Time series modelling of childhood diseases: a dynamical systems approach
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DOI: 10.1111/1467-9876.00187
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Cited by:
- Chuard, Caroline & Schwandt, Hannes & Becker, Alex & Haraguchi, Masahiko, 2022.
"Economic vs. Epidemiological Approaches to Measuring the Human Capital Impacts of Infectious Disease Elimination,"
IZA Discussion Papers
15420, Institute of Labor Economics (IZA).
- Caroline Chuard & Hannes Schwandt & Alexander D. Becker & Masahiko Haraguchi, 2022. "Economic vs. Epidemiological Approaches to Measuring the Human Capital Impacts of Infectious Disease Elimination," NBER Working Papers 30202, National Bureau of Economic Research, Inc.
- Kimberly M. Thompson, 2016. "Evolution and Use of Dynamic Transmission Models for Measles and Rubella Risk and Policy Analysis," Risk Analysis, John Wiley & Sons, vol. 36(7), pages 1383-1403, July.
- Frits Bijleveld & Jacques Commandeur & Phillip Gould & Siem Jan Koopman, 2008.
"Model‐based measurement of latent risk in time series with applications,"
Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 265-277, January.
- Frits Bijleveld & Jacques Commandeur & Phillip Gould & Siem Jan Koopman, 2005. "Model-based Measurement of Latent Risk in Time Series with Applications," Tinbergen Institute Discussion Papers 05-118/4, Tinbergen Institute.
- Rachel E. Baker & Ayesha S. Mahmud & C. Jessica E. Metcalf, 2018. "Dynamic response of airborne infections to climate change: predictions for varicella," Climatic Change, Springer, vol. 148(4), pages 547-560, June.
- Julliard, Christian & Shi, Ran & Yuan, Kathy, 2023.
"The spread of COVID-19 in London: Network effects and optimal lockdowns,"
Journal of Econometrics, Elsevier, vol. 235(2), pages 2125-2154.
- Julliard, Christian & Shi, Ran & Yuan, Kathy, 2020. "The spread of COVID-19 in London: network effects and optimal lockdowns," LSE Research Online Documents on Economics 118864, London School of Economics and Political Science, LSE Library.
- Julliard, Christian & Shi, Ran & Yuan, Kathy, 2023. "The spread of COVID-19 in London: network effects and optimal lockdowns," LSE Research Online Documents on Economics 118825, London School of Economics and Political Science, LSE Library.
- Alexander D Becker & Bryan T Grenfell, 2017. "tsiR: An R package for time-series Susceptible-Infected-Recovered models of epidemics," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-10, September.
- Maria Bekker‐Nielsen Dunbar & Felix Hofmann & Leonhard Held & the SUSPend modelling consortium, 2022. "Assessing the effect of school closures on the spread of COVID‐19 in Zurich," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S1), pages 131-142, November.
- Joanna N. Lahey & Marianne H. Wanamaker, 2022. "Effects of Restrictive Abortion Legislation on Cohort Mortality Evidence from 19th Century Law Variation," NBER Working Papers 30201, National Bureau of Economic Research, Inc.
- H. J. Whitaker & C. P. Farrington, 2004. "Infections with Varying Contact Rates: Application to Varicella," Biometrics, The International Biometric Society, vol. 60(3), pages 615-623, September.
- Calsina, Àngel & Cuadrado, Sílvia & Vidiella, Blai & Sardanyés, Josep, 2023. "About ghost transients in spatial continuous media," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
- David M Williams & Amy C Dechen Quinn & William F Porter, 2014. "Informing Disease Models with Temporal and Spatial Contact Structure among GPS-Collared Individuals in Wild Populations," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-12, January.
- Patrick W. Schmidt, 2020. "Inference under Superspreading: Determinants of SARS-CoV-2 Transmission in Germany," Papers 2011.04002, arXiv.org.
- Wan Yang & Liang Wen & Shen-Long Li & Kai Chen & Wen-Yi Zhang & Jeffrey Shaman, 2017. "Geospatial characteristics of measles transmission in China during 2005−2014," PLOS Computational Biology, Public Library of Science, vol. 13(4), pages 1-21, April.
- Mikael Jagan & Michelle S deJonge & Olga Krylova & David J D Earn, 2020. "Fast estimation of time-varying infectious disease transmission rates," PLOS Computational Biology, Public Library of Science, vol. 16(9), pages 1-39, September.
- Hao Yu & Xu Sun & Wei Deng Solvang & Xu Zhao, 2020. "Reverse Logistics Network Design for Effective Management of Medical Waste in Epidemic Outbreaks: Insights from the Coronavirus Disease 2019 (COVID-19) Outbreak in Wuhan (China)," IJERPH, MDPI, vol. 17(5), pages 1-25, March.
- Victor Zakharov & Yulia Balykina & Igor Ilin & Andrea Tick, 2022. "Forecasting a New Type of Virus Spread: A Case Study of COVID-19 with Stochastic Parameters," Mathematics, MDPI, vol. 10(20), pages 1-18, October.
- David A Rasmussen & Oliver Ratmann & Katia Koelle, 2011. "Inference for Nonlinear Epidemiological Models Using Genealogies and Time Series," PLOS Computational Biology, Public Library of Science, vol. 7(8), pages 1-11, August.
- Metcalf, C.J.E. & Lessler, J. & Klepac, P. & Morice, A. & Grenfell, B.T. & Bjørnstad, O.N., 2012. "Structured models of infectious disease: Inference with discrete data," Theoretical Population Biology, Elsevier, vol. 82(4), pages 275-282.
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