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Time series modelling of childhood diseases: a dynamical systems approach

Citations

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Cited by:

  1. Patrick W. Schmidt, 2020. "Inference under Superspreading: Determinants of SARS-CoV-2 Transmission in Germany," Papers 2011.04002, arXiv.org.
  2. repec:plo:pcbi00:1003312 is not listed on IDEAS
  3. Lahey, Joanna N. & Wanamaker, Marianne H., 2025. "Effects of restrictive abortion legislation on cohort mortality evidence from 19th century law variation," Journal of Public Economics, Elsevier, vol. 243(C).
  4. 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.
  5. repec:plo:pcbi00:1004655 is not listed on IDEAS
  6. 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.
  7. 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).
  8. 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.
  9. repec:plo:pcbi00:1007305 is not listed on IDEAS
  10. repec:plo:pcbi00:1006211 is not listed on IDEAS
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. repec:plo:pone00:0074208 is not listed on IDEAS
  20. repec:plo:pmed00:1001958 is not listed on IDEAS
  21. 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.
  22. 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.
  23. Calsina, Àngel & Cuadrado, Sílvia & Vidiella, Blai & Sardanyés, Josep, 2023. "About ghost transients in spatial continuous media," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
  24. 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.
  25. Wang, Lengyang & Zhang, Mingke, 2025. "Statistical modeling of Dengue transmission dynamics with environmental factors," Computational Statistics & Data Analysis, Elsevier, vol. 203(C).
  26. Wyatt G Madden & Wei Jin & Benjamin Lopman & Andreas Zufle & Benjamin Dalziel & C Jessica E. Metcalf & Bryan T Grenfell & Max S Y Lau, 2024. "Deep neural networks for endemic measles dynamics: Comparative analysis and integration with mechanistic models," PLOS Computational Biology, Public Library of Science, vol. 20(11), pages 1-17, November.
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