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J Infect Dis. 2016 Mar 15;213(6):883-90. doi: 10.1093/infdis/jiv517. Epub 2015 Oct 30.

Improving Control of Antibiotic-Resistant Gonorrhea by Integrating Research Agendas Across Disciplines: Key Questions Arising From Mathematical Modeling.

Author information

1
Department of Immunology and Infectious Diseases Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard T. H. Chan School of Public Health, and Division of Infectious Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
2
Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard T. H. Chan School of Public Health, and.
3
Department of Immunology and Infectious Diseases Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard T. H. Chan School of Public Health, and.
4
Modelling and Economics Unit, Centre for Infectious Disease Surveillance and Control, Public Health England MRC Centre for Outbreak Analysis and Modelling NIHR Health Protection Research Unit in Modelling Methodology, School of Public Health, Imperial College London, United Kingdom.

Abstract

The rise in gonococcal antibiotic resistance and the threat of untreatable infection are focusing attention on strategies to limit the spread of drug-resistant gonorrhea. Mathematical models provide a framework to link the natural history of infection and patient behavior to epidemiological outcomes and can be used to guide research and enhance the public health impact of interventions. While limited knowledge of key disease parameters and networks of spread has impeded development of operational models of gonococcal transmission, new tools in gonococcal surveillance may provide useful data to aid tracking and modeling. Here, we highlight critical questions in the management of gonorrhea that can be addressed by mathematical models and identify key data needs. Our overarching aim is to articulate a shared agenda across gonococcus-related fields from microbiology to epidemiology that will catalyze a comprehensive evidence-based clinical and public health strategy for management of gonococcal infections and antimicrobial resistance.

KEYWORDS:

Neisseria gonorrhoeae; antibiotic resistance; gonorrhea; immunity; mathematical modeling; sexually transmitted infections; vaccine

PMID:
26518045
PMCID:
PMC4760416
DOI:
10.1093/infdis/jiv517
[Indexed for MEDLINE]
Free PMC Article

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