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1.
J Gen Virol ; 105(11)2024 Nov.
Article in English | MEDLINE | ID: mdl-39485726

ABSTRACT

Highly pathogenic avian influenza (HPAI) poses a substantial threat to several raptors. Between 2021 and 2023, HPAI viruses (HPAIVs) of the Goose/Guangdong lineage H5 clade 2.3.4.4b became widespread in wild birds in Norway, and H5N1 and H5N5 viruses were detected in 31 white-tailed eagles (Haliaeetus albicilla, WTEs). Post-mortem examinations of four WTEs revealed no macroscopic pathological findings. Microscopic examinations showed the presence of myocardial and splenic necroses and a few lesions in the brain. In situ hybridization revealed the presence of the virus in several organs, suggesting a multisystemic infection. The detection of HPAIV H5N5 in a WTE in February 2022 marked the first recorded occurrence of this subtype in Norway. Since then, the virus has persisted, sporadically being detected in WTEs and other wild bird species. Phylogenetic analyses reveal that at least two distinct incursions of HPAIV H5N1 Eurasian (EA) genotype C affected WTEs, likely introduced by migratory birds from Eurasia and seabirds entering from Western and Central Europe. Some WTE isolates from 2021 to 2022 clustered with those from Canada and Ireland, aligning with the transatlantic spread of H5N1. Others were related to the 2021 mass mortality of great skuas in the UK or outbreaks in seabird populations, including gannets, gulls and terns, during 2022 in the North Sea region. This suggests that the WTEs were likely preying on the affected birds. Our study highlights that WTEs can act as sentinels for some HPAIV strains, but the absence of several known circulating genotypes in WTEs suggests varying pathogenic effects on this species.


Subject(s)
Eagles , Influenza A Virus, H5N1 Subtype , Influenza in Birds , Phylogeny , Animals , Influenza in Birds/virology , Influenza in Birds/epidemiology , Influenza A Virus, H5N1 Subtype/genetics , Influenza A Virus, H5N1 Subtype/isolation & purification , Influenza A Virus, H5N1 Subtype/classification , Influenza A Virus, H5N1 Subtype/pathogenicity , Norway/epidemiology , Eagles/virology , Animals, Wild/virology , Influenza A virus/genetics , Influenza A virus/classification , Influenza A virus/isolation & purification , Influenza A virus/pathogenicity , Genotype
2.
Euro Surveill ; 27(35)2022 09.
Article in English | MEDLINE | ID: mdl-36052721

ABSTRACT

BackgroundUnderlying conditions are risk factors for severe COVID-19 outcomes but evidence is limited about how risks differ with age.AimWe sought to estimate age-specific associations between underlying conditions and hospitalisation, death and in-hospital death among COVID-19 cases.MethodsWe analysed case-based COVID-19 data submitted to The European Surveillance System between 2 June and 13 December 2020 by nine European countries. Eleven underlying conditions among cases with only one condition and the number of underlying conditions among multimorbid cases were used as exposures. Adjusted odds ratios (aOR) were estimated using 39 different age-adjusted and age-interaction multivariable logistic regression models, with marginal means from the latter used to estimate probabilities of severe outcome for each condition-age group combination.ResultsCancer, cardiac disorder, diabetes, immunodeficiency, kidney, liver and lung disease, neurological disorders and obesity were associated with elevated risk (aOR: 1.5-5.6) of hospitalisation and death, after controlling for age, sex, reporting period and country. As age increased, age-specific aOR were lower and predicted probabilities higher. However, for some conditions, predicted probabilities were at least as high in younger individuals with the condition as in older cases without it. In multimorbid patients, the aOR for severe disease increased with number of conditions for all outcomes and in all age groups.ConclusionWhile supporting age-based vaccine roll-out, our findings could inform a more nuanced, age- and condition-specific approach to vaccine prioritisation. This is relevant as countries consider vaccination of younger people, boosters and dosing intervals in response to vaccine escape variants.


