The inverse method for a childhood infectious disease model with its application to pre-vaccination and post-vaccination measles data

DOI10.1007/s11538-015-0121-5zbMath1342.92247OpenAlexW2248076159WikidataQ35845846 ScholiaQ35845846MaRDI QIDQ5963806

Jude Dzevela Kong, Chaochao Jin, Hao Wang

Publication date: 23 February 2016

Published in: Bulletin of Mathematical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11538-015-0121-5

zbMATH Keywords

Fourier transforminverse problemsensitivity analysisvaccinationmeasleschildhood infectious diseaseincidence algorithmprevalence algorithmtime-dependent transmission rate

Mathematics Subject Classification ID

Epidemiology (92D30)

Related Items (6)

A hypothesis-free bridging of disease dynamics and non-pharmaceutical policies ⋮ From policy to prediction: forecasting COVID-19 dynamics under imperfect vaccination ⋮ Climate-dependent effectiveness of nonpharmaceutical interventions on COVID-19 mitigation ⋮ Extinction and Quasi-Stationarity for Discrete-Time, Endemic SIS and SIR Models ⋮ Reconstruction of disease transmission rates: applications to measles, dengue, and influenza ⋮ Parameter identification for a stochastic \textit{SEIRS} epidemic model: case study influenza

Cites Work

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• Parameter identification in epidemic models
• Melnikov analysis of chaos in a simple epidemiological model
• Extracting the time-dependent transmission rate from infection data via solution of an inverse ODE problem
• Seasonally forced disease dynamics explored as switching between attractors

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