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Hyperendemicity associated with increased dengue burden

Over 105 million dengue infections are estimated to occur annually. Understanding the disease dynamics of dengue is often difficult due to multiple strains circulating within a population. Interactions between dengue serotype dynamics may result in complex cross-immunity dynamics at the population l...

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Autores principales: Lim, Jue Tao, Dickens, Borame Sue, Tan, Ken Wei, Koo, Joel Ruihan, Seah, Annabel, Ho, Soon Hoe, Ong, Janet, Rajarethinam, Jayanthi, Soh, Stacy, Cook, Alex R., Ng, Lee Ching
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8440027/
https://www.ncbi.nlm.nih.gov/pubmed/34520691
http://dx.doi.org/10.1098/rsif.2021.0565
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author Lim, Jue Tao
Dickens, Borame Sue
Tan, Ken Wei
Koo, Joel Ruihan
Seah, Annabel
Ho, Soon Hoe
Ong, Janet
Rajarethinam, Jayanthi
Soh, Stacy
Cook, Alex R.
Ng, Lee Ching
author_facet Lim, Jue Tao
Dickens, Borame Sue
Tan, Ken Wei
Koo, Joel Ruihan
Seah, Annabel
Ho, Soon Hoe
Ong, Janet
Rajarethinam, Jayanthi
Soh, Stacy
Cook, Alex R.
Ng, Lee Ching
author_sort Lim, Jue Tao
collection PubMed
description Over 105 million dengue infections are estimated to occur annually. Understanding the disease dynamics of dengue is often difficult due to multiple strains circulating within a population. Interactions between dengue serotype dynamics may result in complex cross-immunity dynamics at the population level and create difficulties in terms of formulating intervention strategies for the disease. In this study, a nationally representative 16-year time series with over 43 000 serotyped dengue infections was used to infer the long-run effects of between and within strain interactions and their impacts on past outbreaks. We used a novel identification strategy incorporating sign-identified Bayesian vector autoregressions, using structural impulse responses, historical decompositions and counterfactual analysis to conduct inference on dengue dynamics post-estimation. We found that on the population level: (i) across-serotype interactions on the population level were highly persistent, with a one time increase in any other serotype associated with long run decreases in the serotype of interest (range: 0.5–2.5 years) and (ii) over 38.7% of dengue cases of any serotype were associated with across-serotype interactions. The findings in this paper will substantially impact public health policy interventions with respect to dengue.
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spelling pubmed-84400272021-09-15 Hyperendemicity associated with increased dengue burden Lim, Jue Tao Dickens, Borame Sue Tan, Ken Wei Koo, Joel Ruihan Seah, Annabel Ho, Soon Hoe Ong, Janet Rajarethinam, Jayanthi Soh, Stacy Cook, Alex R. Ng, Lee Ching J R Soc Interface Life Sciences–Mathematics interface Over 105 million dengue infections are estimated to occur annually. Understanding the disease dynamics of dengue is often difficult due to multiple strains circulating within a population. Interactions between dengue serotype dynamics may result in complex cross-immunity dynamics at the population level and create difficulties in terms of formulating intervention strategies for the disease. In this study, a nationally representative 16-year time series with over 43 000 serotyped dengue infections was used to infer the long-run effects of between and within strain interactions and their impacts on past outbreaks. We used a novel identification strategy incorporating sign-identified Bayesian vector autoregressions, using structural impulse responses, historical decompositions and counterfactual analysis to conduct inference on dengue dynamics post-estimation. We found that on the population level: (i) across-serotype interactions on the population level were highly persistent, with a one time increase in any other serotype associated with long run decreases in the serotype of interest (range: 0.5–2.5 years) and (ii) over 38.7% of dengue cases of any serotype were associated with across-serotype interactions. The findings in this paper will substantially impact public health policy interventions with respect to dengue. The Royal Society 2021-09-15 /pmc/articles/PMC8440027/ /pubmed/34520691 http://dx.doi.org/10.1098/rsif.2021.0565 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Life Sciences–Mathematics interface
Lim, Jue Tao
Dickens, Borame Sue
Tan, Ken Wei
Koo, Joel Ruihan
Seah, Annabel
Ho, Soon Hoe
Ong, Janet
Rajarethinam, Jayanthi
Soh, Stacy
Cook, Alex R.
Ng, Lee Ching
Hyperendemicity associated with increased dengue burden
title Hyperendemicity associated with increased dengue burden
title_full Hyperendemicity associated with increased dengue burden
title_fullStr Hyperendemicity associated with increased dengue burden
title_full_unstemmed Hyperendemicity associated with increased dengue burden
title_short Hyperendemicity associated with increased dengue burden
title_sort hyperendemicity associated with increased dengue burden
topic Life Sciences–Mathematics interface
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8440027/
https://www.ncbi.nlm.nih.gov/pubmed/34520691
http://dx.doi.org/10.1098/rsif.2021.0565
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