Subject(s)
COVID-19 , Age Factors , Aged , Hospital Mortality , Hospitalization , Humans , SARS-CoV-2
3.
Euro Surveill ; 25(26)2020 07.
Article in English | MEDLINE | ID: mdl-32643601

ABSTRACT

A remarkable excess mortality has coincided with the COVID-19 pandemic in Europe. We present preliminary pooled estimates of all-cause mortality for 24 European countries/federal states participating in the European monitoring of excess mortality for public health action (EuroMOMO) network, for the period March-April 2020. Excess mortality particularly affected ≥ 65 year olds (91% of all excess deaths), but also 45-64 (8%) and 15-44 year olds (1%). No excess mortality was observed in 0-14 year olds.


Subject(s)
Cause of Death/trends , Coronavirus Infections/mortality , Coronavirus/isolation & purification , Influenza, Human/mortality , Pneumonia, Viral/mortality , Adolescent , Adult , Age Distribution , Aged , Aged, 80 and over , Betacoronavirus , COVID-19 , Child , Child, Preschool , Coronavirus Infections/diagnosis , Disease Outbreaks , Europe/epidemiology , Female , Humans , Infant , Infant, Newborn , Influenza, Human/diagnosis , Male , Middle Aged , Mortality/trends , Pandemics , Pneumonia, Viral/diagnosis , Population Surveillance , Preliminary Data , SARS-CoV-2 , Young Adult
4.
Tidsskr Nor Laegeforen ; 140(18)2020 12 15.
Article in English, Norwegian | MEDLINE | ID: mdl-33322870

ABSTRACT

BACKGROUND: Three different data sources exist for monitoring COVID-19-associated hospitalisations in Norway: The Directorate of Health, the Norwegian Intensive Care and Pandemic Registry (NIPaR), and the linking of the Norwegian Patient Registry (NPR) and the Norwegian Surveillance System for Communicable Diseases (MSIS). A comparison of results from different data sources is important to increase understanding of the data and to further optimise current and future surveillance. We compared results from the three data sources from March to June 2020. MATERIAL AND METHOD: We analysed the number of new admissions, as well as the total number of hospitalised patients and those on ventilatory support, reported per day and by regional health authority. The analysis was descriptive. RESULTS: The cumulative number of new admissions according to NPR-MSIS (n=1260) was higher than NIPaR (n=1153). The discrepancy was high early in the epidemic (93 as of 29 March). The trend in the number of hospitalised patients was similar for all three sources throughout the study period. NPR-MSIS overestimated the number of hospitalised patients on ventilatory support. INTERPRETATION: The discrepancy in new admissions between NIPaR and NPR-MSIS is primarily due to missing registrations for some patients admitted before NIPaR became operational. Basic information retrieved daily by the Directorate of Health give comparable results to more comprehensive daily information retrieval undertaken in NIPaR and NPR-MSIS, adjusted retrospectively. Further analysis is necessary regarding whether NIPaR and NPR-MSIS provide timely data and function as required in an emergency preparedness situation.


Subject(s)
COVID-19/epidemiology , Hospitalization , Information Storage and Retrieval , Humans , Norway/epidemiology , Retrospective Studies
5.
Tidsskr Nor Laegeforen ; 140(18)2020 12 15.
Article in English, Norwegian | MEDLINE | ID: mdl-33322882

