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Background Influenza B virus (IBV) contributes significantly to morbidity and mortality during Influenza seasons annually. However, IBV genomic surveillance occurs unevenly across the globe, particularly within the African region, obscuring its epidemiology. This study aims to elucidate the epidemiological dynamics of IBV in Kenya and Uganda between 2010 and 2022. Methods In this study, 83 near complete IBV genomes circulating in Kenya and Uganda between 2010 and 2022 were generated through Oxford Nanopore Technologies sequencing (ONT). Publicly available IBV datasets were incorporated to evaluate the public context of these genomes. Further evolutionary dynamics analysis investigated the antigenic mutation, reassortment and glycosylation patterns of IBVs circulating in Kenya and Uganda within this period. Results Alternating IBV lineage predominance and clade turnover was observed consistent with global patterns. No B/Yamagata strains were detected at the study sites after 2019. Multiple B/Victoria clade/subclades (V1A, V1A.3, V1A.3a, V1A.3a.2) and B/Yamagata clades (Y2 and Y3) were identified with no inter-lineage reassortments observed. Over time, the clades/subclades appeared to diversify through the accumulation of amino acid changes along the hemagglutinin (HA) segment backbone, especially within the known antigenic sites. Local outbreak strains appeared to be putatively introduced from both within and outside Africa. Conclusions The congruence of local and global strains in circulating lineages and amino acid changes suggests potential effectiveness of vaccines recommended for the Northern and Southern Hemispheres in East Africa.

BackgroundBetween November 2023 and March 2024, coastal Kenya experienced another wave of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections detected through our continued genomic surveillance. Herein, we report the clinical and genomic epidemiology of SARS-CoV-2 infections from 179 individuals (a total of 185 positive samples) residing in the Kilifi Health and Demographic Surveillance System (KHDSS) area (~ 900 km2).MethodsWe analyzed genetic, clinical, and epidemiological data from SARS-CoV-2 positive cases across pediatric inpatient, health facility outpatient, and homestead community surveillance platforms. Phylogenetic analyses were performed using maximum-likelihood and Bayesian frameworks. Temporal trends were summarized, comparisons conducted using Kruskal–Wallis and Wilcoxon tests, and associations examined using univariate and multivariable logistic regression models.ResultsSixteen SARS-CoV-2 lineages within 3 subvariants [XBB.2.3-like (58.4%), JN.1-like (40.5%), and XBB.1-like (1.1%)] were identified. The symptomatic infection rate was estimated at 16.0% (95% CI, 11.1–23.9%) based on community testing regardless of symptom status and did not differ across the subvariants (p = 0.13). The most common infection symptoms in community cases were cough (49.2%), fever (27.0%), sore throat (7.3%), headache (6.9%), and difficulty in breathing (5.5%). One case succumbed to the infection. Genomic analysis of the virus from serial positive samples confirmed repeat infections among 5 participants under follow-up (median interval 21 days, range 16–95 days); in 4 participants, the same virus lineage was responsible in both episodes, whereas 1 participant had a different lineage in the second compared with the first episode. Phylogenetic analysis including > 18,000 contemporaneous global sequences provided evidence for at least 38 independent virus introduction events into the study area (KHDSS) during the wave, the majority likely originating in North America and Europe.ConclusionsOur study highlights that coastal Kenya, like most other localities, continues to face new SARS-CoV-2 infection waves characterized by circulation of new variants, multiple lineage importations, and reinfections. Locally, the virus may circulate unrecognized, as most infections are asymptomatic in part due to high population immunity after several waves of infection. Our findings highlight the need for sustained SARS-CoV-2 surveillance to inform appropriate public health responses, such as scheduled vaccination for populations at risk of severe infection.

Abstract Background Although 7 human adenovirus (HAdV) species are known to exist, only F (types 40 and 41) and G are identified as diarrheal disease agents. The role of other HAdV species in diarrheal disease remains unclear, and data on their prevalence are limited. We describe HAdV species and types in hospitalized children with diarrhea in coastal Kenya. Methods Three hundred twenty-nine stool samples collected between June 2022 and August 2023 from children aged <13 years were screened for HAdV using quantitative polymerase chain reaction (qPCR). Positive HAdV cases were genotyped by adenovirus primers from the RespiCoV panel by amplification, next-generation sequencing, and phylogenetic analysis. Results Sixty-five samples (20%) tested HadV positive, of which 5 HAdV species were identified. Other than HAdV F, other species included A, B, C, and D; these were detected as either mono-detections or coinfections. Six HAdV F identified by NGS had been missed by our qPCR typing method. This appeared to be as a result of a 133-nucleotide deletion in the long fiber protein, which abrogated a primer and probe binding site. Based on grading of diarrheal disease severity using VESIKARI scores, 93% of the HAdV cases presented with severe disease. One child with an HAdV F infection died. Conclusions Our study shows the enormous diversity and clinical characteristics of HAdV species in children with diarrhea in coastal Kenya. These data offer an opportunity to improve current diagnostic assays and increase knowledge of HAdV in Africa for control of outbreaks in the future.

The COVID-19 pandemic and relevant non-pharmaceutical interventions (NPIs) interrupted the circulation of common respiratory viruses. These viruses demonstrated an unprecedented asynchronous resurgence as NPIs were relaxed. We compiled a global dataset from a systematic review, online surveillance reports and unpublished data from Respiratory Virus Global Epidemiology Network, encompassing 92 sites. We compared the resurgence timings of respiratory viruses within each site and synthesised differences in timings across sites, using a generalised linear mixed-effects model. We revealed a distinct sequential timing in the first post-pandemic resurgence: rhinovirus resurged the earliest, followed by seasonal coronavirus, parainfluenza virus, respiratory syncytial virus, adenovirus, metapneumovirus and influenza A virus, with influenza B virus exhibiting the latest resurgence. Similar sequential timing was observed in the second resurgence except influenza A virus caught up with metapneumovirus. The consistent asynchrony across geographical regions suggests that virus-specific characteristics, rather than location-specific factors, determining the relative timing of resurgence. COVID-19-related non-pharmaceutical interventions impacted the circulation of other pathogens. Here, the authors compile a global viral activity dataset and compare the timing of resurgence of seven common respiratory viruses following the relaxation of interventions across different geographical regions.