Cytokine Kinetics during Progression of COVID-19 in Rwanda Patients: Could IL-9/IFNγ Ratio Predict Disease Severity?

For effective treatments and preventive measures against severe COVID-19, it is essential to determine early markers of disease severity in different populations. We analysed the cytokine kinetics of 129 COVID-19 patients with mild symptoms, 68 severe cases, and 20 healthy controls for the first time in Rwanda. Pro-inflammatory (IFNγ, IL-6, TNFα), Treg (IL-10, TGFß1, TGFß3), Th9 (IL-9), Th17 (IL-17), and Th2 (IL-4, IL-13) cytokines, total IgM and IgG, as well as gene expressions of FoxP3, STAT5+, IFNγ-R1, and ROR alpha+, were measured at day 1, day 7, day 14, day 21, and day 28 post-infection. Severe cases showed a significantly stronger increase than mild patients in levels of all cytokines (except IL-9) and all gene expression on day 1 of infection. Some cytokine levels dropped to levels comparable to mild cases at later time points. Further analysis identified IFNγ as a marker of severity throughout the disease course, while TGFß1, IL-6, and IL-17 were markers of severity only at an early phase. Importantly, this study revealed a striking low IL-9 level and high IFNγ/IL-9 ratio in the plasma of patients who later died compared to mild and severe cases who recovered, suggesting that this could be an important biomarker for predicting the severity of COVID-19 and post-COVID-19 syndrome.

Genomic sequencing of SARS-CoV-2 in Rwanda reveals the importance of incoming travelers on lineage diversity.

COVID-19 transmission rates are often linked to locally circulating strains of SARS-CoV-2. Here we describe 203 SARS-CoV-2 whole genome sequences analyzed from strains circulating in Rwanda from May 2020 to February 2021. In particular, we report a shift in variant distribution towards the emerging sub-lineage A.23.1 that is currently dominating. Furthermore, we report the detection of the first Rwandan cases of the B.1.1.7 and B.1.351 variants of concern among incoming travelers tested at Kigali International Airport. To assess the importance of viral introductions from neighboring countries and local transmission, we exploit available individual travel history metadata to inform spatio-temporal phylogeographic inference, enabling us to take into account infections from unsampled locations. We uncover an important role of neighboring countries in seeding introductions into Rwanda, including those from which no genomic sequences were available. Our results highlight the importance of systematic genomic surveillance and regional collaborations for a durable response towards combating COVID-19.