PandemCap: Decision support tool for epidemic management

Abstract

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.

Uncovering chains of infections through spatio-temporal and visual analysis of COVID-19 contact traces

“…Other approaches take a more general epidemiological approach and address emergent pandemics [11] , the role of social networks in epidemiology [12] , [13] , or rather epidemic management [14] , [15] . Epidemic management and immediate outbreak control are also the focus of SORMAS [16] (originally developed for Ebola outbreaks), which is used in some German DPHs in addition to SurvNet@RKI, but not for the interactive detection of infection clusters with link predictions.…”

Visual Analytics of Contact Tracing Policy Simulations During an Emergency Response

“…Visual analytics systems have been used in the public health domain, for example through health records [HHO∗16, GXZ∗18, RWA∗13, MLL∗13] and epidemiological data [PL20]. For infectious disease control in particular, visual analytics approaches have been used for simulated disease data from spatio‐temporal perspectives [BWMM15], used as decision support tools for pandemic management [MLR∗11, YDH∗17] and used to trace back disease outbreaks to their origin in hospitals [BPW∗21,MPW∗20].…”

In Search of Patient Zero: Visual Analytics of Pathogen Transmission Pathways in Hospitals

“…Disease surveillance and epidemiology has also been of interest [49]. Visual analytics approaches for epidemiologists focus on the spatio-temporal evolution of a disease at a population level-how many people will be infected, in which geographic area(s), and the speed of the spread [12,39,82]. These visual analytics approaches target disease spreading over a large population at a macroscopic level.…”