Early estimation of the reproduction number in the presence of imported cases: pandemic influenza H1N1-2009 in New Zealand.

We analyse data from the early epidemic of H1N1-2009 in New Zealand, and estimate the reproduction number R. We employ a renewal process which accounts for imported cases, illustrate some technical pitfalls, and propose a novel estimation method to address these pitfalls. Explicitly accounting for t...

Full description

Bibliographic Details
Main Authors: Michael George Roberts, Hiroshi Nishiura
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2011-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3102662?pdf=render
id doaj-a95b05d0e3b34cc684e1ede019f9bba6
record_format Article
spelling doaj-a95b05d0e3b34cc684e1ede019f9bba62020-11-24T21:35:43ZengPublic Library of Science (PLoS)PLoS ONE1932-62032011-01-0165e1783510.1371/journal.pone.0017835Early estimation of the reproduction number in the presence of imported cases: pandemic influenza H1N1-2009 in New Zealand.Michael George RobertsHiroshi NishiuraWe analyse data from the early epidemic of H1N1-2009 in New Zealand, and estimate the reproduction number R. We employ a renewal process which accounts for imported cases, illustrate some technical pitfalls, and propose a novel estimation method to address these pitfalls. Explicitly accounting for the infection-age distribution of imported cases and for the delay in transmission dynamics due to international travel, R was estimated to be (95% confidence interval: 107,1.47). Hence we show that a previous study, which did not account for these factors, overestimated R. Our approach also permitted us to examine the infection-age at which secondary transmission occurs as a function of calendar time, demonstrating the downward bias during the beginning of the epidemic. These technical issues may compromise the usefulness of a well-known estimator of R--the inverse of the moment-generating function of the generation time given the intrinsic growth rate. Explicit modelling of the infection-age distribution among imported cases and the examination of the time dependency of the generation time play key roles in avoiding a biased estimate of R, especially when one only has data covering a short time interval during the early growth phase of the epidemic.http://europepmc.org/articles/PMC3102662?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Michael George Roberts
Hiroshi Nishiura
spellingShingle Michael George Roberts
Hiroshi Nishiura
Early estimation of the reproduction number in the presence of imported cases: pandemic influenza H1N1-2009 in New Zealand.
PLoS ONE
author_facet Michael George Roberts
Hiroshi Nishiura
author_sort Michael George Roberts
title Early estimation of the reproduction number in the presence of imported cases: pandemic influenza H1N1-2009 in New Zealand.
title_short Early estimation of the reproduction number in the presence of imported cases: pandemic influenza H1N1-2009 in New Zealand.
title_full Early estimation of the reproduction number in the presence of imported cases: pandemic influenza H1N1-2009 in New Zealand.
title_fullStr Early estimation of the reproduction number in the presence of imported cases: pandemic influenza H1N1-2009 in New Zealand.
title_full_unstemmed Early estimation of the reproduction number in the presence of imported cases: pandemic influenza H1N1-2009 in New Zealand.
title_sort early estimation of the reproduction number in the presence of imported cases: pandemic influenza h1n1-2009 in new zealand.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2011-01-01
description We analyse data from the early epidemic of H1N1-2009 in New Zealand, and estimate the reproduction number R. We employ a renewal process which accounts for imported cases, illustrate some technical pitfalls, and propose a novel estimation method to address these pitfalls. Explicitly accounting for the infection-age distribution of imported cases and for the delay in transmission dynamics due to international travel, R was estimated to be (95% confidence interval: 107,1.47). Hence we show that a previous study, which did not account for these factors, overestimated R. Our approach also permitted us to examine the infection-age at which secondary transmission occurs as a function of calendar time, demonstrating the downward bias during the beginning of the epidemic. These technical issues may compromise the usefulness of a well-known estimator of R--the inverse of the moment-generating function of the generation time given the intrinsic growth rate. Explicit modelling of the infection-age distribution among imported cases and the examination of the time dependency of the generation time play key roles in avoiding a biased estimate of R, especially when one only has data covering a short time interval during the early growth phase of the epidemic.
url http://europepmc.org/articles/PMC3102662?pdf=render
work_keys_str_mv AT michaelgeorgeroberts earlyestimationofthereproductionnumberinthepresenceofimportedcasespandemicinfluenzah1n12009innewzealand
AT hiroshinishiura earlyestimationofthereproductionnumberinthepresenceofimportedcasespandemicinfluenzah1n12009innewzealand
_version_ 1725944302724448256