ABSTRACT

BACKGROUND: The first case of SARS-CoV-2 infection in Norway was confirmed on 26 February 2020. Following sharpened advice on general infection control measures at the beginning of the outbreak, extensive national control measures were implemented on 12 March, and testing was focused on those with severe illness. We describe the first six weeks of the outbreak in Norway, viewed in light of testing criteria and control measures. MATERIAL AND METHOD: We described all laboratory-confirmed cases of COVID-19 reported to three different surveillance systems under the Norwegian Institute of Public Health up to 5 April 2020, and compared cases reported up to 12 March with those reported from 13 March. RESULTS: By 12 March, 1 128 cases had been reported. Their median age was 47 years, 64 % were male, 66 % had travelled abroad, 6 % were hospitalised at the time of reporting, and < 1 % had died. The median age of the 4 742 cases reported from 13 March was 48 years, 47 % were male, 18 % had travelled abroad, 15 % were hospitalised, and 3 % died. INTERPETATION: The distribution of COVID-19 cases before and after 12 March reflects different phases of the outbreak. However, findings must be interpreted in the light of criteria for testing, testing activity, control measures and characteristics of surveillance systems.


Subject(s)
COVID-19/epidemiology , Pandemics , Female , Humans , Male , Middle Aged , Norway/epidemiology , SARS-CoV-2
6.
Euro Surveill ; 22(14)2017 Apr 06.
Article in English | MEDLINE | ID: mdl-28424146

ABSTRACT

Since December 2016, excess all-cause mortality was observed in many European countries, especially among people aged ≥ 65 years. We estimated all-cause and influenza-attributable mortality in 19 European countries/regions. Excess mortality was primarily explained by circulation of influenza virus A(H3N2). Cold weather snaps contributed in some countries. The pattern was similar to the last major influenza A(H3N2) season in 2014/15 in Europe, although starting earlier in line with the early influenza season start.


Subject(s)
Influenza, Human/mortality , Mortality , Seasons , Adolescent , Adult , Aged , Cause of Death , Child , Child, Preschool , Europe , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Public Health , Sentinel Surveillance , Young Adult
8.
Virol J ; 10: 112, 2013 Apr 10.
Article in English | MEDLINE | ID: mdl-23575317

ABSTRACT

BACKGROUND: Wild aquatic birds constitute the natural reservoir for avian influenza viruses (AIVs). Separate Eurasian and American AIV gene pools exist. Here, the prevalence and diversity of AIVs in gulls and dabbling ducks in Norway were described. The influence of host species and temporal changes on AIV prevalence was examined. Five AIVs from Norway, including three from common gull (Larus canus), were analyzed along with 10 available AIV genomes from gulls in Eurasia to search for evidence of intracontinental and intercontinental reassortment of gene segments encoding the internal viral proteins. METHODS: Swabs collected from 2417 dabbling ducks and gulls in the south-west of Norway during five ordinary hunting seasons (August-December) in the period 2005-2010 were analyzed for presence of AIV. Multivariate linear regression was used to identify associations between AIV prevalence, host species and sampling time. Five AIVs from mallard (Anas platyrhynchos) (H3N8, H9N2) and common gull (H6N8, H13N2, H16N3) were full-length characterized and phylogenetically analyzed together with GenBank reference sequences. RESULTS: Low pathogenic AIVs were detected in 15.5% (CI: 14.1-17.0) of the samples. The overall AIV prevalence was lower in December compared to that found in August to November (p = 0.003). AIV was detected in 18.7% (CI: 16.8-20.6) of the dabbling ducks. A high AIV prevalence of 7.8% (CI; 5.9-10.0) was found in gulls. A similar temporal pattern in AIV prevalence was found in both bird groups. Thirteen hemagglutinin and eight neuraminidase subtypes were detected. No evidence of intercontinental reassortment was found. Eurasian avian (non H13 and H16) PB2 or PA genes were identified in five reference Eurasian gull (H13 and H16) AIV genomes from GenBank. The NA gene from the Norwegian H13N2 gull isolate was of Eurasian avian origin. CONCLUSIONS: The similar temporal pattern in AIV prevalence found in dabbling ducks and gulls, the relatively high virus prevalence detected in gulls and the evidence of intracontinental reassortment in AIVs from gulls indicate that gulls that interact with dabbling ducks are likely to be mixing vessels for AIVs from waterfowl and gulls. Our results support that intercontinental reassortment is rare in AIVs from gulls in Eurasia.


