Mathematical Biosciences and Engineering, 2011, 8(1): 49-64. doi: 10.3934/mbe.2011.8.49.

Primary: 00A71, 37N25; Secondary: 92C60, 92D30.

Export file:


  • RIS(for EndNote,Reference Manager,ProCite)
  • BibTex
  • Text


  • Citation Only
  • Citation and Abstract

Joint quantification of transmission dynamics and diagnostic accuracy applied to influenza

1. PRESTO, Japan Science and Technology Agency (JST), 4-1-8 Honcho Kawaguchi, Saitama 332-0012

The influenza A (H1N1) pandemic 2009 posed an epidemiological challenge in ascertaining all cases. Although the counting of all influenza cases in real time is often not feasible, empirical observations always involve diagnostic test procedures. This offers an opportunity to jointly quantify transmission dynamics and diagnostic accuracy. We have developed a joint estimation procedure that exploits parsimonious models to describe the epidemic dynamics and that parameterizes the number of test positives and test negatives as a function of time. Our analyses of simulated data and data from the empirical observation of interpandemic influenza A (H1N1) from 2007-08 in Japan indicate that the proposed approach permits a more precise quantification of the transmission dynamics compared to methods that rely on test positive cases alone. The analysis of entry screening data for the H1N1 pandemic 2009 at Tokyo-Narita airport helped us quantify the very limited specificity of influenza-like illness in detecting actual influenza cases in the passengers. The joint quantification does not require us to condition diagnostic accuracy on any pre-defined study population. Our study suggests that by consistently reporting both test positive and test negative cases, the usefulness of extractable information from routine surveillance record of infectious diseases would be maximized.
  Article Metrics

Keywords diagnosis; influenza.; Transmission; epidemiology; model

Citation: Hiroshi Nishiura. Joint quantification of transmission dynamics and diagnostic accuracy applied to influenza. Mathematical Biosciences and Engineering, 2011, 8(1): 49-64. doi: 10.3934/mbe.2011.8.49


This article has been cited by

  • 1. Welling Oei, Hiroshi Nishiura, The Relationship between Tuberculosis and Influenza Death during the Influenza (H1N1) Pandemic from 1918-19, Computational and Mathematical Methods in Medicine, 2012, 2012, 1, 10.1155/2012/124861
  • 2. Andrew Noymer, Ann M. Nguyen, Influenza as a Proportion of Pneumonia Mortality: United States, 1959–2009, Biodemography and Social Biology, 2013, 59, 2, 178, 10.1080/19485565.2013.833816
  • 3. Hiroshi Nishiura, Kazuko Kamiya, Fever screening during the influenza (H1N1-2009) pandemic at Narita International Airport, Japan, BMC Infectious Diseases, 2011, 11, 1, 10.1186/1471-2334-11-111
  • 4. Hiroshi Nishiura, Hisashi Inaba, Estimation of the incubation period of influenza A (H1N1-2009) among imported cases: Addressing censoring using outbreak data at the origin of importation, Journal of Theoretical Biology, 2011, 272, 1, 123, 10.1016/j.jtbi.2010.12.017
  • 5. Ryosuke Omori, Hiroshi Nishiura, Theoretical basis to measure the impact of short-lasting control of an infectious disease on the epidemic peak, Theoretical Biology and Medical Modelling, 2011, 8, 1, 10.1186/1742-4682-8-2
  • 6. Hiroshi Nishiura, Backcalculating the Incidence of Infection with COVID-19 on the Diamond Princess, Journal of Clinical Medicine, 2020, 9, 3, 657, 10.3390/jcm9030657

Reader Comments

your name: *   your email: *  

Copyright Info: 2011, , licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (

Download full text in PDF

Export Citation

Copyright © AIMS Press All Rights Reserved