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Literature on branching process applications

Source: vignettes/branching_process_literature.Rmd
branching_process_literature.Rmd

Note

bpmodels is now retired and will no longer be maintained. We recommend using {epichains} instead. If you need help converting your code to use {epichains}, please open a discussion on epichains.

Below, we provide a bibliography on the application of branching processes to infectious disease modelling.

It is our intention to grow this list to serve as a point of reference for budding modellers with an interest in the subject.

If you would like to extend this list, the easiest way would be to file an issue, listing the new additions and we’ll take it from there, or submit a pull request with an updated version of the bibliography file found in “vignettes/branching_process_literature.json”.

Bibliography

Abbott, Sam, Joel Hellewell, James Munday, Sebastian Funk, CMMID nCoV working group, et al. 2020. “The Transmissibility of Novel Coronavirus in the Early Stages of the 2019-20 Outbreak in Wuhan: Exploring Initial Point-Source Exposure Sizes and Durations Using Scenario Analysis.” Wellcome Open Research 5.
Becker, Niels, and International Biometric Society. 1977. “Estimation for Discrete Time Branching Processes with Application to Epidemics.” Biometrics 33 (3): 515–22.
Blumberg, Seth, and James O. Lloyd-Smith. 2013. “Inference of R0 and Transmission Heterogeneity from the Size Distribution of Stuttering Chains.” PLoS Computational Biology 9 (5): 1–17. https://doi.org/10.1371/journal.pcbi.1002993.
Blumberg, S., and J. O. Lloyd-Smith. 2013. “Comparing Methods for Estimating R0 from the Size Distribution of Subcritical Transmission Chains.” Epidemics 5 (3): 131–45. https://doi.org/10.1016/j.epidem.2013.05.002.
Farrington, C. P., and A. D. Grant. 1999. “The Distribution of Time to Extinction in Subcritical Branching Processes: Applications to Outbreaks of Infectious Disease.” Journal of Applied Probability 36 (3): 771–79. https://doi.org/10.1239/jap/1032374633.
Farrington, C. P., M. N. Kanaan, and N. J. Gay. 2003. “Branching Process Models for Surveillance of Infectious Diseases Controlled by Mass Vaccination.” Biostatistics (Oxford, England) 4 (2): 279–95. https://doi.org/10.1093/biostatistics/4.2.279.
Hellewell, Joel, Sam Abbott, Amy Gimma, Nikos I. Bosse, Christopher I. Jarvis, Timothy W. Russell, James D. Munday, et al. 2020. “Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts.” The Lancet Global Health 8 (4): e488–96. https://doi.org/10.1016/S2214-109X(20)30074-7.
Jacob, Christine. 2010. “Branching Processes: Their Role in Epidemiology.” International Journal of Environmental Research and Public Health 7 (3): 1186–1204. https://doi.org/10.3390/ijerph7031204.
Kucharski, Adam J., and W. John Edmunds. 2015. “Characterizing the Transmission Potential of Zoonotic Infections from Minor Outbreaks.” PLOS Computational Biology 11 (4): e1004154. https://doi.org/10.1371/journal.pcbi.1004154.
Kucharski, Adam J., Rosalind M. Eggo, Conall H. Watson, Anton Camacho, Sebastian Funk, and W. John Edmunds. 2016. “Effectiveness of Ring Vaccination as Control Strategy for Ebola Virus Disease.” Emerging Infectious Diseases 22 (1): 105–8. https://doi.org/10.3201/eid2201.151410.
Lloyd-Smith, J. O., S. J. Schreiber, P. E. Kopp, and W. M. Getz. 2005. “Superspreading and the Effect of Individual Variation on Disease Emergence.” Nature 438 (7066): 355–59. https://doi.org/10.1038/nature04153.
Nishiura, Hiroshi, Ping Yan, Candace K. Sleeman, and Charles J. Mode. 2012. “Estimating the Transmission Potential of Supercritical Processes Based on the Final Size Distribution of Minor Outbreaks.” Journal of Theoretical Biology 294: 48–55. https://doi.org/10.1016/j.jtbi.2011.10.039.
Pearson, Carl A.B., Cari van Schalkwyk, Anna M. Foss, Kathleen M. O’Reilly, and Juliet R.C. Pulliam. 2020. “Projected Early Spread of COVID-19 in Africa Through 1 June 2020.” Eurosurveillance 25 (18): 1–6. https://doi.org/10.2807/1560-7917.ES.2020.25.18.2000543.
Ratnayake, Ruwan, Francesco Checchi, Christopher I. Jarvis, W. John Edmunds, and Flavio Finger. 2022. “Inference Is Bliss: Simulation for Power Estimation for an Observational Study of a Cholera Outbreak Intervention.” Edited by Ruifu Yang. PLOS Neglected Tropical Diseases 16 (2): e0010163. https://doi.org/10.1371/journal.pntd.0010163.