Global patterns of seasonal influenza activity, duration of activity and virus (sub)type circulation from 2010 to 2020.

BACKGROUND: Seasonal influenza viruses undergo unpredictable changes, which may lead to antigenic mismatch between circulating and vaccine strains and to a reduced vaccine effectiveness. A continuously updated knowledge of influenza strain circulation and seasonality is essential to optimize the effectiveness of influenza vaccination campaigns. We described the global epidemiology of influenza between the 2009 A(H1N1)p and the 2020 COVID-19 pandemic. METHODS: Influenza virological surveillance data were obtained from the WHO-FluNet database. We determined the median proportion of influenza cases caused by the different influenza virus types, subtypes, and lineages; the typical timing of the epidemic peak; and the median duration of influenza epidemics (applying the annual average percentage method with a 75% threshold). RESULTS: We included over 4.6 million influenza cases from 149 countries. The median proportion of influenza cases caused by type A viruses was 75.5%, highest in the Southern hemisphere (81.6%) and lowest in the intertropical belt (73.0%), and ranged across seasons between 60.9% in 2017 and 88.7% in 2018. Epidemic peaks typically occurred during winter months in Northern and Southern hemisphere countries, while much more variability emerged in tropical countries. Influenza epidemics lasted a median of 25 weeks (range 8-42) in countries lying between 30°N and 26°S, and a median of 9 weeks (range 5-25) in countries outside this latitude range. CONCLUSIONS: This work will establish an important baseline to better understand factors that influence seasonal influenza dynamics and how COVID-19 may have affected seasonal activity and influenza virus types, subtypes, and lineages circulation patterns.

Molecular Evolution and Epidemiological Characteristics of SARS COV-2 in (Northwestern) Poland.

The emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) evolved into a worldwide outbreak, with the first Polish cases in February/March 2020. This study aimed to investigate the molecular epidemiology of the circulating virus lineages between March 2020 and February 2021. We performed variant identification, spike mutation pattern analysis, and phylogenetic and evolutionary analyses for 1106 high-coverage whole-genome sequences, implementing maximum likelihood, multiple continuous-time Markov chain, and Bayesian birth-death skyline models. For time trends, logistic regression was used. In the dataset, virus B.1.221 lineage was predominant (15.37%), followed by B.1.258 (15.01%) and B.1.1.29 (11.48%) strains. Three clades were identified, being responsible for 74.41% of infections over the analyzed period. Expansion in variant diversity was observed since September 2020 with increasing frequency of the number in spike substitutions, mainly H69V70 deletion, P681H, N439K, and S98F. In population dynamics inferences, three periods with exponential increase in infection were observed, beginning in March, July, and September 2020, respectively, and were driven by different virus clades. Additionally, a notable increase in infections caused by the B.1.1.7 lineage since February 2021 was noted. Over time, the virus accumulated mutations related to optimized transmissibility; therefore, faster dissemination is reflected by the second wave of epidemics in Poland.

Dynamics and predisposition of respiratory viral co-infections in children and adults.

OBJECTIVES: The epidemiology of respiratory co-infection pairings is poorly understood. Here we assess the dynamics of respiratory viral co-infections in children and adults and determine predisposition for or against specific viral pairings. METHODS: Over five respiratory seasons from 30 November 2013 through 6 June 2018, the mono-infection and co-infection prevalence of 13 viral pathogens was tabulated at The Cleveland Clinic. Employing a model to proportionally distribute viral pairs using individual virus co-infection rate with prevalence patterns of concurrent co-circulating viruses, we compared predicted occurrence with observed occurrence of 132 viral pairing permutations using binomial analysis. RESULTS: Of 30 535 respiratory samples, 9843 (32.2%) were positive for at least one virus and 1018 (10.8%) of these were co-infected. Co-infected samples predominantly originated from children. Co-infection rate in paediatric population was 35.0% (2068/5906), compared with only 5.8% (270/4591) in adults. Adenovirus C (ADVC) had the highest co-infection rate (426/623, 68.3%) while influenza virus B had the lowest (55/546, 10.0%). ADVC-rhinovirus (HRV), respiratory syncytial virus A (RSVA)-HRV and RSVB-HRV pairings occurred at significantly higher frequencies than predicted by the proportional distribution model (p < 0.05). Additionally, several viral pairings had fewer co-infections than predicted by our model: notably metapneumovirus (hMPV)-parainfluenza virus 3, hMPV-RSVA and RSVA-RSVB. CONCLUSIONS: This is one of the largest studies on respiratory viral co-infections in children and adults. Co-infections are substantially more common in children, especially under 5 years of age, and the most frequent pairings occurred at a higher frequency than would be expected by random. Specific pairings occur at altered rates compared with those predicted by proportional distribution, suggesting either direct or indirect interactions result between specific viral pathogens.