Dataset Information

A large A(H3N2) influenza outbreak with a high attack rate in a drug user community in Italy, April 2022.

ABSTRACT: Despite the COVID-19 pandemic, influenza remains an important issue. Especially in community settings, influenza outbreaks can be difficult to control and can result in high attack rates. In April 2022, a large A(H3N2) influenza outbreak spread in the largest Italian drug-rehabilitation community. One hundred eighty-four individuals presented influenza-like symptoms (attack rate of 26.2%); 56% previously received the influenza vaccine. Sequence analyses highlighted a genetic drift from the vaccine strain, which may have caused the observed lack of protection.

SUBMITTER: Gori M

PROVIDER: S-EPMC9990381 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A large A(H3N2) influenza outbreak with a high attack rate in a drug user community in Italy, April 2022.

Gori Maria M Fappani Clara C Bianchi Silvia S Canuti Marta M Colzani Daniela D Ottogalli Paolo P Duehren Sarah S Tanzi Elisabetta E Amendola Antonella A Boschini Antonio A

Epidemiology and infection 20230119

Despite the COVID-19 pandemic, influenza remains an important issue. Especially in community settings, influenza outbreaks can be difficult to control and can result in high attack rates. In April 2022, a large A(H3N2) influenza outbreak spread in the largest Italian drug-rehabilitation community. One hundred eighty-four individuals presented influenza-like symptoms (attack rate of 26.2%); 56% previously received the influenza vaccine. Sequence analyses highlighted a genetic drift from the vacci ...[more]

PMID: 36655522

Similar Datasets

Project description:Seroprevalence survey is the most practical method for accurately estimating infection attack rate (IAR) in an epidemic such as influenza. These studies typically entail selecting an arbitrary titer threshold for seropositivity (e.g. microneutralization [MN] 1∶40) and assuming the probability of seropositivity given infection (infection-seropositivity probability, ISP) is 100% or similar to that among clinical cases. We hypothesize that such conventions are not necessarily robust because different thresholds may result in different IAR estimates and serologic responses of clinical cases may not be representative. To illustrate our hypothesis, we used an age-structured transmission model to fully characterize the transmission dynamics and seroprevalence rises of 2009 influenza pandemic A/H1N1 (pdmH1N1) during its first wave in Hong Kong. We estimated that while 99% of pdmH1N1 infections became MN1∶20 seropositive, only 72%, 62%, 58% and 34% of infections among age 3-12, 13-19, 20-29, 30-59 became MN1∶40 seropositive, which was much lower than the 90%-100% observed among clinical cases. The fitted model was consistent with prevailing consensus on pdmH1N1 transmission characteristics (e.g. initial reproductive number of 1.28 and mean generation time of 2.4 days which were within the consensus range), hence our ISP estimates were consistent with the transmission dynamics and temporal buildup of population-level immunity. IAR estimates in influenza seroprevalence studies are sensitive to seropositivity thresholds and ISP adjustments which in current practice are mostly chosen based on conventions instead of systematic criteria. Our results thus highlighted the need for reexamining conventional practice to develop standards for analyzing influenza serologic data (e.g. real-time assessment of bias in ISP adjustments by evaluating the consistency of IAR across multiple thresholds and with mixture models), especially in the context of pandemics when robustness and comparability of IAR estimates are most needed for informing situational awareness and risk assessment. The same principles are broadly applicable for seroprevalence studies of other infectious disease outbreaks.

Project description:AimsTo assess influenza viruses (IVs) circulation and to evaluate A(H3N2) molecular evolution during the 2021-2022 season in Italy.Materials and methods12,393 respiratory specimens (nasopharyngeal swabs or broncho-alveolar lavages) collected from in/outpatients with influenza illness in the period spanning from January 1, 2022 (week 2022-01) to May 31, 2022 (week 2022-22) were analysed to identify IV genome and were molecularly characterized by 12 laboratories throughout Italy. A(H3N2) evolution was studied by conducting an in-depth phylogenetic analysis of the hemagglutinin (HA) gene sequences. The predicted vaccine efficacy (pVE) of vaccine strain against circulating A(H3N2) viruses was estimated using the sequence-based Pepitope model.ResultsThe overall IV-positive rate was 7.2% (894/12,393), all were type A IVs. Almost all influenza A viruses (846/894; 94.6%) were H3N2 that circulated in Italy with a clear epidemic trend, with 10% positivity rate threshold crossed for six consecutive weeks from week 2022-11 to week 2022-16. According to the phylogenetic analysis of a subset of A(H3N2) strains (n=161), the study HA sequences were distributed into five different genetic clusters, all of them belonging to the clade 3C.2a, sub-clade 3C.2a1 and the genetic subgroup 3C.2a1b.2a.2. The selective pressure analysis of A(H3N2) sequences showed evidence of diversifying selection particularly in the amino acid position 156. The comparison between the predicted amino acid sequence of the 2021-2022 vaccine strain (A/Cambodia/e0826360/2020) and the study strains revealed 65 mutations in 59 HA amino acid positions, including the substitution H156S and Y159N in antigenic site B, within major antigenic sites adjacent to the receptor-binding site, suggesting the presence of drifted strains. According to the sequence-based Pepitope model, antigenic site B was the dominant antigenic site and the p(VE) against circulating A(H3N2) viruses was estimated to be -28.9%.Discussion and conclusionAfter a long period of very low IV activity since public health control measures have been introduced to face COVID-19 pandemic, along came A(H3N2) with a new phylogenetic makeup. Although the delayed 2021-2022 influenza season in Italy was characterized by a significant reduction of the width of the epidemic curve and in the intensity of the influenza activity compared to historical data, a marked genetic diversity of the HA of circulating A(H3N2) strains was observed. The identification of the H156S and Y159N substitutions within the main antigenic sites of most HA sequences also suggested the circulation of drifted variants with respect to the 2021-2022 vaccine strain. Molecular surveillance plays a critical role in the influenza surveillance architecture and it has to be strengthened also at local level to timely assess vaccine effectiveness and detect novel strains with potential impact on public health.

Dataset Information

A large A(H3N2) influenza outbreak with a high attack rate in a drug user community in Italy, April 2022.

Publications

A large A(H3N2) influenza outbreak with a high attack rate in a drug user community in Italy, April 2022.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets