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. 2022 Nov 16;13:7003. doi: 10.1038/s41467-022-33713-y

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© The Author(s) 2022

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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 4 — Covariates that show the highest correlation with the overall percentage of COVID-19 sequenced cases (during the period shown in Fig. 1, with geographic regions colored as shown in that figure). A Expenditure on R&D per capita (slope = 1.30, CI = (0.76, 1.84), t-value = 4.76). B GDP per capita (slope = 0.75, CI = (0.44, 1.05), t-value = 4.83). C Socio-demographic index (slope = 0.25, CI = (0.07, 0.44), t-value = 2.70). D Overall proportion of sequenced genomes per influenza death in 2019 (HA segment) (slope = 0.89, CI = (0.40, 1.37), t-value = 3.62). For correlations between covariates and turnaround time, see Fig. S10. The color scheme is the same as in Figs. 1 and 2. Solid line shows the linear fit; correlation is Pearson’s correlation; p values are reported based on the t-statistic using two-sided hypothesis, with the null hypothesis being that the slope of the linear trend is zero. There was no need for multiple comparison adjustments. *PPP purchasing power parity, USD US dollar 2005.