Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Who is the infector? Epidemic models with symptomatic and asymptomatic cases
Stockholm University, Faculty of Science, Department of Mathematics.ORCID iD: 0000-0002-7596-7641
Stockholm University, Faculty of Science, Department of Mathematics.
Stockholm University, Faculty of Science, Department of Mathematics.ORCID iD: 0000-0002-9228-7357
Number of Authors: 32018 (English)In: Mathematical Biosciences, ISSN 0025-5564, E-ISSN 1879-3134, Vol. 301, p. 190-198Article in journal (Refereed) Published
Abstract [en]

What role do asymptomatically infected individuals play in the transmission dynamics? There are many diseases, such as norovirus and influenza, where some infected hosts show symptoms of the disease while others are asymptomatically infected, i.e.do not show any symptoms. The current paper considers a class of epidemic models following an SEIR (Susceptible -> Exposed -> Infectious -> Recovered) structure that allows for both symptomatic and asymptomatic cases. The following question is addressed: what fraction p of those individuals getting infected are infected by symptomatic (asymptomatic) cases? This is a more complicated question than the related question for the beginning of the epidemic: what fraction of the expected number of secondary cases of a typical newly infected individual, i.e. what fraction of the basic reproduction number R-0,R- is caused by symptomatic individuals? The latter fraction only depends on the type-specific reproduction numbers, while the former fraction p also depends on timing and hence on the probabilistic distributions of latent and infectious periods of the two types (not only their means). Bounds on p are derived for the situation where these distributions (and even their means) are unknown. Special attention is given to the class of Markov models and the class of continuous-time Reed-Frost models as two classes of distribution functions for latent and infectious periods. We show how these two classes of models can exhibit very different behaviour.

Place, publisher, year, edition, pages
2018. Vol. 301, p. 190-198
Keywords [en]
Two-type SEIR epidemic, Final size, Type of infector, Continuous-time Reed-Frost models, Markov models
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:su:diva-158349DOI: 10.1016/j.mbs.2018.04.002ISI: 000438006200018PubMedID: 29654792OAI: oai:DiVA.org:su-158349DiVA, id: diva2:1239049
Available from: 2018-08-15 Created: 2018-08-15 Last updated: 2019-12-16Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Leung, Ka YinTrapman, PieterBritton, Tom
By organisation
Department of Mathematics
In the same journal
Mathematical Biosciences
Biological Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 15 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf