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Using surveillance data for early warning modelling of highly pathogenic avian influenza in Europe reveals a seasonal shift in transmission, 2016-2022.

ABSTRACT: Avian influenza in wild birds and poultry flocks constitutes a problem for animal welfare, food security and public health. In recent years there have been increasing numbers of outbreaks in Europe, with many poultry flocks culled after being infected with highly pathogenic avian influenza (HPAI). Continuous monitoring is crucial to enable timely implementation of control to prevent HPAI spread from wild birds to poultry and between poultry flocks within a country. We here utilize readily available public surveillance data and time-series models to predict HPAI detections within European countries and show a seasonal shift that happened during 2021-2022. The output is models capable of monitoring the weekly risk of HPAI outbreaks, to support decision making.

SUBMITTER: Jung Kjær L

PROVIDER: S-EPMC10505205 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Using surveillance data for early warning modelling of highly pathogenic avian influenza in Europe reveals a seasonal shift in transmission, 2016-2022.

Jung Kjær Lene L Ward Michael P MP Boklund Anette Ella AE Larsen Lars Erik LE Hjulsager Charlotte Kristiane CK Kirkeby Carsten Thure CT

Scientific reports 20230916 1

Avian influenza in wild birds and poultry flocks constitutes a problem for animal welfare, food security and public health. In recent years there have been increasing numbers of outbreaks in Europe, with many poultry flocks culled after being infected with highly pathogenic avian influenza (HPAI). Continuous monitoring is crucial to enable timely implementation of control to prevent HPAI spread from wild birds to poultry and between poultry flocks within a country. We here utilize readily availa ...[more]

PMID: 37717056

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Project description:ObjectivesThis study aimed to identify the aetiological spectrum, seasonal distribution and antimicrobial resistance patterns of diarrhoeal diseases in Bhutan.Study design and settingThe study used a cross-sectional, retrospective analysis of secondary data gathered through a passive, hospital-based sentinel surveillance for diarrhoeal disease across 12 hospitals, representing Bhutan's demographically diverse regions.ParticipantsA total of 3429 participants' data of all age groups who presented with diarrhoea at sentinel hospitals between 1 January 1 2016 and 31 December 2022 were analysed.ResultsDiarrhoeagenic Escherichia coli (DEC), Shigella, Salmonella and Aeromonas spp. were predominant bacterial pathogens, while Rotavirus, Astrovirus and Norovirus were the leading viral pathogens. Coinfections were observed in 195 cases. Children under nine were significantly affected than the other age groups. Seasonal trends revealed that bacterial pathogen incidence peaked during the summer/monsoon season, viral pathogens were more common in winter and spring, and parasites persisted year-round. Among the antibiotics tested, gentamicin, chloramphenicol, ceftriaxone and tetracycline exhibited high efficacy, with susceptibility rates of 93.4%, 87.2%, 81.5% and 69.5%, respectively. Conversely, high resistance rates were observed for amoxicillin (80.3%), ampicillin (77.4%) and nalidixic acid (69.5%). Multidrug resistance was prevalent, with β-lactamase production contributing to resistance rates of 80.7% to penicillin and 65.4% to fluoroquinolones groups. Cephalosporin resistance was also notable, with rates of 34.4% for cephalexin, 40.0% for cefazolin and 16.9% for ceftriaxone.ConclusionsDEC and Rotavirus were identified as the leading causes of diarrhoea, with significant resistance patterns observed in common bacterial isolates. These findings underscore the need for DEC screening in paediatric cases and emphasise the need for sustained antimicrobial resistance surveillance.

Dataset Information

Using surveillance data for early warning modelling of highly pathogenic avian influenza in Europe reveals a seasonal shift in transmission, 2016-2022.

Publications

Using surveillance data for early warning modelling of highly pathogenic avian influenza in Europe reveals a seasonal shift in transmission, 2016-2022.

Similar Datasets

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