Subject(s)
Genetic Variation , Influenza A virus/classification , Influenza A virus/genetics , Influenza in Birds/epidemiology , Influenza in Birds/virology , Animals , Charadriiformes , Cluster Analysis , Ducks , Influenza A virus/isolation & purification , Molecular Epidemiology , Norway/epidemiology , Phylogeny , Prevalence , RNA, Viral/genetics , Sequence Analysis, DNA
9.
Front Microbiol ; 13: 973257, 2022.
Article in English | MEDLINE | ID: mdl-36106084

ABSTRACT

Invasive Haemophilus influenzae (Hi) disease has decreased in countries that included Hi type b (Hib) vaccination in their childhood immunization programs in the 1990s. Non-typeable (NT) and non-b strains are now the leading causes of invasive Hi disease in Europe, with most cases reported in young children and the elderly. Concerningly, no vaccines toward such strains are available and beta-lactam resistance is increasing. We describe the epidemiology of invasive Hi disease reported to the Norwegian Surveillance System for Communicable Diseases (MSIS) (2017-2021, n = 407). Whole-genome sequencing (WGS) was performed on 245 isolates. We investigated the molecular epidemiology (core genome phylogeny) and the presence of antibiotic resistance markers (including chromosomal mutations associated with beta-lactam or quinolone resistance). For isolates characterized with both WGS and phenotypic antibiotic susceptibility testing (AST) (n = 113) we assessed correlation between resistance markers and susceptibility categorization by calculation of sensitivity, specificity, and predictive values. Incidence rates of invasive Hi disease in Norway ranged from 0.7 to 2.3 per 100,000 inhabitants/year (mean 1.5 per 100,000) and declined during the COVID-19 pandemic. The bacterial population consisted of two major phylogenetic groups with subclustering by serotype and multi-locus sequence type (ST). NTHi accounted for 71.8% (176). The distribution of STs was in line with previous European reports. We identified 13 clusters, including four encapsulated and three previously described international NTHi clones with bla TEM-1 (ST103) or altered PBP3 (rPBP3) (ST14/IIA and ST367/IIA). Resistance markers were detected in 25.3% (62/245) of the isolates, with bla TEM-1 (31, 50.0%) and rPBP3 (28, 45.2%) being the most frequent. All isolates categorized as resistant to aminopenicillins, tetracycline or chloramphenicol possessed relevant resistance markers, and the absence of relevant substitutions in PBP3 and GyrA/ParC predicted susceptibility to cefotaxime, ceftriaxone, meropenem and quinolones. Among the 132 WGS-only isolates, one isolate had PBP3 substitutions associated with resistance to third-generation cephalosporins, and one isolate had GyrA/ParC alterations associated with quinolone resistance. The detection of international virulent and resistant NTHi clones underlines the need for a global molecular surveillance system. WGS is a useful supplement to AST and should be performed on all invasive isolates.

10.
Avian Dis ; 55(4): 680-5, 2011 Dec.
Article in English | MEDLINE | ID: mdl-22312991

ABSTRACT

The infectivity, transmission, and pathogenicity potential of avian influenza virus (AIV) subtype H16N3, isolated from the European herring gull (Larus argentatus), was examined in chickens. Nineteen 6-wk-old commercial Lohmann white chickens were inoculated intranasally with 1 x 10(6) 50% egg infectious dose and clinical signs, humoral immune response, virus shedding, virus transmission, and pathologic changes in the respiratory tract were studied. Oropharyngeal and cloacal swabs were collected for viral RNA detection by real-time reverse transcriptase-PCR (rRT-PCR). Sera were collected and examined for H16-specific antibodies using a hemagglutination inhibition test. Tissue samples from the nasal cavity, trachea, and lung were collected at postmortem examination for histopathology and viral RNA detection by rRT-PCR. In one bird, bilateral serous nasal discharge was observed at 2 days postinoculation (DPI) and viral RNA was detected in oropharyngeal swabs at 2 and 4 DPI. Viral RNA was also detected from the oropharynx of an additional bird at 5 DPI. Moreover, H16-specific antibodies were detected in sera from these two birds at 14 and 21 DPI. No viral RNA was detected from cloacal swabs, and no virus transmission between virus-inoculated chickens and noninoculated contact chickens was observed. Tissue samples from the nasal cavity, trachea and lung were negative for viral RNA and no gross or histopathologic lesions were observed in the virus-inoculated birds. These results indicate that gull-derived AIV subtype H16N3 causes only limited infection in chickens under experimental conditions.


