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Modelling response strategies for controlling gonorrhoea outbreaks in men who have sex with men in Australia.

Authors :
Duan Q
Carmody C
Donovan B
Guy RJ
Hui BB
Kaldor JM
Lahra MM
Law MG
Lewis DA
Maley M
McGregor S
McNulty A
Selvey C
Templeton DJ
Whiley DM
Regan DG
Wood JG
Source :
PLoS computational biology [PLoS Comput Biol] 2021 Nov 04; Vol. 17 (11), pp. e1009385. Date of Electronic Publication: 2021 Nov 04 (Print Publication: 2021).
Publication Year :
2021

Abstract

The ability to treat gonorrhoea with current first-line drugs is threatened by the global spread of extensively drug resistant (XDR) Neisseria gonorrhoeae (NG) strains. In Australia, urban transmission is high among men who have sex with men (MSM) and importation of an XDR NG strain in this population could result in an epidemic that would be difficult and costly to control. An individual-based, anatomical site-specific mathematical model of NG transmission among Australian MSM was developed and used to evaluate the potential for elimination of an imported NG strain under a range of case-based and population-based test-and-treat strategies. When initiated upon detection of the imported strain, these strategies enhance the probability of elimination and reduce the outbreak size compared with current practice (current testing levels and no contact tracing). The most effective strategies combine testing targeted at regular and casual partners with increased rates of population testing. However, even with the most effective strategies, outbreaks can persist for up to 2 years post-detection. Our simulations suggest that local elimination of imported NG strains can be achieved with high probability using combined case-based and population-based test-and-treat strategies. These strategies may be an effective means of preserving current treatments in the event of wider XDR NG emergence.<br />Competing Interests: The authors have declared that no competing interests exist. Author Christine Selvey was unable to confirm their authorship contributions. On their behalf, the corresponding author has reported their contributions to the best of their knowledge.

Details

Language :
English
ISSN :
1553-7358
Volume :
17
Issue :
11
Database :
MEDLINE
Journal :
PLoS computational biology
Publication Type :
Academic Journal
Accession number :
34735428
Full Text :
https://doi.org/10.1371/journal.pcbi.1009385