Literature DB >> 25294601

Serial intervals of respiratory infectious diseases: a systematic review and analysis.

Margaretha Annelie Vink, Martinus Christoffel Jozef Bootsma, Jacco Wallinga.   

Abstract

The serial interval of an infectious disease represents the duration between symptom onset of a primary case and symptom onset of its secondary cases. A good evidence base for such values is essential, because they allow investigators to identify epidemiologic links between cases and serve as an important parameter in epidemic transmission models used to design infection control strategies. We reviewed the literature for available data sets containing serial intervals and for reported values of serial intervals. We were able to collect data on outbreaks within households, which we reanalyzed to infer a mean serial interval using a common statistical method. We estimated the mean serial intervals for influenza A(H3N2) (2.2 days), pandemic influenza A(H1N1)pdm09 (2.8 days), respiratory syncytial virus (7.5 days), measles (11.7 days), varicella (14.0 days), smallpox (17.7 days), mumps (18.0 days), rubella (18.3 days), and pertussis (22.8 days). For varicella, we found an evidence-based value that deviates substantially from the 21 days commonly used in transmission models. This value of the serial interval for pertussis is, to the best of our knowledge, the first that is based on observations. Our review reveals that, for most infectious diseases, there is very limited evidence to support the serial intervals that are often cited.
© The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  generation interval; generation time; respiratory infectious diseases; serial interval

Mesh:

Year:  2014        PMID: 25294601     DOI: 10.1093/aje/kwu209

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  73 in total

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3.  Application of an Individual-Based Transmission Hazard Model for Estimation of Influenza Vaccine Effectiveness in a Household Cohort.

Authors:  Joshua G Petrie; Marisa C Eisenberg; Sophia Ng; Ryan E Malosh; Kyu Han Lee; Suzanne E Ohmit; Arnold S Monto
Journal:  Am J Epidemiol       Date:  2017-12-15       Impact factor: 4.897

4.  Estimating the relative probability of direct transmission between infectious disease patients.

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5.  Some Dissimilarity Measures of Branching Processes and Optimal Decision Making in the Presence of Potential Pandemics.

Authors:  Niels B Kammerer; Wolfgang Stummer
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6.  Case-control study of household contacts to examine immunological protection from Bordetella pertussis transmission - study protocol.

Authors:  Shelly Bolotin; Caitlin Johnson; Susan Quach; Ardith Ambrose; Sarah DeCoutere; Shelley L Deeks; Steven Drews; Amna Faheem; Karen Green; Scott A Halperin; Linda Hoang; Frances Jamieson; Tobias Kollmann; Alex Marchand-Austin; Deirdre McCormack; Allison McGeer; Michelle Murti; Alison Orth Bba; Anu Rebbapragada; Otto G Vanderkooi; Jun Wang; Bryna Warshawsky; Natasha S Crowcroft
Journal:  CMAJ Open       Date:  2017-12-19

7.  Game theory of pre-emptive vaccination before bioterrorism or accidental release of smallpox.

Authors:  Chai Molina; David J D Earn
Journal:  J R Soc Interface       Date:  2015-06-06       Impact factor: 4.118

8.  Heterogeneity in social and epidemiological factors determines the risk of measles outbreaks.

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9.  Clinical Performance of the AllplexTM Respiratory Panel 1 Test Compared to SimplexaTM Flu A/B and RSV for Detection of Influenza Virus and Respiratory Syncytial Virus Infection Including Their Subtyping.

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Journal:  Med Princ Pract       Date:  2019-03-04       Impact factor: 1.927

Review 10.  Pertussis: Microbiology, Disease, Treatment, and Prevention.

Authors:  Paul E Kilgore; Abdulbaset M Salim; Marcus J Zervos; Heinz-Josef Schmitt
Journal:  Clin Microbiol Rev       Date:  2016-07       Impact factor: 26.132

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