Reducing disease burden in an influenza pandemic by targeted delivery of neuraminidase inhibitors: mathematical models in the Australian context

BMC Infectious Diseases

Research Article

Allen C. Cheng¹  Robert Moss²  Jodie McVernon³  James M. McCaw⁴  Aeron C. Hurt⁵ 

[1] Infectious Disease Epidemiology Unit, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia;Infection Prevention and Healthcare Epidemiology Unit, Alfred Health, Melbourne, Australia;Modelling and Simulation Unit Centre for Epidemiology and Biostatistics Melbourne School of Population and Global Health, The University of Melbourne, Level 3, 207 Bouverie St, 3010, Melbourne, Victoria, Australia;Modelling and Simulation Unit Centre for Epidemiology and Biostatistics Melbourne School of Population and Global Health, The University of Melbourne, Level 3, 207 Bouverie St, 3010, Melbourne, Victoria, Australia;Murdoch Childrens Research Institute, Melbourne, Australia;Modelling and Simulation Unit Centre for Epidemiology and Biostatistics Melbourne School of Population and Global Health, The University of Melbourne, Level 3, 207 Bouverie St, 3010, Melbourne, Victoria, Australia;School of Mathematics and Statistics, The University of Melbourne, Melbourne, Australia;Murdoch Childrens Research Institute, Melbourne, Australia;WHO Collaborating Centre for Reference and Research on Influenza, Peter Doherty Institute, Melbourne, Australia;

关键词: Influenza;    Pandemic preparedness;    Neuraminidase inhibitor;    Emergency response;   

DOI  :  10.1186/s12879-016-1866-7

 received in 2016-04-28, accepted in 2016-09-23,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundMany nations maintain stockpiles of neuraminidase inhibitor (NAI) antiviral agents for use in influenza pandemics to reduce transmission and mitigate the course of clinical infection. Pandemic preparedness plans include the use of these stockpiles to deliver proportionate responses, informed by emerging evidence of clinical impact. Recent uncertainty about the effectiveness of NAIs has prompted these nations to reconsider the role of NAIs in pandemic response, with implications for pandemic planning and for NAI stockpile size.MethodsWe combined a dynamic model of influenza epidemiology with a model of the clinical care pathways in the Australian health care system to identify effective NAI strategies for reducing morbidity and mortality in pandemic events, and the stockpile requirements for these strategies. The models were informed by a 2015 assessment of NAI effectiveness against susceptibility, pathogenicity, and transmission of influenza.ResultsLiberal distribution of NAIs for early treatment in outpatient settings yielded the greatest benefits in all of the considered scenarios. Restriction of community-based treatment to risk groups was effective in those groups, but failed to prevent the large proportion of cases arising from lower risk individuals who comprise the majority of the population.ConclusionsThese targeted strategies are only effective if they can be deployed within the constraints of existing health care infrastructure. This finding highlights the critical importance of identifying optimal models of care delivery for effective emergency health care response.

【 授权许可】

CC BY   
© The Author(s) 2016