Source attribution of campylobacteriosis in Australia, 2017-2019
| dc.contributor.author | McLure, Angus | |
| dc.contributor.author | Smith, James J. | |
| dc.contributor.author | Firestone, Simon | |
| dc.contributor.author | Kirk, Martyn | |
| dc.contributor.author | French, Nigel | |
| dc.contributor.author | Fearnley, Emily | |
| dc.contributor.author | Wallace, Rhiannon | |
| dc.contributor.author | Valcanis, Mary | |
| dc.contributor.author | Bulach, Dieter | |
| dc.contributor.author | Moffatt, Cameron | |
| dc.contributor.author | Selvey, Linda | |
| dc.contributor.author | Jennison, Amy V. | |
| dc.contributor.author | Cribb, Dani | |
| dc.contributor.author | Glass, Katie | |
| dc.date.accessioned | 2024-07-14T23:45:01Z | |
| dc.date.available | 2024-07-14T23:45:01Z | |
| dc.date.issued | 2023 | |
| dc.date.updated | 2024-05-19T08:17:04Z | |
| dc.description.abstract | Campylobacter jejuni and Campylobacter coli infections are the leading cause of foodborne gastroenteritis in high-income countries. Campylobacter colonizes a variety of warm-blooded hosts that are reservoirs for human campylobacteriosis. The proportions of Australian cases attributable to different animal reservoirs are unknown but can be estimated by comparing the frequency of different sequence types in cases and reservoirs. Campylobacter isolates were obtained from notified human cases and raw meat and offal from the major livestock in Australia between 2017 and 2019. Isolates were typed using multi-locus sequence genotyping. We used Bayesian source attribution models including the asymmetric island model, the modified Hald model, and their generalizations. Some models included an “unsampled” source to estimate the proportion of cases attributable to wild, feral, or domestic animal reservoirs not sampled in our study. Model fits were compared using the Watanabe–Akaike information criterion. We included 612 food and 710 human case isolates. The best fitting models attributed >80% of Campylobacter cases to chickens, with a greater proportion of C. coli (>84%) than C. jejuni (>77%). The best fitting model that included an unsampled source attributed 14% (95% credible interval [CrI]: 0.3%–32%) to the unsampled source and only 2% to ruminants (95% CrI: 0.3%–12%) and 2% to pigs (95% CrI: 0.2%–11%) The best fitting model that did not include an unsampled source attributed 12% to ruminants (95% CrI: 1.3%–33%) and 6% to pigs (95% CrI: 1.1%–19%). Chickens were the leading source of human Campylobacter infections in Australia in 2017–2019 and should remain the focus of interventions to reduce burden. | |
| dc.description.sponsorship | Agrifutures Australia; ACT Health; Department of Health, Australian Government; Food Standards Australia New Zealand; Queensland Health; New South Wales Food Authority | |
| dc.format.mimetype | application/pdf | en_AU |
| dc.identifier.issn | 0272-4332 | |
| dc.identifier.uri | https://hdl.handle.net/1885/733713873 | |
| dc.language.iso | en_AU | en_AU |
| dc.provenance | This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium,provided the original work is properly cited and is not used for commercial purposes | |
| dc.publisher | Blackwell Publishing Ltd | |
| dc.relation | http://purl.org/au-research/grants/nhmrc/1116294 | |
| dc.relation | http://purl.org/au-research/grants/nhmrc/145997 | |
| dc.relation | http://purl.org/au-research/grants/arc/ DP180100246 | |
| dc.rights | © 2023 The authors | |
| dc.rights.license | Creative Commons Attribution licence | |
| dc.rights.uri | http://creativecommons.org/licenses/ by-nc/4.0/ | |
| dc.source | Risk Analysis | |
| dc.subject | Bayesian analysis | |
| dc.subject | Campylobacter | |
| dc.subject | source attribution | |
| dc.title | Source attribution of campylobacteriosis in Australia, 2017-2019 | |
| dc.type | Journal article | |
| dcterms.accessRights | Open Access | |
| local.bibliographicCitation.issue | 12 | |
| local.bibliographicCitation.lastpage | 2548 | |
| local.bibliographicCitation.startpage | 2527 | |
| local.contributor.affiliation | McLure, Angus, College of Health and Medicine, ANU | |
| local.contributor.affiliation | Smith, James J., Queensland University of Technology | |
| local.contributor.affiliation | Firestone, Simon, University of Melbourne | |
| local.contributor.affiliation | Kirk, Martyn, College of Health and Medicine, ANU | |
| local.contributor.affiliation | French, Nigel, Massey University | |
| local.contributor.affiliation | Fearnley, Emily, South Australia Health | |
| local.contributor.affiliation | Wallace, Rhiannon, Agassiz Research and Development Centre | |
| local.contributor.affiliation | Valcanis, Mary, University of Melbourne | |
| local.contributor.affiliation | Bulach, Dieter, University of Melbourne | |
| local.contributor.affiliation | Moffatt, Cameron, College of Health and Medicine, ANU | |
| local.contributor.affiliation | Selvey, Linda, The University of Queensland | |
| local.contributor.affiliation | Jennison, Amy V., Queensland Health | |
| local.contributor.affiliation | Cribb, Dani, College of Health and Medicine, ANU | |
| local.contributor.affiliation | Glass, Katie, College of Health and Medicine, ANU | |
| local.contributor.authoruid | McLure, Angus, u4859599 | |
| local.contributor.authoruid | Kirk, Martyn, u3853379 | |
| local.contributor.authoruid | Moffatt, Cameron, u4170813 | |
| local.contributor.authoruid | Cribb, Dani, u5348216 | |
| local.contributor.authoruid | Glass, Katie, u4053649 | |
| local.description.notes | Imported from ARIES | |
| local.identifier.absfor | 420205 - Epidemiological modelling | |
| local.identifier.ariespublication | a383154xPUB41221 | |
| local.identifier.citationvolume | 43 | |
| local.identifier.doi | 10.1111/risa.14138 | |
| local.identifier.scopusID | 2-s2.0-85152271058 | |
| local.publisher.url | https://onlinelibrary.wiley.com/ | |
| local.type.status | Published Version |
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