When new outbreaks of a disease are detected, epidemiologists use a variety of data sources to determine the risk of spread. Along with near real-time maps to monitor the outbreak of COVID-19 (also known informally as the Novel Coronavirus), there are maps and online data dashboards being developed to assess the risk of this novel coronavirus spreading. These maps look at a patterns of transmission, existing cases, and other factors such as airline travel to assess the relative risk of the disease spreading both within China and to other countries.
At Northeastern University, the MOBS Lab is using data from crowdsourced sources such a DXY.cn, an online Chinese community for medical health professionals, along with other data sources to estimate the risk of international dissemination of 2019-nCoV. The model assesses the mobility of individuals from 3,200 census areas in about 190 different countries to determine the risk of international dissemination.
The risk is visualization onto a map using EpiRisk, built by Northeastern’s GLEAMviz (GLEAM stands for Global Epidemic and Mobility Model). The interactive map visualizes the risk of the coronavirus outbreak spreading by factoring in commuting and airline travel. The computational platform can also be used to understand how changes to those travel patterns can alter the spread of an outbreak.
The results of calculations from EpiRisk have contributed to a brief paper published by MOBS Lab, “Early epidemiological analysis of the 2019-nCoV outbreak based on a crowdsourced data.“ Users can explore the statistical details from the analysis in a Google Data Studio dashboard.