Related Experiment Video
Updated: Sep 2, 2025

Author Spotlight: Developing a Point-of-Care Hemoglobin Estimation Method for Anemia Management
Published on: January 19, 2024
Monitoring supply networks from mobile phone data for estimating the systemic risk of an economy
Tobias Reisch1,2, Georg Heiler2,3, Christian Diem2,4
1Section for Science of Complex Systems, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, 1090, Vienna, Austria.
Abstract:
Remarkably little is known about the structure, formation, and dynamics of supply- and production networks that form one foundation of society. Neither the resilience of these networks is known, nor do we have ways to systematically monitor their ongoing change. Systemic risk contributions of individual companies were hitherto not quantifiable since data on supply networks on the firm-level do not exist with the exception of a very few countries. Here we use telecommunication meta data to reconstruct nationwide firm-level supply networks in almost real-time. We find the probability of observing a supply-link, given the existence of a strong communication-link between two companies, to be about 90%. The so reconstructed supply networks allow us to reliably quantify the systemic risk of individual companies and thus obtain an estimate for a country's economic resilience. We identify about 65 companies, from a broad range of company sizes and from 22 different industry sectors, that could potentially cause massive damages. The method can be used for objectively monitoring change in production processes which might become essential during the green transition.
Related Concept Videos
Steps in Outbreak Investigation
Design Example: Analyzing Capacity Contours for Flood Risk Assessment
Principles of Disease Surveillance
Mechanistic Models: Compartment Models in Individual and Population Analysis
Systematic Sampling Method
Systematic sampling is one of the simplest methods...
Pharmacovigilance
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...

