Monitoring and prediction of an epidemic outbreak using syndromic observations

DOI10.1016/j.mbs.2012.05.010zbMath1319.92058arXiv1110.4696OpenAlexW1980645921WikidataQ43861892 ScholiaQ43861892MaRDI QIDQ452459

Branko Ristic, Alex Skvortsov

Publication date: 21 September 2012

Published in: Mathematical Biosciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1110.4696

zbMATH Keywords

nonlinear filteringparticle filterbio-surveillanceemerging epidemicsepidemiological inferencesyndromic data

Mathematics Subject Classification ID

Epidemiology (92D30)

Related Items (3)

Detecting disease outbreaks using a combined Bayesian network and particle filter approach ⋮ Efficient real-time monitoring of an emerging influenza pandemic: how feasible? ⋮ Comparison of the performance of particle filter algorithms applied to tracking of a disease epidemic

Cites Work

• Semi-empirical power-law scaling of new infection rate to model epidemic dynamics with inhomogeneous mixing
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• Using the Kalman filter and dynamic models to assess the changing HIV/AIDS epidemic
• Mathematics of data fusion
• Stochastic epidemics: Major outbreaks and the duration of the endemic period
• Stochastic processes and filtering theory
• Sequential Monte Carlo Methods in Practice
• A Guide to First-Passage Processes
• The Speed of Epidemic Waves in a One-Dimensional Lattice of SIR Models
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