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Accounting for cross-immunity can improve forecast accuracy during influenza epidemics

Abstract:

Previous exposure to influenza viruses confers cross-immunity against future infections with related strains. However, this is not always accounted for explicitly in mathematical models used for forecasting during influenza outbreaks. We show that, if an influenza outbreak is due to a strain that is similar to one that has emerged previously, then accounting for cross-immunity explicitly can improve the accuracy of real-time forecasts. To do this, we consider two infectious disease outbreak f...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.epidem.2020.100432

Authors


More by this author
Institution:
University of Oxford
Department:
Mathematical Institute
Oxford college:
St Anne's College
Role:
Author
More by this author
Institution:
University of Oxford
Department:
MATHEMATICAL INSTITUTE
Sub department:
Mathematical Institute
Oxford college:
Keble College
Role:
Author
ORCID:
0000-0003-1771-5910
Publisher:
Elsevier Publisher's website
Journal:
Epidemics Journal website
Volume:
34
Issue:
March 2021
Article number:
100432
Publication date:
2020-12-17
Acceptance date:
2020-12-15
DOI:
EISSN:
1878-0067
ISSN:
1755-4365
Pmid:
33360870
Language:
English
Keywords:
Pubs id:
1150416
Local pid:
pubs:1150416
Deposit date:
2021-01-15

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