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- PMID: 21077712
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Article: Time variations in the generation time of an infectious disease: Implications for sampling to appropriately quantify transmission potential
Title | Time variations in the generation time of an infectious disease: Implications for sampling to appropriately quantify transmission potential | ||||
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Authors | |||||
Keywords | Epidemiology Influenza Model Plague Transmission | ||||
Issue Date | 2010 | ||||
Publisher | American Institute of Mathematical Sciences | ||||
Citation | Mathematical Biosciences And Engineering, 2010, v. 7 n. 4, p. 851-869 How to Cite? | ||||
Abstract | Although the generation time of an infectious disease plays a key role in estimating its transmission potential, the impact of the sampling time of generation times on the estimation procedure has yet to be clarified. The present study defines the period and cohort generation times, both of which are timeinhomogeneous, as a function of the infection time of secondary and primary cases, respectively. By means of analytical and numerical approaches, it is shown that the period generation time increases with calendar time, whereas the cohort generation time decreases as the incidence increases. The initial growth phase of an epidemic of Asian influenza A (H2N2) in the Netherlands in 1957 was reanalyzed, and estimates of the basic reproduction number, R0, from the Lotka-Euler equation were examined. It was found that the sampling time of generation time during the course of the epidemic introduced a time-effect to the estimate of R0. Other historical data of a primary pneumonic plague in Manchuria in 1911 were also examined to help illustrate the empirical evidence of the period generation time. If the serial intervals, which eventually determine the generation times, are sampled during the course of an epidemic, direct application of the sampled generation-time distribution to the Lotka-Euler equation leads to a biased estimate of R0. An appropriate quantification of the transmission potential requires the estimation of the cohort generation time during the initial growth phase of an epidemic or adjustment of the time-effect (e.g., adjustment of the growth rate of the epidemic during the sampling time) on the period generation time. A similar issue also applies to the estimation of the effective reproduction number as a function of calendar time. Mathematical properties of the generation time distribution in a heterogeneously mixing population need to be clarified further. | ||||
Persistent Identifier | http://hdl.handle.net/10722/134190 | ||||
ISSN | 2022 Impact Factor: 2.6 2023 SCImago Journal Rankings: 0.481 | ||||
ISI Accession Number ID |
Funding Information: The work of H Nishiura was supported by the JST PRESTO program. | ||||
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Nishiura, H | en_HK |
dc.date.accessioned | 2011-06-13T07:20:45Z | - |
dc.date.available | 2011-06-13T07:20:45Z | - |
dc.date.issued | 2010 | en_HK |
dc.identifier.citation | Mathematical Biosciences And Engineering, 2010, v. 7 n. 4, p. 851-869 | en_HK |
dc.identifier.issn | 1547-1063 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/134190 | - |
dc.description.abstract | Although the generation time of an infectious disease plays a key role in estimating its transmission potential, the impact of the sampling time of generation times on the estimation procedure has yet to be clarified. The present study defines the period and cohort generation times, both of which are timeinhomogeneous, as a function of the infection time of secondary and primary cases, respectively. By means of analytical and numerical approaches, it is shown that the period generation time increases with calendar time, whereas the cohort generation time decreases as the incidence increases. The initial growth phase of an epidemic of Asian influenza A (H2N2) in the Netherlands in 1957 was reanalyzed, and estimates of the basic reproduction number, R0, from the Lotka-Euler equation were examined. It was found that the sampling time of generation time during the course of the epidemic introduced a time-effect to the estimate of R0. Other historical data of a primary pneumonic plague in Manchuria in 1911 were also examined to help illustrate the empirical evidence of the period generation time. If the serial intervals, which eventually determine the generation times, are sampled during the course of an epidemic, direct application of the sampled generation-time distribution to the Lotka-Euler equation leads to a biased estimate of R0. An appropriate quantification of the transmission potential requires the estimation of the cohort generation time during the initial growth phase of an epidemic or adjustment of the time-effect (e.g., adjustment of the growth rate of the epidemic during the sampling time) on the period generation time. A similar issue also applies to the estimation of the effective reproduction number as a function of calendar time. Mathematical properties of the generation time distribution in a heterogeneously mixing population need to be clarified further. | en_HK |
dc.language | eng | en_US |
dc.publisher | American Institute of Mathematical Sciences | en_US |
dc.relation.ispartof | Mathematical Biosciences and Engineering | en_HK |
dc.subject | Epidemiology | en_US |
dc.subject | Influenza | en_US |
dc.subject | Model | en_US |
dc.subject | Plague | en_US |
dc.subject | Transmission | en_US |
dc.subject.mesh | Basic Reproduction Number | en_HK |
dc.subject.mesh | China - epidemiology | en_HK |
dc.subject.mesh | Communicable Diseases - epidemiology - history - transmission | en_HK |
dc.subject.mesh | History, 20th Century | en_HK |
dc.subject.mesh | Humans | en_HK |
dc.subject.mesh | Incidence | en_HK |
dc.subject.mesh | Influenza A Virus, H2N2 Subtype | en_HK |
dc.subject.mesh | Influenza, Human - epidemiology - history - transmission | en_HK |
dc.subject.mesh | Models, Biological | en_HK |
dc.subject.mesh | Netherlands - epidemiology | en_HK |
dc.subject.mesh | Plague - epidemiology - history - transmission | en_HK |
dc.subject.mesh | Selection Bias | en_HK |
dc.title | Time variations in the generation time of an infectious disease: Implications for sampling to appropriately quantify transmission potential | en_HK |
dc.type | Article | en_HK |
dc.identifier.email | Nishiura, H:nishiura@hku.hk | en_HK |
dc.identifier.authority | Nishiura, H=rp01488 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.3934/mbe.2010.7.851 | en_HK |
dc.identifier.pmid | 21077712 | - |
dc.identifier.scopus | eid_2-s2.0-77958038941 | en_HK |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-77958038941&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 7 | en_HK |
dc.identifier.issue | 4 | en_HK |
dc.identifier.spage | 851 | en_HK |
dc.identifier.epage | 869 | en_HK |
dc.identifier.eissn | 1551-0018 | - |
dc.identifier.isi | WOS:000283346800009 | - |
dc.publisher.place | United States | en_HK |
dc.identifier.scopusauthorid | Nishiura, H=7005501836 | en_HK |
dc.identifier.issnl | 1547-1063 | - |