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. 2021 Jul 14;11:14495. doi: 10.1038/s41598-021-93238-0

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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El Salvador sensitivity analysis. Sensitivity analysis showing the impact of varying the prior mean for the distance kernel shaping parameter, β. The different colours and shapes represent different means and standard deviations respectively of the normally-distributed prior of epsilon, ε, which represents shapes represent different hazards of infection by an external, unobserved source. For A-D, the x-axis represents the prior mean used for β. (A) the y-axis shows the maximum a posteriori parameter estimate for the parameter β. (B) shows the same results, stratified by the prior mean of ε for clarity. (C) Shows the impact of priors for β and ε on the mean Rc estimate, and again (D) shows the same result, stratified by the prior mean of ε.