trained users. Limitations of laboratory-based devices often result in geographical separation of labs from cases creating delays and barriers for diagnosis. There is increasing interest in the use of point-of-care diagnostics during outbreaks to enable more dispersed field diagnostic approaches and improve accessibility of testing. Point-of-care diagnostics, however, are often less accurate than laboratory-based tests, which can make them a less trusted option. This thesis explores the possibility that accessible, less accurate point-of-care devices could enable more efficient containment of disease outbreaks compared to current practices that employ expensive, and often distant laboratory-based tests. Although the benefit of point-of-care devices has been discussed anecdotally, little work has been done to quantify the relative impact of point-of-care diagnostics on transmission characteristics during an outbreak. This thesis aims to establish a basic cross-domain simulation model that considers medical, engineering, and societal/cultural factors that contribute to disease outbreak outcomes. The simulation approach is used to assess the trade-off between diagnostic access and accuracy during the 2014 West Africa Ebola outbreak to determine if point-of-care devices could have offered a benefit. A sensitivity analysis is also conducted to assess the potential impact of diagnostics on future outbreaks. Simulation results support the hypothesis that deployment of point-of-care devices to increase accessibility of testing could significantly reduce the number of secondary infections during an outbreak. This finding is shown to be true across outbreaks of varying sizes and transmission characteristics and for devices with varying accuracy performance.