RESUMEN
A systematic surveillance against influenza A viruses (IAVs) in the Suidae population is essential, considering their role as IAV mixing vessels. However, the viral circulation in wild Sus scrofa species is poorly investigated in comparison to the knowledge of IAV infection dynamics in domestic pigs. This study investigated the circulation and the genetic diversity of wild boars' IAVs detected in the Emilia-Romagna region (2017-2022). A total of 4605 lung samples were screened via an M gene real-time RT-PCR for SwIAV; positive samples were subtyped by multiplex RT-PCR, and viral isolation was attempted. Isolated strains (3 out of the 17 positives) were fully sequenced to evaluate viral genotypic diversity. H1N1 was the most frequently detected subtype, with identification of H1pdm09N1 and H1avN1. Whole-genome phylogenetic analysis revealed SwIAVs belonging to different genotypes, with different genetic combinations, and highlighted the simultaneous circulation of the same genotypes in both pigs and wild boars, supporting the hypothesis of SwIAV spillover events at the wildlife-livestock interface. This study represents an update on the wild boar SwIAV Italian situation, and the strains' complete genome analysis showed an evolving and interesting situation that deserves further investigation.
RESUMEN
Swine play an important role in the ecology of influenza A viruses (IAVs), acting as mixing vessels. Swine (sw) IAVs of H1N1 (including H1N1pdm09), H3N2, and H1N2 subtypes are enzootic in pigs globally, with different geographic distributions. This study investigated the genetic diversity of swIAVs detected during passive surveillance of pig farms in Northern Italy between 2017 and 2020. A total of 672 samples, IAV-positive according to RT-PCR, were subtyped by multiplex RT-PCR. A selection of strains was fully sequenced. High genotypic diversity was detected among the H1N1 and H1N2 strains, while the H3N2 strains showed a stable genetic pattern. The hemagglutinin of the H1Nx swIAVs belonged to HA-1A, HA-1B, and HA-1C lineages. Increasing variability was found in HA-1C strains with the circulation of HA-1C.2, HA-1C.2.1 and HA-1C.2.2 sublineages. Amino acid deletions in the HA-1C receptor binding site were observed and antigenic drift was confirmed. HA-1B strains were mostly represented by the Δ146-147 Italian lineage HA-1B.1.2.2, in combination with the 1990s human-derived NA gene. One antigenic variant cluster in HA-1A strains was identified in 2020. SwIAV circulation in pigs must be monitored continuously since the IAVs' evolution could generate strains with zoonotic potential.
Asunto(s)
Análisis de Datos , Variación Genética , Virus de la Influenza A/genética , Infecciones por Orthomyxoviridae/virología , Enfermedades de los Porcinos/virología , Animales , Variación Antigénica , Evolución Molecular , Granjas , Genotipo , Glicoproteínas Hemaglutininas del Virus de la Influenza/genética , Humanos , Subtipo H1N1 del Virus de la Influenza A/genética , Subtipo H1N2 del Virus de la Influenza A/genética , Subtipo H3N2 del Virus de la Influenza A/genética , Italia , PorcinosRESUMEN
OBJECTIVES: To measure the reliability and predictive validity of a four-level triage system (I-4L). METHODS: This observational study was conducted in an urban hospital. Five nurses were randomly selected to assign a triage level to 246 paper scenarios, using the I-4L model. The I-4L model is a four-level triage system: urgency category (UC) 1 requires immediate response; UCs 2, 3 and 4 require assessment within 20, 60 and 120 min, respectively. Weighted kappa statistics were used to measure the inter-rater and intrarater reliability of the triage tool and the validity of the model was assessed based on the accuracy in predicting admission and in predicting a reference standard's triage code. RESULTS: The I-4L model's inter-rater reliability was kappa=0.73 (95% CI 0.67 to 0.79), and the intrarater reliability was kappa=0.82 (95% CI 0.67 to 0.96). Its accuracy of triage rating for admission and for prediction of a reference standard's triage code was good: 79% (95% CI 73% to 86%) and 93% (95% CI 89% to 96%), respectively. The percentages of patients admitted per triage level using the I-4L model was: 100% UC 1; 42% UC 2; 6% UC 3; and 2% UC 4. CONCLUSIONS: The I-4L triage model shows a good inter-rater and intrarater reliability for rating triage acuity and for accuracy in patient admission and prediction of a reference standard's triage code.