Implications of a travel connectivity-based approach for infectious disease transmission risks in Oceania
| dc.contributor.author | Cadavid Restrepo, Angela | |
| dc.contributor.author | Furuya-Kanamori, Luis | |
| dc.contributor.author | Mayfield, Helen | |
| dc.contributor.author | Nilles, Eric | |
| dc.contributor.author | Lau, Colleen | |
| dc.date.accessioned | 2024-02-04T22:57:54Z | |
| dc.date.available | 2024-02-04T22:57:54Z | |
| dc.date.issued | 2021 | |
| dc.date.updated | 2022-10-09T07:17:02Z | |
| dc.description.abstract | Introduction The increase in international travel brought about by globalisation has enabled the rapid spread of emerging pathogens with epidemic and pandemic potential. While travel connectivity-based assessments may help understand patterns of travel network-mediated epidemics, such approaches are rarely carried out in sufficient detail for Oceania where air travel is the dominant method of transportation between countries. Design Travel data from the Australian Bureau of Statistics, Stats NZ and the United Nations World Tourism Organization websites were used to calculate travel volumes in 2018 within Oceania and between Oceania and the rest of the world. The Infectious Disease Vulnerability Index (IDVI) was incorporated into the analysis as an indicator of each country’s capacity to contain an outbreak. Travel networks were developed to assess the spread of infectious diseases (1) into and from Oceania, (2) within Oceania and (3) between each of the Pacific Island Countries and Territories (PICTs) and their most connected countries. Results Oceania was highly connected to countries in Asia, Europe and North America. Australia, New Zealand and several PICTs were highly connected to the USA and the UK (least vulnerable countries for outbreaks based on the IDVI), and to China (intermediate low vulnerable country). High variability was also observed between the PICTs in the geographical distribution of their international connections. The PICTs with the highest number of international connections were Fiji, French Polynesia, Guam and Papua New Guinea. Conclusion Travel connectivity assessments may help to accurately stratify the risk of infectious disease importation and outbreaks in countries depending on disease transmission in other parts of the world. This information is essential to track future requirements for scaling up and targeting outbreak surveillance and control strategies in Oceania. | en_AU |
| dc.format.mimetype | application/pdf | en_AU |
| dc.identifier.issn | 2044-6055 | en_AU |
| dc.identifier.uri | http://hdl.handle.net/1885/313121 | |
| dc.language.iso | en_AU | en_AU |
| dc.provenance | This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. | en_AU |
| dc.publisher | BMJ Publishing Group | en_AU |
| dc.relation | http://purl.org/au-research/grants/nhmrc/1193826 | en_AU |
| dc.relation | http://purl.org/au-research/grants/nhmrc/1158469 | en_AU |
| dc.rights | © 2021 The authors | en_AU |
| dc.rights.license | Creative Commons Attribution licence | en_AU |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | en_AU |
| dc.source | BMJ Open | en_AU |
| dc.title | Implications of a travel connectivity-based approach for infectious disease transmission risks in Oceania | en_AU |
| dc.type | Journal article | en_AU |
| dcterms.accessRights | Open Access | en_AU |
| local.bibliographicCitation.issue | 8 | en_AU |
| local.contributor.affiliation | Cadavid Restrepo, Angela, College of Health and Medicine, ANU | en_AU |
| local.contributor.affiliation | Furuya Kanamori, Luis, College of Health and Medicine, ANU | en_AU |
| local.contributor.affiliation | Mayfield, Helen, College of Health and Medicine, ANU | en_AU |
| local.contributor.affiliation | Nilles, Eric, Harvard University | en_AU |
| local.contributor.affiliation | Lau, Colleen, College of Health and Medicine, ANU | en_AU |
| local.contributor.authoruid | Cadavid Restrepo, Angela, u5608765 | en_AU |
| local.contributor.authoruid | Furuya Kanamori, Luis, u5127170 | en_AU |
| local.contributor.authoruid | Mayfield, Helen, u1028048 | en_AU |
| local.contributor.authoruid | Lau, Colleen, u5651486 | en_AU |
| local.description.notes | Imported from ARIES | en_AU |
| local.identifier.absfor | 420200 - Epidemiology | en_AU |
| local.identifier.ariespublication | a383154xPUB21253 | en_AU |
| local.identifier.citationvolume | 11 | en_AU |
| local.identifier.doi | 10.1136/bmjopen-2020-046206 | en_AU |
| local.identifier.scopusID | 2-s2.0-85113138903 | |
| local.identifier.thomsonID | WOS:000686755900022 | |
| local.publisher.url | https://bmjopen.bmj.com/ | en_AU |
| local.type.status | Published Version | en_AU |
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