PandemCap: decision support tool for epidemic management

Yanez, Andrea, Duggan, Jim, Hayes, Conor, Jilani, Musfira, & Connolly, Maire. (2017). PandemCap: decision support tool for epidemic management. Paper presented at the VAHC 2017 (8th workshop on Visual Analytics in Healthcare) - Affiliated with IEEE VIS 2017, Phoenix, Arizona. DOI: 10.13025/S8QW7M

Abstract

Pandemics or high impact epidemics are one of the biggest threats facing humanity today. While a complete elimination of the occurrence of such threats is improbable, it is possible to contain their impact by efficient management which in turn depends on effective decision-making. In the event of a pandemic the data flows are enormous and pose severe cognitive overload to the public health decision-makers. In this context, this paper presents PandemCap, an innovative decision support tool that can be used by the public health officials for making better and well informed decisions in the event of pandemics or high impact epidemics. PandemCap provides an interactive, flexible platform to public health decision-makers by making extensive use of techniques from the domains of visual analytics and epidemic modeling. In addition, the tool also allows for the study of the impact of various interventions or control measures such as the use of vaccines, anti-virals, hospital beds, and ventilators.

Publisher

NUI Galway

Rights

Attribution-NonCommercial-NoDerivs 3.0 Ireland

cbn

Collections

Data Science Institute (Conference Papers)