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. 2024 Oct 9;24:293. doi: 10.1186/s12911-024-02702-0

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© The Author(s) 2024

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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Fig. 4 — Pearson Correlation between current SARI incidence values and past incidence of detected respiratory viruses. Heatmaps show the Pearson Correlation Coefficient (PCC) between the SARI incidence and the incidence of individual respiratory viruses. The virus incidence values were shifted back in time to visualize how well past values from the different viruses correlate with present SARI values. For example, the RV value at position (-3 days, 2017) represents the Pearson correlation between the SARI incidence on a specific day and the RV incidence 3 days before that day, calculated over all time points from 2017. White areas (see PIV2 for 2012) describe cases in which the numbers were too sparse to compute a PCC. The viruses investigated are influenza (FLU), respiratory syncytial virus (RSV), rhinovirus (RV), parainfluenza virus 1–3 (PIV), human metapneumovirus (HMPV), enterovirus (ENTV), and adenovirus (ADV)