A new approach to characterising infectious disease transmission dynamics from sentinel surveillance: application to the Italian 2009–2010 A/H1N1 influenza pandemic
File(s)
Published version
Author(s)
Dorigatti, I
Cauchemez, S
Pugliese, A
Ferguson, NM
Type
Journal Article
Abstract
Syndromic and virological data are routinely collected by many countries and are often the only information available in real time. The analysis of surveillance data poses many statistical challenges that have not yet been addressed. For instance, the fraction of cases that seek healthcare and are thus detected is often unknown. Here, we propose a general statistical framework that explicitly takes into account the way the surveillance data are generated. Our approach couples a deterministic mathematical model with a statistical description of the reporting process and is applied to surveillance data collected in Italy during the 2009–2010 A/H1N1 influenza pandemic. We estimate that the reproduction number R was initially into the range 1.2–1.4 and that case detection in children was significantly higher than in adults. According to the best fit models, we estimate that school-age children experienced the highest infection rate overall. In terms of both estimated peak-incidence and overall attack rate, according to the Susceptibility and Immunity models the 5–14 years age-class was about 5 times more infected than the 65+ years old age-group and about twice more than the 15–64 years age-class. The multiplying factors are doubled using the Baseline model. Overall, the estimated attack rate was about 16% according to the Baseline model and 30% according to the Susceptibility and Immunity models.
Date Issued
2011-11-28
Date Acceptance
2011-11-17
Citation
Epidemics, 2011, 4 (1), pp.9-21
ISSN
1878-0067
Publisher
Elsevier
Start Page
9
End Page
21
Journal / Book Title
Epidemics
Volume
4
Issue
1
Copyright Statement
© 2011 Elsevier B.V. All rights reserved. Made available under a CC BY NC ND license.
Sponsor
Medical Research Council (MRC)
Grant Number
G0600719B
Subjects
Science & Technology
Life Sciences & Biomedicine
Infectious Diseases
INFECTIOUS DISEASES
SEIR model
Epidemic modelling
Markov Chain Monte Carlo methods
Bayesian inference
Reporting process
A H1N1 VIRUS
EPIDEMIC MODELS
A(H1N1)
RATES
PREVALENCE
STRATEGIES
HOUSEHOLD
SEVERITY
BEHAVIOR
IMMUNITY
Adolescent
Child
Child, Preschool
Disease Susceptibility
Female
Humans
Influenza A Virus, H1N1 Subtype
Influenza, Human
Italy
Male
Models, Statistical
Pandemics
Sentinel Surveillance
1103 Clinical Sciences
1117 Public Health And Health Services
Publication Status
Published