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Báo cáo y học: " Key transmission parameters of an institutional outbreak during the 1918 influenza pandemic estimated by mathematical modelling"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học quốc tế cung cấp cho các bạn kiến thức về ngành y đề tài: " Key transmission parameters of an institutional outbreak during the 1918 influenza pandemic estimated by mathematical modelling | Theoretical Biology and Medical Modelling BioMed Central Research Key transmission parameters of an institutional outbreak during the 1918 influenza pandemic estimated by mathematical modelling Gabriel Sertsou1 Nick Wilson 1 Michael Baker1 Peter Nelson1 and Mick G Roberts2 Open Access Address Department of Public Health Wellington School of Medicine Health Sciences University of Otago Wellington New Zealand and 2Centre for Mathematical Biology Institute of Information and Mathematical Sciences Massey University Auckland New Zealand Email Gabriel Sertsou - gabriel.sertsou@otago.ac.nz Nick Wilson - nick.wilson@otago.ac.nz Michael Baker - michael.baker@otago.ac.nz Peter Nelson - nelpe060@student.otago.ac.nz Mick G Roberts - m.g.roberts@massey.ac.nz Corresponding author Published 30 November 2006 Received 26 September 2006 Theoretical Biology and Medical Modelling 2006 3 38 doi 10.1186 1742-4682-3-38 Accepted 30 November 2006 This article is available from http www.tbiomed.com content 3 1 38 2006 Sertsou et al licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http creativecommons.org licenses by 2.0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Aim To estimate the key transmission parameters associated with an outbreak of pandemic influenza in an institutional setting New Zealand 1918 . Methods Historical morbidity and mortality data were obtained from the report of the medical officer for a large military camp. A susceptible-exposed-infectious-recovered epidemiological model was solved numerically to find a range of best-fit estimates for key epidemic parameters and an incidence curve. Mortality data were subsequently modelled by performing a convolution of incidence distribution with a best-fit incidence-mortality lag distribution. Results Basic reproduction number R0 values for three possible scenarios