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  • 1. Afset, J. E.
    et al.
    Larssen, K. W.
    Bergh, K.
    Larkeryd, A.
    Sjodin, A.
    Johansson, Anders
    Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS). Umeå University, Faculty of Medicine, Department of Clinical Microbiology, Clinical Bacteriology.
    Forsman, M.
    Phylogeographical pattern of Francisella tularensis in a nationwide outbreak of tularaemia in Norway, 20112015In: Eurosurveillance, ISSN 1025-496X, E-ISSN 1560-7917, Vol. 20, no 19, p. 9-14, article id 21125Article in journal (Refereed)
    Abstract [en]

    In 2011, a nationwide outbreak of tularaemia occurred in Norway with 180 recorded cases. It was associated with the largest peak in lemming density seen in 40 years. Francisella tularensis was isolated from 18 patients. To study the geographical distribution of F. tularensis genotypes in Norway and correlate genotype with epidemiology and clinical presentation, we performed whole genome sequencing of patient isolates. All 18 genomes from the outbreak carried genetic signatures of F. tularensis subsp. holarctica and were assigned to genetic clades using canonical single nucleotide polymorphisms. Ten isolates were assigned to major genetic clade B.6 (subclade B.7), seven to clade B.12, and one to clade B.4. The B.6 subclade B.7 was most common in southern and central Norway, while clade B.12 was evenly distributed between the southern, central and northern parts of the country. There was no association between genotype and clinical presentation of tularaemia, time of year or specimen type. We found extensive sequence similarity with F. tularensis subsp. holarctica genomes from high-endemic tularaemia areas in Sweden. Finding nearly identical genomes across large geographical distances in Norway and Sweden imply a life cycle of the bacterium without replication between the outbreaks and raise new questions about long-range migration mechanisms.

  • 2. Karadenizli, A.
    et al.
    Forsman, M.
    Simsek, H.
    Taner, M.
    Ohrman, C.
    Myrtennas, K.
    Larkeryd, A.
    Johansson, Anders
    Umeå University, Faculty of Medicine, Department of Clinical Microbiology. Umeå University, Faculty of Medicine, Molecular Infection Medicine Sweden (MIMS).
    Ozdemir, L.
    Sjodin, A.
    Genomic analyses of Francisella tularensis strains confirm disease transmission from drinking water sources, Turkey, 2008, 2009 and 20122015In: Eurosurveillance, ISSN 1025-496X, E-ISSN 1560-7917, Vol. 20, no 21Article in journal (Refereed)
    Abstract [en]

    Waterborne epidemics of tularaemia caused by Francisella tularensis are increasingly reported in Turkey. We have used whole genome sequencing to investigate if F. tularensis isolated from patients could be traced back to drinking water sources. Tonsil swabs from 33 patients diagnosed with oropharyngeal tularaemia in three outbreaks and 140 water specimens were analysed. F. tularensis subsp. holarctica was confirmed by microagglutination and PCR in 12 patients and five water specimens. Genomic analysis of three pairs of patient and water isolates from outbreaks in Sivas, Corum, and Kocaeli showed the isolates to belong to two new clusters of the F. tularensis B. 12 genetic clade. The clusters were defined by 19 and 15 single nucleotide polymorphisms (SNPs) in a multiple alignment based on 507 F. tularensis genomes. One synonymous SNP was chosen as a new canonical SNP (canSNP) for each cluster for future use in diagnostic assays. No SNP was identified between the genomes from the patient-water pair of isolates from Kocaeli, one SNP between the pair of isolates from Sivas, whereas the pair from Corum differed at seven SNPs. These results illustrate the power of whole genome sequencing for tracing F. tularensis patient isolates back to their environmental source.

  • 3.
    Timpka, Toomas
    et al.
    Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
    Spreco, A.
    Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
    Eriksson, O.
    Department of Computer and Information Science, Linköping University, Linköping, Sweden.
    Dahlström, Ö.
    Linnaeus Centre HEAD, Department of Behavioural Sciences, Linköping University, Linköping, Sweden.
    Gursky, E. A.
    National Strategies Support Directorate, ANSER/Analytic Services Inc, Arlington, Virginia, United States of America.
    Strömgren, Magnus
    Umeå University, Faculty of Social Sciences, Department of Geography and Economic History.
    Holm, Einar
    Umeå University, Faculty of Social Sciences, Department of Geography and Economic History.
    Ekberg, J.
    Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
    Hinkula, J.
    Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.
    Nyce, J. M.
    Department of Anthropology, Ball State University, Muncie, Indiana, United States of America.
    Eriksson, H.
    Department of Computer and Information Science, Linköping University, Linköping, Sweden.
    Predictive performance of telenursing complaints in influenza surveillance: a prospective cohort study in Sweden2014In: Eurosurveillance, ISSN 1025-496X, E-ISSN 1560-7917, Vol. 19, no 46, p. 20966-Article in journal (Refereed)
    Abstract [en]

    Syndromic data sources have been sought to improve the timely detection of increased influenza transmission. This study set out to examine the prospective performance of telenursing chief complaints in predicting influenza activity. Data from two influenza seasons (2007/08 and 2008/09) were collected in a Swedish county (population 427,000) to retrospectively determine which grouping of telenursing chief complaints had the largest correlation with influenza case rates. This grouping was prospectively evaluated in the three subsequent seasons. The best performing telenursing complaint grouping in the retrospective algorithm calibration was fever (child, adult) and syncope (r=0.66; p<0.001). In the prospective evaluation, the performance of 14-day predictions was acceptable for the part of the evaluation period including the 2009 influenza pandemic (area under the curve (AUC)=0.84; positive predictive value (PPV)=0.58), while it was strong (AUC=0.89; PPV=0.93) for the remaining evaluation period including only influenza winter seasons. We recommend the use of telenursing complaints for predicting winter influenza seasons. The method requires adjustments when used during pandemics.

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