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Diaoulé Diallo

As seen in: PLOS, MDPI
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Articles

Network-based proactive contact tracing: A pre-emptive, degree-based alerting framework for privacy-preserving COVID-19 apps

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By Diaoulé Diallo, Sankt Augustin, Tobias Hecking
| PLOS
Citation: Diallo D, Hecking T (2025) Network-based proactive contact tracing: A pre-emptive, degree-based alerting framework for privacy-preserving COVID-19 apps. PLOS Digit Health 4(11): e0000966. https://doi.org/10.1371/journal.pdig.0000966 Editor: Onicio Batista Leal-Neto, The University of Arizona, UNITED STATES OF AMERICA Received: July 15, 2025; Accepted: October 31, 2025; Published: November 19, 2025 Copyright: © 2025 Diallo, Hecking.
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Integrating Human Mobility Models with Epidemic Modeling: A Framework for Generating Synthetic Temporal Contact Networks

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By Diaoulé Diallo, Rene Schmieding, Jurij Schoenfeld, Sascha Korf
| preprints.org
You are already at the latest version High-resolution temporal contact networks are useful ingredients for realistic epidemic simulations. Existing solutions typically rely either on empirical studies that capture fine-grained interactions via Bluetooth or wearable sensors in confined settings, or on large-scale simulation frameworks that model entire populations using generalized assumptions.
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Dynamic Contact Networks in Confined Spaces: Synthesizing Micro-Level Encounter Patterns through Human Mobility Models from Real-World Data

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By Diaoulé Diallo, Jurij Schönfeld, Tessa F. Blanken, Tobias Hecking
| MDPI
1. Introduction The study of mobility patterns and the formation of complex contact networks remains a cornerstone in epidemic research, providing important insights into the dynamics of disease spread and informing mitigation strategies and public health policies [1,2,3,4]. This recognition has been underscored by the global COVID-19 pandemic, where the analysis of contact networks has played a pivotal role in forecasting the virus’s trajectory [5,6,7].
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