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Using dimension reduction to improve outbreak predictability of multistrain diseases
Multistrain diseases have multiple distinct coexisting serotypes (strains). For some diseases, such as dengue fever, the serotypes interact by antibody-dependent enhancement (ADE), in which infection with a single serotype is asymptomatic, but contact with a second serotype leads to higher viral loa...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer-Verlag
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7080105/ https://www.ncbi.nlm.nih.gov/pubmed/17318630 http://dx.doi.org/10.1007/s00285-007-0074-x |
_version_ | 1783507960000937984 |
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author | Shaw, Leah B. Billings, Lora Schwartz, Ira B. |
author_facet | Shaw, Leah B. Billings, Lora Schwartz, Ira B. |
author_sort | Shaw, Leah B. |
collection | PubMed |
description | Multistrain diseases have multiple distinct coexisting serotypes (strains). For some diseases, such as dengue fever, the serotypes interact by antibody-dependent enhancement (ADE), in which infection with a single serotype is asymptomatic, but contact with a second serotype leads to higher viral load and greater infectivity. We present and analyze a dynamic compartmental model for multiple serotypes exhibiting ADE. Using center manifold techniques, we show how the dynamics rapidly collapses to a lower dimensional system. Using the constructed reduced model, we can explain previously observed synchrony between certain classes of primary and secondary infectives (Schwartz et al. in Phys Rev E 72:066201, 2005). Additionally, we show numerically that the center manifold equations apply even to noisy systems. Both deterministic and stochastic versions of the model enable prediction of asymptomatic individuals that are difficult to track during an epidemic. We also show how this technique may be applicable to other multistrain disease models, such as those with cross-immunity. |
format | Online Article Text |
id | pubmed-7080105 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Springer-Verlag |
record_format | MEDLINE/PubMed |
spelling | pubmed-70801052020-03-23 Using dimension reduction to improve outbreak predictability of multistrain diseases Shaw, Leah B. Billings, Lora Schwartz, Ira B. J Math Biol Article Multistrain diseases have multiple distinct coexisting serotypes (strains). For some diseases, such as dengue fever, the serotypes interact by antibody-dependent enhancement (ADE), in which infection with a single serotype is asymptomatic, but contact with a second serotype leads to higher viral load and greater infectivity. We present and analyze a dynamic compartmental model for multiple serotypes exhibiting ADE. Using center manifold techniques, we show how the dynamics rapidly collapses to a lower dimensional system. Using the constructed reduced model, we can explain previously observed synchrony between certain classes of primary and secondary infectives (Schwartz et al. in Phys Rev E 72:066201, 2005). Additionally, we show numerically that the center manifold equations apply even to noisy systems. Both deterministic and stochastic versions of the model enable prediction of asymptomatic individuals that are difficult to track during an epidemic. We also show how this technique may be applicable to other multistrain disease models, such as those with cross-immunity. Springer-Verlag 2007-02-22 2007 /pmc/articles/PMC7080105/ /pubmed/17318630 http://dx.doi.org/10.1007/s00285-007-0074-x Text en © Springer-Verlag 2007 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Shaw, Leah B. Billings, Lora Schwartz, Ira B. Using dimension reduction to improve outbreak predictability of multistrain diseases |
title | Using dimension reduction to improve outbreak predictability of multistrain diseases |
title_full | Using dimension reduction to improve outbreak predictability of multistrain diseases |
title_fullStr | Using dimension reduction to improve outbreak predictability of multistrain diseases |
title_full_unstemmed | Using dimension reduction to improve outbreak predictability of multistrain diseases |
title_short | Using dimension reduction to improve outbreak predictability of multistrain diseases |
title_sort | using dimension reduction to improve outbreak predictability of multistrain diseases |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7080105/ https://www.ncbi.nlm.nih.gov/pubmed/17318630 http://dx.doi.org/10.1007/s00285-007-0074-x |
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