Measles Metapopulation Modeling using Ideal Flow of Transportation Networks

• Main Authors: Montalan, Jann Railey, Estuar, Ma. Regina Justina E, Teknomo, Kardi
• Format: text
• Published: Archīum Ateneo 2019
• Subjects: Applied computing; Life and medical sciences; Health informatics; Computing methodologies; Modeling and simulation; Simulation theory; Network science; Mathematics of computing; Mathematical analysis; Differential equations; Ordinary differential equations; Computer Sciences; Health Information Technology
• Online Access: https://archium.ateneo.edu/discs-faculty-pubs/185; https://dl.acm.org/doi/abs/10.1145/3305160.3305210
• Institution: Ateneo De Manila University

In developing countries with limited access to medical resources, infectious diseases like measles can develop rapidly within and between communities. Combination of data coming from various sources that report historical disease incidences and transportation infrastructures are valuable sources of knowledge that can assist in public health policies and initiatives surrounding disease surveillance. This study integrates population, disease incidence, and transportation network data into measles modeling. Results show that a hybrid metapopulation modeling approach using ideal flow distribution over mobility networks can yield more accurate models for measles progression. This demonstrates the feasibility of using big data in the monitoring of measles propagation.