Rt trajectory fits for EpiFusion models on datasets with increasing observation noise.

<p>The real Rt (black line) is smooth with increasing uncertainty in the fits introduced by noisy data, where the sampling rate changed every 7 days. The row labels (right) indicate the noise level (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1012528#...

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Bibliographic Details
Main Author:	Ciara Judge (20161514) (author)
Other Authors:	Timothy Vaughan (5654278) (author), Timothy Russell (20161517) (author), Sam Abbott (9548946) (author), Louis du Plessis (3264087) (author), Tanja Stadler (118822) (author), Oliver Brady (5331668) (author), Sarah Hill (101064) (author)
Published:	2024
Subjects:	Genetics Biotechnology Evolutionary Biology Cancer Infectious Diseases Computational Biology Mathematical Sciences not elsewhere classified surveillance rapidly changes scaled trees estimated remain largely distinct poorly sampled epidemics effective reproduction number accommodate future extensions respiratory virus outbreaks approach scales efficiently 2014 ebola outbreak phylodynamic observation models div >< p </ sub >) </ sub simulated outbreaks outbreak dynamics joint approach xlink "> weighted according sierra leone retrospective analysis phylogenetic uncertainty pathogen phylodynamics joint inference integrating phylodynamic infectious disease increases certainty genetic sequences fundamental challenge existing methods demonstrate advances dataset size complementary strengths circulating pathogen case incidence accurately estimating
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Rt trajectory fits for EpiFusion models on datasets with increasing observation noise.

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