Subject(s)
Charadriiformes , Chickens , Influenza A virus/pathogenicity , Influenza in Birds/virology , Animals , Female , Influenza A virus/classification , Phylogeny , Virulence
11.
PLoS One ; 8(4): e63270, 2013.
Article in English | MEDLINE | ID: mdl-23646204

ABSTRACT

Gulls are the primary hosts of H13 and H16 avian influenza viruses (AIVs). The molecular basis for this host restriction is only partially understood. In this study, amino acid sequences from Eurasian gull H13 and H16 AIVs and Eurasian AIVs (non H13 and H16) were compared to determine if specific signatures are present only in the internal proteins of H13 and H16 AIVs, using a bioinformatics approach. Amino acids identified in an initial analysis performed on 15 selected sequences were checked against a comprehensive set of AIV sequences retrieved from Genbank to verify them as H13 and H16 specific signatures. Analysis of protein similarities and prediction of subcellular localization signals were performed to search for possible functions associated with the confirmed signatures. H13 and H16 AIV specific signatures were found in all the internal proteins examined, but most were found in the non-structural protein 1 (NS1) and in the nucleoprotein. A putative functional signature was predicted to be present in the nuclear export protein. Moreover, it was predicted that the NS1 of H13 and H16 AIVs lack one of the nuclear localization signals present in NS1 of other AIV subtypes. These findings suggest that the signatures found in the internal proteins of H13 and H16 viruses are possibly related to host restriction.


Subject(s)
Host Specificity , Influenza A virus/physiology , Amino Acid Sequence , Animals , Birds , Charadriiformes , Computational Biology , Computer Simulation , Genome, Viral , Genomics , Influenza A virus/classification , Viral Proteins/chemistry , Viral Proteins/genetics , Viral Tropism
12.
Theriogenology ; 75(5): 911-9, 2011 Mar 15.
Article in English | MEDLINE | ID: mdl-21196028

ABSTRACT

Despite the long history of purebred dogs and the large number of existing breeds, few studies of canine litter size based upon a large number of breeds exist. Previous studies are either old or include only one or a few selected breeds. The aim of this large-scale retrospective study was to estimate the mean litter size in a large population of purebred dogs and to describe some factors that might influence the litter size. A total of 10,810 litters of 224 breeds registered in the Norwegian Kennel Club from 2006 to 2007 were included in the study. The overall mean litter size at birth was 5.4 (± 0.025). A generalized linear mixed model with a random intercept for breed revealed that the litter size was significantly influenced by the size of the breed, the method of mating and the age of the bitch. A significant interaction between breed size and age was detected, in that the expected number of puppies born decreased more for older bitches of large breeds. Mean litter size increased with breed size, from 3.5 (± 0.04) puppies in miniature breeds to 7.1 (± 0.13) puppies in giant breeds. No effect on litter size was found for the season of birth or the parity of the bitch. The large number of breeds and the detail of the registered information on the litters in this study are unique. In conclusion, the size of the breed, the age of the bitch and the method of mating were found to influence litter size in purebred dogs when controlling for breed, with the size of the breed as the strongest determinant.


Subject(s)
Breeding , Dogs/physiology , Litter Size , Age Factors , Animals , Body Size , Breeding/methods , Female , Insemination, Artificial/veterinary , Pregnancy , Retrospective Studies , Seasons , Species Specificity
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